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https://github.com/hwchase17/langchain.git
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@@ -1,49 +0,0 @@
|
||||
# Dev container
|
||||
|
||||
This project includes a [dev container](https://containers.dev/), which lets you use a container as a full-featured dev environment.
|
||||
|
||||
You can use the dev container configuration in this folder to build and run the app without needing to install any of its tools locally! You can use it in [GitHub Codespaces](https://github.com/features/codespaces) or the [VS Code Dev Containers extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers).
|
||||
|
||||
## GitHub Codespaces
|
||||
|
||||
[](https://codespaces.new/langchain-ai/langchain)
|
||||
|
||||
You may use the button above, or follow these steps to open this repo in a Codespace:
|
||||
|
||||
1. Click the **Code** drop-down menu at the top of <https://github.com/langchain-ai/langchain>.
|
||||
1. Click on the **Codespaces** tab.
|
||||
1. Click **Create codespace on master**.
|
||||
|
||||
For more info, check out the [GitHub documentation](https://docs.github.com/en/free-pro-team@latest/github/developing-online-with-codespaces/creating-a-codespace#creating-a-codespace).
|
||||
|
||||
## VS Code Dev Containers
|
||||
|
||||
[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain)
|
||||
|
||||
> [!NOTE]
|
||||
> If you click the link above you will open the main repo (`langchain-ai/langchain`) and *not* your local cloned repo. This is fine if you only want to run and test the library, but if you want to contribute you can use the link below and replace with your username and cloned repo name:
|
||||
|
||||
```txt
|
||||
https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/<YOUR_USERNAME>/<YOUR_CLONED_REPO_NAME>
|
||||
```
|
||||
|
||||
Then you will have a local cloned repo where you can contribute and then create pull requests.
|
||||
|
||||
If you already have VS Code and Docker installed, you can use the button above to get started. This will use VSCode to automatically install the Dev Containers extension if needed, clone the source code into a container volume, and spin up a dev container for use.
|
||||
|
||||
Alternatively you can also follow these steps to open this repo in a container using the VS Code Dev Containers extension:
|
||||
|
||||
1. If this is your first time using a development container, please ensure your system meets the pre-reqs (i.e. have Docker installed) in the [getting started steps](https://aka.ms/vscode-remote/containers/getting-started).
|
||||
|
||||
2. Open a locally cloned copy of the code:
|
||||
|
||||
- Fork and Clone this repository to your local filesystem.
|
||||
- Press <kbd>F1</kbd> and select the **Dev Containers: Open Folder in Container...** command.
|
||||
- Select the cloned copy of this folder, wait for the container to start, and try things out!
|
||||
|
||||
You can learn more in the [Dev Containers documentation](https://code.visualstudio.com/docs/devcontainers/containers).
|
||||
|
||||
## Tips and tricks
|
||||
|
||||
- If you are working with the same repository folder in a container and Windows, you'll want consistent line endings (otherwise you may see hundreds of changes in the SCM view). The `.gitattributes` file in the root of this repo will disable line ending conversion and should prevent this. See [tips and tricks](https://code.visualstudio.com/docs/devcontainers/tips-and-tricks#_resolving-git-line-ending-issues-in-containers-resulting-in-many-modified-files) for more info.
|
||||
- If you'd like to review the contents of the image used in this dev container, you can check it out in the [devcontainers/images](https://github.com/devcontainers/images/tree/main/src/python) repo.
|
||||
@@ -1,58 +0,0 @@
|
||||
// For format details, see https://aka.ms/devcontainer.json. For config options, see the
|
||||
// README at: https://github.com/devcontainers/templates/tree/main/src/docker-existing-docker-compose
|
||||
{
|
||||
// Name for the dev container
|
||||
"name": "langchain",
|
||||
// Point to a Docker Compose file
|
||||
"dockerComposeFile": "./docker-compose.yaml",
|
||||
// Required when using Docker Compose. The name of the service to connect to once running
|
||||
"service": "langchain",
|
||||
// The optional 'workspaceFolder' property is the path VS Code should open by default when
|
||||
// connected. This is typically a file mount in .devcontainer/docker-compose.yml
|
||||
"workspaceFolder": "/workspaces/langchain",
|
||||
"mounts": [
|
||||
"source=langchain-workspaces,target=/workspaces/langchain,type=volume"
|
||||
],
|
||||
// Prevent the container from shutting down
|
||||
"overrideCommand": true,
|
||||
// Features to add to the dev container. More info: https://containers.dev/features
|
||||
"features": {
|
||||
"ghcr.io/devcontainers/features/git:1": {},
|
||||
"ghcr.io/devcontainers/features/github-cli:1": {}
|
||||
},
|
||||
"containerEnv": {
|
||||
"UV_LINK_MODE": "copy"
|
||||
},
|
||||
// Use 'forwardPorts' to make a list of ports inside the container available locally.
|
||||
// "forwardPorts": [],
|
||||
// Run commands after the container is created
|
||||
"postCreateCommand": "uv sync && echo 'LangChain (Python) dev environment ready!'",
|
||||
// Configure tool-specific properties.
|
||||
"customizations": {
|
||||
"vscode": {
|
||||
"extensions": [
|
||||
"ms-python.python",
|
||||
"ms-python.debugpy",
|
||||
"ms-python.mypy-type-checker",
|
||||
"ms-python.isort",
|
||||
"unifiedjs.vscode-mdx",
|
||||
"davidanson.vscode-markdownlint",
|
||||
"ms-toolsai.jupyter",
|
||||
"GitHub.copilot",
|
||||
"GitHub.copilot-chat"
|
||||
],
|
||||
"settings": {
|
||||
"python.defaultInterpreterPath": ".venv/bin/python",
|
||||
"python.formatting.provider": "none",
|
||||
"[python]": {
|
||||
"editor.formatOnSave": true,
|
||||
"editor.codeActionsOnSave": {
|
||||
"source.organizeImports": true
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
|
||||
// "remoteUser": "root"
|
||||
}
|
||||
@@ -1,13 +0,0 @@
|
||||
version: '3'
|
||||
services:
|
||||
langchain:
|
||||
build:
|
||||
dockerfile: libs/langchain/dev.Dockerfile
|
||||
context: ..
|
||||
|
||||
networks:
|
||||
- langchain-network
|
||||
|
||||
networks:
|
||||
langchain-network:
|
||||
driver: bridge
|
||||
@@ -1,52 +0,0 @@
|
||||
# top-most EditorConfig file
|
||||
root = true
|
||||
|
||||
# All files
|
||||
[*]
|
||||
charset = utf-8
|
||||
end_of_line = lf
|
||||
insert_final_newline = true
|
||||
trim_trailing_whitespace = true
|
||||
|
||||
# Python files
|
||||
[*.py]
|
||||
indent_style = space
|
||||
indent_size = 4
|
||||
max_line_length = 88
|
||||
|
||||
# JSON files
|
||||
[*.json]
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
|
||||
# YAML files
|
||||
[*.{yml,yaml}]
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
|
||||
# Markdown files
|
||||
[*.md]
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
trim_trailing_whitespace = false
|
||||
|
||||
# Configuration files
|
||||
[*.{toml,ini,cfg}]
|
||||
indent_style = space
|
||||
indent_size = 4
|
||||
|
||||
# Shell scripts
|
||||
[*.sh]
|
||||
indent_style = space
|
||||
indent_size = 2
|
||||
|
||||
# Makefile
|
||||
[Makefile]
|
||||
indent_style = tab
|
||||
indent_size = 4
|
||||
|
||||
# Jupyter notebooks
|
||||
[*.ipynb]
|
||||
# Jupyter may include trailing whitespace in cell
|
||||
# outputs that's semantically meaningful
|
||||
trim_trailing_whitespace = false
|
||||
@@ -1,6 +1,5 @@
|
||||
[flake8]
|
||||
exclude =
|
||||
venv
|
||||
.venv
|
||||
__pycache__
|
||||
notebooks
|
||||
3
.gitattributes
vendored
3
.gitattributes
vendored
@@ -1,3 +0,0 @@
|
||||
* text=auto eol=lf
|
||||
*.{cmd,[cC][mM][dD]} text eol=crlf
|
||||
*.{bat,[bB][aA][tT]} text eol=crlf
|
||||
3
.github/CODEOWNERS
vendored
3
.github/CODEOWNERS
vendored
@@ -1,3 +0,0 @@
|
||||
/.github/ @baskaryan @ccurme @eyurtsev
|
||||
/libs/core/ @eyurtsev
|
||||
/libs/partners/ @ccurme @mdrxy
|
||||
132
.github/CODE_OF_CONDUCT.md
vendored
132
.github/CODE_OF_CONDUCT.md
vendored
@@ -1,132 +0,0 @@
|
||||
# Contributor Covenant Code of Conduct
|
||||
|
||||
## Our Pledge
|
||||
|
||||
We as members, contributors, and leaders pledge to make participation in our
|
||||
community a harassment-free experience for everyone, regardless of age, body
|
||||
size, visible or invisible disability, ethnicity, sex characteristics, gender
|
||||
identity and expression, level of experience, education, socio-economic status,
|
||||
nationality, personal appearance, race, caste, color, religion, or sexual
|
||||
identity and orientation.
|
||||
|
||||
We pledge to act and interact in ways that contribute to an open, welcoming,
|
||||
diverse, inclusive, and healthy community.
|
||||
|
||||
## Our Standards
|
||||
|
||||
Examples of behavior that contributes to a positive environment for our
|
||||
community include:
|
||||
|
||||
* Demonstrating empathy and kindness toward other people
|
||||
* Being respectful of differing opinions, viewpoints, and experiences
|
||||
* Giving and gracefully accepting constructive feedback
|
||||
* Accepting responsibility and apologizing to those affected by our mistakes,
|
||||
and learning from the experience
|
||||
* Focusing on what is best not just for us as individuals, but for the overall
|
||||
community
|
||||
|
||||
Examples of unacceptable behavior include:
|
||||
|
||||
* The use of sexualized language or imagery, and sexual attention or advances of
|
||||
any kind
|
||||
* Trolling, insulting or derogatory comments, and personal or political attacks
|
||||
* Public or private harassment
|
||||
* Publishing others' private information, such as a physical or email address,
|
||||
without their explicit permission
|
||||
* Other conduct which could reasonably be considered inappropriate in a
|
||||
professional setting
|
||||
|
||||
## Enforcement Responsibilities
|
||||
|
||||
Community leaders are responsible for clarifying and enforcing our standards of
|
||||
acceptable behavior and will take appropriate and fair corrective action in
|
||||
response to any behavior that they deem inappropriate, threatening, offensive,
|
||||
or harmful.
|
||||
|
||||
Community leaders have the right and responsibility to remove, edit, or reject
|
||||
comments, commits, code, wiki edits, issues, and other contributions that are
|
||||
not aligned to this Code of Conduct, and will communicate reasons for moderation
|
||||
decisions when appropriate.
|
||||
|
||||
## Scope
|
||||
|
||||
This Code of Conduct applies within all community spaces, and also applies when
|
||||
an individual is officially representing the community in public spaces.
|
||||
Examples of representing our community include using an official e-mail address,
|
||||
posting via an official social media account, or acting as an appointed
|
||||
representative at an online or offline event.
|
||||
|
||||
## Enforcement
|
||||
|
||||
Instances of abusive, harassing, or otherwise unacceptable behavior may be
|
||||
reported to the community leaders responsible for enforcement at
|
||||
conduct@langchain.dev.
|
||||
All complaints will be reviewed and investigated promptly and fairly.
|
||||
|
||||
All community leaders are obligated to respect the privacy and security of the
|
||||
reporter of any incident.
|
||||
|
||||
## Enforcement Guidelines
|
||||
|
||||
Community leaders will follow these Community Impact Guidelines in determining
|
||||
the consequences for any action they deem in violation of this Code of Conduct:
|
||||
|
||||
### 1. Correction
|
||||
|
||||
**Community Impact**: Use of inappropriate language or other behavior deemed
|
||||
unprofessional or unwelcome in the community.
|
||||
|
||||
**Consequence**: A private, written warning from community leaders, providing
|
||||
clarity around the nature of the violation and an explanation of why the
|
||||
behavior was inappropriate. A public apology may be requested.
|
||||
|
||||
### 2. Warning
|
||||
|
||||
**Community Impact**: A violation through a single incident or series of
|
||||
actions.
|
||||
|
||||
**Consequence**: A warning with consequences for continued behavior. No
|
||||
interaction with the people involved, including unsolicited interaction with
|
||||
those enforcing the Code of Conduct, for a specified period of time. This
|
||||
includes avoiding interactions in community spaces as well as external channels
|
||||
like social media. Violating these terms may lead to a temporary or permanent
|
||||
ban.
|
||||
|
||||
### 3. Temporary Ban
|
||||
|
||||
**Community Impact**: A serious violation of community standards, including
|
||||
sustained inappropriate behavior.
|
||||
|
||||
**Consequence**: A temporary ban from any sort of interaction or public
|
||||
communication with the community for a specified period of time. No public or
|
||||
private interaction with the people involved, including unsolicited interaction
|
||||
with those enforcing the Code of Conduct, is allowed during this period.
|
||||
Violating these terms may lead to a permanent ban.
|
||||
|
||||
### 4. Permanent Ban
|
||||
|
||||
**Community Impact**: Demonstrating a pattern of violation of community
|
||||
standards, including sustained inappropriate behavior, harassment of an
|
||||
individual, or aggression toward or disparagement of classes of individuals.
|
||||
|
||||
**Consequence**: A permanent ban from any sort of public interaction within the
|
||||
community.
|
||||
|
||||
## Attribution
|
||||
|
||||
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
|
||||
version 2.1, available at
|
||||
[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
|
||||
|
||||
Community Impact Guidelines were inspired by
|
||||
[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
|
||||
|
||||
For answers to common questions about this code of conduct, see the FAQ at
|
||||
[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
|
||||
[https://www.contributor-covenant.org/translations][translations].
|
||||
|
||||
[homepage]: https://www.contributor-covenant.org
|
||||
[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
|
||||
[Mozilla CoC]: https://github.com/mozilla/diversity
|
||||
[FAQ]: https://www.contributor-covenant.org/faq
|
||||
[translations]: https://www.contributor-covenant.org/translations
|
||||
6
.github/CONTRIBUTING.md
vendored
6
.github/CONTRIBUTING.md
vendored
@@ -1,6 +0,0 @@
|
||||
# Contributing to LangChain
|
||||
|
||||
Hi there! Thank you for even being interested in contributing to LangChain.
|
||||
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether they involve new features, improved infrastructure, better documentation, or bug fixes.
|
||||
|
||||
To learn how to contribute to LangChain, please follow the [contribution guide here](https://docs.langchain.com/oss/python/contributing).
|
||||
121
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
121
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
@@ -1,121 +0,0 @@
|
||||
name: "\U0001F41B Bug Report"
|
||||
description: Report a bug in LangChain. To report a security issue, please instead use the security option below. For questions, please use the LangChain forum.
|
||||
labels: ["bug"]
|
||||
type: bug
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thank you for taking the time to file a bug report.
|
||||
|
||||
Use this to report BUGS in LangChain. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
|
||||
|
||||
Relevant links to check before filing a bug report to see if your issue has already been reported, fixed or
|
||||
if there's another way to solve your problem:
|
||||
|
||||
* [LangChain Forum](https://forum.langchain.com/),
|
||||
* [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
|
||||
* [API Reference](https://reference.langchain.com/python/),
|
||||
* [LangChain ChatBot](https://chat.langchain.com/)
|
||||
* [GitHub search](https://github.com/langchain-ai/langchain),
|
||||
- type: checkboxes
|
||||
id: checks
|
||||
attributes:
|
||||
label: Checked other resources
|
||||
description: Please confirm and check all the following options.
|
||||
options:
|
||||
- label: This is a bug, not a usage question.
|
||||
required: true
|
||||
- label: I added a clear and descriptive title that summarizes this issue.
|
||||
required: true
|
||||
- label: I used the GitHub search to find a similar question and didn't find it.
|
||||
required: true
|
||||
- label: I am sure that this is a bug in LangChain rather than my code.
|
||||
required: true
|
||||
- label: The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).
|
||||
required: true
|
||||
- label: This is not related to the langchain-community package.
|
||||
required: true
|
||||
- label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
|
||||
required: true
|
||||
- label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
|
||||
required: true
|
||||
- type: textarea
|
||||
id: reproduction
|
||||
validations:
|
||||
required: true
|
||||
attributes:
|
||||
label: Example Code
|
||||
description: |
|
||||
Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
|
||||
|
||||
If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
|
||||
|
||||
**Important!**
|
||||
|
||||
* Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
|
||||
* Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
|
||||
* Use code tags (e.g., ```python ... ```) to correctly [format your code](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting).
|
||||
* INCLUDE the language label (e.g. `python`) after the first three backticks to enable syntax highlighting. (e.g., ```python rather than ```).
|
||||
|
||||
placeholder: |
|
||||
The following code:
|
||||
|
||||
```python
|
||||
from langchain_core.runnables import RunnableLambda
|
||||
|
||||
def bad_code(inputs) -> int:
|
||||
raise NotImplementedError('For demo purpose')
|
||||
|
||||
chain = RunnableLambda(bad_code)
|
||||
chain.invoke('Hello!')
|
||||
```
|
||||
- type: textarea
|
||||
id: error
|
||||
validations:
|
||||
required: false
|
||||
attributes:
|
||||
label: Error Message and Stack Trace (if applicable)
|
||||
description: |
|
||||
If you are reporting an error, please include the full error message and stack trace.
|
||||
placeholder: |
|
||||
Exception + full stack trace
|
||||
- type: textarea
|
||||
id: description
|
||||
attributes:
|
||||
label: Description
|
||||
description: |
|
||||
What is the problem, question, or error?
|
||||
|
||||
Write a short description telling what you are doing, what you expect to happen, and what is currently happening.
|
||||
placeholder: |
|
||||
* I'm trying to use the `langchain` library to do X.
|
||||
* I expect to see Y.
|
||||
* Instead, it does Z.
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: system-info
|
||||
attributes:
|
||||
label: System Info
|
||||
description: |
|
||||
Please share your system info with us. Do NOT skip this step and please don't trim
|
||||
the output. Most users don't include enough information here and it makes it harder
|
||||
for us to help you.
|
||||
|
||||
Run the following command in your terminal and paste the output here:
|
||||
|
||||
`python -m langchain_core.sys_info`
|
||||
|
||||
or if you have an existing python interpreter running:
|
||||
|
||||
```python
|
||||
from langchain_core import sys_info
|
||||
sys_info.print_sys_info()
|
||||
```
|
||||
|
||||
alternatively, put the entire output of `pip freeze` here.
|
||||
placeholder: |
|
||||
python -m langchain_core.sys_info
|
||||
validations:
|
||||
required: true
|
||||
9
.github/ISSUE_TEMPLATE/config.yml
vendored
9
.github/ISSUE_TEMPLATE/config.yml
vendored
@@ -1,9 +0,0 @@
|
||||
blank_issues_enabled: false
|
||||
version: 2.1
|
||||
contact_links:
|
||||
- name: 📚 Documentation
|
||||
url: https://github.com/langchain-ai/docs/issues/new?template=01-langchain.yml
|
||||
about: Report an issue related to the LangChain documentation
|
||||
- name: 💬 LangChain Forum
|
||||
url: https://forum.langchain.com/
|
||||
about: General community discussions and support
|
||||
118
.github/ISSUE_TEMPLATE/feature-request.yml
vendored
118
.github/ISSUE_TEMPLATE/feature-request.yml
vendored
@@ -1,118 +0,0 @@
|
||||
name: "✨ Feature Request"
|
||||
description: Request a new feature or enhancement for LangChain. For questions, please use the LangChain forum.
|
||||
labels: ["feature request"]
|
||||
type: feature
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thank you for taking the time to request a new feature.
|
||||
|
||||
Use this to request NEW FEATURES or ENHANCEMENTS in LangChain. For bug reports, please use the bug report template. For usage questions and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
|
||||
|
||||
Relevant links to check before filing a feature request to see if your request has already been made or
|
||||
if there's another way to achieve what you want:
|
||||
|
||||
* [LangChain Forum](https://forum.langchain.com/),
|
||||
* [LangChain documentation with the integrated search](https://docs.langchain.com/oss/python/langchain/overview),
|
||||
* [API Reference](https://reference.langchain.com/python/),
|
||||
* [LangChain ChatBot](https://chat.langchain.com/)
|
||||
* [GitHub search](https://github.com/langchain-ai/langchain),
|
||||
- type: checkboxes
|
||||
id: checks
|
||||
attributes:
|
||||
label: Checked other resources
|
||||
description: Please confirm and check all the following options.
|
||||
options:
|
||||
- label: This is a feature request, not a bug report or usage question.
|
||||
required: true
|
||||
- label: I added a clear and descriptive title that summarizes the feature request.
|
||||
required: true
|
||||
- label: I used the GitHub search to find a similar feature request and didn't find it.
|
||||
required: true
|
||||
- label: I checked the LangChain documentation and API reference to see if this feature already exists.
|
||||
required: true
|
||||
- label: This is not related to the langchain-community package.
|
||||
required: true
|
||||
- type: textarea
|
||||
id: feature-description
|
||||
validations:
|
||||
required: true
|
||||
attributes:
|
||||
label: Feature Description
|
||||
description: |
|
||||
Please provide a clear and concise description of the feature you would like to see added to LangChain.
|
||||
|
||||
What specific functionality are you requesting? Be as detailed as possible.
|
||||
placeholder: |
|
||||
I would like LangChain to support...
|
||||
|
||||
This feature would allow users to...
|
||||
- type: textarea
|
||||
id: use-case
|
||||
validations:
|
||||
required: true
|
||||
attributes:
|
||||
label: Use Case
|
||||
description: |
|
||||
Describe the specific use case or problem this feature would solve.
|
||||
|
||||
Why do you need this feature? What problem does it solve for you or other users?
|
||||
placeholder: |
|
||||
I'm trying to build an application that...
|
||||
|
||||
Currently, I have to work around this by...
|
||||
|
||||
This feature would help me/users to...
|
||||
- type: textarea
|
||||
id: proposed-solution
|
||||
validations:
|
||||
required: false
|
||||
attributes:
|
||||
label: Proposed Solution
|
||||
description: |
|
||||
If you have ideas about how this feature could be implemented, please describe them here.
|
||||
|
||||
This is optional but can be helpful for maintainers to understand your vision.
|
||||
placeholder: |
|
||||
I think this could be implemented by...
|
||||
|
||||
The API could look like...
|
||||
|
||||
```python
|
||||
# Example of how the feature might work
|
||||
```
|
||||
- type: textarea
|
||||
id: alternatives
|
||||
validations:
|
||||
required: false
|
||||
attributes:
|
||||
label: Alternatives Considered
|
||||
description: |
|
||||
Have you considered any alternative solutions or workarounds?
|
||||
|
||||
What other approaches have you tried or considered?
|
||||
placeholder: |
|
||||
I've tried using...
|
||||
|
||||
Alternative approaches I considered:
|
||||
1. ...
|
||||
2. ...
|
||||
|
||||
But these don't work because...
|
||||
- type: textarea
|
||||
id: additional-context
|
||||
validations:
|
||||
required: false
|
||||
attributes:
|
||||
label: Additional Context
|
||||
description: |
|
||||
Add any other context, screenshots, examples, or references that would help explain your feature request.
|
||||
placeholder: |
|
||||
Related issues: #...
|
||||
|
||||
Similar features in other libraries:
|
||||
- ...
|
||||
|
||||
Additional context or examples:
|
||||
- ...
|
||||
20
.github/ISSUE_TEMPLATE/privileged.yml
vendored
20
.github/ISSUE_TEMPLATE/privileged.yml
vendored
@@ -1,20 +0,0 @@
|
||||
name: 🔒 Privileged
|
||||
description: You are a LangChain maintainer, or was asked directly by a maintainer to create an issue here. If not, check the other options.
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
If you are not a LangChain maintainer, employee, or were not asked directly by a maintainer to create an issue, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead.
|
||||
- type: checkboxes
|
||||
id: privileged
|
||||
attributes:
|
||||
label: Privileged issue
|
||||
description: Confirm that you are allowed to create an issue here.
|
||||
options:
|
||||
- label: I am a LangChain maintainer, or was asked directly by a LangChain maintainer to create an issue here.
|
||||
required: true
|
||||
- type: textarea
|
||||
id: content
|
||||
attributes:
|
||||
label: Issue Content
|
||||
description: Add the content of the issue here.
|
||||
91
.github/ISSUE_TEMPLATE/task.yml
vendored
91
.github/ISSUE_TEMPLATE/task.yml
vendored
@@ -1,91 +0,0 @@
|
||||
name: "📋 Task"
|
||||
description: Create a task for project management and tracking by LangChain maintainers. If you are not a maintainer, please use other templates or the forum.
|
||||
labels: ["task"]
|
||||
type: task
|
||||
body:
|
||||
- type: markdown
|
||||
attributes:
|
||||
value: |
|
||||
Thanks for creating a task to help organize LangChain development.
|
||||
|
||||
This template is for **maintainer tasks** such as project management, development planning, refactoring, documentation updates, and other organizational work.
|
||||
|
||||
If you are not a LangChain maintainer or were not asked directly by a maintainer to create a task, then please start the conversation on the [LangChain Forum](https://forum.langchain.com/) instead or use the appropriate bug report or feature request templates on the previous page.
|
||||
- type: checkboxes
|
||||
id: maintainer
|
||||
attributes:
|
||||
label: Maintainer task
|
||||
description: Confirm that you are allowed to create a task here.
|
||||
options:
|
||||
- label: I am a LangChain maintainer, or was asked directly by a LangChain maintainer to create a task here.
|
||||
required: true
|
||||
- type: textarea
|
||||
id: task-description
|
||||
attributes:
|
||||
label: Task Description
|
||||
description: |
|
||||
Provide a clear and detailed description of the task.
|
||||
|
||||
What needs to be done? Be specific about the scope and requirements.
|
||||
placeholder: |
|
||||
This task involves...
|
||||
|
||||
The goal is to...
|
||||
|
||||
Specific requirements:
|
||||
- ...
|
||||
- ...
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: acceptance-criteria
|
||||
attributes:
|
||||
label: Acceptance Criteria
|
||||
description: |
|
||||
Define the criteria that must be met for this task to be considered complete.
|
||||
|
||||
What are the specific deliverables or outcomes expected?
|
||||
placeholder: |
|
||||
This task will be complete when:
|
||||
- [ ] ...
|
||||
- [ ] ...
|
||||
- [ ] ...
|
||||
validations:
|
||||
required: true
|
||||
- type: textarea
|
||||
id: context
|
||||
attributes:
|
||||
label: Context and Background
|
||||
description: |
|
||||
Provide any relevant context, background information, or links to related issues/PRs.
|
||||
|
||||
Why is this task needed? What problem does it solve?
|
||||
placeholder: |
|
||||
Background:
|
||||
- ...
|
||||
|
||||
Related issues/PRs:
|
||||
- #...
|
||||
|
||||
Additional context:
|
||||
- ...
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
id: dependencies
|
||||
attributes:
|
||||
label: Dependencies
|
||||
description: |
|
||||
List any dependencies or blockers for this task.
|
||||
|
||||
Are there other tasks, issues, or external factors that need to be completed first?
|
||||
placeholder: |
|
||||
This task depends on:
|
||||
- [ ] Issue #...
|
||||
- [ ] PR #...
|
||||
- [ ] External dependency: ...
|
||||
|
||||
Blocked by:
|
||||
- ...
|
||||
validations:
|
||||
required: false
|
||||
28
.github/PULL_REQUEST_TEMPLATE.md
vendored
28
.github/PULL_REQUEST_TEMPLATE.md
vendored
@@ -1,28 +0,0 @@
|
||||
(Replace this entire block of text)
|
||||
|
||||
Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
|
||||
|
||||
- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
|
||||
- Examples:
|
||||
- feat(core): add multi-tenant support
|
||||
- fix(cli): resolve flag parsing error
|
||||
- docs(openai): update API usage examples
|
||||
- Allowed `{TYPE}` values:
|
||||
- feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
|
||||
- Allowed `{SCOPE}` values (optional):
|
||||
- core, cli, langchain, standard-tests, text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant, xai, infra
|
||||
- Once you've written the title, please delete this checklist item; do not include it in the PR.
|
||||
|
||||
- [ ] **PR message**: ***Delete this entire checklist*** and replace with
|
||||
- **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable to a relevant issue.
|
||||
- **Issue:** the issue # it fixes, if applicable (e.g. Fixes #123)
|
||||
- **Dependencies:** any dependencies required for this change
|
||||
|
||||
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://docs.langchain.com/oss/python/contributing) for more.
|
||||
|
||||
Additional guidelines:
|
||||
|
||||
- Most PRs should not touch more than one package.
|
||||
- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests. Likewise, please do not update the `uv.lock` files unless you are adding a required dependency.
|
||||
- Changes should be backwards compatible.
|
||||
- Make sure optional dependencies are imported within a function.
|
||||
39
.github/actions/uv_setup/action.yml
vendored
39
.github/actions/uv_setup/action.yml
vendored
@@ -1,39 +0,0 @@
|
||||
# Helper to set up Python and uv with caching
|
||||
|
||||
name: uv-install
|
||||
description: Set up Python and uv with caching
|
||||
|
||||
inputs:
|
||||
python-version:
|
||||
description: Python version, supporting MAJOR.MINOR only
|
||||
required: true
|
||||
enable-cache:
|
||||
description: Enable caching for uv dependencies
|
||||
required: false
|
||||
default: "true"
|
||||
cache-suffix:
|
||||
description: Custom cache key suffix for cache invalidation
|
||||
required: false
|
||||
default: ""
|
||||
working-directory:
|
||||
description: Working directory for cache glob scoping
|
||||
required: false
|
||||
default: "**"
|
||||
|
||||
env:
|
||||
UV_VERSION: "0.5.25"
|
||||
|
||||
runs:
|
||||
using: composite
|
||||
steps:
|
||||
- name: Install uv and set the python version
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
version: ${{ env.UV_VERSION }}
|
||||
python-version: ${{ inputs.python-version }}
|
||||
enable-cache: ${{ inputs.enable-cache }}
|
||||
cache-dependency-glob: |
|
||||
${{ inputs.working-directory }}/pyproject.toml
|
||||
${{ inputs.working-directory }}/uv.lock
|
||||
${{ inputs.working-directory }}/requirements*.txt
|
||||
cache-suffix: ${{ inputs.cache-suffix }}
|
||||
330
.github/copilot-instructions.md
vendored
330
.github/copilot-instructions.md
vendored
@@ -1,330 +0,0 @@
|
||||
# Global Development Guidelines for LangChain Projects
|
||||
|
||||
## Core Development Principles
|
||||
|
||||
### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
|
||||
|
||||
**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
|
||||
|
||||
❌ **Bad - Breaking Change:**
|
||||
|
||||
```python
|
||||
def get_user(id, verbose=False): # Changed from `user_id`
|
||||
pass
|
||||
```
|
||||
|
||||
✅ **Good - Stable Interface:**
|
||||
|
||||
```python
|
||||
def get_user(user_id: str, verbose: bool = False) -> User:
|
||||
"""Retrieve user by ID with optional verbose output."""
|
||||
pass
|
||||
```
|
||||
|
||||
**Before making ANY changes to public APIs:**
|
||||
|
||||
- Check if the function/class is exported in `__init__.py`
|
||||
- Look for existing usage patterns in tests and examples
|
||||
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
|
||||
- Mark experimental features clearly with docstring admonitions (using MkDocs Material, like `!!! warning`)
|
||||
|
||||
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
|
||||
|
||||
### 2. Code Quality Standards
|
||||
|
||||
**All Python code MUST include type hints and return types.**
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def p(u, d):
|
||||
return [x for x in u if x not in d]
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
|
||||
"""Filter out users that are not in the known users set.
|
||||
|
||||
Args:
|
||||
users: List of user identifiers to filter.
|
||||
known_users: Set of known/valid user identifiers.
|
||||
|
||||
Returns:
|
||||
List of users that are not in the known_users set.
|
||||
"""
|
||||
return [user for user in users if user not in known_users]
|
||||
```
|
||||
|
||||
**Style Requirements:**
|
||||
|
||||
- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
|
||||
- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
|
||||
- Avoid unnecessary abstraction or premature optimization
|
||||
- Follow existing patterns in the codebase you're modifying
|
||||
|
||||
### 3. Testing Requirements
|
||||
|
||||
**Every new feature or bugfix MUST be covered by unit tests.**
|
||||
|
||||
**Test Organization:**
|
||||
|
||||
- Unit tests: `tests/unit_tests/` (no network calls allowed)
|
||||
- Integration tests: `tests/integration_tests/` (network calls permitted)
|
||||
- Use `pytest` as the testing framework
|
||||
|
||||
**Test Quality Checklist:**
|
||||
|
||||
- [ ] Tests fail when your new logic is broken
|
||||
- [ ] Happy path is covered
|
||||
- [ ] Edge cases and error conditions are tested
|
||||
- [ ] Use fixtures/mocks for external dependencies
|
||||
- [ ] Tests are deterministic (no flaky tests)
|
||||
|
||||
Checklist questions:
|
||||
|
||||
- [ ] Does the test suite fail if your new logic is broken?
|
||||
- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
|
||||
- [ ] Do tests use fixtures or mocks where needed?
|
||||
|
||||
```python
|
||||
def test_filter_unknown_users():
|
||||
"""Test filtering unknown users from a list."""
|
||||
users = ["alice", "bob", "charlie"]
|
||||
known_users = {"alice", "bob"}
|
||||
|
||||
result = filter_unknown_users(users, known_users)
|
||||
|
||||
assert result == ["charlie"]
|
||||
assert len(result) == 1
|
||||
```
|
||||
|
||||
### 4. Security and Risk Assessment
|
||||
|
||||
**Security Checklist:**
|
||||
|
||||
- No `eval()`, `exec()`, or `pickle` on user-controlled input
|
||||
- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
|
||||
- Remove unreachable/commented code before committing
|
||||
- Race conditions or resource leaks (file handles, sockets, threads).
|
||||
- Ensure proper resource cleanup (file handles, connections)
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def load_config(path):
|
||||
with open(path) as f:
|
||||
return eval(f.read()) # ⚠️ Never eval config
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
def load_config(path: str) -> dict:
|
||||
with open(path) as f:
|
||||
return json.load(f)
|
||||
```
|
||||
|
||||
### 5. Documentation Standards
|
||||
|
||||
**Use Google-style docstrings with Args and Returns sections for all public functions.**
|
||||
|
||||
❌ **Insufficient Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to, msg):
|
||||
"""Send an email to a recipient."""
|
||||
```
|
||||
|
||||
✅ **Complete Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
|
||||
"""
|
||||
Send an email to a recipient with specified priority.
|
||||
|
||||
Args:
|
||||
to: The email address of the recipient.
|
||||
msg: The message body to send.
|
||||
priority: Email priority level.
|
||||
|
||||
Returns:
|
||||
True if email was sent successfully, False otherwise.
|
||||
|
||||
Raises:
|
||||
InvalidEmailError: If the email address format is invalid.
|
||||
SMTPConnectionError: If unable to connect to email server.
|
||||
"""
|
||||
```
|
||||
|
||||
**Documentation Guidelines:**
|
||||
|
||||
- Types go in function signatures, NOT in docstrings
|
||||
- Focus on "why" rather than "what" in descriptions
|
||||
- Document all parameters, return values, and exceptions
|
||||
- Keep descriptions concise but clear
|
||||
|
||||
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
|
||||
|
||||
### 6. Architectural Improvements
|
||||
|
||||
**When you encounter code that could be improved, suggest better designs:**
|
||||
|
||||
❌ **Poor Design:**
|
||||
|
||||
```python
|
||||
def process_data(data, db_conn, email_client, logger):
|
||||
# Function doing too many things
|
||||
validated = validate_data(data)
|
||||
result = db_conn.save(validated)
|
||||
email_client.send_notification(result)
|
||||
logger.log(f"Processed {len(data)} items")
|
||||
return result
|
||||
```
|
||||
|
||||
✅ **Better Design:**
|
||||
|
||||
```python
|
||||
@dataclass
|
||||
class ProcessingResult:
|
||||
"""Result of data processing operation."""
|
||||
items_processed: int
|
||||
success: bool
|
||||
errors: List[str] = field(default_factory=list)
|
||||
|
||||
class DataProcessor:
|
||||
"""Handles data validation, storage, and notification."""
|
||||
|
||||
def __init__(self, db_conn: Database, email_client: EmailClient):
|
||||
self.db = db_conn
|
||||
self.email = email_client
|
||||
|
||||
def process(self, data: List[dict]) -> ProcessingResult:
|
||||
"""Process and store data with notifications.
|
||||
|
||||
Args:
|
||||
data: List of data items to process.
|
||||
|
||||
Returns:
|
||||
ProcessingResult with details of the operation.
|
||||
"""
|
||||
validated = self._validate_data(data)
|
||||
result = self.db.save(validated)
|
||||
self._notify_completion(result)
|
||||
return result
|
||||
```
|
||||
|
||||
**Design Improvement Areas:**
|
||||
|
||||
If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
|
||||
|
||||
- Reduce code duplication through shared utilities
|
||||
- Make unit testing easier
|
||||
- Improve separation of concerns (single responsibility)
|
||||
- Make unit testing easier through dependency injection
|
||||
- Add clarity without adding complexity
|
||||
- Prefer dataclasses for structured data
|
||||
|
||||
## Development Tools & Commands
|
||||
|
||||
### Package Management
|
||||
|
||||
```bash
|
||||
# Add package
|
||||
uv add package-name
|
||||
|
||||
# Sync project dependencies
|
||||
uv sync
|
||||
uv lock
|
||||
```
|
||||
|
||||
### Testing
|
||||
|
||||
```bash
|
||||
# Run unit tests (no network)
|
||||
make test
|
||||
|
||||
# Don't run integration tests, as API keys must be set
|
||||
|
||||
# Run specific test file
|
||||
uv run --group test pytest tests/unit_tests/test_specific.py
|
||||
```
|
||||
|
||||
### Code Quality
|
||||
|
||||
```bash
|
||||
# Lint code
|
||||
make lint
|
||||
|
||||
# Format code
|
||||
make format
|
||||
|
||||
# Type checking
|
||||
uv run --group lint mypy .
|
||||
```
|
||||
|
||||
### Dependency Management Patterns
|
||||
|
||||
**Local Development Dependencies:**
|
||||
|
||||
```toml
|
||||
[tool.uv.sources]
|
||||
langchain-core = { path = "../core", editable = true }
|
||||
langchain-tests = { path = "../standard-tests", editable = true }
|
||||
```
|
||||
|
||||
**For tools, use the `@tool` decorator from `langchain_core.tools`:**
|
||||
|
||||
```python
|
||||
from langchain_core.tools import tool
|
||||
|
||||
@tool
|
||||
def search_database(query: str) -> str:
|
||||
"""Search the database for relevant information.
|
||||
|
||||
Args:
|
||||
query: The search query string.
|
||||
"""
|
||||
# Implementation here
|
||||
return results
|
||||
```
|
||||
|
||||
## Commit Standards
|
||||
|
||||
**Use Conventional Commits format for PR titles:**
|
||||
|
||||
- `feat(core): add multi-tenant support`
|
||||
- `!fix(cli): resolve flag parsing error` (breaking change uses exclamation mark)
|
||||
- `docs: update API usage examples`
|
||||
- `docs(openai): update API usage examples`
|
||||
|
||||
## Framework-Specific Guidelines
|
||||
|
||||
- Follow the existing patterns in `langchain_core` for base abstractions
|
||||
- Implement proper streaming support where applicable
|
||||
- Avoid deprecated components
|
||||
|
||||
### Partner Integrations
|
||||
|
||||
- Follow the established patterns in existing partner libraries
|
||||
- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
|
||||
- Include comprehensive integration tests
|
||||
- Document API key requirements and authentication
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference Checklist
|
||||
|
||||
Before submitting code changes:
|
||||
|
||||
- [ ] **Breaking Changes**: Verified no public API changes
|
||||
- [ ] **Type Hints**: All functions have complete type annotations
|
||||
- [ ] **Tests**: New functionality is fully tested
|
||||
- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
|
||||
- [ ] **Documentation**: Google-style docstrings for public functions
|
||||
- [ ] **Code Quality**: `make lint` and `make format` pass
|
||||
- [ ] **Architecture**: Suggested improvements where applicable
|
||||
- [ ] **Commit Message**: Follows Conventional Commits format
|
||||
11
.github/dependabot.yml
vendored
11
.github/dependabot.yml
vendored
@@ -1,11 +0,0 @@
|
||||
# Please see the documentation for all configuration options:
|
||||
# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
|
||||
# and
|
||||
# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
|
||||
|
||||
version: 2
|
||||
updates:
|
||||
- package-ecosystem: "github-actions"
|
||||
directory: "/"
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
25
.github/images/logo-dark.svg
vendored
25
.github/images/logo-dark.svg
vendored
@@ -1,25 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1584.81 250">
|
||||
<defs>
|
||||
<style>
|
||||
.cls-1 {
|
||||
fill: #1c3c3c;
|
||||
stroke-width: 0px;
|
||||
}
|
||||
</style>
|
||||
</defs>
|
||||
<g id="LanChain-logo">
|
||||
<g id="LangChain-logotype">
|
||||
<polygon class="cls-1" points="596.33 49.07 596.33 200.67 700.76 200.67 700.76 177.78 620.04 177.78 620.04 49.07 596.33 49.07"/>
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||||
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||||
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||||
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<circle class="cls-1" cx="1450.93" cy="64.47" r="15.37"/>
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||||
</g>
|
||||
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||||
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|
||||
|
Before Width: | Height: | Size: 6.4 KiB |
25
.github/images/logo-light.svg
vendored
25
.github/images/logo-light.svg
vendored
@@ -1,25 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1584.81 250">
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||||
<defs>
|
||||
<style>
|
||||
.cls-1 {
|
||||
fill: #fff;
|
||||
stroke-width: 0px;
|
||||
}
|
||||
</style>
|
||||
</defs>
|
||||
<g id="LanChain-logo">
|
||||
<g id="LangChain-logotype">
|
||||
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|
||||
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|
Before Width: | Height: | Size: 6.4 KiB |
84
.github/pr-file-labeler.yml
vendored
84
.github/pr-file-labeler.yml
vendored
@@ -1,84 +0,0 @@
|
||||
# Label PRs (config)
|
||||
# Automatically applies labels based on changed files and branch patterns
|
||||
|
||||
# Core packages
|
||||
core:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/core/**/*"
|
||||
|
||||
langchain:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/langchain/**/*"
|
||||
- "libs/langchain_v1/**/*"
|
||||
|
||||
v1:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/langchain_v1/**/*"
|
||||
|
||||
cli:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/cli/**/*"
|
||||
|
||||
standard-tests:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/standard-tests/**/*"
|
||||
|
||||
text-splitters:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/text-splitters/**/*"
|
||||
|
||||
# Partner integrations
|
||||
integration:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "libs/partners/**/*"
|
||||
|
||||
# Infrastructure and DevOps
|
||||
infra:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- ".github/**/*"
|
||||
- "Makefile"
|
||||
- ".pre-commit-config.yaml"
|
||||
- "scripts/**/*"
|
||||
- "docker/**/*"
|
||||
- "Dockerfile*"
|
||||
|
||||
github_actions:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- ".github/workflows/**/*"
|
||||
- ".github/actions/**/*"
|
||||
|
||||
dependencies:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "**/pyproject.toml"
|
||||
- "uv.lock"
|
||||
- "**/requirements*.txt"
|
||||
- "**/poetry.lock"
|
||||
|
||||
# Documentation
|
||||
documentation:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "**/*.md"
|
||||
- "**/*.rst"
|
||||
- "**/README*"
|
||||
|
||||
# Security related changes
|
||||
security:
|
||||
- changed-files:
|
||||
- any-glob-to-any-file:
|
||||
- "**/*security*"
|
||||
- "**/*auth*"
|
||||
- "**/*credential*"
|
||||
- "**/*secret*"
|
||||
- "**/*token*"
|
||||
- ".github/workflows/security*"
|
||||
340
.github/scripts/check_diff.py
vendored
340
.github/scripts/check_diff.py
vendored
@@ -1,340 +0,0 @@
|
||||
"""Analyze git diffs to determine which directories need to be tested.
|
||||
|
||||
Intelligently determines which LangChain packages and directories need to be tested,
|
||||
linted, or built based on the changes. Handles dependency relationships between
|
||||
packages, maps file changes to appropriate CI job configurations, and outputs JSON
|
||||
configurations for GitHub Actions.
|
||||
|
||||
- Maps changed files to affected package directories (libs/core, libs/partners/*, etc.)
|
||||
- Builds dependency graph to include dependent packages when core components change
|
||||
- Generates test matrix configurations with appropriate Python versions
|
||||
- Handles special cases for Pydantic version testing and performance benchmarks
|
||||
|
||||
Used as part of the check_diffs workflow.
|
||||
"""
|
||||
|
||||
import glob
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from collections import defaultdict
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Set
|
||||
|
||||
import tomllib
|
||||
from get_min_versions import get_min_version_from_toml
|
||||
from packaging.requirements import Requirement
|
||||
|
||||
LANGCHAIN_DIRS = [
|
||||
"libs/core",
|
||||
"libs/text-splitters",
|
||||
"libs/langchain",
|
||||
"libs/langchain_v1",
|
||||
"libs/model-profiles",
|
||||
]
|
||||
|
||||
# When set to True, we are ignoring core dependents
|
||||
# in order to be able to get CI to pass for each individual
|
||||
# package that depends on core
|
||||
# e.g. if you touch core, we don't then add textsplitters/etc to CI
|
||||
IGNORE_CORE_DEPENDENTS = False
|
||||
|
||||
# ignored partners are removed from dependents
|
||||
# but still run if directly edited
|
||||
IGNORED_PARTNERS = [
|
||||
# remove huggingface from dependents because of CI instability
|
||||
# specifically in huggingface jobs
|
||||
# https://github.com/langchain-ai/langchain/issues/25558
|
||||
"huggingface",
|
||||
# prompty exhibiting issues with numpy for Python 3.13
|
||||
# https://github.com/langchain-ai/langchain/actions/runs/12651104685/job/35251034969?pr=29065
|
||||
"prompty",
|
||||
]
|
||||
|
||||
|
||||
def all_package_dirs() -> Set[str]:
|
||||
return {
|
||||
"/".join(path.split("/")[:-1]).lstrip("./")
|
||||
for path in glob.glob("./libs/**/pyproject.toml", recursive=True)
|
||||
if "libs/cli" not in path and "libs/standard-tests" not in path
|
||||
}
|
||||
|
||||
|
||||
def dependents_graph() -> dict:
|
||||
"""Construct a mapping of package -> dependents
|
||||
|
||||
Done such that we can run tests on all dependents of a package when a change is made.
|
||||
"""
|
||||
dependents = defaultdict(set)
|
||||
|
||||
for path in glob.glob("./libs/**/pyproject.toml", recursive=True):
|
||||
if "template" in path:
|
||||
continue
|
||||
|
||||
# load regular and test deps from pyproject.toml
|
||||
with open(path, "rb") as f:
|
||||
pyproject = tomllib.load(f)
|
||||
|
||||
pkg_dir = "libs" + "/".join(path.split("libs")[1].split("/")[:-1])
|
||||
for dep in [
|
||||
*pyproject["project"]["dependencies"],
|
||||
*pyproject["dependency-groups"]["test"],
|
||||
]:
|
||||
requirement = Requirement(dep)
|
||||
package_name = requirement.name
|
||||
if "langchain" in dep:
|
||||
dependents[package_name].add(pkg_dir)
|
||||
continue
|
||||
|
||||
# load extended deps from extended_testing_deps.txt
|
||||
package_path = Path(path).parent
|
||||
extended_requirement_path = package_path / "extended_testing_deps.txt"
|
||||
if extended_requirement_path.exists():
|
||||
with open(extended_requirement_path, "r") as f:
|
||||
extended_deps = f.read().splitlines()
|
||||
for depline in extended_deps:
|
||||
if depline.startswith("-e "):
|
||||
# editable dependency
|
||||
assert depline.startswith("-e ../partners/"), (
|
||||
"Extended test deps should only editable install partner packages"
|
||||
)
|
||||
partner = depline.split("partners/")[1]
|
||||
dep = f"langchain-{partner}"
|
||||
else:
|
||||
dep = depline.split("==")[0]
|
||||
|
||||
if "langchain" in dep:
|
||||
dependents[dep].add(pkg_dir)
|
||||
|
||||
for k in dependents:
|
||||
for partner in IGNORED_PARTNERS:
|
||||
if f"libs/partners/{partner}" in dependents[k]:
|
||||
dependents[k].remove(f"libs/partners/{partner}")
|
||||
return dependents
|
||||
|
||||
|
||||
def add_dependents(dirs_to_eval: Set[str], dependents: dict) -> List[str]:
|
||||
updated = set()
|
||||
for dir_ in dirs_to_eval:
|
||||
# handle core manually because it has so many dependents
|
||||
if "core" in dir_:
|
||||
updated.add(dir_)
|
||||
continue
|
||||
pkg = "langchain-" + dir_.split("/")[-1]
|
||||
updated.update(dependents[pkg])
|
||||
updated.add(dir_)
|
||||
return list(updated)
|
||||
|
||||
|
||||
def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
|
||||
if job == "test-pydantic":
|
||||
return _get_pydantic_test_configs(dir_)
|
||||
|
||||
if job == "codspeed":
|
||||
py_versions = ["3.13"]
|
||||
elif dir_ == "libs/core":
|
||||
py_versions = ["3.10", "3.11", "3.12", "3.13", "3.14"]
|
||||
# custom logic for specific directories
|
||||
elif dir_ in {"libs/partners/chroma"}:
|
||||
py_versions = ["3.10", "3.13"]
|
||||
else:
|
||||
py_versions = ["3.10", "3.14"]
|
||||
|
||||
return [{"working-directory": dir_, "python-version": py_v} for py_v in py_versions]
|
||||
|
||||
|
||||
def _get_pydantic_test_configs(
|
||||
dir_: str, *, python_version: str = "3.12"
|
||||
) -> List[Dict[str, str]]:
|
||||
with open("./libs/core/uv.lock", "rb") as f:
|
||||
core_uv_lock_data = tomllib.load(f)
|
||||
for package in core_uv_lock_data["package"]:
|
||||
if package["name"] == "pydantic":
|
||||
core_max_pydantic_minor = package["version"].split(".")[1]
|
||||
break
|
||||
|
||||
with open(f"./{dir_}/uv.lock", "rb") as f:
|
||||
dir_uv_lock_data = tomllib.load(f)
|
||||
|
||||
for package in dir_uv_lock_data["package"]:
|
||||
if package["name"] == "pydantic":
|
||||
dir_max_pydantic_minor = package["version"].split(".")[1]
|
||||
break
|
||||
|
||||
core_min_pydantic_version = get_min_version_from_toml(
|
||||
"./libs/core/pyproject.toml", "release", python_version, include=["pydantic"]
|
||||
)["pydantic"]
|
||||
core_min_pydantic_minor = (
|
||||
core_min_pydantic_version.split(".")[1]
|
||||
if "." in core_min_pydantic_version
|
||||
else "0"
|
||||
)
|
||||
dir_min_pydantic_version = get_min_version_from_toml(
|
||||
f"./{dir_}/pyproject.toml", "release", python_version, include=["pydantic"]
|
||||
).get("pydantic", "0.0.0")
|
||||
dir_min_pydantic_minor = (
|
||||
dir_min_pydantic_version.split(".")[1]
|
||||
if "." in dir_min_pydantic_version
|
||||
else "0"
|
||||
)
|
||||
|
||||
max_pydantic_minor = min(
|
||||
int(dir_max_pydantic_minor),
|
||||
int(core_max_pydantic_minor),
|
||||
)
|
||||
min_pydantic_minor = max(
|
||||
int(dir_min_pydantic_minor),
|
||||
int(core_min_pydantic_minor),
|
||||
)
|
||||
|
||||
configs = [
|
||||
{
|
||||
"working-directory": dir_,
|
||||
"pydantic-version": f"2.{v}.0",
|
||||
"python-version": python_version,
|
||||
}
|
||||
for v in range(min_pydantic_minor, max_pydantic_minor + 1)
|
||||
]
|
||||
return configs
|
||||
|
||||
|
||||
def _get_configs_for_multi_dirs(
|
||||
job: str, dirs_to_run: Dict[str, Set[str]], dependents: dict
|
||||
) -> List[Dict[str, str]]:
|
||||
if job == "lint":
|
||||
dirs = add_dependents(
|
||||
dirs_to_run["lint"] | dirs_to_run["test"] | dirs_to_run["extended-test"],
|
||||
dependents,
|
||||
)
|
||||
elif job in ["test", "compile-integration-tests", "dependencies", "test-pydantic"]:
|
||||
dirs = add_dependents(
|
||||
dirs_to_run["test"] | dirs_to_run["extended-test"], dependents
|
||||
)
|
||||
elif job == "extended-tests":
|
||||
dirs = list(dirs_to_run["extended-test"])
|
||||
elif job == "codspeed":
|
||||
dirs = list(dirs_to_run["codspeed"])
|
||||
else:
|
||||
raise ValueError(f"Unknown job: {job}")
|
||||
|
||||
return [
|
||||
config for dir_ in dirs for config in _get_configs_for_single_dir(job, dir_)
|
||||
]
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
files = sys.argv[1:]
|
||||
|
||||
dirs_to_run: Dict[str, set] = {
|
||||
"lint": set(),
|
||||
"test": set(),
|
||||
"extended-test": set(),
|
||||
"codspeed": set(),
|
||||
}
|
||||
docs_edited = False
|
||||
|
||||
if len(files) >= 300:
|
||||
# max diff length is 300 files - there are likely files missing
|
||||
dirs_to_run["lint"] = all_package_dirs()
|
||||
dirs_to_run["test"] = all_package_dirs()
|
||||
dirs_to_run["extended-test"] = set(LANGCHAIN_DIRS)
|
||||
|
||||
for file in files:
|
||||
if any(
|
||||
file.startswith(dir_)
|
||||
for dir_ in (
|
||||
".github/workflows",
|
||||
".github/tools",
|
||||
".github/actions",
|
||||
".github/scripts/check_diff.py",
|
||||
)
|
||||
):
|
||||
# Infrastructure changes (workflows, actions, CI scripts) trigger tests on
|
||||
# all core packages as a safety measure. This ensures that changes to CI/CD
|
||||
# infrastructure don't inadvertently break package testing, even if the change
|
||||
# appears unrelated (e.g., documentation build workflows). This is intentionally
|
||||
# conservative to catch unexpected side effects from workflow modifications.
|
||||
#
|
||||
# Example: A PR modifying .github/workflows/api_doc_build.yml will trigger
|
||||
# lint/test jobs for libs/core, libs/text-splitters, libs/langchain, and
|
||||
# libs/langchain_v1, even though the workflow may only affect documentation.
|
||||
dirs_to_run["extended-test"].update(LANGCHAIN_DIRS)
|
||||
|
||||
if file.startswith("libs/core"):
|
||||
dirs_to_run["codspeed"].add("libs/core")
|
||||
if any(file.startswith(dir_) for dir_ in LANGCHAIN_DIRS):
|
||||
# add that dir and all dirs after in LANGCHAIN_DIRS
|
||||
# for extended testing
|
||||
|
||||
found = False
|
||||
for dir_ in LANGCHAIN_DIRS:
|
||||
if dir_ == "libs/core" and IGNORE_CORE_DEPENDENTS:
|
||||
dirs_to_run["extended-test"].add(dir_)
|
||||
continue
|
||||
if file.startswith(dir_):
|
||||
found = True
|
||||
if found:
|
||||
dirs_to_run["extended-test"].add(dir_)
|
||||
elif file.startswith("libs/standard-tests"):
|
||||
# TODO: update to include all packages that rely on standard-tests (all partner packages)
|
||||
# Note: won't run on external repo partners
|
||||
dirs_to_run["lint"].add("libs/standard-tests")
|
||||
dirs_to_run["test"].add("libs/standard-tests")
|
||||
dirs_to_run["test"].add("libs/partners/mistralai")
|
||||
dirs_to_run["test"].add("libs/partners/openai")
|
||||
dirs_to_run["test"].add("libs/partners/anthropic")
|
||||
dirs_to_run["test"].add("libs/partners/fireworks")
|
||||
dirs_to_run["test"].add("libs/partners/groq")
|
||||
|
||||
elif file.startswith("libs/cli"):
|
||||
dirs_to_run["lint"].add("libs/cli")
|
||||
dirs_to_run["test"].add("libs/cli")
|
||||
|
||||
elif file.startswith("libs/partners"):
|
||||
partner_dir = file.split("/")[2]
|
||||
if os.path.isdir(f"libs/partners/{partner_dir}") and [
|
||||
filename
|
||||
for filename in os.listdir(f"libs/partners/{partner_dir}")
|
||||
if not filename.startswith(".")
|
||||
] != ["README.md"]:
|
||||
dirs_to_run["test"].add(f"libs/partners/{partner_dir}")
|
||||
# Skip codspeed for partners without benchmarks or in IGNORED_PARTNERS
|
||||
if partner_dir not in IGNORED_PARTNERS:
|
||||
dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
|
||||
# Skip if the directory was deleted or is just a tombstone readme
|
||||
elif file.startswith("libs/"):
|
||||
# Check if this is a root-level file in libs/ (e.g., libs/README.md)
|
||||
file_parts = file.split("/")
|
||||
if len(file_parts) == 2:
|
||||
# Root-level file in libs/, skip it (no tests needed)
|
||||
continue
|
||||
raise ValueError(
|
||||
f"Unknown lib: {file}. check_diff.py likely needs "
|
||||
"an update for this new library!"
|
||||
)
|
||||
elif file in [
|
||||
"pyproject.toml",
|
||||
"uv.lock",
|
||||
]: # root uv files
|
||||
docs_edited = True
|
||||
|
||||
dependents = dependents_graph()
|
||||
|
||||
# we now have dirs_by_job
|
||||
# todo: clean this up
|
||||
map_job_to_configs = {
|
||||
job: _get_configs_for_multi_dirs(job, dirs_to_run, dependents)
|
||||
for job in [
|
||||
"lint",
|
||||
"test",
|
||||
"extended-tests",
|
||||
"compile-integration-tests",
|
||||
"dependencies",
|
||||
"test-pydantic",
|
||||
"codspeed",
|
||||
]
|
||||
}
|
||||
|
||||
for key, value in map_job_to_configs.items():
|
||||
json_output = json.dumps(value)
|
||||
print(f"{key}={json_output}")
|
||||
36
.github/scripts/check_prerelease_dependencies.py
vendored
36
.github/scripts/check_prerelease_dependencies.py
vendored
@@ -1,36 +0,0 @@
|
||||
"""Check that no dependencies allow prereleases unless we're releasing a prerelease."""
|
||||
|
||||
import sys
|
||||
|
||||
import tomllib
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Get the TOML file path from the command line argument
|
||||
toml_file = sys.argv[1]
|
||||
|
||||
with open(toml_file, "rb") as file:
|
||||
toml_data = tomllib.load(file)
|
||||
|
||||
# See if we're releasing an rc or dev version
|
||||
version = toml_data["project"]["version"]
|
||||
releasing_rc = "rc" in version or "dev" in version
|
||||
|
||||
# If not, iterate through dependencies and make sure none allow prereleases
|
||||
if not releasing_rc:
|
||||
dependencies = toml_data["project"]["dependencies"]
|
||||
for dep_version in dependencies:
|
||||
dep_version_string = (
|
||||
dep_version["version"] if isinstance(dep_version, dict) else dep_version
|
||||
)
|
||||
|
||||
if "rc" in dep_version_string:
|
||||
raise ValueError(
|
||||
f"Dependency {dep_version} has a prerelease version. Please remove this."
|
||||
)
|
||||
|
||||
if isinstance(dep_version, dict) and dep_version.get(
|
||||
"allow-prereleases", False
|
||||
):
|
||||
raise ValueError(
|
||||
f"Dependency {dep_version} has allow-prereleases set to true. Please remove this."
|
||||
)
|
||||
199
.github/scripts/get_min_versions.py
vendored
199
.github/scripts/get_min_versions.py
vendored
@@ -1,199 +0,0 @@
|
||||
"""Get minimum versions of dependencies from a pyproject.toml file."""
|
||||
|
||||
import sys
|
||||
from collections import defaultdict
|
||||
|
||||
if sys.version_info >= (3, 11):
|
||||
import tomllib
|
||||
else:
|
||||
# For Python 3.10 and below, which doesnt have stdlib tomllib
|
||||
import tomli as tomllib
|
||||
|
||||
import re
|
||||
from typing import List
|
||||
|
||||
import requests
|
||||
from packaging.requirements import Requirement
|
||||
from packaging.specifiers import SpecifierSet
|
||||
from packaging.version import Version, parse
|
||||
|
||||
MIN_VERSION_LIBS = [
|
||||
"langchain-core",
|
||||
"langchain",
|
||||
"langchain-text-splitters",
|
||||
"numpy",
|
||||
"SQLAlchemy",
|
||||
]
|
||||
|
||||
# some libs only get checked on release because of simultaneous changes in
|
||||
# multiple libs
|
||||
SKIP_IF_PULL_REQUEST = [
|
||||
"langchain-core",
|
||||
"langchain-text-splitters",
|
||||
"langchain",
|
||||
]
|
||||
|
||||
|
||||
def get_pypi_versions(package_name: str) -> List[str]:
|
||||
"""Fetch all available versions for a package from PyPI.
|
||||
|
||||
Args:
|
||||
package_name: Name of the package
|
||||
|
||||
Returns:
|
||||
List of all available versions
|
||||
|
||||
Raises:
|
||||
requests.exceptions.RequestException: If PyPI API request fails
|
||||
KeyError: If package not found or response format unexpected
|
||||
"""
|
||||
pypi_url = f"https://pypi.org/pypi/{package_name}/json"
|
||||
response = requests.get(pypi_url)
|
||||
response.raise_for_status()
|
||||
return list(response.json()["releases"].keys())
|
||||
|
||||
|
||||
def get_minimum_version(package_name: str, spec_string: str) -> str | None:
|
||||
"""Find the minimum published version that satisfies the given constraints.
|
||||
|
||||
Args:
|
||||
package_name: Name of the package
|
||||
spec_string: Version specification string (e.g., ">=0.2.43,<0.4.0,!=0.3.0")
|
||||
|
||||
Returns:
|
||||
Minimum compatible version or None if no compatible version found
|
||||
"""
|
||||
# Rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
|
||||
spec_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", spec_string)
|
||||
# Rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1 (can be anywhere in constraint string)
|
||||
for y in range(1, 10):
|
||||
spec_string = re.sub(
|
||||
rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}", spec_string
|
||||
)
|
||||
# Rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
|
||||
for x in range(1, 10):
|
||||
spec_string = re.sub(
|
||||
rf"\^{x}\.(\d+)\.(\d+)", rf">={x}.\1.\2,<{x + 1}", spec_string
|
||||
)
|
||||
|
||||
spec_set = SpecifierSet(spec_string)
|
||||
all_versions = get_pypi_versions(package_name)
|
||||
|
||||
valid_versions = []
|
||||
for version_str in all_versions:
|
||||
try:
|
||||
version = parse(version_str)
|
||||
if spec_set.contains(version):
|
||||
valid_versions.append(version)
|
||||
except ValueError:
|
||||
continue
|
||||
|
||||
return str(min(valid_versions)) if valid_versions else None
|
||||
|
||||
|
||||
def _check_python_version_from_requirement(
|
||||
requirement: Requirement, python_version: str
|
||||
) -> bool:
|
||||
if not requirement.marker:
|
||||
return True
|
||||
else:
|
||||
marker_str = str(requirement.marker)
|
||||
if "python_version" or "python_full_version" in marker_str:
|
||||
python_version_str = "".join(
|
||||
char
|
||||
for char in marker_str
|
||||
if char.isdigit() or char in (".", "<", ">", "=", ",")
|
||||
)
|
||||
return check_python_version(python_version, python_version_str)
|
||||
return True
|
||||
|
||||
|
||||
def get_min_version_from_toml(
|
||||
toml_path: str,
|
||||
versions_for: str,
|
||||
python_version: str,
|
||||
*,
|
||||
include: list | None = None,
|
||||
):
|
||||
# Parse the TOML file
|
||||
with open(toml_path, "rb") as file:
|
||||
toml_data = tomllib.load(file)
|
||||
|
||||
dependencies = defaultdict(list)
|
||||
for dep in toml_data["project"]["dependencies"]:
|
||||
requirement = Requirement(dep)
|
||||
dependencies[requirement.name].append(requirement)
|
||||
|
||||
# Initialize a dictionary to store the minimum versions
|
||||
min_versions = {}
|
||||
|
||||
# Iterate over the libs in MIN_VERSION_LIBS
|
||||
for lib in set(MIN_VERSION_LIBS + (include or [])):
|
||||
if versions_for == "pull_request" and lib in SKIP_IF_PULL_REQUEST:
|
||||
# some libs only get checked on release because of simultaneous
|
||||
# changes in multiple libs
|
||||
continue
|
||||
# Check if the lib is present in the dependencies
|
||||
if lib in dependencies:
|
||||
if include and lib not in include:
|
||||
continue
|
||||
requirements = dependencies[lib]
|
||||
for requirement in requirements:
|
||||
if _check_python_version_from_requirement(requirement, python_version):
|
||||
version_string = str(requirement.specifier)
|
||||
break
|
||||
|
||||
# Use parse_version to get the minimum supported version from version_string
|
||||
min_version = get_minimum_version(lib, version_string)
|
||||
|
||||
# Store the minimum version in the min_versions dictionary
|
||||
min_versions[lib] = min_version
|
||||
|
||||
return min_versions
|
||||
|
||||
|
||||
def check_python_version(version_string, constraint_string):
|
||||
"""Check if the given Python version matches the given constraints.
|
||||
|
||||
Args:
|
||||
version_string: A string representing the Python version (e.g. "3.8.5").
|
||||
constraint_string: A string representing the package's Python version
|
||||
constraints (e.g. ">=3.6, <4.0").
|
||||
|
||||
Returns:
|
||||
True if the version matches the constraints
|
||||
"""
|
||||
|
||||
# Rewrite occurrences of ^0.0.z to 0.0.z (can be anywhere in constraint string)
|
||||
constraint_string = re.sub(r"\^0\.0\.(\d+)", r"0.0.\1", constraint_string)
|
||||
# Rewrite occurrences of ^0.y.z to >=0.y.z,<0.y+1.0 (can be anywhere in constraint string)
|
||||
for y in range(1, 10):
|
||||
constraint_string = re.sub(
|
||||
rf"\^0\.{y}\.(\d+)", rf">=0.{y}.\1,<0.{y + 1}.0", constraint_string
|
||||
)
|
||||
# Rewrite occurrences of ^x.y.z to >=x.y.z,<x+1.0.0 (can be anywhere in constraint string)
|
||||
for x in range(1, 10):
|
||||
constraint_string = re.sub(
|
||||
rf"\^{x}\.0\.(\d+)", rf">={x}.0.\1,<{x + 1}.0.0", constraint_string
|
||||
)
|
||||
|
||||
try:
|
||||
version = Version(version_string)
|
||||
constraints = SpecifierSet(constraint_string)
|
||||
return version in constraints
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
return False
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Get the TOML file path from the command line argument
|
||||
toml_file = sys.argv[1]
|
||||
versions_for = sys.argv[2]
|
||||
python_version = sys.argv[3]
|
||||
assert versions_for in ["release", "pull_request"]
|
||||
|
||||
# Call the function to get the minimum versions
|
||||
min_versions = get_min_version_from_toml(toml_file, versions_for, python_version)
|
||||
|
||||
print(" ".join([f"{lib}=={version}" for lib, version in min_versions.items()]))
|
||||
756
.github/tools/git-restore-mtime
vendored
756
.github/tools/git-restore-mtime
vendored
@@ -1,756 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
#
|
||||
# git-restore-mtime - Change mtime of files based on commit date of last change
|
||||
#
|
||||
# Copyright (C) 2012 Rodrigo Silva (MestreLion) <linux@rodrigosilva.com>
|
||||
#
|
||||
# This program is free software: you can redistribute it and/or modify
|
||||
# it under the terms of the GNU General Public License as published by
|
||||
# the Free Software Foundation, either version 3 of the License, or
|
||||
# (at your option) any later version.
|
||||
#
|
||||
# This program is distributed in the hope that it will be useful,
|
||||
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
# GNU General Public License for more details.
|
||||
#
|
||||
# You should have received a copy of the GNU General Public License
|
||||
# along with this program. See <http://www.gnu.org/licenses/gpl.html>
|
||||
#
|
||||
# Source: https://github.com/MestreLion/git-tools
|
||||
# Version: July 13, 2023 (commit hash 5f832e72453e035fccae9d63a5056918d64476a2)
|
||||
"""
|
||||
Change the modification time (mtime) of files in work tree, based on the
|
||||
date of the most recent commit that modified the file, including renames.
|
||||
|
||||
Ignores untracked files and uncommitted deletions, additions and renames, and
|
||||
by default modifications too.
|
||||
---
|
||||
Useful prior to generating release tarballs, so each file is archived with a
|
||||
date that is similar to the date when the file was actually last modified,
|
||||
assuming the actual modification date and its commit date are close.
|
||||
"""
|
||||
|
||||
# TODO:
|
||||
# - Add -z on git whatchanged/ls-files, so we don't deal with filename decoding
|
||||
# - When Python is bumped to 3.7, use text instead of universal_newlines on subprocess
|
||||
# - Update "Statistics for some large projects" with modern hardware and repositories.
|
||||
# - Create a README.md for git-restore-mtime alone. It deserves extensive documentation
|
||||
# - Move Statistics there
|
||||
# - See git-extras as a good example on project structure and documentation
|
||||
|
||||
# FIXME:
|
||||
# - When current dir is outside the worktree, e.g. using --work-tree, `git ls-files`
|
||||
# assume any relative pathspecs are to worktree root, not the current dir. As such,
|
||||
# relative pathspecs may not work.
|
||||
# - Renames are tricky:
|
||||
# - R100 should not change mtime, but original name is not on filelist. Should
|
||||
# track renames until a valid (A, M) mtime found and then set on current name.
|
||||
# - Should set mtime for both current and original directories.
|
||||
# - Check mode changes with unchanged blobs?
|
||||
# - Check file (A, D) for the directory mtime is not sufficient:
|
||||
# - Renames also change dir mtime, unless rename was on a parent dir
|
||||
# - If most recent change of all files in a dir was a Modification (M),
|
||||
# dir might not be touched at all.
|
||||
# - Dirs containing only subdirectories but no direct files will also
|
||||
# not be touched. They're files' [grand]parent dir, but never their dirname().
|
||||
# - Some solutions:
|
||||
# - After files done, perform some dir processing for missing dirs, finding latest
|
||||
# file (A, D, R)
|
||||
# - Simple approach: dir mtime is the most recent child (dir or file) mtime
|
||||
# - Use a virtual concept of "created at most at" to fill missing info, bubble up
|
||||
# to parents and grandparents
|
||||
# - When handling [grand]parent dirs, stay inside <pathspec>
|
||||
# - Better handling of merge commits. `-m` is plain *wrong*. `-c/--cc` is perfect, but
|
||||
# painfully slow. First pass without merge commits is not accurate. Maybe add a new
|
||||
# `--accurate` mode for `--cc`?
|
||||
|
||||
if __name__ != "__main__":
|
||||
raise ImportError("{} should not be used as a module.".format(__name__))
|
||||
|
||||
import argparse
|
||||
import datetime
|
||||
import logging
|
||||
import os.path
|
||||
import shlex
|
||||
import signal
|
||||
import subprocess
|
||||
import sys
|
||||
import time
|
||||
|
||||
__version__ = "2022.12+dev"
|
||||
|
||||
# Update symlinks only if the platform supports not following them
|
||||
UPDATE_SYMLINKS = bool(os.utime in getattr(os, "supports_follow_symlinks", []))
|
||||
|
||||
# Call os.path.normpath() only if not in a POSIX platform (Windows)
|
||||
NORMALIZE_PATHS = os.path.sep != "/"
|
||||
|
||||
# How many files to process in each batch when re-trying merge commits
|
||||
STEPMISSING = 100
|
||||
|
||||
# (Extra) keywords for the os.utime() call performed by touch()
|
||||
UTIME_KWS = {} if not UPDATE_SYMLINKS else {"follow_symlinks": False}
|
||||
|
||||
|
||||
# Command-line interface ######################################################
|
||||
|
||||
|
||||
def parse_args():
|
||||
parser = argparse.ArgumentParser(description=__doc__.split("\n---")[0])
|
||||
|
||||
group = parser.add_mutually_exclusive_group()
|
||||
group.add_argument(
|
||||
"--quiet",
|
||||
"-q",
|
||||
dest="loglevel",
|
||||
action="store_const",
|
||||
const=logging.WARNING,
|
||||
default=logging.INFO,
|
||||
help="Suppress informative messages and summary statistics.",
|
||||
)
|
||||
group.add_argument(
|
||||
"--verbose",
|
||||
"-v",
|
||||
action="count",
|
||||
help="""
|
||||
Print additional information for each processed file.
|
||||
Specify twice to further increase verbosity.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--cwd",
|
||||
"-C",
|
||||
metavar="DIRECTORY",
|
||||
help="""
|
||||
Run as if %(prog)s was started in directory %(metavar)s.
|
||||
This affects how --work-tree, --git-dir and PATHSPEC arguments are handled.
|
||||
See 'man 1 git' or 'git --help' for more information.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--git-dir",
|
||||
dest="gitdir",
|
||||
metavar="GITDIR",
|
||||
help="""
|
||||
Path to the git repository, by default auto-discovered by searching
|
||||
the current directory and its parents for a .git/ subdirectory.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--work-tree",
|
||||
dest="workdir",
|
||||
metavar="WORKTREE",
|
||||
help="""
|
||||
Path to the work tree root, by default the parent of GITDIR if it's
|
||||
automatically discovered, or the current directory if GITDIR is set.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--force",
|
||||
"-f",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Force updating files with uncommitted modifications.
|
||||
Untracked files and uncommitted deletions, renames and additions are
|
||||
always ignored.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--merge",
|
||||
"-m",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Include merge commits.
|
||||
Leads to more recent times and more files per commit, thus with the same
|
||||
time, which may or may not be what you want.
|
||||
Including merge commits may lead to fewer commits being evaluated as files
|
||||
are found sooner, which can improve performance, sometimes substantially.
|
||||
But as merge commits are usually huge, processing them may also take longer.
|
||||
By default, merge commits are only used for files missing from regular commits.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--first-parent",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Consider only the first parent, the "main branch", when evaluating merge commits.
|
||||
Only effective when merge commits are processed, either when --merge is
|
||||
used or when finding missing files after the first regular log search.
|
||||
See --skip-missing.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--skip-missing",
|
||||
"-s",
|
||||
dest="missing",
|
||||
default=True,
|
||||
action="store_false",
|
||||
help="""
|
||||
Do not try to find missing files.
|
||||
If merge commits were not evaluated with --merge and some files were
|
||||
not found in regular commits, by default %(prog)s searches for these
|
||||
files again in the merge commits.
|
||||
This option disables this retry, so files found only in merge commits
|
||||
will not have their timestamp updated.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--no-directories",
|
||||
"-D",
|
||||
dest="dirs",
|
||||
default=True,
|
||||
action="store_false",
|
||||
help="""
|
||||
Do not update directory timestamps.
|
||||
By default, use the time of its most recently created, renamed or deleted file.
|
||||
Note that just modifying a file will NOT update its directory time.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--test",
|
||||
"-t",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="Test run: do not actually update any file timestamp.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--commit-time",
|
||||
"-c",
|
||||
dest="commit_time",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="Use commit time instead of author time.",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--oldest-time",
|
||||
"-o",
|
||||
dest="reverse_order",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Update times based on the oldest, instead of the most recent commit of a file.
|
||||
This reverses the order in which the git log is processed to emulate a
|
||||
file "creation" date. Note this will be inaccurate for files deleted and
|
||||
re-created at later dates.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--skip-older-than",
|
||||
metavar="SECONDS",
|
||||
type=int,
|
||||
help="""
|
||||
Ignore files that are currently older than %(metavar)s.
|
||||
Useful in workflows that assume such files already have a correct timestamp,
|
||||
as it may improve performance by processing fewer files.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--skip-older-than-commit",
|
||||
"-N",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Ignore files older than the timestamp it would be updated to.
|
||||
Such files may be considered "original", likely in the author's repository.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--unique-times",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="""
|
||||
Set the microseconds to a unique value per commit.
|
||||
Allows telling apart changes that would otherwise have identical timestamps,
|
||||
as git's time accuracy is in seconds.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"pathspec",
|
||||
nargs="*",
|
||||
metavar="PATHSPEC",
|
||||
help="""
|
||||
Only modify paths matching %(metavar)s, relative to current directory.
|
||||
By default, update all but untracked files and submodules.
|
||||
""",
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--version",
|
||||
"-V",
|
||||
action="version",
|
||||
version="%(prog)s version {version}".format(version=get_version()),
|
||||
)
|
||||
|
||||
args_ = parser.parse_args()
|
||||
if args_.verbose:
|
||||
args_.loglevel = max(logging.TRACE, logging.DEBUG // args_.verbose)
|
||||
args_.debug = args_.loglevel <= logging.DEBUG
|
||||
return args_
|
||||
|
||||
|
||||
def get_version(version=__version__):
|
||||
if not version.endswith("+dev"):
|
||||
return version
|
||||
try:
|
||||
cwd = os.path.dirname(os.path.realpath(__file__))
|
||||
return Git(cwd=cwd, errors=False).describe().lstrip("v")
|
||||
except Git.Error:
|
||||
return "-".join((version, "unknown"))
|
||||
|
||||
|
||||
# Helper functions ############################################################
|
||||
|
||||
|
||||
def setup_logging():
|
||||
"""Add TRACE logging level and corresponding method, return the root logger"""
|
||||
logging.TRACE = TRACE = logging.DEBUG // 2
|
||||
logging.Logger.trace = lambda _, m, *a, **k: _.log(TRACE, m, *a, **k)
|
||||
return logging.getLogger()
|
||||
|
||||
|
||||
def normalize(path):
|
||||
r"""Normalize paths from git, handling non-ASCII characters.
|
||||
|
||||
Git stores paths as UTF-8 normalization form C.
|
||||
If path contains non-ASCII or non-printable characters, git outputs the UTF-8
|
||||
in octal-escaped notation, escaping double-quotes and backslashes, and then
|
||||
double-quoting the whole path.
|
||||
https://git-scm.com/docs/git-config#Documentation/git-config.txt-corequotePath
|
||||
|
||||
This function reverts this encoding, so:
|
||||
normalize(r'"Back\\slash_double\"quote_a\303\247a\303\255"') =>
|
||||
r'Back\slash_double"quote_açaí')
|
||||
|
||||
Paths with invalid UTF-8 encoding, such as single 0x80-0xFF bytes (e.g, from
|
||||
Latin1/Windows-1251 encoding) are decoded using surrogate escape, the same
|
||||
method used by Python for filesystem paths. So 0xE6 ("æ" in Latin1, r'\\346'
|
||||
from Git) is decoded as "\udce6". See https://peps.python.org/pep-0383/ and
|
||||
https://vstinner.github.io/painful-history-python-filesystem-encoding.html
|
||||
|
||||
Also see notes on `windows/non-ascii-paths.txt` about path encodings on
|
||||
non-UTF-8 platforms and filesystems.
|
||||
"""
|
||||
if path and path[0] == '"':
|
||||
# Python 2: path = path[1:-1].decode("string-escape")
|
||||
# Python 3: https://stackoverflow.com/a/46650050/624066
|
||||
path = (
|
||||
path[1:-1] # Remove enclosing double quotes
|
||||
.encode("latin1") # Convert to bytes, required by 'unicode-escape'
|
||||
.decode("unicode-escape") # Perform the actual octal-escaping decode
|
||||
.encode("latin1") # 1:1 mapping to bytes, UTF-8 encoded
|
||||
.decode("utf8", "surrogateescape")
|
||||
) # Decode from UTF-8
|
||||
if NORMALIZE_PATHS:
|
||||
# Make sure the slash matches the OS; for Windows we need a backslash
|
||||
path = os.path.normpath(path)
|
||||
return path
|
||||
|
||||
|
||||
def dummy(*_args, **_kwargs):
|
||||
"""No-op function used in dry-run tests"""
|
||||
|
||||
|
||||
def touch(path, mtime):
|
||||
"""The actual mtime update"""
|
||||
os.utime(path, (mtime, mtime), **UTIME_KWS)
|
||||
|
||||
|
||||
def touch_ns(path, mtime_ns):
|
||||
"""The actual mtime update, using nanoseconds for unique timestamps"""
|
||||
os.utime(path, None, ns=(mtime_ns, mtime_ns), **UTIME_KWS)
|
||||
|
||||
|
||||
def isodate(secs: int):
|
||||
# time.localtime() accepts floats, but discards fractional part
|
||||
return time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(secs))
|
||||
|
||||
|
||||
def isodate_ns(ns: int):
|
||||
# for integers fromtimestamp() is equivalent and ~16% slower than isodate()
|
||||
return datetime.datetime.fromtimestamp(ns / 1000000000).isoformat(sep=" ")
|
||||
|
||||
|
||||
def get_mtime_ns(secs: int, idx: int):
|
||||
# Time resolution for filesystems and functions:
|
||||
# ext-4 and other POSIX filesystems: 1 nanosecond
|
||||
# NTFS (Windows default): 100 nanoseconds
|
||||
# datetime.datetime() (due to 64-bit float epoch): 1 microsecond
|
||||
us = idx % 1000000 # 10**6
|
||||
return 1000 * (1000000 * secs + us)
|
||||
|
||||
|
||||
def get_mtime_path(path):
|
||||
return os.path.getmtime(path)
|
||||
|
||||
|
||||
# Git class and parse_log(), the heart of the script ##########################
|
||||
|
||||
|
||||
class Git:
|
||||
def __init__(self, workdir=None, gitdir=None, cwd=None, errors=True):
|
||||
self.gitcmd = ["git"]
|
||||
self.errors = errors
|
||||
self._proc = None
|
||||
if workdir:
|
||||
self.gitcmd.extend(("--work-tree", workdir))
|
||||
if gitdir:
|
||||
self.gitcmd.extend(("--git-dir", gitdir))
|
||||
if cwd:
|
||||
self.gitcmd.extend(("-C", cwd))
|
||||
self.workdir, self.gitdir = self._get_repo_dirs()
|
||||
|
||||
def ls_files(self, paths: list = None):
|
||||
return (normalize(_) for _ in self._run("ls-files --full-name", paths))
|
||||
|
||||
def ls_dirty(self, force=False):
|
||||
return (
|
||||
normalize(_[3:].split(" -> ", 1)[-1])
|
||||
for _ in self._run("status --porcelain")
|
||||
if _[:2] != "??" and (not force or (_[0] in ("R", "A") or _[1] == "D"))
|
||||
)
|
||||
|
||||
def log(
|
||||
self,
|
||||
merge=False,
|
||||
first_parent=False,
|
||||
commit_time=False,
|
||||
reverse_order=False,
|
||||
paths: list = None,
|
||||
):
|
||||
cmd = "whatchanged --pretty={}".format("%ct" if commit_time else "%at")
|
||||
if merge:
|
||||
cmd += " -m"
|
||||
if first_parent:
|
||||
cmd += " --first-parent"
|
||||
if reverse_order:
|
||||
cmd += " --reverse"
|
||||
return self._run(cmd, paths)
|
||||
|
||||
def describe(self):
|
||||
return self._run("describe --tags", check=True)[0]
|
||||
|
||||
def terminate(self):
|
||||
if self._proc is None:
|
||||
return
|
||||
try:
|
||||
self._proc.terminate()
|
||||
except OSError:
|
||||
# Avoid errors on OpenBSD
|
||||
pass
|
||||
|
||||
def _get_repo_dirs(self):
|
||||
return (
|
||||
os.path.normpath(_)
|
||||
for _ in self._run(
|
||||
"rev-parse --show-toplevel --absolute-git-dir", check=True
|
||||
)
|
||||
)
|
||||
|
||||
def _run(self, cmdstr: str, paths: list = None, output=True, check=False):
|
||||
cmdlist = self.gitcmd + shlex.split(cmdstr)
|
||||
if paths:
|
||||
cmdlist.append("--")
|
||||
cmdlist.extend(paths)
|
||||
popen_args = dict(universal_newlines=True, encoding="utf8")
|
||||
if not self.errors:
|
||||
popen_args["stderr"] = subprocess.DEVNULL
|
||||
log.trace("Executing: %s", " ".join(cmdlist))
|
||||
if not output:
|
||||
return subprocess.call(cmdlist, **popen_args)
|
||||
if check:
|
||||
try:
|
||||
stdout: str = subprocess.check_output(cmdlist, **popen_args)
|
||||
return stdout.splitlines()
|
||||
except subprocess.CalledProcessError as e:
|
||||
raise self.Error(e.returncode, e.cmd, e.output, e.stderr)
|
||||
self._proc = subprocess.Popen(cmdlist, stdout=subprocess.PIPE, **popen_args)
|
||||
return (_.rstrip() for _ in self._proc.stdout)
|
||||
|
||||
def __del__(self):
|
||||
self.terminate()
|
||||
|
||||
class Error(subprocess.CalledProcessError):
|
||||
"""Error from git executable"""
|
||||
|
||||
|
||||
def parse_log(filelist, dirlist, stats, git, merge=False, filterlist=None):
|
||||
mtime = 0
|
||||
datestr = isodate(0)
|
||||
for line in git.log(
|
||||
merge, args.first_parent, args.commit_time, args.reverse_order, filterlist
|
||||
):
|
||||
stats["loglines"] += 1
|
||||
|
||||
# Blank line between Date and list of files
|
||||
if not line:
|
||||
continue
|
||||
|
||||
# Date line
|
||||
if line[0] != ":": # Faster than `not line.startswith(':')`
|
||||
stats["commits"] += 1
|
||||
mtime = int(line)
|
||||
if args.unique_times:
|
||||
mtime = get_mtime_ns(mtime, stats["commits"])
|
||||
if args.debug:
|
||||
datestr = isodate(mtime)
|
||||
continue
|
||||
|
||||
# File line: three tokens if it describes a renaming, otherwise two
|
||||
tokens = line.split("\t")
|
||||
|
||||
# Possible statuses:
|
||||
# M: Modified (content changed)
|
||||
# A: Added (created)
|
||||
# D: Deleted
|
||||
# T: Type changed: to/from regular file, symlinks, submodules
|
||||
# R099: Renamed (moved), with % of unchanged content. 100 = pure rename
|
||||
# Not possible in log: C=Copied, U=Unmerged, X=Unknown, B=pairing Broken
|
||||
status = tokens[0].split(" ")[-1]
|
||||
file = tokens[-1]
|
||||
|
||||
# Handles non-ASCII chars and OS path separator
|
||||
file = normalize(file)
|
||||
|
||||
def do_file():
|
||||
if args.skip_older_than_commit and get_mtime_path(file) <= mtime:
|
||||
stats["skip"] += 1
|
||||
return
|
||||
if args.debug:
|
||||
log.debug(
|
||||
"%d\t%d\t%d\t%s\t%s",
|
||||
stats["loglines"],
|
||||
stats["commits"],
|
||||
stats["files"],
|
||||
datestr,
|
||||
file,
|
||||
)
|
||||
try:
|
||||
touch(os.path.join(git.workdir, file), mtime)
|
||||
stats["touches"] += 1
|
||||
except Exception as e:
|
||||
log.error("ERROR: %s: %s", e, file)
|
||||
stats["errors"] += 1
|
||||
|
||||
def do_dir():
|
||||
if args.debug:
|
||||
log.debug(
|
||||
"%d\t%d\t-\t%s\t%s",
|
||||
stats["loglines"],
|
||||
stats["commits"],
|
||||
datestr,
|
||||
"{}/".format(dirname or "."),
|
||||
)
|
||||
try:
|
||||
touch(os.path.join(git.workdir, dirname), mtime)
|
||||
stats["dirtouches"] += 1
|
||||
except Exception as e:
|
||||
log.error("ERROR: %s: %s", e, dirname)
|
||||
stats["direrrors"] += 1
|
||||
|
||||
if file in filelist:
|
||||
stats["files"] -= 1
|
||||
filelist.remove(file)
|
||||
do_file()
|
||||
|
||||
if args.dirs and status in ("A", "D"):
|
||||
dirname = os.path.dirname(file)
|
||||
if dirname in dirlist:
|
||||
dirlist.remove(dirname)
|
||||
do_dir()
|
||||
|
||||
# All files done?
|
||||
if not stats["files"]:
|
||||
git.terminate()
|
||||
return
|
||||
|
||||
|
||||
# Main Logic ##################################################################
|
||||
|
||||
|
||||
def main():
|
||||
start = time.time() # yes, Wall time. CPU time is not realistic for users.
|
||||
stats = {
|
||||
_: 0
|
||||
for _ in (
|
||||
"loglines",
|
||||
"commits",
|
||||
"touches",
|
||||
"skip",
|
||||
"errors",
|
||||
"dirtouches",
|
||||
"direrrors",
|
||||
)
|
||||
}
|
||||
|
||||
logging.basicConfig(level=args.loglevel, format="%(message)s")
|
||||
log.trace("Arguments: %s", args)
|
||||
|
||||
# First things first: Where and Who are we?
|
||||
if args.cwd:
|
||||
log.debug("Changing directory: %s", args.cwd)
|
||||
try:
|
||||
os.chdir(args.cwd)
|
||||
except OSError as e:
|
||||
log.critical(e)
|
||||
return e.errno
|
||||
# Using both os.chdir() and `git -C` is redundant, but might prevent side effects
|
||||
# `git -C` alone could be enough if we make sure that:
|
||||
# - all paths, including args.pathspec, are processed by git: ls-files, rev-parse
|
||||
# - touch() / os.utime() path argument is always prepended with git.workdir
|
||||
try:
|
||||
git = Git(workdir=args.workdir, gitdir=args.gitdir, cwd=args.cwd)
|
||||
except Git.Error as e:
|
||||
# Not in a git repository, and git already informed user on stderr. So we just...
|
||||
return e.returncode
|
||||
|
||||
# Get the files managed by git and build file list to be processed
|
||||
if UPDATE_SYMLINKS and not args.skip_older_than:
|
||||
filelist = set(git.ls_files(args.pathspec))
|
||||
else:
|
||||
filelist = set()
|
||||
for path in git.ls_files(args.pathspec):
|
||||
fullpath = os.path.join(git.workdir, path)
|
||||
|
||||
# Symlink (to file, to dir or broken - git handles the same way)
|
||||
if not UPDATE_SYMLINKS and os.path.islink(fullpath):
|
||||
log.warning(
|
||||
"WARNING: Skipping symlink, no OS support for updates: %s", path
|
||||
)
|
||||
continue
|
||||
|
||||
# skip files which are older than given threshold
|
||||
if (
|
||||
args.skip_older_than
|
||||
and start - get_mtime_path(fullpath) > args.skip_older_than
|
||||
):
|
||||
continue
|
||||
|
||||
# Always add files relative to worktree root
|
||||
filelist.add(path)
|
||||
|
||||
# If --force, silently ignore uncommitted deletions (not in the filesystem)
|
||||
# and renames / additions (will not be found in log anyway)
|
||||
if args.force:
|
||||
filelist -= set(git.ls_dirty(force=True))
|
||||
# Otherwise, ignore any dirty files
|
||||
else:
|
||||
dirty = set(git.ls_dirty())
|
||||
if dirty:
|
||||
log.warning(
|
||||
"WARNING: Modified files in the working directory were ignored."
|
||||
"\nTo include such files, commit your changes or use --force."
|
||||
)
|
||||
filelist -= dirty
|
||||
|
||||
# Build dir list to be processed
|
||||
dirlist = set(os.path.dirname(_) for _ in filelist) if args.dirs else set()
|
||||
|
||||
stats["totalfiles"] = stats["files"] = len(filelist)
|
||||
log.info("{0:,} files to be processed in work dir".format(stats["totalfiles"]))
|
||||
|
||||
if not filelist:
|
||||
# Nothing to do. Exit silently and without errors, just like git does
|
||||
return
|
||||
|
||||
# Process the log until all files are 'touched'
|
||||
log.debug("Line #\tLog #\tF.Left\tModification Time\tFile Name")
|
||||
parse_log(filelist, dirlist, stats, git, args.merge, args.pathspec)
|
||||
|
||||
# Missing files
|
||||
if filelist:
|
||||
# Try to find them in merge logs, if not done already
|
||||
# (usually HUGE, thus MUCH slower!)
|
||||
if args.missing and not args.merge:
|
||||
filterlist = list(filelist)
|
||||
missing = len(filterlist)
|
||||
log.info(
|
||||
"{0:,} files not found in log, trying merge commits".format(missing)
|
||||
)
|
||||
for i in range(0, missing, STEPMISSING):
|
||||
parse_log(
|
||||
filelist,
|
||||
dirlist,
|
||||
stats,
|
||||
git,
|
||||
merge=True,
|
||||
filterlist=filterlist[i : i + STEPMISSING],
|
||||
)
|
||||
|
||||
# Still missing some?
|
||||
for file in filelist:
|
||||
log.warning("WARNING: not found in the log: %s", file)
|
||||
|
||||
# Final statistics
|
||||
# Suggestion: use git-log --before=mtime to brag about skipped log entries
|
||||
def log_info(msg, *a, width=13):
|
||||
ifmt = "{:%d,}" % (width,) # not using 'n' for consistency with ffmt
|
||||
ffmt = "{:%d,.2f}" % (width,)
|
||||
# %-formatting lacks a thousand separator, must pre-render with .format()
|
||||
log.info(msg.replace("%d", ifmt).replace("%f", ffmt).format(*a))
|
||||
|
||||
log_info(
|
||||
"Statistics:\n%f seconds\n%d log lines processed\n%d commits evaluated",
|
||||
time.time() - start,
|
||||
stats["loglines"],
|
||||
stats["commits"],
|
||||
)
|
||||
|
||||
if args.dirs:
|
||||
if stats["direrrors"]:
|
||||
log_info("%d directory update errors", stats["direrrors"])
|
||||
log_info("%d directories updated", stats["dirtouches"])
|
||||
|
||||
if stats["touches"] != stats["totalfiles"]:
|
||||
log_info("%d files", stats["totalfiles"])
|
||||
if stats["skip"]:
|
||||
log_info("%d files skipped", stats["skip"])
|
||||
if stats["files"]:
|
||||
log_info("%d files missing", stats["files"])
|
||||
if stats["errors"]:
|
||||
log_info("%d file update errors", stats["errors"])
|
||||
|
||||
log_info("%d files updated", stats["touches"])
|
||||
|
||||
if args.test:
|
||||
log.info("TEST RUN - No files modified!")
|
||||
|
||||
|
||||
# Keep only essential, global assignments here. Any other logic must be in main()
|
||||
log = setup_logging()
|
||||
args = parse_args()
|
||||
|
||||
# Set the actual touch() and other functions based on command-line arguments
|
||||
if args.unique_times:
|
||||
touch = touch_ns
|
||||
isodate = isodate_ns
|
||||
|
||||
# Make sure this is always set last to ensure --test behaves as intended
|
||||
if args.test:
|
||||
touch = dummy
|
||||
|
||||
# UI done, it's showtime!
|
||||
try:
|
||||
sys.exit(main())
|
||||
except KeyboardInterrupt:
|
||||
log.info("\nAborting")
|
||||
signal.signal(signal.SIGINT, signal.SIG_DFL)
|
||||
os.kill(os.getpid(), signal.SIGINT)
|
||||
65
.github/workflows/_compile_integration_test.yml
vendored
65
.github/workflows/_compile_integration_test.yml
vendored
@@ -1,65 +0,0 @@
|
||||
# Validates that a package's integration tests compile without syntax or import errors.
|
||||
#
|
||||
# (If an integration test fails to compile, it won't run.)
|
||||
#
|
||||
# Called as part of check_diffs.yml workflow
|
||||
#
|
||||
# Runs pytest with compile marker to check syntax/imports.
|
||||
|
||||
name: "🔗 Compile Integration Tests"
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
python-version:
|
||||
required: true
|
||||
type: string
|
||||
description: "Python version to use"
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
UV_FROZEN: "true"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
name: "Python ${{ inputs.python-version }}"
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
cache-suffix: compile-integration-tests-${{ inputs.working-directory }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: "📦 Install Integration Dependencies"
|
||||
shell: bash
|
||||
run: uv sync --group test --group test_integration
|
||||
|
||||
- name: "🔗 Check Integration Tests Compile"
|
||||
shell: bash
|
||||
run: uv run pytest -m compile tests/integration_tests
|
||||
|
||||
- name: "🧹 Verify Clean Working Directory"
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(git status)"
|
||||
echo "$STATUS"
|
||||
|
||||
# grep will exit non-zero if the target message isn't found,
|
||||
# and `set -e` above will cause the step to fail.
|
||||
echo "$STATUS" | grep 'nothing to commit, working tree clean'
|
||||
75
.github/workflows/_lint.yml
vendored
75
.github/workflows/_lint.yml
vendored
@@ -1,75 +0,0 @@
|
||||
# Runs linting.
|
||||
#
|
||||
# Uses the package's Makefile to run the checks, specifically the
|
||||
# `lint_package` and `lint_tests` targets.
|
||||
#
|
||||
# Called as part of check_diffs.yml workflow.
|
||||
|
||||
name: "🧹 Linting"
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
python-version:
|
||||
required: true
|
||||
type: string
|
||||
description: "Python version to use"
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}
|
||||
|
||||
# This env var allows us to get inline annotations when ruff has complaints.
|
||||
RUFF_OUTPUT_FORMAT: github
|
||||
|
||||
UV_FROZEN: "true"
|
||||
|
||||
jobs:
|
||||
# Linting job - runs quality checks on package and test code
|
||||
build:
|
||||
name: "Python ${{ inputs.python-version }}"
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
steps:
|
||||
- name: "📋 Checkout Code"
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
cache-suffix: lint-${{ inputs.working-directory }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: "📦 Install Lint & Typing Dependencies"
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
uv sync --group lint --group typing
|
||||
|
||||
- name: "🔍 Analyze Package Code with Linters"
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
make lint_package
|
||||
|
||||
- name: "📦 Install Test Dependencies (non-partners)"
|
||||
# (For directories NOT starting with libs/partners/)
|
||||
if: ${{ ! startsWith(inputs.working-directory, 'libs/partners/') }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
uv sync --inexact --group test
|
||||
- name: "📦 Install Test Dependencies"
|
||||
if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
uv sync --inexact --group test --group test_integration
|
||||
|
||||
- name: "🔍 Analyze Test Code with Linters"
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
make lint_tests
|
||||
556
.github/workflows/_release.yml
vendored
556
.github/workflows/_release.yml
vendored
@@ -1,556 +0,0 @@
|
||||
# Builds and publishes LangChain packages to PyPI.
|
||||
#
|
||||
# Manually triggered, though can be used as a reusable workflow (workflow_call).
|
||||
#
|
||||
# Handles version bumping, building, and publishing to PyPI with authentication.
|
||||
|
||||
name: "🚀 Package Release"
|
||||
run-name: "Release ${{ inputs.working-directory }} ${{ inputs.release-version }}"
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
default: "libs/langchain"
|
||||
release-version:
|
||||
required: true
|
||||
type: string
|
||||
default: "0.1.0"
|
||||
description: "New version of package being released"
|
||||
dangerous-nonmaster-release:
|
||||
required: false
|
||||
type: boolean
|
||||
default: false
|
||||
description: "Release from a non-master branch (danger!) - Only use for hotfixes"
|
||||
|
||||
env:
|
||||
PYTHON_VERSION: "3.11"
|
||||
UV_FROZEN: "true"
|
||||
UV_NO_SYNC: "true"
|
||||
|
||||
permissions:
|
||||
contents: write # Required for creating GitHub releases
|
||||
|
||||
jobs:
|
||||
# Build the distribution package and extract version info
|
||||
# Runs in isolated environment with minimal permissions for security
|
||||
build:
|
||||
if: github.ref == 'refs/heads/master' || inputs.dangerous-nonmaster-release
|
||||
environment: Scheduled testing
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
outputs:
|
||||
pkg-name: ${{ steps.check-version.outputs.pkg-name }}
|
||||
version: ${{ steps.check-version.outputs.version }}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: Set up Python + uv
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
# We want to keep this build stage *separate* from the release stage,
|
||||
# so that there's no sharing of permissions between them.
|
||||
# (Release stage has trusted publishing and GitHub repo contents write access,
|
||||
#
|
||||
# Otherwise, a malicious `build` step (e.g. via a compromised dependency)
|
||||
# could get access to our GitHub or PyPI credentials.
|
||||
#
|
||||
# Per the trusted publishing GitHub Action:
|
||||
# > It is strongly advised to separate jobs for building [...]
|
||||
# > from the publish job.
|
||||
# https://github.com/pypa/gh-action-pypi-publish#non-goals
|
||||
- name: Build project for distribution
|
||||
run: uv build
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Upload build
|
||||
uses: actions/upload-artifact@v5
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Check version
|
||||
id: check-version
|
||||
shell: python
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
import os
|
||||
import tomllib
|
||||
with open("pyproject.toml", "rb") as f:
|
||||
data = tomllib.load(f)
|
||||
pkg_name = data["project"]["name"]
|
||||
version = data["project"]["version"]
|
||||
with open(os.environ["GITHUB_OUTPUT"], "a") as f:
|
||||
f.write(f"pkg-name={pkg_name}\n")
|
||||
f.write(f"version={version}\n")
|
||||
release-notes:
|
||||
needs:
|
||||
- build
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
outputs:
|
||||
release-body: ${{ steps.generate-release-body.outputs.release-body }}
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
repository: langchain-ai/langchain
|
||||
path: langchain
|
||||
sparse-checkout: | # this only grabs files for relevant dir
|
||||
${{ inputs.working-directory }}
|
||||
ref: ${{ github.ref }} # this scopes to just ref'd branch
|
||||
fetch-depth: 0 # this fetches entire commit history
|
||||
- name: Check tags
|
||||
id: check-tags
|
||||
shell: bash
|
||||
working-directory: langchain/${{ inputs.working-directory }}
|
||||
env:
|
||||
PKG_NAME: ${{ needs.build.outputs.pkg-name }}
|
||||
VERSION: ${{ needs.build.outputs.version }}
|
||||
run: |
|
||||
# Handle regular versions and pre-release versions differently
|
||||
if [[ "$VERSION" == *"-"* ]]; then
|
||||
# This is a pre-release version (contains a hyphen)
|
||||
# Extract the base version without the pre-release suffix
|
||||
BASE_VERSION=${VERSION%%-*}
|
||||
# Look for the latest release of the same base version
|
||||
REGEX="^$PKG_NAME==$BASE_VERSION\$"
|
||||
PREV_TAG=$(git tag --sort=-creatordate | (grep -P "$REGEX" || true) | head -1)
|
||||
|
||||
# If no exact base version match, look for the latest release of any kind
|
||||
if [ -z "$PREV_TAG" ]; then
|
||||
REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$"
|
||||
PREV_TAG=$(git tag --sort=-creatordate | (grep -P "$REGEX" || true) | head -1)
|
||||
fi
|
||||
else
|
||||
# Regular version handling
|
||||
PREV_TAG="$PKG_NAME==${VERSION%.*}.$(( ${VERSION##*.} - 1 ))"; [[ "${VERSION##*.}" -eq 0 ]] && PREV_TAG=""
|
||||
|
||||
# backup case if releasing e.g. 0.3.0, looks up last release
|
||||
# note if last release (chronologically) was e.g. 0.1.47 it will get
|
||||
# that instead of the last 0.2 release
|
||||
if [ -z "$PREV_TAG" ]; then
|
||||
REGEX="^$PKG_NAME==\\d+\\.\\d+\\.\\d+\$"
|
||||
echo $REGEX
|
||||
PREV_TAG=$(git tag --sort=-creatordate | (grep -P $REGEX || true) | head -1)
|
||||
fi
|
||||
fi
|
||||
|
||||
# if PREV_TAG is empty or came out to 0.0.0, let it be empty
|
||||
if [ -z "$PREV_TAG" ] || [ "$PREV_TAG" = "$PKG_NAME==0.0.0" ]; then
|
||||
echo "No previous tag found - first release"
|
||||
else
|
||||
# confirm prev-tag actually exists in git repo with git tag
|
||||
GIT_TAG_RESULT=$(git tag -l "$PREV_TAG")
|
||||
if [ -z "$GIT_TAG_RESULT" ]; then
|
||||
echo "Previous tag $PREV_TAG not found in git repo"
|
||||
exit 1
|
||||
fi
|
||||
fi
|
||||
|
||||
|
||||
TAG="${PKG_NAME}==${VERSION}"
|
||||
if [ "$TAG" == "$PREV_TAG" ]; then
|
||||
echo "No new version to release"
|
||||
exit 1
|
||||
fi
|
||||
echo tag="$TAG" >> $GITHUB_OUTPUT
|
||||
echo prev-tag="$PREV_TAG" >> $GITHUB_OUTPUT
|
||||
- name: Generate release body
|
||||
id: generate-release-body
|
||||
working-directory: langchain
|
||||
env:
|
||||
WORKING_DIR: ${{ inputs.working-directory }}
|
||||
PKG_NAME: ${{ needs.build.outputs.pkg-name }}
|
||||
TAG: ${{ steps.check-tags.outputs.tag }}
|
||||
PREV_TAG: ${{ steps.check-tags.outputs.prev-tag }}
|
||||
run: |
|
||||
PREAMBLE="Changes since $PREV_TAG"
|
||||
# if PREV_TAG is empty or 0.0.0, then we are releasing the first version
|
||||
if [ -z "$PREV_TAG" ] || [ "$PREV_TAG" = "$PKG_NAME==0.0.0" ]; then
|
||||
PREAMBLE="Initial release"
|
||||
PREV_TAG=$(git rev-list --max-parents=0 HEAD)
|
||||
fi
|
||||
{
|
||||
echo 'release-body<<EOF'
|
||||
echo $PREAMBLE
|
||||
echo
|
||||
git log --format="%s" "$PREV_TAG"..HEAD -- $WORKING_DIR
|
||||
echo EOF
|
||||
} >> "$GITHUB_OUTPUT"
|
||||
|
||||
test-pypi-publish:
|
||||
needs:
|
||||
- build
|
||||
- release-notes
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
# This permission is used for trusted publishing:
|
||||
# https://blog.pypi.org/posts/2023-04-20-introducing-trusted-publishers/
|
||||
#
|
||||
# Trusted publishing has to also be configured on PyPI for each package:
|
||||
# https://docs.pypi.org/trusted-publishers/adding-a-publisher/
|
||||
id-token: write
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- uses: actions/download-artifact@v6
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Publish to test PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ${{ inputs.working-directory }}/dist/
|
||||
verbose: true
|
||||
print-hash: true
|
||||
repository-url: https://test.pypi.org/legacy/
|
||||
# We overwrite any existing distributions with the same name and version.
|
||||
# This is *only for CI use* and is *extremely dangerous* otherwise!
|
||||
# https://github.com/pypa/gh-action-pypi-publish#tolerating-release-package-file-duplicates
|
||||
skip-existing: true
|
||||
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
|
||||
attestations: false
|
||||
|
||||
pre-release-checks:
|
||||
needs:
|
||||
- build
|
||||
- release-notes
|
||||
- test-pypi-publish
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
timeout-minutes: 20
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
# We explicitly *don't* set up caching here. This ensures our tests are
|
||||
# maximally sensitive to catching breakage.
|
||||
#
|
||||
# For example, here's a way that caching can cause a falsely-passing test:
|
||||
# - Make the langchain package manifest no longer list a dependency package
|
||||
# as a requirement. This means it won't be installed by `pip install`,
|
||||
# and attempting to use it would cause a crash.
|
||||
# - That dependency used to be required, so it may have been cached.
|
||||
# When restoring the venv packages from cache, that dependency gets included.
|
||||
# - Tests pass, because the dependency is present even though it wasn't specified.
|
||||
# - The package is published, and it breaks on the missing dependency when
|
||||
# used in the real world.
|
||||
|
||||
- name: Set up Python + uv
|
||||
uses: "./.github/actions/uv_setup"
|
||||
id: setup-python
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
- uses: actions/download-artifact@v6
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Import dist package
|
||||
shell: bash
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
env:
|
||||
PKG_NAME: ${{ needs.build.outputs.pkg-name }}
|
||||
VERSION: ${{ needs.build.outputs.version }}
|
||||
# Here we use:
|
||||
# - The default regular PyPI index as the *primary* index, meaning
|
||||
# that it takes priority (https://pypi.org/simple)
|
||||
# - The test PyPI index as an extra index, so that any dependencies that
|
||||
# are not found on test PyPI can be resolved and installed anyway.
|
||||
# (https://test.pypi.org/simple). This will include the PKG_NAME==VERSION
|
||||
# package because VERSION will not have been uploaded to regular PyPI yet.
|
||||
# - attempt install again after 5 seconds if it fails because there is
|
||||
# sometimes a delay in availability on test pypi
|
||||
run: |
|
||||
uv venv
|
||||
VIRTUAL_ENV=.venv uv pip install dist/*.whl
|
||||
|
||||
# Replace all dashes in the package name with underscores,
|
||||
# since that's how Python imports packages with dashes in the name.
|
||||
# also remove _official suffix
|
||||
IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g | sed s/_official//g)"
|
||||
|
||||
uv run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
|
||||
|
||||
- name: Import test dependencies
|
||||
run: uv sync --group test
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
# Overwrite the local version of the package with the built version
|
||||
- name: Import published package (again)
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
shell: bash
|
||||
env:
|
||||
PKG_NAME: ${{ needs.build.outputs.pkg-name }}
|
||||
VERSION: ${{ needs.build.outputs.version }}
|
||||
run: |
|
||||
VIRTUAL_ENV=.venv uv pip install dist/*.whl
|
||||
|
||||
- name: Check for prerelease versions
|
||||
# Block release if any dependencies allow prerelease versions
|
||||
# (unless this is itself a prerelease version)
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
run: |
|
||||
uv run python $GITHUB_WORKSPACE/.github/scripts/check_prerelease_dependencies.py pyproject.toml
|
||||
|
||||
- name: Run unit tests
|
||||
run: make tests
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Get minimum versions
|
||||
# Find the minimum published versions that satisfies the given constraints
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
id: min-version
|
||||
run: |
|
||||
VIRTUAL_ENV=.venv uv pip install packaging requests
|
||||
python_version="$(uv run python --version | awk '{print $2}')"
|
||||
min_versions="$(uv run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml release $python_version)"
|
||||
echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT"
|
||||
echo "min-versions=$min_versions"
|
||||
|
||||
- name: Run unit tests with minimum dependency versions
|
||||
if: ${{ steps.min-version.outputs.min-versions != '' }}
|
||||
env:
|
||||
MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
|
||||
run: |
|
||||
VIRTUAL_ENV=.venv uv pip install --force-reinstall --editable .
|
||||
VIRTUAL_ENV=.venv uv pip install --force-reinstall $MIN_VERSIONS
|
||||
make tests
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Import integration test dependencies
|
||||
run: uv sync --group test --group test_integration
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: Run integration tests
|
||||
# Uses the Makefile's `integration_tests` target for the specified package
|
||||
if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
|
||||
env:
|
||||
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
|
||||
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
|
||||
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
|
||||
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
|
||||
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
|
||||
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
|
||||
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
|
||||
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
|
||||
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
|
||||
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
|
||||
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
|
||||
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
|
||||
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
|
||||
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
|
||||
WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
|
||||
WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
|
||||
ASTRA_DB_API_ENDPOINT: ${{ secrets.ASTRA_DB_API_ENDPOINT }}
|
||||
ASTRA_DB_APPLICATION_TOKEN: ${{ secrets.ASTRA_DB_APPLICATION_TOKEN }}
|
||||
ASTRA_DB_KEYSPACE: ${{ secrets.ASTRA_DB_KEYSPACE }}
|
||||
ES_URL: ${{ secrets.ES_URL }}
|
||||
ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
|
||||
ES_API_KEY: ${{ secrets.ES_API_KEY }}
|
||||
MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
|
||||
UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
|
||||
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
|
||||
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
|
||||
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
|
||||
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
|
||||
LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
|
||||
run: make integration_tests
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
# Test select published packages against new core
|
||||
# Done when code changes are made to langchain-core
|
||||
test-prior-published-packages-against-new-core:
|
||||
# Installs the new core with old partners: Installs the new unreleased core
|
||||
# alongside the previously published partner packages and runs integration tests
|
||||
needs:
|
||||
- build
|
||||
- release-notes
|
||||
- test-pypi-publish
|
||||
- pre-release-checks
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
strategy:
|
||||
matrix:
|
||||
partner: [openai]
|
||||
fail-fast: false # Continue testing other partners if one fails
|
||||
env:
|
||||
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
|
||||
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
|
||||
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
|
||||
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
|
||||
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
|
||||
LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
# We implement this conditional as Github Actions does not have good support
|
||||
# for conditionally needing steps. https://github.com/actions/runner/issues/491
|
||||
# TODO: this seems to be resolved upstream, so we can probably remove this workaround
|
||||
- name: Check if libs/core
|
||||
run: |
|
||||
if [ "${{ startsWith(inputs.working-directory, 'libs/core') }}" != "true" ]; then
|
||||
echo "Not in libs/core. Exiting successfully."
|
||||
exit 0
|
||||
fi
|
||||
|
||||
- name: Set up Python + uv
|
||||
if: startsWith(inputs.working-directory, 'libs/core')
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
- uses: actions/download-artifact@v6
|
||||
if: startsWith(inputs.working-directory, 'libs/core')
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Test against ${{ matrix.partner }}
|
||||
if: startsWith(inputs.working-directory, 'libs/core')
|
||||
run: |
|
||||
# Identify latest tag, excluding pre-releases
|
||||
LATEST_PACKAGE_TAG="$(
|
||||
git ls-remote --tags origin "langchain-${{ matrix.partner }}*" \
|
||||
| awk '{print $2}' \
|
||||
| sed 's|refs/tags/||' \
|
||||
| grep -E '[0-9]+\.[0-9]+\.[0-9]+$' \
|
||||
| sort -Vr \
|
||||
| head -n 1
|
||||
)"
|
||||
echo "Latest package tag: $LATEST_PACKAGE_TAG"
|
||||
|
||||
# Shallow-fetch just that single tag
|
||||
git fetch --depth=1 origin tag "$LATEST_PACKAGE_TAG"
|
||||
|
||||
# Checkout the latest package files
|
||||
rm -rf $GITHUB_WORKSPACE/libs/partners/${{ matrix.partner }}/*
|
||||
rm -rf $GITHUB_WORKSPACE/libs/standard-tests/*
|
||||
cd $GITHUB_WORKSPACE/libs/
|
||||
git checkout "$LATEST_PACKAGE_TAG" -- standard-tests/
|
||||
git checkout "$LATEST_PACKAGE_TAG" -- partners/${{ matrix.partner }}/
|
||||
cd partners/${{ matrix.partner }}
|
||||
|
||||
# Print as a sanity check
|
||||
echo "Version number from pyproject.toml: "
|
||||
cat pyproject.toml | grep "version = "
|
||||
|
||||
# Run tests
|
||||
uv sync --group test --group test_integration
|
||||
uv pip install ../../core/dist/*.whl
|
||||
make integration_tests
|
||||
|
||||
publish:
|
||||
# Publishes the package to PyPI
|
||||
needs:
|
||||
- build
|
||||
- release-notes
|
||||
- test-pypi-publish
|
||||
- pre-release-checks
|
||||
- test-prior-published-packages-against-new-core
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
# This permission is used for trusted publishing:
|
||||
# https://blog.pypi.org/posts/2023-04-20-introducing-trusted-publishers/
|
||||
#
|
||||
# Trusted publishing has to also be configured on PyPI for each package:
|
||||
# https://docs.pypi.org/trusted-publishers/adding-a-publisher/
|
||||
id-token: write
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: Set up Python + uv
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
- uses: actions/download-artifact@v6
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Publish package distributions to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: ${{ inputs.working-directory }}/dist/
|
||||
verbose: true
|
||||
print-hash: true
|
||||
# Temp workaround since attestations are on by default as of gh-action-pypi-publish v1.11.0
|
||||
attestations: false
|
||||
|
||||
mark-release:
|
||||
# Marks the GitHub release with the new version tag
|
||||
needs:
|
||||
- build
|
||||
- release-notes
|
||||
- test-pypi-publish
|
||||
- pre-release-checks
|
||||
- publish
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
# This permission is needed by `ncipollo/release-action` to
|
||||
# create the GitHub release/tag
|
||||
contents: write
|
||||
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: Set up Python + uv
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
- uses: actions/download-artifact@v6
|
||||
with:
|
||||
name: dist
|
||||
path: ${{ inputs.working-directory }}/dist/
|
||||
|
||||
- name: Create Tag
|
||||
uses: ncipollo/release-action@v1
|
||||
with:
|
||||
artifacts: "dist/*"
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
generateReleaseNotes: false
|
||||
tag: ${{needs.build.outputs.pkg-name}}==${{ needs.build.outputs.version }}
|
||||
body: ${{ needs.release-notes.outputs.release-body }}
|
||||
commit: ${{ github.sha }}
|
||||
makeLatest: ${{ needs.build.outputs.pkg-name == 'langchain-core'}}
|
||||
85
.github/workflows/_test.yml
vendored
85
.github/workflows/_test.yml
vendored
@@ -1,85 +0,0 @@
|
||||
# Runs unit tests with both current and minimum supported dependency versions
|
||||
# to ensure compatibility across the supported range.
|
||||
|
||||
name: "🧪 Unit Testing"
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
python-version:
|
||||
required: true
|
||||
type: string
|
||||
description: "Python version to use"
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
UV_FROZEN: "true"
|
||||
UV_NO_SYNC: "true"
|
||||
|
||||
jobs:
|
||||
# Main test job - runs unit tests with current deps, then retests with minimum versions
|
||||
build:
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
name: "Python ${{ inputs.python-version }}"
|
||||
steps:
|
||||
- name: "📋 Checkout Code"
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
|
||||
uses: "./.github/actions/uv_setup"
|
||||
id: setup-python
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
cache-suffix: test-${{ inputs.working-directory }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: "📦 Install Test Dependencies"
|
||||
shell: bash
|
||||
run: uv sync --group test --dev
|
||||
|
||||
- name: "🧪 Run Core Unit Tests"
|
||||
shell: bash
|
||||
run: |
|
||||
make test
|
||||
|
||||
- name: "🔍 Calculate Minimum Dependency Versions"
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
id: min-version
|
||||
shell: bash
|
||||
run: |
|
||||
VIRTUAL_ENV=.venv uv pip install packaging tomli requests
|
||||
python_version="$(uv run python --version | awk '{print $2}')"
|
||||
min_versions="$(uv run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml pull_request $python_version)"
|
||||
echo "min-versions=$min_versions" >> "$GITHUB_OUTPUT"
|
||||
echo "min-versions=$min_versions"
|
||||
|
||||
- name: "🧪 Run Tests with Minimum Dependencies"
|
||||
if: ${{ steps.min-version.outputs.min-versions != '' }}
|
||||
env:
|
||||
MIN_VERSIONS: ${{ steps.min-version.outputs.min-versions }}
|
||||
run: |
|
||||
VIRTUAL_ENV=.venv uv pip install $MIN_VERSIONS
|
||||
make tests
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: "🧹 Verify Clean Working Directory"
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(git status)"
|
||||
echo "$STATUS"
|
||||
|
||||
# grep will exit non-zero if the target message isn't found,
|
||||
# and `set -e` above will cause the step to fail.
|
||||
echo "$STATUS" | grep 'nothing to commit, working tree clean'
|
||||
73
.github/workflows/_test_pydantic.yml
vendored
73
.github/workflows/_test_pydantic.yml
vendored
@@ -1,73 +0,0 @@
|
||||
# Facilitate unit testing against different Pydantic versions for a provided package.
|
||||
|
||||
name: "🐍 Pydantic Version Testing"
|
||||
|
||||
on:
|
||||
workflow_call:
|
||||
inputs:
|
||||
working-directory:
|
||||
required: true
|
||||
type: string
|
||||
description: "From which folder this pipeline executes"
|
||||
python-version:
|
||||
required: false
|
||||
type: string
|
||||
description: "Python version to use"
|
||||
default: "3.12"
|
||||
pydantic-version:
|
||||
required: true
|
||||
type: string
|
||||
description: "Pydantic version to test."
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
UV_FROZEN: "true"
|
||||
UV_NO_SYNC: "true"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
name: "Pydantic ~=${{ inputs.pydantic-version }}"
|
||||
steps:
|
||||
- name: "📋 Checkout Code"
|
||||
uses: actions/checkout@v5
|
||||
|
||||
- name: "🐍 Set up Python ${{ inputs.python-version }} + UV"
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
cache-suffix: test-pydantic-${{ inputs.working-directory }}
|
||||
working-directory: ${{ inputs.working-directory }}
|
||||
|
||||
- name: "📦 Install Test Dependencies"
|
||||
shell: bash
|
||||
run: uv sync --group test
|
||||
|
||||
- name: "🔄 Install Specific Pydantic Version"
|
||||
shell: bash
|
||||
env:
|
||||
PYDANTIC_VERSION: ${{ inputs.pydantic-version }}
|
||||
run: VIRTUAL_ENV=.venv uv pip install "pydantic~=$PYDANTIC_VERSION"
|
||||
|
||||
- name: "🧪 Run Core Tests"
|
||||
shell: bash
|
||||
run: |
|
||||
make test
|
||||
|
||||
- name: "🧹 Verify Clean Working Directory"
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(git status)"
|
||||
echo "$STATUS"
|
||||
|
||||
# grep will exit non-zero if the target message isn't found,
|
||||
# and `set -e` above will cause the step to fail.
|
||||
echo "$STATUS" | grep 'nothing to commit, working tree clean'
|
||||
51
.github/workflows/check_core_versions.yml
vendored
51
.github/workflows/check_core_versions.yml
vendored
@@ -1,51 +0,0 @@
|
||||
# Ensures version numbers in pyproject.toml and version.py stay in sync.
|
||||
#
|
||||
# (Prevents releases with mismatched version numbers)
|
||||
|
||||
name: "🔍 Check Version Equality"
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
paths:
|
||||
- "libs/core/pyproject.toml"
|
||||
- "libs/core/langchain_core/version.py"
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
check_version_equality:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: "✅ Verify pyproject.toml & version.py Match"
|
||||
run: |
|
||||
# Check core versions
|
||||
CORE_PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/core/pyproject.toml)
|
||||
CORE_VERSION_PY_VERSION=$(grep -Po '(?<=^VERSION = ")[^"]*' libs/core/langchain_core/version.py)
|
||||
|
||||
# Compare core versions
|
||||
if [ "$CORE_PYPROJECT_VERSION" != "$CORE_VERSION_PY_VERSION" ]; then
|
||||
echo "langchain-core versions in pyproject.toml and version.py do not match!"
|
||||
echo "pyproject.toml version: $CORE_PYPROJECT_VERSION"
|
||||
echo "version.py version: $CORE_VERSION_PY_VERSION"
|
||||
exit 1
|
||||
else
|
||||
echo "Core versions match: $CORE_PYPROJECT_VERSION"
|
||||
fi
|
||||
|
||||
# Check langchain_v1 versions
|
||||
LANGCHAIN_PYPROJECT_VERSION=$(grep -Po '(?<=^version = ")[^"]*' libs/langchain_v1/pyproject.toml)
|
||||
LANGCHAIN_INIT_PY_VERSION=$(grep -Po '(?<=^__version__ = ")[^"]*' libs/langchain_v1/langchain/__init__.py)
|
||||
|
||||
# Compare langchain_v1 versions
|
||||
if [ "$LANGCHAIN_PYPROJECT_VERSION" != "$LANGCHAIN_INIT_PY_VERSION" ]; then
|
||||
echo "langchain_v1 versions in pyproject.toml and __init__.py do not match!"
|
||||
echo "pyproject.toml version: $LANGCHAIN_PYPROJECT_VERSION"
|
||||
echo "version.py version: $LANGCHAIN_INIT_PY_VERSION"
|
||||
exit 1
|
||||
else
|
||||
echo "Langchain v1 versions match: $LANGCHAIN_PYPROJECT_VERSION"
|
||||
fi
|
||||
261
.github/workflows/check_diffs.yml
vendored
261
.github/workflows/check_diffs.yml
vendored
@@ -1,261 +0,0 @@
|
||||
# Primary CI workflow.
|
||||
#
|
||||
# Only runs against packages that have changed files.
|
||||
#
|
||||
# Runs:
|
||||
# - Linting (_lint.yml)
|
||||
# - Unit Tests (_test.yml)
|
||||
# - Pydantic compatibility tests (_test_pydantic.yml)
|
||||
# - Integration test compilation checks (_compile_integration_test.yml)
|
||||
# - Extended test suites that require additional dependencies
|
||||
# - Codspeed benchmarks (if not labeled 'codspeed-ignore')
|
||||
#
|
||||
# Reports status to GitHub checks and PR status.
|
||||
|
||||
name: "🔧 CI"
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [master]
|
||||
pull_request:
|
||||
merge_group:
|
||||
|
||||
# Optimizes CI performance by canceling redundant workflow runs
|
||||
# If another push to the same PR or branch happens while this workflow is still running,
|
||||
# cancel the earlier run in favor of the next run.
|
||||
#
|
||||
# There's no point in testing an outdated version of the code. GitHub only allows
|
||||
# a limited number of job runners to be active at the same time, so it's better to
|
||||
# cancel pointless jobs early so that more useful jobs can run sooner.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
UV_FROZEN: "true"
|
||||
UV_NO_SYNC: "true"
|
||||
|
||||
jobs:
|
||||
# This job analyzes which files changed and creates a dynamic test matrix
|
||||
# to only run tests/lints for the affected packages, improving CI efficiency
|
||||
build:
|
||||
name: "Detect Changes & Set Matrix"
|
||||
runs-on: ubuntu-latest
|
||||
if: ${{ !contains(github.event.pull_request.labels.*.name, 'ci-ignore') }}
|
||||
steps:
|
||||
- name: "📋 Checkout Code"
|
||||
uses: actions/checkout@v5
|
||||
- name: "🐍 Setup Python 3.11"
|
||||
uses: actions/setup-python@v6
|
||||
with:
|
||||
python-version: "3.11"
|
||||
- name: "📂 Get Changed Files"
|
||||
id: files
|
||||
uses: Ana06/get-changed-files@v2.3.0
|
||||
- name: "🔍 Analyze Changed Files & Generate Build Matrix"
|
||||
id: set-matrix
|
||||
run: |
|
||||
python -m pip install packaging requests
|
||||
python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT
|
||||
outputs:
|
||||
lint: ${{ steps.set-matrix.outputs.lint }}
|
||||
test: ${{ steps.set-matrix.outputs.test }}
|
||||
extended-tests: ${{ steps.set-matrix.outputs.extended-tests }}
|
||||
compile-integration-tests: ${{ steps.set-matrix.outputs.compile-integration-tests }}
|
||||
dependencies: ${{ steps.set-matrix.outputs.dependencies }}
|
||||
test-pydantic: ${{ steps.set-matrix.outputs.test-pydantic }}
|
||||
codspeed: ${{ steps.set-matrix.outputs.codspeed }}
|
||||
# Run linting only on packages that have changed files
|
||||
lint:
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.lint != '[]' }}
|
||||
strategy:
|
||||
matrix:
|
||||
job-configs: ${{ fromJson(needs.build.outputs.lint) }}
|
||||
fail-fast: false
|
||||
uses: ./.github/workflows/_lint.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
python-version: ${{ matrix.job-configs.python-version }}
|
||||
secrets: inherit
|
||||
|
||||
# Run unit tests only on packages that have changed files
|
||||
test:
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.test != '[]' }}
|
||||
strategy:
|
||||
matrix:
|
||||
job-configs: ${{ fromJson(needs.build.outputs.test) }}
|
||||
fail-fast: false
|
||||
uses: ./.github/workflows/_test.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
python-version: ${{ matrix.job-configs.python-version }}
|
||||
secrets: inherit
|
||||
|
||||
# Test compatibility with different Pydantic versions for affected packages
|
||||
test-pydantic:
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.test-pydantic != '[]' }}
|
||||
strategy:
|
||||
matrix:
|
||||
job-configs: ${{ fromJson(needs.build.outputs.test-pydantic) }}
|
||||
fail-fast: false
|
||||
uses: ./.github/workflows/_test_pydantic.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
pydantic-version: ${{ matrix.job-configs.pydantic-version }}
|
||||
secrets: inherit
|
||||
|
||||
# Verify integration tests compile without actually running them (faster feedback)
|
||||
compile-integration-tests:
|
||||
name: "Compile Integration Tests"
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.compile-integration-tests != '[]' }}
|
||||
strategy:
|
||||
matrix:
|
||||
job-configs: ${{ fromJson(needs.build.outputs.compile-integration-tests) }}
|
||||
fail-fast: false
|
||||
uses: ./.github/workflows/_compile_integration_test.yml
|
||||
with:
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
python-version: ${{ matrix.job-configs.python-version }}
|
||||
secrets: inherit
|
||||
|
||||
# Run extended test suites that require additional dependencies
|
||||
extended-tests:
|
||||
name: "Extended Tests"
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.extended-tests != '[]' }}
|
||||
strategy:
|
||||
matrix:
|
||||
# note different variable for extended test dirs
|
||||
job-configs: ${{ fromJson(needs.build.outputs.extended-tests) }}
|
||||
fail-fast: false
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
defaults:
|
||||
run:
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: "🐍 Set up Python ${{ matrix.job-configs.python-version }} + UV"
|
||||
uses: "./.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ matrix.job-configs.python-version }}
|
||||
cache-suffix: extended-tests-${{ matrix.job-configs.working-directory }}
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
|
||||
- name: "📦 Install Dependencies & Run Extended Tests"
|
||||
shell: bash
|
||||
run: |
|
||||
echo "Running extended tests, installing dependencies with uv..."
|
||||
uv venv
|
||||
uv sync --group test
|
||||
VIRTUAL_ENV=.venv uv pip install -r extended_testing_deps.txt
|
||||
VIRTUAL_ENV=.venv make extended_tests
|
||||
|
||||
- name: "🧹 Verify Clean Working Directory"
|
||||
shell: bash
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(git status)"
|
||||
echo "$STATUS"
|
||||
|
||||
# grep will exit non-zero if the target message isn't found,
|
||||
# and `set -e` above will cause the step to fail.
|
||||
echo "$STATUS" | grep 'nothing to commit, working tree clean'
|
||||
|
||||
# Run codspeed benchmarks only on packages that have changed files
|
||||
codspeed:
|
||||
name: "⚡ CodSpeed Benchmarks"
|
||||
needs: [build]
|
||||
if: ${{ needs.build.outputs.codspeed != '[]' && !contains(github.event.pull_request.labels.*.name, 'codspeed-ignore') }}
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
job-configs: ${{ fromJson(needs.build.outputs.codspeed) }}
|
||||
fail-fast: false
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
|
||||
- name: "📦 Install UV Package Manager"
|
||||
uses: astral-sh/setup-uv@v7
|
||||
with:
|
||||
python-version: "3.13"
|
||||
|
||||
- uses: actions/setup-python@v6
|
||||
with:
|
||||
python-version: "3.13"
|
||||
|
||||
- name: "📦 Install Test Dependencies"
|
||||
run: uv sync --group test
|
||||
working-directory: ${{ matrix.job-configs.working-directory }}
|
||||
|
||||
- name: "⚡ Run Benchmarks: ${{ matrix.job-configs.working-directory }}"
|
||||
uses: CodSpeedHQ/action@v4
|
||||
env:
|
||||
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
|
||||
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
|
||||
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
|
||||
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
|
||||
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
|
||||
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
|
||||
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
|
||||
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
|
||||
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
|
||||
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
|
||||
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
|
||||
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
|
||||
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
|
||||
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
|
||||
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
|
||||
with:
|
||||
token: ${{ secrets.CODSPEED_TOKEN }}
|
||||
run: |
|
||||
cd ${{ matrix.job-configs.working-directory }}
|
||||
if [ "${{ matrix.job-configs.working-directory }}" = "libs/core" ]; then
|
||||
uv run --no-sync pytest ./tests/benchmarks --codspeed
|
||||
else
|
||||
uv run --no-sync pytest ./tests/ --codspeed
|
||||
fi
|
||||
mode: ${{ matrix.job-configs.working-directory == 'libs/core' && 'walltime' || 'instrumentation' }}
|
||||
|
||||
# Final status check - ensures all required jobs passed before allowing merge
|
||||
ci_success:
|
||||
name: "✅ CI Success"
|
||||
needs:
|
||||
[
|
||||
build,
|
||||
lint,
|
||||
test,
|
||||
compile-integration-tests,
|
||||
extended-tests,
|
||||
test-pydantic,
|
||||
codspeed,
|
||||
]
|
||||
if: |
|
||||
always()
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
JOBS_JSON: ${{ toJSON(needs) }}
|
||||
RESULTS_JSON: ${{ toJSON(needs.*.result) }}
|
||||
EXIT_CODE: ${{!contains(needs.*.result, 'failure') && !contains(needs.*.result, 'cancelled') && '0' || '1'}}
|
||||
steps:
|
||||
- name: "🎉 All Checks Passed"
|
||||
run: |
|
||||
echo $JOBS_JSON
|
||||
echo $RESULTS_JSON
|
||||
echo "Exiting with $EXIT_CODE"
|
||||
exit $EXIT_CODE
|
||||
181
.github/workflows/integration_tests.yml
vendored
181
.github/workflows/integration_tests.yml
vendored
@@ -1,181 +0,0 @@
|
||||
# Routine integration tests against partner libraries with live API credentials.
|
||||
#
|
||||
# Uses `make integration_tests` for each library in the matrix.
|
||||
#
|
||||
# Runs daily. Can also be triggered manually for immediate updates.
|
||||
|
||||
name: "⏰ Integration Tests"
|
||||
run-name: "Run Integration Tests - ${{ inputs.working-directory-force || 'all libs' }} (Python ${{ inputs.python-version-force || '3.10, 3.13' }})"
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
working-directory-force:
|
||||
type: string
|
||||
description: "From which folder this pipeline executes - defaults to all in matrix - example value: libs/partners/anthropic"
|
||||
python-version-force:
|
||||
type: string
|
||||
description: "Python version to use - defaults to 3.10 and 3.13 in matrix - example value: 3.11"
|
||||
schedule:
|
||||
- cron: "0 13 * * *" # Runs daily at 1PM UTC (9AM EDT/6AM PDT)
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
UV_FROZEN: "true"
|
||||
DEFAULT_LIBS: '["libs/partners/openai", "libs/partners/anthropic", "libs/partners/fireworks", "libs/partners/groq", "libs/partners/mistralai", "libs/partners/xai", "libs/partners/google-vertexai", "libs/partners/google-genai", "libs/partners/aws"]'
|
||||
|
||||
jobs:
|
||||
# Generate dynamic test matrix based on input parameters or defaults
|
||||
# Only runs on the main repo (for scheduled runs) or when manually triggered
|
||||
compute-matrix:
|
||||
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
|
||||
runs-on: ubuntu-latest
|
||||
name: "📋 Compute Test Matrix"
|
||||
outputs:
|
||||
matrix: ${{ steps.set-matrix.outputs.matrix }}
|
||||
steps:
|
||||
- name: "🔢 Generate Python & Library Matrix"
|
||||
id: set-matrix
|
||||
env:
|
||||
DEFAULT_LIBS: ${{ env.DEFAULT_LIBS }}
|
||||
WORKING_DIRECTORY_FORCE: ${{ github.event.inputs.working-directory-force || '' }}
|
||||
PYTHON_VERSION_FORCE: ${{ github.event.inputs.python-version-force || '' }}
|
||||
run: |
|
||||
# echo "matrix=..." where matrix is a json formatted str with keys python-version and working-directory
|
||||
# python-version should default to 3.10 and 3.13, but is overridden to [PYTHON_VERSION_FORCE] if set
|
||||
# working-directory should default to DEFAULT_LIBS, but is overridden to [WORKING_DIRECTORY_FORCE] if set
|
||||
python_version='["3.10", "3.13"]'
|
||||
working_directory="$DEFAULT_LIBS"
|
||||
if [ -n "$PYTHON_VERSION_FORCE" ]; then
|
||||
python_version="[\"$PYTHON_VERSION_FORCE\"]"
|
||||
fi
|
||||
if [ -n "$WORKING_DIRECTORY_FORCE" ]; then
|
||||
working_directory="[\"$WORKING_DIRECTORY_FORCE\"]"
|
||||
fi
|
||||
matrix="{\"python-version\": $python_version, \"working-directory\": $working_directory}"
|
||||
echo $matrix
|
||||
echo "matrix=$matrix" >> $GITHUB_OUTPUT
|
||||
# Run integration tests against partner libraries with live API credentials
|
||||
build:
|
||||
if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
|
||||
name: "🐍 Python ${{ matrix.python-version }}: ${{ matrix.working-directory }}"
|
||||
runs-on: ubuntu-latest
|
||||
needs: [compute-matrix]
|
||||
timeout-minutes: 30
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
python-version: ${{ fromJSON(needs.compute-matrix.outputs.matrix).python-version }}
|
||||
working-directory: ${{ fromJSON(needs.compute-matrix.outputs.matrix).working-directory }}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
path: langchain
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
repository: langchain-ai/langchain-google
|
||||
path: langchain-google
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
repository: langchain-ai/langchain-aws
|
||||
path: langchain-aws
|
||||
|
||||
- name: "📦 Organize External Libraries"
|
||||
run: |
|
||||
rm -rf \
|
||||
langchain/libs/partners/google-genai \
|
||||
langchain/libs/partners/google-vertexai
|
||||
mv langchain-google/libs/genai langchain/libs/partners/google-genai
|
||||
mv langchain-google/libs/vertexai langchain/libs/partners/google-vertexai
|
||||
mv langchain-aws/libs/aws langchain/libs/partners/aws
|
||||
|
||||
- name: "🐍 Set up Python ${{ matrix.python-version }} + UV"
|
||||
uses: "./langchain/.github/actions/uv_setup"
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
|
||||
- name: "🔐 Authenticate to Google Cloud"
|
||||
id: "auth"
|
||||
uses: google-github-actions/auth@v3
|
||||
with:
|
||||
credentials_json: "${{ secrets.GOOGLE_CREDENTIALS }}"
|
||||
|
||||
- name: "🔐 Configure AWS Credentials"
|
||||
uses: aws-actions/configure-aws-credentials@v5
|
||||
with:
|
||||
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
|
||||
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
|
||||
aws-region: ${{ secrets.AWS_REGION }}
|
||||
|
||||
- name: "📦 Install Dependencies"
|
||||
run: |
|
||||
echo "Running scheduled tests, installing dependencies with uv..."
|
||||
cd langchain/${{ matrix.working-directory }}
|
||||
uv sync --group test --group test_integration
|
||||
|
||||
- name: "🚀 Run Integration Tests"
|
||||
env:
|
||||
AI21_API_KEY: ${{ secrets.AI21_API_KEY }}
|
||||
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
|
||||
ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
|
||||
ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
|
||||
ASTRA_DB_API_ENDPOINT: ${{ secrets.ASTRA_DB_API_ENDPOINT }}
|
||||
ASTRA_DB_APPLICATION_TOKEN: ${{ secrets.ASTRA_DB_APPLICATION_TOKEN }}
|
||||
ASTRA_DB_KEYSPACE: ${{ secrets.ASTRA_DB_KEYSPACE }}
|
||||
AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
|
||||
AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}
|
||||
AZURE_OPENAI_API_KEY: ${{ secrets.AZURE_OPENAI_API_KEY }}
|
||||
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
|
||||
AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
|
||||
COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
|
||||
DEEPSEEK_API_KEY: ${{ secrets.DEEPSEEK_API_KEY }}
|
||||
ES_URL: ${{ secrets.ES_URL }}
|
||||
ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
|
||||
ES_API_KEY: ${{ secrets.ES_API_KEY }}
|
||||
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
|
||||
FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
|
||||
GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
|
||||
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
|
||||
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
|
||||
GROQ_API_KEY: ${{ secrets.GROQ_API_KEY }}
|
||||
HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
|
||||
MISTRAL_API_KEY: ${{ secrets.MISTRAL_API_KEY }}
|
||||
MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
|
||||
NOMIC_API_KEY: ${{ secrets.NOMIC_API_KEY }}
|
||||
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
|
||||
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
|
||||
PPLX_API_KEY: ${{ secrets.PPLX_API_KEY }}
|
||||
TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
|
||||
UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
|
||||
WATSONX_APIKEY: ${{ secrets.WATSONX_APIKEY }}
|
||||
WATSONX_PROJECT_ID: ${{ secrets.WATSONX_PROJECT_ID }}
|
||||
XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
|
||||
LANGCHAIN_TESTS_USER_AGENT: ${{ secrets.LANGCHAIN_TESTS_USER_AGENT }}
|
||||
run: |
|
||||
cd langchain/${{ matrix.working-directory }}
|
||||
make integration_tests
|
||||
|
||||
- name: "🧹 Clean up External Libraries"
|
||||
# Clean up external libraries to avoid affecting the following git status check
|
||||
run: |
|
||||
rm -rf \
|
||||
langchain/libs/partners/google-genai \
|
||||
langchain/libs/partners/google-vertexai \
|
||||
langchain/libs/partners/aws
|
||||
|
||||
- name: "🧹 Verify Clean Working Directory"
|
||||
working-directory: langchain
|
||||
run: |
|
||||
set -eu
|
||||
|
||||
STATUS="$(git status)"
|
||||
echo "$STATUS"
|
||||
|
||||
# grep will exit non-zero if the target message isn't found,
|
||||
# and `set -e` above will cause the step to fail.
|
||||
echo "$STATUS" | grep 'nothing to commit, working tree clean'
|
||||
23
.github/workflows/lint.yml
vendored
Normal file
23
.github/workflows/lint.yml
vendored
Normal file
@@ -0,0 +1,23 @@
|
||||
name: lint
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ["3.7"]
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v3
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r test_requirements.txt
|
||||
- name: Analysing the code with our lint
|
||||
run: |
|
||||
make lint
|
||||
28
.github/workflows/pr_labeler_file.yml
vendored
28
.github/workflows/pr_labeler_file.yml
vendored
@@ -1,28 +0,0 @@
|
||||
# Label PRs based on changed files.
|
||||
#
|
||||
# See `.github/pr-file-labeler.yml` to see rules for each label/directory.
|
||||
|
||||
name: "🏷️ Pull Request Labeler"
|
||||
|
||||
on:
|
||||
# Safe since we're not checking out or running the PR's code
|
||||
# Never check out the PR's head in a pull_request_target job
|
||||
pull_request_target:
|
||||
types: [opened, synchronize, reopened, edited]
|
||||
|
||||
jobs:
|
||||
labeler:
|
||||
name: "label"
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: write
|
||||
issues: write
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Label Pull Request
|
||||
uses: actions/labeler@v6
|
||||
with:
|
||||
repo-token: "${{ secrets.GITHUB_TOKEN }}"
|
||||
configuration-path: .github/pr-file-labeler.yml
|
||||
sync-labels: false
|
||||
44
.github/workflows/pr_labeler_title.yml
vendored
44
.github/workflows/pr_labeler_title.yml
vendored
@@ -1,44 +0,0 @@
|
||||
# Label PRs based on their titles.
|
||||
#
|
||||
# Uses conventional commit types from PR titles to apply labels.
|
||||
# Note: Scope-based labeling (e.g., integration labels) is handled by pr_labeler_file.yml
|
||||
|
||||
name: "🏷️ PR Title Labeler"
|
||||
|
||||
on:
|
||||
# Safe since we're not checking out or running the PR's code
|
||||
# Never check out the PR's head in a pull_request_target job
|
||||
pull_request_target:
|
||||
types: [opened, edited]
|
||||
|
||||
jobs:
|
||||
pr-title-labeler:
|
||||
name: "label"
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: write
|
||||
issues: write
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- name: Label PR based on title
|
||||
uses: bcoe/conventional-release-labels@v1
|
||||
with:
|
||||
token: ${{ secrets.GITHUB_TOKEN }}
|
||||
type_labels: >-
|
||||
{
|
||||
"feat": "feature",
|
||||
"fix": "fix",
|
||||
"docs": "documentation",
|
||||
"style": "linting",
|
||||
"refactor": "refactor",
|
||||
"perf": "performance",
|
||||
"test": "tests",
|
||||
"build": "infra",
|
||||
"ci": "infra",
|
||||
"chore": "infra",
|
||||
"revert": "revert",
|
||||
"release": "release",
|
||||
"breaking": "breaking"
|
||||
}
|
||||
ignored_types: '[]'
|
||||
108
.github/workflows/pr_lint.yml
vendored
108
.github/workflows/pr_lint.yml
vendored
@@ -1,108 +0,0 @@
|
||||
# PR title linting.
|
||||
#
|
||||
# FORMAT (Conventional Commits 1.0.0):
|
||||
#
|
||||
# <type>[optional scope]: <description>
|
||||
# [optional body]
|
||||
# [optional footer(s)]
|
||||
#
|
||||
# Examples:
|
||||
# feat(core): add multi‐tenant support
|
||||
# fix(cli): resolve flag parsing error
|
||||
# docs: update API usage examples
|
||||
# docs(openai): update API usage examples
|
||||
#
|
||||
# Allowed Types:
|
||||
# * feat — a new feature (MINOR)
|
||||
# * fix — a bug fix (PATCH)
|
||||
# * docs — documentation only changes
|
||||
# * style — formatting, linting, etc.; no code change or typing refactors
|
||||
# * refactor — code change that neither fixes a bug nor adds a feature
|
||||
# * perf — code change that improves performance
|
||||
# * test — adding tests or correcting existing
|
||||
# * build — changes that affect the build system/external dependencies
|
||||
# * ci — continuous integration/configuration changes
|
||||
# * chore — other changes that don't modify source or test files
|
||||
# * revert — reverts a previous commit
|
||||
# * release — prepare a new release
|
||||
#
|
||||
# Allowed Scopes (optional):
|
||||
# core, cli, langchain, langchain_v1, langchain-classic, standard-tests,
|
||||
# text-splitters, docs, anthropic, chroma, deepseek, exa, fireworks, groq,
|
||||
# huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant,
|
||||
# xai, infra, deps
|
||||
#
|
||||
# Rules:
|
||||
# 1. The 'Type' must start with a lowercase letter.
|
||||
# 2. Breaking changes: append "!" after type/scope (e.g., feat!: drop x support)
|
||||
# 3. When releasing (updating the pyproject.toml and uv.lock), the commit message
|
||||
# should be: `release(scope): x.y.z` (e.g., `release(core): 1.2.0` with no
|
||||
# body, footer, or preceeding/proceeding text).
|
||||
#
|
||||
# Enforces Conventional Commits format for pull request titles to maintain a clear and
|
||||
# machine-readable change history.
|
||||
|
||||
name: "🏷️ PR Title Lint"
|
||||
|
||||
permissions:
|
||||
pull-requests: read
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
types: [opened, edited, synchronize]
|
||||
|
||||
jobs:
|
||||
# Validates that PR title follows Conventional Commits 1.0.0 specification
|
||||
lint-pr-title:
|
||||
name: "validate format"
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: "✅ Validate Conventional Commits Format"
|
||||
uses: amannn/action-semantic-pull-request@v6
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
with:
|
||||
types: |
|
||||
feat
|
||||
fix
|
||||
docs
|
||||
style
|
||||
refactor
|
||||
perf
|
||||
test
|
||||
build
|
||||
ci
|
||||
chore
|
||||
revert
|
||||
release
|
||||
scopes: |
|
||||
core
|
||||
cli
|
||||
langchain
|
||||
langchain_classic
|
||||
model-profiles
|
||||
standard-tests
|
||||
text-splitters
|
||||
docs
|
||||
anthropic
|
||||
chroma
|
||||
deepseek
|
||||
exa
|
||||
fireworks
|
||||
groq
|
||||
huggingface
|
||||
mistralai
|
||||
nomic
|
||||
ollama
|
||||
openai
|
||||
perplexity
|
||||
prompty
|
||||
qdrant
|
||||
xai
|
||||
infra
|
||||
requireScope: false
|
||||
disallowScopes: |
|
||||
release
|
||||
[A-Z]+
|
||||
ignoreLabels: |
|
||||
ignore-lint-pr-title
|
||||
23
.github/workflows/test.yml
vendored
Normal file
23
.github/workflows/test.yml
vendored
Normal file
@@ -0,0 +1,23 @@
|
||||
name: test
|
||||
|
||||
on: [push, pull_request]
|
||||
|
||||
jobs:
|
||||
build:
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
matrix:
|
||||
python-version: ["3.7"]
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v3
|
||||
with:
|
||||
python-version: ${{ matrix.python-version }}
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r test_requirements.txt
|
||||
- name: Run unit tests
|
||||
run: |
|
||||
make tests
|
||||
164
.github/workflows/v03_api_doc_build.yml
vendored
164
.github/workflows/v03_api_doc_build.yml
vendored
@@ -1,164 +0,0 @@
|
||||
# Build the API reference documentation for v0.3 branch.
|
||||
#
|
||||
# Manual trigger only.
|
||||
#
|
||||
# Built HTML pushed to langchain-ai/langchain-api-docs-html.
|
||||
#
|
||||
# Looks for langchain-ai org repos in packages.yml and checks them out.
|
||||
# Calls prep_api_docs_build.py.
|
||||
|
||||
name: "📚 API Docs (v0.3)"
|
||||
run-name: "Build & Deploy API Reference (v0.3)"
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
|
||||
env:
|
||||
PYTHON_VERSION: "3.11"
|
||||
|
||||
jobs:
|
||||
build:
|
||||
if: github.repository == 'langchain-ai/langchain' || github.event_name != 'schedule'
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
steps:
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
ref: v0.3
|
||||
path: langchain
|
||||
|
||||
- uses: actions/checkout@v5
|
||||
with:
|
||||
repository: langchain-ai/langchain-api-docs-html
|
||||
path: langchain-api-docs-html
|
||||
token: ${{ secrets.TOKEN_GITHUB_API_DOCS_HTML }}
|
||||
|
||||
- name: "📋 Extract Repository List with yq"
|
||||
id: get-unsorted-repos
|
||||
uses: mikefarah/yq@master
|
||||
with:
|
||||
cmd: |
|
||||
# Extract repos from packages.yml that are in the langchain-ai org
|
||||
# (excluding 'langchain' itself)
|
||||
yq '
|
||||
.packages[]
|
||||
| select(
|
||||
(
|
||||
(.repo | test("^langchain-ai/"))
|
||||
and
|
||||
(.repo != "langchain-ai/langchain")
|
||||
)
|
||||
or
|
||||
(.include_in_api_ref // false)
|
||||
)
|
||||
| .repo
|
||||
' langchain/libs/packages.yml
|
||||
|
||||
- name: "📋 Parse YAML & Checkout Repositories"
|
||||
env:
|
||||
REPOS_UNSORTED: ${{ steps.get-unsorted-repos.outputs.result }}
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
run: |
|
||||
# Get unique repositories
|
||||
REPOS=$(echo "$REPOS_UNSORTED" | sort -u)
|
||||
# Checkout each unique repository
|
||||
for repo in $REPOS; do
|
||||
# Validate repository format (allow any org with proper format)
|
||||
if [[ ! "$repo" =~ ^[a-zA-Z0-9_.-]+/[a-zA-Z0-9_.-]+$ ]]; then
|
||||
echo "Error: Invalid repository format: $repo"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
REPO_NAME=$(echo $repo | cut -d'/' -f2)
|
||||
|
||||
# Additional validation for repo name
|
||||
if [[ ! "$REPO_NAME" =~ ^[a-zA-Z0-9_.-]+$ ]]; then
|
||||
echo "Error: Invalid repository name: $REPO_NAME"
|
||||
exit 1
|
||||
fi
|
||||
echo "Checking out $repo to $REPO_NAME"
|
||||
|
||||
# Special handling for langchain-tavily: checkout by commit hash
|
||||
if [[ "$REPO_NAME" == "langchain-tavily" ]]; then
|
||||
git clone https://github.com/$repo.git $REPO_NAME
|
||||
cd $REPO_NAME
|
||||
git checkout f3515654724a9e87bdfe2c2f509d6cdde646e563
|
||||
cd ..
|
||||
else
|
||||
git clone --depth 1 --branch v0.3 https://github.com/$repo.git $REPO_NAME
|
||||
fi
|
||||
done
|
||||
|
||||
- name: "🐍 Setup Python ${{ env.PYTHON_VERSION }}"
|
||||
uses: actions/setup-python@v6
|
||||
id: setup-python
|
||||
with:
|
||||
python-version: ${{ env.PYTHON_VERSION }}
|
||||
|
||||
- name: "📦 Install Initial Python Dependencies using uv"
|
||||
working-directory: langchain
|
||||
run: |
|
||||
python -m pip install -U uv
|
||||
python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml
|
||||
|
||||
- name: "📦 Organize Library Directories"
|
||||
# Places cloned partner packages into libs/partners structure
|
||||
run: python langchain/.github/scripts/prep_api_docs_build.py
|
||||
|
||||
- name: "🧹 Clear Prior Build"
|
||||
run:
|
||||
# Remove artifacts from prior docs build
|
||||
rm -rf langchain-api-docs-html/api_reference_build/html
|
||||
|
||||
- name: "📦 Install Documentation Dependencies using uv"
|
||||
working-directory: langchain
|
||||
run: |
|
||||
# Install all partner packages in editable mode with overrides
|
||||
python -m uv pip install $(ls ./libs/partners | grep -v azure-ai | xargs -I {} echo "./libs/partners/{}") --overrides ./docs/vercel_overrides.txt --prerelease=allow
|
||||
|
||||
# Install langchain-azure-ai with tools extra
|
||||
python -m uv pip install "./libs/partners/azure-ai[tools]" --overrides ./docs/vercel_overrides.txt --prerelease=allow
|
||||
|
||||
# Install core langchain and other main packages
|
||||
python -m uv pip install libs/core libs/langchain libs/text-splitters libs/community libs/experimental libs/standard-tests
|
||||
|
||||
# Install Sphinx and related packages for building docs
|
||||
python -m uv pip install -r docs/api_reference/requirements.txt
|
||||
|
||||
- name: "🔧 Configure Git Settings"
|
||||
working-directory: langchain
|
||||
run: |
|
||||
git config --local user.email "actions@github.com"
|
||||
git config --local user.name "Github Actions"
|
||||
|
||||
- name: "📚 Build API Documentation"
|
||||
working-directory: langchain
|
||||
run: |
|
||||
# Generate the API reference RST files
|
||||
python docs/api_reference/create_api_rst.py
|
||||
|
||||
# Build the HTML documentation using Sphinx
|
||||
# -T: show full traceback on exception
|
||||
# -E: don't use cached environment (force rebuild, ignore cached doctrees)
|
||||
# -b html: build HTML docs (vs PDS, etc.)
|
||||
# -d: path for the cached environment (parsed document trees / doctrees)
|
||||
# - Separate from output dir for faster incremental builds
|
||||
# -c: path to conf.py
|
||||
# -j auto: parallel build using all available CPU cores
|
||||
python -m sphinx -T -E -b html -d ../langchain-api-docs-html/_build/doctrees -c docs/api_reference docs/api_reference ../langchain-api-docs-html/api_reference_build/html -j auto
|
||||
|
||||
# Post-process the generated HTML
|
||||
python docs/api_reference/scripts/custom_formatter.py ../langchain-api-docs-html/api_reference_build/html
|
||||
|
||||
# Default index page is blank so we copy in the actual home page.
|
||||
cp ../langchain-api-docs-html/api_reference_build/html/{reference,index}.html
|
||||
|
||||
# Removes Sphinx's intermediate build artifacts after the build is complete.
|
||||
rm -rf ../langchain-api-docs-html/_build/
|
||||
|
||||
# Commit and push changes to langchain-api-docs-html repo
|
||||
- uses: EndBug/add-and-commit@v9
|
||||
with:
|
||||
cwd: langchain-api-docs-html
|
||||
message: "Update API docs build from v0.3 branch"
|
||||
8
.github/workflows/v1_changes.md
vendored
8
.github/workflows/v1_changes.md
vendored
@@ -1,8 +0,0 @@
|
||||
With the deprecation of v0 docs, the following files will need to be migrated/supported
|
||||
in the new docs repo:
|
||||
|
||||
- run_notebooks.yml: New repo should run Integration tests on code snippets?
|
||||
- people.yml: Need to fix and somehow display on the new docs site
|
||||
- Subsequently, `.github/actions/people/`
|
||||
- _test_doc_imports.yml
|
||||
- check-broken-links.yml
|
||||
48
.gitignore
vendored
48
.gitignore
vendored
@@ -1,8 +1,4 @@
|
||||
.vs/
|
||||
.claude/
|
||||
.idea/
|
||||
#Emacs backup
|
||||
*~
|
||||
.vscode/
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
@@ -32,12 +28,6 @@ share/python-wheels/
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# Google GitHub Actions credentials files created by:
|
||||
# https://github.com/google-github-actions/auth
|
||||
#
|
||||
# That action recommends adding this gitignore to prevent accidentally committing keys.
|
||||
gha-creds-*.json
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python script from a template
|
||||
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
||||
@@ -61,7 +51,6 @@ coverage.xml
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
.codspeed/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
@@ -80,6 +69,9 @@ instance/
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
target/
|
||||
|
||||
@@ -113,12 +105,12 @@ celerybeat.pid
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.envrc
|
||||
.venv*
|
||||
venv*
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
@@ -132,34 +124,8 @@ env.bak/
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.mypy_cache_test/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# macOS display setting files
|
||||
.DS_Store
|
||||
|
||||
# Wandb directory
|
||||
wandb/
|
||||
|
||||
# asdf tool versions
|
||||
.tool-versions
|
||||
/.ruff_cache/
|
||||
|
||||
*.pkl
|
||||
*.bin
|
||||
|
||||
# integration test artifacts
|
||||
data_map*
|
||||
\[('_type', 'fake'), ('stop', None)]
|
||||
|
||||
# Replit files
|
||||
*replit*
|
||||
|
||||
node_modules
|
||||
|
||||
prof
|
||||
virtualenv/
|
||||
|
||||
@@ -1,14 +0,0 @@
|
||||
{
|
||||
"MD013": false,
|
||||
"MD024": {
|
||||
"siblings_only": true
|
||||
},
|
||||
"MD025": false,
|
||||
"MD033": false,
|
||||
"MD034": false,
|
||||
"MD036": false,
|
||||
"MD041": false,
|
||||
"MD046": {
|
||||
"style": "fenced"
|
||||
}
|
||||
}
|
||||
@@ -1,8 +0,0 @@
|
||||
{
|
||||
"mcpServers": {
|
||||
"docs-langchain": {
|
||||
"type": "http",
|
||||
"url": "https://docs.langchain.com/mcp"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,99 +0,0 @@
|
||||
repos:
|
||||
- repo: local
|
||||
hooks:
|
||||
- id: core
|
||||
name: format and lint core
|
||||
language: system
|
||||
entry: make -C libs/core format lint
|
||||
files: ^libs/core/
|
||||
pass_filenames: false
|
||||
- id: langchain
|
||||
name: format and lint langchain
|
||||
language: system
|
||||
entry: make -C libs/langchain format lint
|
||||
files: ^libs/langchain/
|
||||
pass_filenames: false
|
||||
- id: standard-tests
|
||||
name: format and lint standard-tests
|
||||
language: system
|
||||
entry: make -C libs/standard-tests format lint
|
||||
files: ^libs/standard-tests/
|
||||
pass_filenames: false
|
||||
- id: text-splitters
|
||||
name: format and lint text-splitters
|
||||
language: system
|
||||
entry: make -C libs/text-splitters format lint
|
||||
files: ^libs/text-splitters/
|
||||
pass_filenames: false
|
||||
- id: anthropic
|
||||
name: format and lint partners/anthropic
|
||||
language: system
|
||||
entry: make -C libs/partners/anthropic format lint
|
||||
files: ^libs/partners/anthropic/
|
||||
pass_filenames: false
|
||||
- id: chroma
|
||||
name: format and lint partners/chroma
|
||||
language: system
|
||||
entry: make -C libs/partners/chroma format lint
|
||||
files: ^libs/partners/chroma/
|
||||
pass_filenames: false
|
||||
- id: exa
|
||||
name: format and lint partners/exa
|
||||
language: system
|
||||
entry: make -C libs/partners/exa format lint
|
||||
files: ^libs/partners/exa/
|
||||
pass_filenames: false
|
||||
- id: fireworks
|
||||
name: format and lint partners/fireworks
|
||||
language: system
|
||||
entry: make -C libs/partners/fireworks format lint
|
||||
files: ^libs/partners/fireworks/
|
||||
pass_filenames: false
|
||||
- id: groq
|
||||
name: format and lint partners/groq
|
||||
language: system
|
||||
entry: make -C libs/partners/groq format lint
|
||||
files: ^libs/partners/groq/
|
||||
pass_filenames: false
|
||||
- id: huggingface
|
||||
name: format and lint partners/huggingface
|
||||
language: system
|
||||
entry: make -C libs/partners/huggingface format lint
|
||||
files: ^libs/partners/huggingface/
|
||||
pass_filenames: false
|
||||
- id: mistralai
|
||||
name: format and lint partners/mistralai
|
||||
language: system
|
||||
entry: make -C libs/partners/mistralai format lint
|
||||
files: ^libs/partners/mistralai/
|
||||
pass_filenames: false
|
||||
- id: nomic
|
||||
name: format and lint partners/nomic
|
||||
language: system
|
||||
entry: make -C libs/partners/nomic format lint
|
||||
files: ^libs/partners/nomic/
|
||||
pass_filenames: false
|
||||
- id: ollama
|
||||
name: format and lint partners/ollama
|
||||
language: system
|
||||
entry: make -C libs/partners/ollama format lint
|
||||
files: ^libs/partners/ollama/
|
||||
pass_filenames: false
|
||||
- id: openai
|
||||
name: format and lint partners/openai
|
||||
language: system
|
||||
entry: make -C libs/partners/openai format lint
|
||||
files: ^libs/partners/openai/
|
||||
pass_filenames: false
|
||||
- id: prompty
|
||||
name: format and lint partners/prompty
|
||||
language: system
|
||||
entry: make -C libs/partners/prompty format lint
|
||||
files: ^libs/partners/prompty/
|
||||
pass_filenames: false
|
||||
- id: qdrant
|
||||
name: format and lint partners/qdrant
|
||||
language: system
|
||||
entry: make -C libs/partners/qdrant format lint
|
||||
files: ^libs/partners/qdrant/
|
||||
pass_filenames: false
|
||||
21
.vscode/extensions.json
vendored
21
.vscode/extensions.json
vendored
@@ -1,21 +0,0 @@
|
||||
{
|
||||
"recommendations": [
|
||||
"ms-python.python",
|
||||
"charliermarsh.ruff",
|
||||
"ms-python.mypy-type-checker",
|
||||
"ms-toolsai.jupyter",
|
||||
"ms-toolsai.jupyter-keymap",
|
||||
"ms-toolsai.jupyter-renderers",
|
||||
"ms-toolsai.vscode-jupyter-cell-tags",
|
||||
"ms-toolsai.vscode-jupyter-slideshow",
|
||||
"yzhang.markdown-all-in-one",
|
||||
"davidanson.vscode-markdownlint",
|
||||
"bierner.markdown-mermaid",
|
||||
"bierner.markdown-preview-github-styles",
|
||||
"eamodio.gitlens",
|
||||
"github.vscode-pull-request-github",
|
||||
"github.vscode-github-actions",
|
||||
"redhat.vscode-yaml",
|
||||
"editorconfig.editorconfig",
|
||||
],
|
||||
}
|
||||
78
.vscode/settings.json
vendored
78
.vscode/settings.json
vendored
@@ -1,78 +0,0 @@
|
||||
{
|
||||
"python.analysis.include": [
|
||||
"libs/**",
|
||||
],
|
||||
"python.analysis.exclude": [
|
||||
"**/node_modules",
|
||||
"**/__pycache__",
|
||||
"**/.pytest_cache",
|
||||
"**/.*",
|
||||
],
|
||||
"python.analysis.autoImportCompletions": true,
|
||||
"python.analysis.typeCheckingMode": "basic",
|
||||
"python.testing.cwd": "${workspaceFolder}",
|
||||
"python.linting.enabled": true,
|
||||
"python.linting.ruffEnabled": true,
|
||||
"[python]": {
|
||||
"editor.formatOnSave": true,
|
||||
"editor.codeActionsOnSave": {
|
||||
"source.organizeImports.ruff": "explicit",
|
||||
"source.fixAll": "explicit"
|
||||
},
|
||||
"editor.defaultFormatter": "charliermarsh.ruff"
|
||||
},
|
||||
"editor.rulers": [
|
||||
88
|
||||
],
|
||||
"editor.tabSize": 4,
|
||||
"editor.insertSpaces": true,
|
||||
"editor.trimAutoWhitespace": true,
|
||||
"files.trimTrailingWhitespace": true,
|
||||
"files.insertFinalNewline": true,
|
||||
"files.exclude": {
|
||||
"**/__pycache__": true,
|
||||
"**/.pytest_cache": true,
|
||||
"**/*.pyc": true,
|
||||
"**/.mypy_cache": true,
|
||||
"**/.ruff_cache": true,
|
||||
"_dist/**": true,
|
||||
"**/node_modules": true,
|
||||
"**/.git": false
|
||||
},
|
||||
"search.exclude": {
|
||||
"**/__pycache__": true,
|
||||
"**/*.pyc": true,
|
||||
"_dist/**": true,
|
||||
"**/node_modules": true,
|
||||
"**/.git": true,
|
||||
"uv.lock": true,
|
||||
"yarn.lock": true
|
||||
},
|
||||
"git.autofetch": true,
|
||||
"git.enableSmartCommit": true,
|
||||
"jupyter.askForKernelRestart": false,
|
||||
"jupyter.interactiveWindow.textEditor.executeSelection": true,
|
||||
"[markdown]": {
|
||||
"editor.wordWrap": "on",
|
||||
"editor.quickSuggestions": {
|
||||
"comments": "off",
|
||||
"strings": "off",
|
||||
"other": "off"
|
||||
}
|
||||
},
|
||||
"[yaml]": {
|
||||
"editor.tabSize": 2,
|
||||
"editor.insertSpaces": true
|
||||
},
|
||||
"[json]": {
|
||||
"editor.tabSize": 2,
|
||||
"editor.insertSpaces": true
|
||||
},
|
||||
"python.terminal.activateEnvironment": false,
|
||||
"python.defaultInterpreterPath": "./.venv/bin/python",
|
||||
"github.copilot.chat.commitMessageGeneration.instructions": [
|
||||
{
|
||||
"file": ".github/workflows/pr_lint.yml"
|
||||
}
|
||||
]
|
||||
}
|
||||
326
AGENTS.md
326
AGENTS.md
@@ -1,326 +0,0 @@
|
||||
# Global Development Guidelines for LangChain Projects
|
||||
|
||||
## Core Development Principles
|
||||
|
||||
### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
|
||||
|
||||
**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
|
||||
|
||||
❌ **Bad - Breaking Change:**
|
||||
|
||||
```python
|
||||
def get_user(id, verbose=False): # Changed from `user_id`
|
||||
pass
|
||||
```
|
||||
|
||||
✅ **Good - Stable Interface:**
|
||||
|
||||
```python
|
||||
def get_user(user_id: str, verbose: bool = False) -> User:
|
||||
"""Retrieve user by ID with optional verbose output."""
|
||||
pass
|
||||
```
|
||||
|
||||
**Before making ANY changes to public APIs:**
|
||||
|
||||
- Check if the function/class is exported in `__init__.py`
|
||||
- Look for existing usage patterns in tests and examples
|
||||
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
|
||||
- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
|
||||
|
||||
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
|
||||
|
||||
### 2. Code Quality Standards
|
||||
|
||||
**All Python code MUST include type hints and return types.**
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def p(u, d):
|
||||
return [x for x in u if x not in d]
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
|
||||
"""Filter out users that are not in the known users set.
|
||||
|
||||
Args:
|
||||
users: List of user identifiers to filter.
|
||||
known_users: Set of known/valid user identifiers.
|
||||
|
||||
Returns:
|
||||
List of users that are not in the known_users set.
|
||||
"""
|
||||
return [user for user in users if user not in known_users]
|
||||
```
|
||||
|
||||
**Style Requirements:**
|
||||
|
||||
- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
|
||||
- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
|
||||
- Avoid unnecessary abstraction or premature optimization
|
||||
- Follow existing patterns in the codebase you're modifying
|
||||
|
||||
### 3. Testing Requirements
|
||||
|
||||
**Every new feature or bugfix MUST be covered by unit tests.**
|
||||
|
||||
**Test Organization:**
|
||||
|
||||
- Unit tests: `tests/unit_tests/` (no network calls allowed)
|
||||
- Integration tests: `tests/integration_tests/` (network calls permitted)
|
||||
- Use `pytest` as the testing framework
|
||||
|
||||
**Test Quality Checklist:**
|
||||
|
||||
- [ ] Tests fail when your new logic is broken
|
||||
- [ ] Happy path is covered
|
||||
- [ ] Edge cases and error conditions are tested
|
||||
- [ ] Use fixtures/mocks for external dependencies
|
||||
- [ ] Tests are deterministic (no flaky tests)
|
||||
|
||||
Checklist questions:
|
||||
|
||||
- [ ] Does the test suite fail if your new logic is broken?
|
||||
- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
|
||||
- [ ] Do tests use fixtures or mocks where needed?
|
||||
|
||||
```python
|
||||
def test_filter_unknown_users():
|
||||
"""Test filtering unknown users from a list."""
|
||||
users = ["alice", "bob", "charlie"]
|
||||
known_users = {"alice", "bob"}
|
||||
|
||||
result = filter_unknown_users(users, known_users)
|
||||
|
||||
assert result == ["charlie"]
|
||||
assert len(result) == 1
|
||||
```
|
||||
|
||||
### 4. Security and Risk Assessment
|
||||
|
||||
**Security Checklist:**
|
||||
|
||||
- No `eval()`, `exec()`, or `pickle` on user-controlled input
|
||||
- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
|
||||
- Remove unreachable/commented code before committing
|
||||
- Race conditions or resource leaks (file handles, sockets, threads).
|
||||
- Ensure proper resource cleanup (file handles, connections)
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def load_config(path):
|
||||
with open(path) as f:
|
||||
return eval(f.read()) # ⚠️ Never eval config
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
def load_config(path: str) -> dict:
|
||||
with open(path) as f:
|
||||
return json.load(f)
|
||||
```
|
||||
|
||||
### 5. Documentation Standards
|
||||
|
||||
**Use Google-style docstrings with Args section for all public functions.**
|
||||
|
||||
❌ **Insufficient Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to, msg):
|
||||
"""Send an email to a recipient."""
|
||||
```
|
||||
|
||||
✅ **Complete Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
|
||||
"""
|
||||
Send an email to a recipient with specified priority.
|
||||
|
||||
Args:
|
||||
to: The email address of the recipient.
|
||||
msg: The message body to send.
|
||||
priority: Email priority level (`'low'`, `'normal'`, `'high'`).
|
||||
|
||||
Returns:
|
||||
`True` if email was sent successfully, `False` otherwise.
|
||||
|
||||
Raises:
|
||||
`InvalidEmailError`: If the email address format is invalid.
|
||||
`SMTPConnectionError`: If unable to connect to email server.
|
||||
"""
|
||||
```
|
||||
|
||||
**Documentation Guidelines:**
|
||||
|
||||
- Types go in function signatures, NOT in docstrings
|
||||
- If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
|
||||
- Focus on "why" rather than "what" in descriptions
|
||||
- Document all parameters, return values, and exceptions
|
||||
- Keep descriptions concise but clear
|
||||
- Ensure American English spelling (e.g., "behavior", not "behaviour")
|
||||
|
||||
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
|
||||
|
||||
### 6. Architectural Improvements
|
||||
|
||||
**When you encounter code that could be improved, suggest better designs:**
|
||||
|
||||
❌ **Poor Design:**
|
||||
|
||||
```python
|
||||
def process_data(data, db_conn, email_client, logger):
|
||||
# Function doing too many things
|
||||
validated = validate_data(data)
|
||||
result = db_conn.save(validated)
|
||||
email_client.send_notification(result)
|
||||
logger.log(f"Processed {len(data)} items")
|
||||
return result
|
||||
```
|
||||
|
||||
✅ **Better Design:**
|
||||
|
||||
```python
|
||||
@dataclass
|
||||
class ProcessingResult:
|
||||
"""Result of data processing operation."""
|
||||
items_processed: int
|
||||
success: bool
|
||||
errors: List[str] = field(default_factory=list)
|
||||
|
||||
class DataProcessor:
|
||||
"""Handles data validation, storage, and notification."""
|
||||
|
||||
def __init__(self, db_conn: Database, email_client: EmailClient):
|
||||
self.db = db_conn
|
||||
self.email = email_client
|
||||
|
||||
def process(self, data: List[dict]) -> ProcessingResult:
|
||||
"""Process and store data with notifications."""
|
||||
validated = self._validate_data(data)
|
||||
result = self.db.save(validated)
|
||||
self._notify_completion(result)
|
||||
return result
|
||||
```
|
||||
|
||||
**Design Improvement Areas:**
|
||||
|
||||
If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
|
||||
|
||||
- Reduce code duplication through shared utilities
|
||||
- Make unit testing easier
|
||||
- Improve separation of concerns (single responsibility)
|
||||
- Make unit testing easier through dependency injection
|
||||
- Add clarity without adding complexity
|
||||
- Prefer dataclasses for structured data
|
||||
|
||||
## Development Tools & Commands
|
||||
|
||||
### Package Management
|
||||
|
||||
```bash
|
||||
# Add package
|
||||
uv add package-name
|
||||
|
||||
# Sync project dependencies
|
||||
uv sync
|
||||
uv lock
|
||||
```
|
||||
|
||||
### Testing
|
||||
|
||||
```bash
|
||||
# Run unit tests (no network)
|
||||
make test
|
||||
|
||||
# Don't run integration tests, as API keys must be set
|
||||
|
||||
# Run specific test file
|
||||
uv run --group test pytest tests/unit_tests/test_specific.py
|
||||
```
|
||||
|
||||
### Code Quality
|
||||
|
||||
```bash
|
||||
# Lint code
|
||||
make lint
|
||||
|
||||
# Format code
|
||||
make format
|
||||
|
||||
# Type checking
|
||||
uv run --group lint mypy .
|
||||
```
|
||||
|
||||
### Dependency Management Patterns
|
||||
|
||||
**Local Development Dependencies:**
|
||||
|
||||
```toml
|
||||
[tool.uv.sources]
|
||||
langchain-core = { path = "../core", editable = true }
|
||||
langchain-tests = { path = "../standard-tests", editable = true }
|
||||
```
|
||||
|
||||
**For tools, use the `@tool` decorator from `langchain_core.tools`:**
|
||||
|
||||
```python
|
||||
from langchain_core.tools import tool
|
||||
|
||||
@tool
|
||||
def search_database(query: str) -> str:
|
||||
"""Search the database for relevant information.
|
||||
|
||||
Args:
|
||||
query: The search query string.
|
||||
"""
|
||||
# Implementation here
|
||||
return results
|
||||
```
|
||||
|
||||
## Commit Standards
|
||||
|
||||
**Use Conventional Commits format for PR titles:**
|
||||
|
||||
- `feat(core): add multi-tenant support`
|
||||
- `fix(cli): resolve flag parsing error`
|
||||
- `docs: update API usage examples`
|
||||
- `docs(openai): update API usage examples`
|
||||
|
||||
## Framework-Specific Guidelines
|
||||
|
||||
- Follow the existing patterns in `langchain-core` for base abstractions
|
||||
- Use `langchain_core.callbacks` for execution tracking
|
||||
- Implement proper streaming support where applicable
|
||||
- Avoid deprecated components like legacy `LLMChain`
|
||||
|
||||
### Partner Integrations
|
||||
|
||||
- Follow the established patterns in existing partner libraries
|
||||
- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
|
||||
- Include comprehensive integration tests
|
||||
- Document API key requirements and authentication
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference Checklist
|
||||
|
||||
Before submitting code changes:
|
||||
|
||||
- [ ] **Breaking Changes**: Verified no public API changes
|
||||
- [ ] **Type Hints**: All functions have complete type annotations
|
||||
- [ ] **Tests**: New functionality is fully tested
|
||||
- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
|
||||
- [ ] **Documentation**: Google-style docstrings for public functions
|
||||
- [ ] **Code Quality**: `make lint` and `make format` pass
|
||||
- [ ] **Architecture**: Suggested improvements where applicable
|
||||
- [ ] **Commit Message**: Follows Conventional Commits format
|
||||
@@ -1,8 +0,0 @@
|
||||
cff-version: 1.2.0
|
||||
message: "If you use this software, please cite it as below."
|
||||
authors:
|
||||
- family-names: "Chase"
|
||||
given-names: "Harrison"
|
||||
title: "LangChain"
|
||||
date-released: 2022-10-17
|
||||
url: "https://github.com/langchain-ai/langchain"
|
||||
326
CLAUDE.md
326
CLAUDE.md
@@ -1,326 +0,0 @@
|
||||
# Global Development Guidelines for LangChain Projects
|
||||
|
||||
## Core Development Principles
|
||||
|
||||
### 1. Maintain Stable Public Interfaces ⚠️ CRITICAL
|
||||
|
||||
**Always attempt to preserve function signatures, argument positions, and names for exported/public methods.**
|
||||
|
||||
❌ **Bad - Breaking Change:**
|
||||
|
||||
```python
|
||||
def get_user(id, verbose=False): # Changed from `user_id`
|
||||
pass
|
||||
```
|
||||
|
||||
✅ **Good - Stable Interface:**
|
||||
|
||||
```python
|
||||
def get_user(user_id: str, verbose: bool = False) -> User:
|
||||
"""Retrieve user by ID with optional verbose output."""
|
||||
pass
|
||||
```
|
||||
|
||||
**Before making ANY changes to public APIs:**
|
||||
|
||||
- Check if the function/class is exported in `__init__.py`
|
||||
- Look for existing usage patterns in tests and examples
|
||||
- Use keyword-only arguments for new parameters: `*, new_param: str = "default"`
|
||||
- Mark experimental features clearly with docstring warnings (using MkDocs Material admonitions, like `!!! warning`)
|
||||
|
||||
🧠 *Ask yourself:* "Would this change break someone's code if they used it last week?"
|
||||
|
||||
### 2. Code Quality Standards
|
||||
|
||||
**All Python code MUST include type hints and return types.**
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def p(u, d):
|
||||
return [x for x in u if x not in d]
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
def filter_unknown_users(users: list[str], known_users: set[str]) -> list[str]:
|
||||
"""Filter out users that are not in the known users set.
|
||||
|
||||
Args:
|
||||
users: List of user identifiers to filter.
|
||||
known_users: Set of known/valid user identifiers.
|
||||
|
||||
Returns:
|
||||
List of users that are not in the known_users set.
|
||||
"""
|
||||
return [user for user in users if user not in known_users]
|
||||
```
|
||||
|
||||
**Style Requirements:**
|
||||
|
||||
- Use descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
|
||||
- Attempt to break up complex functions (>20 lines) into smaller, focused functions where it makes sense
|
||||
- Avoid unnecessary abstraction or premature optimization
|
||||
- Follow existing patterns in the codebase you're modifying
|
||||
|
||||
### 3. Testing Requirements
|
||||
|
||||
**Every new feature or bugfix MUST be covered by unit tests.**
|
||||
|
||||
**Test Organization:**
|
||||
|
||||
- Unit tests: `tests/unit_tests/` (no network calls allowed)
|
||||
- Integration tests: `tests/integration_tests/` (network calls permitted)
|
||||
- Use `pytest` as the testing framework
|
||||
|
||||
**Test Quality Checklist:**
|
||||
|
||||
- [ ] Tests fail when your new logic is broken
|
||||
- [ ] Happy path is covered
|
||||
- [ ] Edge cases and error conditions are tested
|
||||
- [ ] Use fixtures/mocks for external dependencies
|
||||
- [ ] Tests are deterministic (no flaky tests)
|
||||
|
||||
Checklist questions:
|
||||
|
||||
- [ ] Does the test suite fail if your new logic is broken?
|
||||
- [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
|
||||
- [ ] Do tests use fixtures or mocks where needed?
|
||||
|
||||
```python
|
||||
def test_filter_unknown_users():
|
||||
"""Test filtering unknown users from a list."""
|
||||
users = ["alice", "bob", "charlie"]
|
||||
known_users = {"alice", "bob"}
|
||||
|
||||
result = filter_unknown_users(users, known_users)
|
||||
|
||||
assert result == ["charlie"]
|
||||
assert len(result) == 1
|
||||
```
|
||||
|
||||
### 4. Security and Risk Assessment
|
||||
|
||||
**Security Checklist:**
|
||||
|
||||
- No `eval()`, `exec()`, or `pickle` on user-controlled input
|
||||
- Proper exception handling (no bare `except:`) and use a `msg` variable for error messages
|
||||
- Remove unreachable/commented code before committing
|
||||
- Race conditions or resource leaks (file handles, sockets, threads).
|
||||
- Ensure proper resource cleanup (file handles, connections)
|
||||
|
||||
❌ **Bad:**
|
||||
|
||||
```python
|
||||
def load_config(path):
|
||||
with open(path) as f:
|
||||
return eval(f.read()) # ⚠️ Never eval config
|
||||
```
|
||||
|
||||
✅ **Good:**
|
||||
|
||||
```python
|
||||
import json
|
||||
|
||||
def load_config(path: str) -> dict:
|
||||
with open(path) as f:
|
||||
return json.load(f)
|
||||
```
|
||||
|
||||
### 5. Documentation Standards
|
||||
|
||||
**Use Google-style docstrings with Args section for all public functions.**
|
||||
|
||||
❌ **Insufficient Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to, msg):
|
||||
"""Send an email to a recipient."""
|
||||
```
|
||||
|
||||
✅ **Complete Documentation:**
|
||||
|
||||
```python
|
||||
def send_email(to: str, msg: str, *, priority: str = "normal") -> bool:
|
||||
"""
|
||||
Send an email to a recipient with specified priority.
|
||||
|
||||
Args:
|
||||
to: The email address of the recipient.
|
||||
msg: The message body to send.
|
||||
priority: Email priority level (`'low'`, `'normal'`, `'high'`).
|
||||
|
||||
Returns:
|
||||
`True` if email was sent successfully, `False` otherwise.
|
||||
|
||||
Raises:
|
||||
`InvalidEmailError`: If the email address format is invalid.
|
||||
`SMTPConnectionError`: If unable to connect to email server.
|
||||
"""
|
||||
```
|
||||
|
||||
**Documentation Guidelines:**
|
||||
|
||||
- Types go in function signatures, NOT in docstrings
|
||||
- If a default is present, DO NOT repeat it in the docstring unless there is post-processing or it is set conditionally.
|
||||
- Focus on "why" rather than "what" in descriptions
|
||||
- Document all parameters, return values, and exceptions
|
||||
- Keep descriptions concise but clear
|
||||
- Ensure American English spelling (e.g., "behavior", not "behaviour")
|
||||
|
||||
📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
|
||||
|
||||
### 6. Architectural Improvements
|
||||
|
||||
**When you encounter code that could be improved, suggest better designs:**
|
||||
|
||||
❌ **Poor Design:**
|
||||
|
||||
```python
|
||||
def process_data(data, db_conn, email_client, logger):
|
||||
# Function doing too many things
|
||||
validated = validate_data(data)
|
||||
result = db_conn.save(validated)
|
||||
email_client.send_notification(result)
|
||||
logger.log(f"Processed {len(data)} items")
|
||||
return result
|
||||
```
|
||||
|
||||
✅ **Better Design:**
|
||||
|
||||
```python
|
||||
@dataclass
|
||||
class ProcessingResult:
|
||||
"""Result of data processing operation."""
|
||||
items_processed: int
|
||||
success: bool
|
||||
errors: List[str] = field(default_factory=list)
|
||||
|
||||
class DataProcessor:
|
||||
"""Handles data validation, storage, and notification."""
|
||||
|
||||
def __init__(self, db_conn: Database, email_client: EmailClient):
|
||||
self.db = db_conn
|
||||
self.email = email_client
|
||||
|
||||
def process(self, data: List[dict]) -> ProcessingResult:
|
||||
"""Process and store data with notifications."""
|
||||
validated = self._validate_data(data)
|
||||
result = self.db.save(validated)
|
||||
self._notify_completion(result)
|
||||
return result
|
||||
```
|
||||
|
||||
**Design Improvement Areas:**
|
||||
|
||||
If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it and suggest improvements that would:
|
||||
|
||||
- Reduce code duplication through shared utilities
|
||||
- Make unit testing easier
|
||||
- Improve separation of concerns (single responsibility)
|
||||
- Make unit testing easier through dependency injection
|
||||
- Add clarity without adding complexity
|
||||
- Prefer dataclasses for structured data
|
||||
|
||||
## Development Tools & Commands
|
||||
|
||||
### Package Management
|
||||
|
||||
```bash
|
||||
# Add package
|
||||
uv add package-name
|
||||
|
||||
# Sync project dependencies
|
||||
uv sync
|
||||
uv lock
|
||||
```
|
||||
|
||||
### Testing
|
||||
|
||||
```bash
|
||||
# Run unit tests (no network)
|
||||
make test
|
||||
|
||||
# Don't run integration tests, as API keys must be set
|
||||
|
||||
# Run specific test file
|
||||
uv run --group test pytest tests/unit_tests/test_specific.py
|
||||
```
|
||||
|
||||
### Code Quality
|
||||
|
||||
```bash
|
||||
# Lint code
|
||||
make lint
|
||||
|
||||
# Format code
|
||||
make format
|
||||
|
||||
# Type checking
|
||||
uv run --group lint mypy .
|
||||
```
|
||||
|
||||
### Dependency Management Patterns
|
||||
|
||||
**Local Development Dependencies:**
|
||||
|
||||
```toml
|
||||
[tool.uv.sources]
|
||||
langchain-core = { path = "../core", editable = true }
|
||||
langchain-tests = { path = "../standard-tests", editable = true }
|
||||
```
|
||||
|
||||
**For tools, use the `@tool` decorator from `langchain_core.tools`:**
|
||||
|
||||
```python
|
||||
from langchain_core.tools import tool
|
||||
|
||||
@tool
|
||||
def search_database(query: str) -> str:
|
||||
"""Search the database for relevant information.
|
||||
|
||||
Args:
|
||||
query: The search query string.
|
||||
"""
|
||||
# Implementation here
|
||||
return results
|
||||
```
|
||||
|
||||
## Commit Standards
|
||||
|
||||
**Use Conventional Commits format for PR titles:**
|
||||
|
||||
- `feat(core): add multi-tenant support`
|
||||
- `fix(cli): resolve flag parsing error`
|
||||
- `docs: update API usage examples`
|
||||
- `docs(openai): update API usage examples`
|
||||
|
||||
## Framework-Specific Guidelines
|
||||
|
||||
- Follow the existing patterns in `langchain-core` for base abstractions
|
||||
- Use `langchain_core.callbacks` for execution tracking
|
||||
- Implement proper streaming support where applicable
|
||||
- Avoid deprecated components like legacy `LLMChain`
|
||||
|
||||
### Partner Integrations
|
||||
|
||||
- Follow the established patterns in existing partner libraries
|
||||
- Implement standard interfaces (`BaseChatModel`, `BaseEmbeddings`, etc.)
|
||||
- Include comprehensive integration tests
|
||||
- Document API key requirements and authentication
|
||||
|
||||
---
|
||||
|
||||
## Quick Reference Checklist
|
||||
|
||||
Before submitting code changes:
|
||||
|
||||
- [ ] **Breaking Changes**: Verified no public API changes
|
||||
- [ ] **Type Hints**: All functions have complete type annotations
|
||||
- [ ] **Tests**: New functionality is fully tested
|
||||
- [ ] **Security**: No dangerous patterns (eval, silent failures, etc.)
|
||||
- [ ] **Documentation**: Google-style docstrings for public functions
|
||||
- [ ] **Code Quality**: `make lint` and `make format` pass
|
||||
- [ ] **Architecture**: Suggested improvements where applicable
|
||||
- [ ] **Commit Message**: Follows Conventional Commits format
|
||||
12
LICENSE
12
LICENSE
@@ -1,6 +1,6 @@
|
||||
MIT License
|
||||
The MIT License
|
||||
|
||||
Copyright (c) LangChain, Inc.
|
||||
Copyright (c) Harrison Chase
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
@@ -9,13 +9,13 @@ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
The above copyright notice and this permission notice shall be included in
|
||||
all copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
|
||||
THE SOFTWARE.
|
||||
3
MANIFEST.in
Normal file
3
MANIFEST.in
Normal file
@@ -0,0 +1,3 @@
|
||||
include langchain/py.typed
|
||||
include langchain/VERSION
|
||||
include LICENSE
|
||||
@@ -1,9 +0,0 @@
|
||||
# Migrating
|
||||
|
||||
Please see the following guides for migrating LangChain code:
|
||||
|
||||
* Migrate to [LangChain v1.0](https://docs.langchain.com/oss/python/migrate/langchain-v1)
|
||||
* Migrate to [LangChain v0.3](https://python.langchain.com/docs/versions/v0_3/)
|
||||
* Migrate to [LangChain v0.2](https://python.langchain.com/docs/versions/v0_2/)
|
||||
* Migrating from [LangChain 0.0.x Chains](https://python.langchain.com/docs/versions/migrating_chains/)
|
||||
* Upgrade to [LangGraph Memory](https://python.langchain.com/docs/versions/migrating_memory/)
|
||||
17
Makefile
Normal file
17
Makefile
Normal file
@@ -0,0 +1,17 @@
|
||||
.PHONY: format lint tests integration_tests
|
||||
|
||||
format:
|
||||
black .
|
||||
isort .
|
||||
|
||||
lint:
|
||||
mypy .
|
||||
black . --check
|
||||
isort . --check
|
||||
flake8 .
|
||||
|
||||
tests:
|
||||
pytest tests/unit_tests
|
||||
|
||||
integration_tests:
|
||||
pytest tests/integration_tests
|
||||
137
README.md
137
README.md
@@ -1,86 +1,91 @@
|
||||
<p align="center">
|
||||
<picture>
|
||||
<source media="(prefers-color-scheme: light)" srcset=".github/images/logo-dark.svg">
|
||||
<source media="(prefers-color-scheme: dark)" srcset=".github/images/logo-light.svg">
|
||||
<img alt="LangChain Logo" src=".github/images/logo-dark.svg" width="80%">
|
||||
</picture>
|
||||
</p>
|
||||
# 🦜️🔗 LangChain
|
||||
|
||||
<p align="center">
|
||||
The platform for reliable agents.
|
||||
</p>
|
||||
⚡ Building applications with LLMs through composability ⚡
|
||||
|
||||
<p align="center">
|
||||
<a href="https://opensource.org/licenses/MIT" target="_blank">
|
||||
<img src="https://img.shields.io/pypi/l/langchain" alt="PyPI - License">
|
||||
</a>
|
||||
<a href="https://pypistats.org/packages/langchain" target="_blank">
|
||||
<img src="https://img.shields.io/pepy/dt/langchain" alt="PyPI - Downloads">
|
||||
</a>
|
||||
<a href="https://pypi.org/project/langchain/#history" target="_blank">
|
||||
<img src="https://img.shields.io/pypi/v/langchain?label=%20" alt="Version">
|
||||
</a>
|
||||
<a href="https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain" target="_blank">
|
||||
<img src="https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode" alt="Open in Dev Containers">
|
||||
</a>
|
||||
<a href="https://codespaces.new/langchain-ai/langchain" target="_blank">
|
||||
<img src="https://github.com/codespaces/badge.svg" alt="Open in Github Codespace" title="Open in Github Codespace" width="150" height="20">
|
||||
</a>
|
||||
<a href="https://codspeed.io/langchain-ai/langchain" target="_blank">
|
||||
<img src="https://img.shields.io/endpoint?url=https://codspeed.io/badge.json" alt="CodSpeed Badge">
|
||||
</a>
|
||||
<a href="https://twitter.com/langchainai" target="_blank">
|
||||
<img src="https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI" alt="Twitter / X">
|
||||
</a>
|
||||
</p>
|
||||
[](https://github.com/hwchase17/langchain/actions/workflows/lint.yml) [](https://github.com/hwchase17/langchain/actions/workflows/test.yml) [](https://opensource.org/licenses/MIT) [](https://twitter.com/langchainai) [](https://discord.gg/6adMQxSpJS)
|
||||
|
||||
LangChain is a framework for building agents and LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development – all while future-proofing decisions as the underlying technology evolves.
|
||||
## Quick Install
|
||||
|
||||
```bash
|
||||
pip install langchain
|
||||
```
|
||||
`pip install langchain`
|
||||
|
||||
If you're looking for more advanced customization or agent orchestration, check out [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our framework for building controllable agent workflows.
|
||||
## 🤔 What is this?
|
||||
|
||||
---
|
||||
Large language models (LLMs) are emerging as a transformative technology, enabling
|
||||
developers to build applications that they previously could not.
|
||||
But using these LLMs in isolation is often not enough to
|
||||
create a truly powerful app - the real power comes when you are able to
|
||||
combine them with other sources of computation or knowledge.
|
||||
|
||||
**Documentation**:
|
||||
This library is aimed at assisting in the development of those types of applications.
|
||||
|
||||
- [docs.langchain.com](https://docs.langchain.com/oss/python/langchain/overview) – Comprehensive documentation, including conceptual overviews and guides
|
||||
- [reference.langchain.com/python](https://reference.langchain.com/python) – API reference docs for LangChain packages
|
||||
## 📖 Documentation
|
||||
|
||||
**Discussions**: Visit the [LangChain Forum](https://forum.langchain.com) to connect with the community and share all of your technical questions, ideas, and feedback.
|
||||
Please see [here](https://langchain.readthedocs.io/en/latest/?) for full documentation on:
|
||||
- Getting started (installation, setting up environment, simple examples)
|
||||
- How-To examples (demos, integrations, helper functions)
|
||||
- Reference (full API docs)
|
||||
- Resources (high level explanation of core concepts)
|
||||
|
||||
> [!NOTE]
|
||||
> Looking for the JS/TS library? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
|
||||
## 🚀 What can this help with?
|
||||
|
||||
## Why use LangChain?
|
||||
There are three main areas (with a forth coming soon) that LangChain is designed to help with.
|
||||
These are, in increasing order of complexity:
|
||||
1. LLM and Prompt usage
|
||||
2. Chaining LLMs with other tools in a deterministic manner
|
||||
3. Having a router LLM which uses other tools as needed
|
||||
4. (Coming Soon) Memory
|
||||
|
||||
LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
|
||||
### LLMs and Prompts
|
||||
Calling out to an LLM once is pretty easy, with most of them being behind well documented APIs.
|
||||
However, there are still some challenges going from that to an application running in production that LangChain attempts to address:
|
||||
- Easy switching costs: by exposing a standard interface for all the top LLM providers, LangChain makes it easy to switch from one provider to another, whether it be for production use cases or just for testing stuff out.
|
||||
- Prompt management: managing your prompts is easy when you only have one simple one, but can get tricky when you have a bunch or when they start to get more complex. LangChain provides a standard way for storing, constructing, and referencing prompts.
|
||||
- Prompt optimization: despite the underlying models getting better and better, there is still currently a need for carefully constructing prompts.
|
||||
- More coming soon
|
||||
|
||||
Use LangChain for:
|
||||
### Chains
|
||||
Using an LLM in isolation is fine for some simple applications, but many more complex ones require chaining LLMs - either with eachother or with other tools.
|
||||
LangChain provides several parts to help with that:
|
||||
- Standard interface for working with Chains
|
||||
- Easy way to construct chains of LLMs
|
||||
- Lots of integrations with other tools that you may want to use in conjunction with LLMs (search, databases, Python REPL, etc)
|
||||
- End-to-end chains for common workflows (database question/answer, recursive summarization, etc)
|
||||
|
||||
- **Real-time data augmentation**. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain's vast library of integrations with model providers, tools, vector stores, retrievers, and more.
|
||||
- **Model interoperability**. Swap models in and out as your engineering team experiments to find the best choice for your application's needs. As the industry frontier evolves, adapt quickly – LangChain's abstractions keep you moving without losing momentum.
|
||||
- **Rapid prototyping**. Quickly build and iterate on LLM applications with LangChain's modular, component-based architecture. Test different approaches and workflows without rebuilding from scratch, accelerating your development cycle.
|
||||
- **Production-ready features**. Deploy reliable applications with built-in support for monitoring, evaluation, and debugging through integrations like LangSmith. Scale with confidence using battle-tested patterns and best practices.
|
||||
- **Vibrant community and ecosystem**. Leverage a rich ecosystem of integrations, templates, and community-contributed components. Benefit from continuous improvements and stay up-to-date with the latest AI developments through an active open-source community.
|
||||
- **Flexible abstraction layers**. Work at the level of abstraction that suits your needs - from high-level chains for quick starts to low-level components for fine-grained control. LangChain grows with your application's complexity.
|
||||
### Routing Chains
|
||||
Some applications will require not just a predetermined chain of calls to LLMs/other tools, but potentially an unknown chain that depends on the user input.
|
||||
In these types of chains, there is a "router" LLM chain which has access to a suite of tools.
|
||||
Depending on the user input, the router can then decide which, if any, of these tools to call.
|
||||
To help develop applications like these, LangChain provides:
|
||||
- Standard router and router chain interfaces
|
||||
- Common router LLM chains from literature
|
||||
- Common chains that can be used as tools
|
||||
|
||||
## LangChain ecosystem
|
||||
### Memory
|
||||
Coming soon.
|
||||
|
||||
While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
|
||||
## 🤖 Developer Guide
|
||||
|
||||
To improve your LLM application development, pair LangChain with:
|
||||
To begin developing on this project, first clone to the repo locally.
|
||||
To install requirements, run `pip install -r requirements.txt`.
|
||||
This will install all requirements for running the package, examples, linting, formatting, and tests.
|
||||
|
||||
- [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview) – Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows – and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
|
||||
- [Integrations](https://docs.langchain.com/oss/python/integrations/providers/overview) – List of LangChain integrations, including chat & embedding models, tools & toolkits, and more
|
||||
- [LangSmith](https://www.langchain.com/langsmith) – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
|
||||
- [LangSmith Deployment](https://docs.langchain.com/langsmith/deployments) – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in [LangSmith Studio](https://docs.langchain.com/langsmith/studio).
|
||||
- [Deep Agents](https://github.com/langchain-ai/deepagents) *(new!)* – Build agents that can plan, use subagents, and leverage file systems for complex tasks
|
||||
Formatting for this project is a combination of [Black](https://black.readthedocs.io/en/stable/) and [isort](https://pycqa.github.io/isort/).
|
||||
To run formatting for this project, run `make format`.
|
||||
|
||||
## Additional resources
|
||||
Linting for this project is a combination of [Black](https://black.readthedocs.io/en/stable/), [isort](https://pycqa.github.io/isort/), [flake8](https://flake8.pycqa.org/en/latest/), and [mypy](http://mypy-lang.org/).
|
||||
To run linting for this project, run `make lint`.
|
||||
We recognize linting can be annoying - if you do not want to do it, please contact a project maintainer and they can help you with it. We do not want this to be a blocker for good code getting contributed.
|
||||
|
||||
- [API Reference](https://reference.langchain.com/python) – Detailed reference on navigating base packages and integrations for LangChain.
|
||||
- [Contributing Guide](https://docs.langchain.com/oss/python/contributing/overview) – Learn how to contribute to LangChain projects and find good first issues.
|
||||
- [Code of Conduct](https://github.com/langchain-ai/langchain/blob/master/.github/CODE_OF_CONDUCT.md) – Our community guidelines and standards for participation.
|
||||
Unit tests cover modular logic that does not require calls to outside apis.
|
||||
To run unit tests, run `make tests`.
|
||||
If you add new logic, please add a unit test.
|
||||
|
||||
Integration tests cover logic that requires making calls to outside APIs (often integration with other services).
|
||||
To run integration tests, run `make integration_tests`.
|
||||
If you add support for a new external API, please add a new integration test.
|
||||
|
||||
If you are adding a Jupyter notebook example, you can run `pip install -e .` to build the langchain package from your local changes, so your new logic can be imported into the notebook.
|
||||
|
||||
Docs are largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/) from the code.
|
||||
For that reason, we ask that you add good documentation to all classes and methods.
|
||||
Similar to linting, we recognize documentation can be annoying - if you do not want to do it, please contact a project maintainer and they can help you with it. We do not want this to be a blocker for good code getting contributed.
|
||||
|
||||
80
SECURITY.md
80
SECURITY.md
@@ -1,80 +0,0 @@
|
||||
# Security Policy
|
||||
|
||||
LangChain has a large ecosystem of integrations with various external resources like local and remote file systems, APIs and databases. These integrations allow developers to create versatile applications that combine the power of LLMs with the ability to access, interact with and manipulate external resources.
|
||||
|
||||
## Best practices
|
||||
|
||||
When building such applications, developers should remember to follow good security practices:
|
||||
|
||||
* [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc., as appropriate for your application.
|
||||
* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it's safest to assume that any LLM able to use those credentials may in fact delete data.
|
||||
* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It's best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use.
|
||||
|
||||
Risks of not doing so include, but are not limited to:
|
||||
|
||||
* Data corruption or loss.
|
||||
* Unauthorized access to confidential information.
|
||||
* Compromised performance or availability of critical resources.
|
||||
|
||||
Example scenarios with mitigation strategies:
|
||||
|
||||
* A user may ask an agent with access to the file system to delete files that should not be deleted or read the content of files that contain sensitive information. To mitigate, limit the agent to only use a specific directory and only allow it to read or write files that are safe to read or write. Consider further sandboxing the agent by running it in a container.
|
||||
* A user may ask an agent with write access to an external API to write malicious data to the API, or delete data from that API. To mitigate, give the agent read-only API keys, or limit it to only use endpoints that are already resistant to such misuse.
|
||||
* A user may ask an agent with access to a database to drop a table or mutate the schema. To mitigate, scope the credentials to only the tables that the agent needs to access and consider issuing READ-ONLY credentials.
|
||||
|
||||
If you're building applications that access external resources like file systems, APIs or databases, consider speaking with your company's security team to determine how to best design and secure your applications.
|
||||
|
||||
## Reporting OSS Vulnerabilities
|
||||
|
||||
LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
|
||||
a bounty program for our open source projects.
|
||||
|
||||
Please report security vulnerabilities associated with the LangChain
|
||||
open source projects at [huntr](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true).
|
||||
|
||||
Before reporting a vulnerability, please review:
|
||||
|
||||
1) In-Scope Targets and Out-of-Scope Targets below.
|
||||
2) The [langchain-ai/langchain](https://docs.langchain.com/oss/python/contributing/code#repository-structure) monorepo structure.
|
||||
3) The [Best Practices](#best-practices) above to understand what we consider to be a security vulnerability vs. developer responsibility.
|
||||
|
||||
### In-Scope Targets
|
||||
|
||||
The following packages and repositories are eligible for bug bounties:
|
||||
|
||||
* langchain-core
|
||||
* langchain (see exceptions)
|
||||
* langchain-community (see exceptions)
|
||||
* langgraph
|
||||
* langserve
|
||||
|
||||
### Out of Scope Targets
|
||||
|
||||
All out of scope targets defined by huntr as well as:
|
||||
|
||||
* **langchain-experimental**: This repository is for experimental code and is not
|
||||
eligible for bug bounties (see [package warning](https://pypi.org/project/langchain-experimental/)), bug reports to it will be marked as interesting or waste of
|
||||
time and published with no bounty attached.
|
||||
* **tools**: Tools in either `langchain` or `langchain-community` are not eligible for bug
|
||||
bounties. This includes the following directories
|
||||
* `libs/langchain/langchain/tools`
|
||||
* `libs/community/langchain_community/tools`
|
||||
* Please review the [Best Practices](#best-practices)
|
||||
for more details, but generally tools interact with the real world. Developers are
|
||||
expected to understand the security implications of their code and are responsible
|
||||
for the security of their tools.
|
||||
* Code documented with security notices. This will be decided on a case-by-case basis, but likely will not be eligible for a bounty as the code is already
|
||||
documented with guidelines for developers that should be followed for making their
|
||||
application secure.
|
||||
* Any LangSmith related repositories or APIs (see [Reporting LangSmith Vulnerabilities](#reporting-langsmith-vulnerabilities)).
|
||||
|
||||
## Reporting LangSmith Vulnerabilities
|
||||
|
||||
Please report security vulnerabilities associated with LangSmith by email to `security@langchain.dev`.
|
||||
|
||||
* LangSmith site: [https://smith.langchain.com](https://smith.langchain.com)
|
||||
* SDK client: [https://github.com/langchain-ai/langsmith-sdk](https://github.com/langchain-ai/langsmith-sdk)
|
||||
|
||||
### Other Security Concerns
|
||||
|
||||
For any other security concerns, please contact us at `security@langchain.dev`.
|
||||
21
docs/Makefile
Normal file
21
docs/Makefile
Normal file
@@ -0,0 +1,21 @@
|
||||
# Minimal makefile for Sphinx documentation
|
||||
#
|
||||
|
||||
# You can set these variables from the command line, and also
|
||||
# from the environment for the first two.
|
||||
SPHINXOPTS ?=
|
||||
SPHINXBUILD ?= sphinx-build
|
||||
SPHINXAUTOBUILD ?= sphinx-autobuild
|
||||
SOURCEDIR = .
|
||||
BUILDDIR = _build
|
||||
|
||||
# Put it first so that "make" without argument is like "make help".
|
||||
help:
|
||||
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
|
||||
|
||||
.PHONY: help Makefile
|
||||
|
||||
# Catch-all target: route all unknown targets to Sphinx using the new
|
||||
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
|
||||
%: Makefile
|
||||
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
|
||||
87
docs/conf.py
Normal file
87
docs/conf.py
Normal file
@@ -0,0 +1,87 @@
|
||||
"""Configuration file for the Sphinx documentation builder."""
|
||||
# Configuration file for the Sphinx documentation builder.
|
||||
#
|
||||
# This file only contains a selection of the most common options. For a full
|
||||
# list see the documentation:
|
||||
# https://www.sphinx-doc.org/en/master/usage/configuration.html
|
||||
|
||||
# -- Path setup --------------------------------------------------------------
|
||||
|
||||
# If extensions (or modules to document with autodoc) are in another directory,
|
||||
# add these directories to sys.path here. If the directory is relative to the
|
||||
# documentation root, use os.path.abspath to make it absolute, like shown here.
|
||||
#
|
||||
# import os
|
||||
# import sys
|
||||
# sys.path.insert(0, os.path.abspath('.'))
|
||||
|
||||
import langchain
|
||||
|
||||
# -- Project information -----------------------------------------------------
|
||||
|
||||
project = "LangChain"
|
||||
copyright = "2022, Harrison Chase"
|
||||
author = "Harrison Chase"
|
||||
|
||||
version = langchain.__version__
|
||||
release = langchain.__version__
|
||||
|
||||
|
||||
# -- General configuration ---------------------------------------------------
|
||||
|
||||
# Add any Sphinx extension module names here, as strings. They can be
|
||||
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
|
||||
# ones.
|
||||
extensions = [
|
||||
"sphinx.ext.autodoc",
|
||||
"sphinx.ext.autodoc.typehints",
|
||||
"sphinx.ext.autosummary",
|
||||
"sphinx.ext.napoleon",
|
||||
"sphinx.ext.viewcode",
|
||||
"sphinxcontrib.autodoc_pydantic",
|
||||
"myst_parser",
|
||||
"nbsphinx",
|
||||
"sphinx_panels",
|
||||
]
|
||||
|
||||
|
||||
autodoc_pydantic_model_show_json = False
|
||||
autodoc_pydantic_field_list_validators = False
|
||||
autodoc_pydantic_config_members = False
|
||||
autodoc_pydantic_model_show_config_summary = False
|
||||
autodoc_pydantic_model_show_validator_members = False
|
||||
autodoc_pydantic_model_show_field_summary = False
|
||||
autodoc_pydantic_model_members = False
|
||||
autodoc_pydantic_model_undoc_members = False
|
||||
# autodoc_typehints = "signature"
|
||||
# autodoc_typehints = "description"
|
||||
|
||||
# Add any paths that contain templates here, relative to this directory.
|
||||
templates_path = ["_templates"]
|
||||
|
||||
# List of patterns, relative to source directory, that match files and
|
||||
# directories to ignore when looking for source files.
|
||||
# This pattern also affects html_static_path and html_extra_path.
|
||||
exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
|
||||
|
||||
|
||||
# -- Options for HTML output -------------------------------------------------
|
||||
|
||||
# The theme to use for HTML and HTML Help pages. See the documentation for
|
||||
# a list of builtin themes.
|
||||
#
|
||||
html_theme = "sphinx_rtd_theme"
|
||||
# html_theme = "sphinx_typlog_theme"
|
||||
|
||||
html_context = {
|
||||
"display_github": True, # Integrate GitHub
|
||||
"github_user": "hwchase17", # Username
|
||||
"github_repo": "langchain", # Repo name
|
||||
"github_version": "master", # Version
|
||||
"conf_py_path": "/docs/", # Path in the checkout to the docs root
|
||||
}
|
||||
|
||||
# Add any paths that contain custom static files (such as style sheets) here,
|
||||
# relative to this directory. They are copied after the builtin static files,
|
||||
# so a file named "default.css" will overwrite the builtin "default.css".
|
||||
html_static_path: list = []
|
||||
25
docs/examples/demos.rst
Normal file
25
docs/examples/demos.rst
Normal file
@@ -0,0 +1,25 @@
|
||||
Demos
|
||||
=====
|
||||
|
||||
The examples here are all end-to-end chains of specific applications.
|
||||
They are separated into normal chains and then routing chains.
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:glob:
|
||||
:caption: Chains
|
||||
|
||||
demos/llm_math.ipynb
|
||||
demos/map_reduce.ipynb
|
||||
demos/simple_prompts.ipynb
|
||||
demos/sqlite.ipynb
|
||||
demos/vector_db_qa.ipynb
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:glob:
|
||||
:caption: Routing Chains
|
||||
|
||||
demos/mrkl.ipynb
|
||||
demos/react.ipynb
|
||||
demos/self_ask_with_search.ipynb
|
||||
91
docs/examples/demos/llm_math.ipynb
Normal file
91
docs/examples/demos/llm_math.ipynb
Normal file
@@ -0,0 +1,91 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e71e720f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# LLM Math\n",
|
||||
"\n",
|
||||
"This notebook showcases using LLMs and Python REPLs to do complex word math problems."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "44e9ba31",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"How many of the integers between 0 and 99 inclusive are divisible by 8?\u001b[102m\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"count = 0\n",
|
||||
"for i in range(100):\n",
|
||||
" if i % 8 == 0:\n",
|
||||
" count += 1\n",
|
||||
"print(count)\n",
|
||||
"```\n",
|
||||
"\u001b[0m\n",
|
||||
"Answer: \u001b[103m13\n",
|
||||
"\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Answer: 13\\n'"
|
||||
]
|
||||
},
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain import OpenAI, LLMMathChain\n",
|
||||
"\n",
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"llm_math = LLMMathChain(llm=llm, verbose=True)\n",
|
||||
"\n",
|
||||
"llm_math.run(\"How many of the integers between 0 and 99 inclusive are divisible by 8?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f62f0c75",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
93
docs/examples/demos/map_reduce.ipynb
Normal file
93
docs/examples/demos/map_reduce.ipynb
Normal file
@@ -0,0 +1,93 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d9a0131f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Map Reduce\n",
|
||||
"\n",
|
||||
"This notebok showcases an example of map-reduce chains: recursive summarization."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "e9db25f3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import OpenAI, PromptTemplate, LLMChain\n",
|
||||
"from langchain.text_splitter import CharacterTextSplitter\n",
|
||||
"from langchain.chains.mapreduce import MapReduceChain\n",
|
||||
"\n",
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"\n",
|
||||
"_prompt = \"\"\"Write a concise summary of the following:\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"{text}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"CONCISE SUMMARY:\"\"\"\n",
|
||||
"prompt = PromptTemplate(template=_prompt, input_variables=[\"text\"])\n",
|
||||
"\n",
|
||||
"text_splitter = CharacterTextSplitter()\n",
|
||||
"\n",
|
||||
"mp_chain = MapReduceChain.from_params(llm, prompt, text_splitter)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "99bbe19b",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"\\n\\nThe President discusses the recent aggression by Russia, and the response by the United States and its allies. He announces new sanctions against Russia, and says that the free world is united in holding Putin accountable. The President also discusses the American Rescue Plan, the Bipartisan Infrastructure Law, and the Bipartisan Innovation Act. Finally, the President addresses the need for women's rights and equality for LGBTQ+ Americans.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"with open('../state_of_the_union.txt') as f:\n",
|
||||
" state_of_the_union = f.read()\n",
|
||||
"mp_chain.run(state_of_the_union)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b581501e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
226
docs/examples/demos/mrkl.ipynb
Normal file
226
docs/examples/demos/mrkl.ipynb
Normal file
@@ -0,0 +1,226 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f1390152",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# MRKL\n",
|
||||
"\n",
|
||||
"This notebook showcases using the MRKL chain to route between tasks"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "39ea3638",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"This uses the example Chinook database.\n",
|
||||
"To set it up follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the `.db` file in a notebooks folder at the root of this repository."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "ac561cc4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import LLMMathChain, OpenAI, SerpAPIChain, MRKLChain, SQLDatabase, SQLDatabaseChain\n",
|
||||
"from langchain.chains.mrkl.base import ChainConfig"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "07e96d99",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"search = SerpAPIChain()\n",
|
||||
"llm_math_chain = LLMMathChain(llm=llm, verbose=True)\n",
|
||||
"db = SQLDatabase.from_uri(\"sqlite:///../../../notebooks/Chinook.db\")\n",
|
||||
"db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)\n",
|
||||
"chains = [\n",
|
||||
" ChainConfig(\n",
|
||||
" action_name = \"Search\",\n",
|
||||
" action=search.run,\n",
|
||||
" action_description=\"useful for when you need to answer questions about current events\"\n",
|
||||
" ),\n",
|
||||
" ChainConfig(\n",
|
||||
" action_name=\"Calculator\",\n",
|
||||
" action=llm_math_chain.run,\n",
|
||||
" action_description=\"useful for when you need to answer questions about math\"\n",
|
||||
" ),\n",
|
||||
" \n",
|
||||
" ChainConfig(\n",
|
||||
" action_name=\"FooBar DB\",\n",
|
||||
" action=db_chain.run,\n",
|
||||
" action_description=\"useful for when you need to answer questions about FooBar. Input should be in the form of a question\"\n",
|
||||
" )\n",
|
||||
"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "a069c4b6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"mrkl = MRKLChain.from_chains(llm, chains, verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "e603cd7d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"What is the age of Olivia Wilde's boyfriend raised to the 0.23 power?\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to find the age of Olivia Wilde's boyfriend\n",
|
||||
"Action: Search\n",
|
||||
"Action Input: \"Olivia Wilde's boyfriend\"\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mOlivia Wilde started dating Harry Styles after ending her years-long engagement to Jason Sudeikis — see their relationship timeline.\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to find the age of Harry Styles\n",
|
||||
"Action: Search\n",
|
||||
"Action Input: \"Harry Styles age\"\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m28 years\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to calculate 28 to the 0.23 power\n",
|
||||
"Action: Calculator\n",
|
||||
"Action Input: 28^0.23\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"28^0.23\u001b[32;1m\u001b[1;3m\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"print(28**0.23)\n",
|
||||
"```\n",
|
||||
"\u001b[0m\n",
|
||||
"Answer: \u001b[33;1m\u001b[1;3m2.1520202182226886\n",
|
||||
"\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.1520202182226886\n",
|
||||
"\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: 2.1520202182226886\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'2.1520202182226886'"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mrkl.run(\"What is the age of Olivia Wilde's boyfriend raised to the 0.23 power?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "a5c07010",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"Who recently released an album called 'The Storm Before the Calm' and are they in the FooBar database? If so, what albums of theirs are in the FooBar database?\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to find an album called 'The Storm Before the Calm'\n",
|
||||
"Action: Search\n",
|
||||
"Action Input: \"The Storm Before the Calm album\"\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mThe Storm Before the Calm (stylized in all lowercase) is the tenth (and eighth international) studio album by Canadian-American singer-songwriter Alanis ...\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to check if Alanis is in the FooBar database\n",
|
||||
"Action: FooBar DB\n",
|
||||
"Action Input: \"Does Alanis Morissette exist in the FooBar database?\"\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"Does Alanis Morissette exist in the FooBar database?\n",
|
||||
"SQLQuery:\u001b[32;1m\u001b[1;3m SELECT * FROM Artist WHERE Name = 'Alanis Morissette'\u001b[0m\n",
|
||||
"SQLResult: \u001b[33;1m\u001b[1;3m[(4, 'Alanis Morissette')]\u001b[0m\n",
|
||||
"Answer:\u001b[32;1m\u001b[1;3m Yes\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[38;5;200m\u001b[1;3m Yes\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to find out what albums of Alanis's are in the FooBar database\n",
|
||||
"Action: FooBar DB\n",
|
||||
"Action Input: \"What albums by Alanis Morissette are in the FooBar database?\"\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"What albums by Alanis Morissette are in the FooBar database?\n",
|
||||
"SQLQuery:\u001b[32;1m\u001b[1;3m SELECT Album.Title FROM Album JOIN Artist ON Album.ArtistId = Artist.ArtistId WHERE Artist.Name = 'Alanis Morissette'\u001b[0m\n",
|
||||
"SQLResult: \u001b[33;1m\u001b[1;3m[('Jagged Little Pill',)]\u001b[0m\n",
|
||||
"Answer:\u001b[32;1m\u001b[1;3m Jagged Little Pill\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[38;5;200m\u001b[1;3m Jagged Little Pill\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: The album is by Alanis Morissette and the albums in the FooBar database by her are Jagged Little Pill\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'The album is by Alanis Morissette and the albums in the FooBar database by her are Jagged Little Pill'"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"mrkl.run(\"Who recently released an album called 'The Storm Before the Calm' and are they in the FooBar database? If so, what albums of theirs are in the FooBar database?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d7c2e6ac",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
88
docs/examples/demos/natbot.py
Normal file
88
docs/examples/demos/natbot.py
Normal file
@@ -0,0 +1,88 @@
|
||||
"""Run NatBot."""
|
||||
import time
|
||||
|
||||
from langchain.chains.natbot.base import NatBotChain
|
||||
from langchain.chains.natbot.crawler import Crawler # type: ignore
|
||||
|
||||
|
||||
def run_cmd(cmd: str, _crawler: Crawler) -> None:
|
||||
"""Run command."""
|
||||
cmd = cmd.split("\n")[0]
|
||||
|
||||
if cmd.startswith("SCROLL UP"):
|
||||
_crawler.scroll("up")
|
||||
elif cmd.startswith("SCROLL DOWN"):
|
||||
_crawler.scroll("down")
|
||||
elif cmd.startswith("CLICK"):
|
||||
commasplit = cmd.split(",")
|
||||
id = commasplit[0].split(" ")[1]
|
||||
_crawler.click(id)
|
||||
elif cmd.startswith("TYPE"):
|
||||
spacesplit = cmd.split(" ")
|
||||
id = spacesplit[1]
|
||||
text_pieces = spacesplit[2:]
|
||||
text = " ".join(text_pieces)
|
||||
# Strip leading and trailing double quotes
|
||||
text = text[1:-1]
|
||||
|
||||
if cmd.startswith("TYPESUBMIT"):
|
||||
text += "\n"
|
||||
_crawler.type(id, text)
|
||||
|
||||
time.sleep(2)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
objective = "Make a reservation for 2 at 7pm at bistro vida in menlo park"
|
||||
print("\nWelcome to natbot! What is your objective?")
|
||||
i = input()
|
||||
if len(i) > 0:
|
||||
objective = i
|
||||
quiet = False
|
||||
nat_bot_chain = NatBotChain.from_default(objective)
|
||||
_crawler = Crawler()
|
||||
_crawler.go_to_page("google.com")
|
||||
try:
|
||||
while True:
|
||||
browser_content = "\n".join(_crawler.crawl())
|
||||
llm_command = nat_bot_chain.execute(_crawler.page.url, browser_content)
|
||||
if not quiet:
|
||||
print("URL: " + _crawler.page.url)
|
||||
print("Objective: " + objective)
|
||||
print("----------------\n" + browser_content + "\n----------------\n")
|
||||
if len(llm_command) > 0:
|
||||
print("Suggested command: " + llm_command)
|
||||
|
||||
command = input()
|
||||
if command == "r" or command == "":
|
||||
run_cmd(llm_command, _crawler)
|
||||
elif command == "g":
|
||||
url = input("URL:")
|
||||
_crawler.go_to_page(url)
|
||||
elif command == "u":
|
||||
_crawler.scroll("up")
|
||||
time.sleep(1)
|
||||
elif command == "d":
|
||||
_crawler.scroll("down")
|
||||
time.sleep(1)
|
||||
elif command == "c":
|
||||
id = input("id:")
|
||||
_crawler.click(id)
|
||||
time.sleep(1)
|
||||
elif command == "t":
|
||||
id = input("id:")
|
||||
text = input("text:")
|
||||
_crawler.type(id, text)
|
||||
time.sleep(1)
|
||||
elif command == "o":
|
||||
objective = input("Objective:")
|
||||
else:
|
||||
print(
|
||||
"(g) to visit url\n(u) scroll up\n(d) scroll down\n(c) to click"
|
||||
"\n(t) to type\n(h) to view commands again"
|
||||
"\n(r/enter) to run suggested command\n(o) change objective"
|
||||
)
|
||||
except KeyboardInterrupt:
|
||||
print("\n[!] Ctrl+C detected, exiting gracefully.")
|
||||
exit(0)
|
||||
98
docs/examples/demos/react.ipynb
Normal file
98
docs/examples/demos/react.ipynb
Normal file
@@ -0,0 +1,98 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "82140df0",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# ReAct\n",
|
||||
"\n",
|
||||
"This notebook showcases the implementation of the ReAct chain logic."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "4e272b47",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import OpenAI, ReActChain, Wikipedia\n",
|
||||
"\n",
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"react = ReActChain(llm=llm, docstore=Wikipedia(), verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "8078c8f1",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"Author David Chanoff has collaborated with a U.S. Navy admiral who served as the ambassador to the United Kingdom under which President?\n",
|
||||
"Thought 1:\u001b[32;1m\u001b[1;3m I need to search David Chanoff and find the U.S. Navy admiral he collaborated\n",
|
||||
"with.\n",
|
||||
"Action 1: Search[David Chanoff]\u001b[0m\n",
|
||||
"Observation 1: \u001b[36;1m\u001b[1;3mDavid Chanoff is a noted author of non-fiction work. His work has typically involved collaborations with the principal protagonist of the work concerned. His collaborators have included; Augustus A. White, Joycelyn Elders, Đoàn Văn Toại, William J. Crowe, Ariel Sharon, Kenneth Good and Felix Zandman. He has also written about a wide range of subjects including literary history, education and foreign for The Washington Post, The New Republic and The New York Times Magazine. He has published more than twelve books.\u001b[0m\n",
|
||||
"Thought 2:\u001b[32;1m\u001b[1;3m The U.S. Navy admiral David Chanoff collaborated with is William J. Crowe.\n",
|
||||
"Action 2: Search[William J. Crowe]\u001b[0m\n",
|
||||
"Observation 2: \u001b[36;1m\u001b[1;3mWilliam James Crowe Jr. (January 2, 1925 – October 18, 2007) was a United States Navy admiral and diplomat who served as the 11th chairman of the Joint Chiefs of Staff under Presidents Ronald Reagan and George H. W. Bush, and as the ambassador to the United Kingdom and Chair of the Intelligence Oversight Board under President Bill Clinton.\u001b[0m\n",
|
||||
"Thought 3:\u001b[32;1m\u001b[1;3m William J. Crowe served as the ambassador to the United Kingdom under President Bill Clinton.\n",
|
||||
"Action 3: Finish[Bill Clinton]\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Bill Clinton'"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"question = \"Author David Chanoff has collaborated with a U.S. Navy admiral who served as the ambassador to the United Kingdom under which President?\"\n",
|
||||
"react.run(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "3cb9d77c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
88
docs/examples/demos/self_ask_with_search.ipynb
Normal file
88
docs/examples/demos/self_ask_with_search.ipynb
Normal file
@@ -0,0 +1,88 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "0c3f1df8",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Self Ask With Search\n",
|
||||
"\n",
|
||||
"This notebook showcases the Self Ask With Search chain."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "7e3b513e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"What is the hometown of the reigning men's U.S. Open champion?\n",
|
||||
"Are follow up questions needed here:\u001b[32;1m\u001b[1;3m Yes.\n",
|
||||
"Follow up: Who is the reigning men's U.S. Open champion?\u001b[0m\n",
|
||||
"Intermediate answer: \u001b[36;1m\u001b[1;3mCarlos Alcaraz\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mFollow up: Where is Carlos Alcaraz from?\u001b[0m\n",
|
||||
"Intermediate answer: \u001b[36;1m\u001b[1;3mEl Palmar, Spain\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mSo the final answer is: El Palmar, Spain\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'El Palmar, Spain'"
|
||||
]
|
||||
},
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain import SelfAskWithSearchChain, OpenAI, SerpAPIChain\n",
|
||||
"\n",
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"search = SerpAPIChain()\n",
|
||||
"\n",
|
||||
"self_ask_with_search = SelfAskWithSearchChain(llm=llm, search_chain=search, verbose=True)\n",
|
||||
"\n",
|
||||
"self_ask_with_search.run(\"What is the hometown of the reigning men's U.S. Open champion?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "683d69e7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
89
docs/examples/demos/simple_prompts.ipynb
Normal file
89
docs/examples/demos/simple_prompts.ipynb
Normal file
@@ -0,0 +1,89 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d8a5c5d4",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Simple Example\n",
|
||||
"\n",
|
||||
"This notebook showcases a simple chain."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "51a54c4d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"Prompt after formatting:\n",
|
||||
"\u001b[32;1m\u001b[1;3mQuestion: What NFL team won the Super Bowl in the year Justin Beiber was born?\n",
|
||||
"\n",
|
||||
"Answer: Let's think step by step.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"' The year Justin Beiber was born was 1994. In 1994, the Dallas Cowboys won the Super Bowl.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain import PromptTemplate, OpenAI, LLMChain\n",
|
||||
"\n",
|
||||
"template = \"\"\"Question: {question}\n",
|
||||
"\n",
|
||||
"Answer: Let's think step by step.\"\"\"\n",
|
||||
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])\n",
|
||||
"llm_chain = LLMChain(prompt=prompt, llm=OpenAI(temperature=0), verbose=True)\n",
|
||||
"\n",
|
||||
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
|
||||
"\n",
|
||||
"llm_chain.run(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "03dd6918",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
129
docs/examples/demos/sqlite.ipynb
Normal file
129
docs/examples/demos/sqlite.ipynb
Normal file
@@ -0,0 +1,129 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "0ed6aab1",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"# SQLite example\n",
|
||||
"\n",
|
||||
"This example showcases hooking up an LLM to answer questions over a database."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b2f66479",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"This uses the example Chinook database.\n",
|
||||
"To set it up follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the `.db` file in a notebooks folder at the root of this repository."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "d0e27d88",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import OpenAI, SQLDatabase, SQLDatabaseChain"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "72ede462",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"db = SQLDatabase.from_uri(\"sqlite:///../../../notebooks/Chinook.db\")\n",
|
||||
"llm = OpenAI(temperature=0)\n",
|
||||
"db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "15ff81df",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"How many employees are there?\n",
|
||||
"SQLQuery:\u001b[102m SELECT COUNT(*) FROM Employee\u001b[0m\n",
|
||||
"SQLResult: \u001b[103m[(8,)]\u001b[0m\n",
|
||||
"Answer:\u001b[102m 8\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"' 8'"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"db_chain.run(\"How many employees are there?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "61d91b85",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
104
docs/examples/demos/vector_db_qa.ipynb
Normal file
104
docs/examples/demos/vector_db_qa.ipynb
Normal file
@@ -0,0 +1,104 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "07c1e3b9",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Vector DB Question/Answering\n",
|
||||
"\n",
|
||||
"This example showcases question answering over a vector database."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "82525493",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
|
||||
"from langchain.vectorstores.faiss import FAISS\n",
|
||||
"from langchain.text_splitter import CharacterTextSplitter\n",
|
||||
"from langchain import OpenAI, VectorDBQA"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "5c7049db",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open('../state_of_the_union.txt') as f:\n",
|
||||
" state_of_the_union = f.read()\n",
|
||||
"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
|
||||
"texts = text_splitter.split_text(state_of_the_union)\n",
|
||||
"\n",
|
||||
"embeddings = OpenAIEmbeddings()\n",
|
||||
"docsearch = FAISS.from_texts(texts, embeddings)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "3018f865",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"qa = VectorDBQA(llm=OpenAI(), vectorstore=docsearch)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "032a47f8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"' The President said that Ketanji Brown Jackson is a consensus builder and has received a broad range of support since she was nominated.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
|
||||
"qa.run(query)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f0f20b92",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
10
docs/examples/integrations.rst
Normal file
10
docs/examples/integrations.rst
Normal file
@@ -0,0 +1,10 @@
|
||||
Integrations
|
||||
============
|
||||
|
||||
The examples here all highlight a specific type of integration.
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:glob:
|
||||
|
||||
integrations/*
|
||||
177
docs/examples/integrations/embeddings.ipynb
Normal file
177
docs/examples/integrations/embeddings.ipynb
Normal file
@@ -0,0 +1,177 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7ef4d402-6662-4a26-b612-35b542066487",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"# Embeddings & VectorStores\n",
|
||||
"\n",
|
||||
"This notebook show cases how to use embeddings to create a VectorStore"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "965eecee",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
|
||||
"from langchain.text_splitter import CharacterTextSplitter\n",
|
||||
"from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch\n",
|
||||
"from langchain.vectorstores.faiss import FAISS"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "68481687",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open('../state_of_the_union.txt') as f:\n",
|
||||
" state_of_the_union = f.read()\n",
|
||||
"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
|
||||
"texts = text_splitter.split_text(state_of_the_union)\n",
|
||||
"\n",
|
||||
"embeddings = OpenAIEmbeddings()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "015f4ff5",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"docsearch = FAISS.from_texts(texts, embeddings)\n",
|
||||
"\n",
|
||||
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
|
||||
"docs = docsearch.similarity_search(query)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "67baf32e",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
|
||||
"\n",
|
||||
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
|
||||
"\n",
|
||||
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence. \n",
|
||||
"\n",
|
||||
"A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. \n",
|
||||
"\n",
|
||||
"And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"print(docs[0].page_content)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "eea6e627",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Requires having ElasticSearch setup"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "4906b8a3",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"docsearch = ElasticVectorSearch.from_texts(texts, embeddings, elasticsearch_url=\"http://localhost:9200\")\n",
|
||||
"\n",
|
||||
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
|
||||
"docs = docsearch.similarity_search(query)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "95f9eee9",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n",
|
||||
"\n",
|
||||
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
|
||||
"\n",
|
||||
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence. \n",
|
||||
"\n",
|
||||
"A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. \n",
|
||||
"\n",
|
||||
"And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"print(docs[0].page_content)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
71
docs/examples/integrations/huggingface_hub.ipynb
Normal file
71
docs/examples/integrations/huggingface_hub.ipynb
Normal file
@@ -0,0 +1,71 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "959300d4",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# HuggingFace Hub\n",
|
||||
"\n",
|
||||
"This example showcases how to connect to the HuggingFace Hub."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "3acf0069",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"The Seattle Seahawks won the Super Bowl in 2010. Justin Beiber was born in 2010. The\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain import PromptTemplate, HuggingFaceHub, LLMChain\n",
|
||||
"\n",
|
||||
"template = \"\"\"Question: {question}\n",
|
||||
"\n",
|
||||
"Answer: Let's think step by step.\"\"\"\n",
|
||||
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])\n",
|
||||
"llm_chain = LLMChain(prompt=prompt, llm=HuggingFaceHub(repo_id=\"google/flan-t5-xl\", model_kwargs={\"temperature\":1e-10}))\n",
|
||||
"\n",
|
||||
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
|
||||
"\n",
|
||||
"print(llm_chain.run(question))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ae4559c7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -0,0 +1,180 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b118c9dc",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# HuggingFace Tokenizers\n",
|
||||
"\n",
|
||||
"This notebook show cases how to use HuggingFace tokenizers to split text."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "e82c4685",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.text_splitter import CharacterTextSplitter"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "a8ce51d5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from transformers import GPT2TokenizerFast\n",
|
||||
"\n",
|
||||
"tokenizer = GPT2TokenizerFast.from_pretrained(\"gpt2\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "ca5e72c0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open('../state_of_the_union.txt') as f:\n",
|
||||
" state_of_the_union = f.read()\n",
|
||||
"text_splitter = CharacterTextSplitter.from_huggingface_tokenizer(tokenizer, chunk_size=1000, chunk_overlap=0)\n",
|
||||
"texts = text_splitter.split_text(state_of_the_union)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "37cdfbeb",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans. \n",
|
||||
"\n",
|
||||
"Last year COVID-19 kept us apart. This year we are finally together again. \n",
|
||||
"\n",
|
||||
"Tonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. \n",
|
||||
"\n",
|
||||
"With a duty to one another to the American people to the Constitution. \n",
|
||||
"\n",
|
||||
"And with an unwavering resolve that freedom will always triumph over tyranny. \n",
|
||||
"\n",
|
||||
"Six days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. \n",
|
||||
"\n",
|
||||
"He thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined. \n",
|
||||
"\n",
|
||||
"He met the Ukrainian people. \n",
|
||||
"\n",
|
||||
"From President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world. \n",
|
||||
"\n",
|
||||
"Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n",
|
||||
"\n",
|
||||
"In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n",
|
||||
"\n",
|
||||
"Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world. \n",
|
||||
"\n",
|
||||
"Please rise if you are able and show that, Yes, we the United States of America stand with the Ukrainian people. \n",
|
||||
"\n",
|
||||
"Throughout our history we’ve learned this lesson when dictators do not pay a price for their aggression they cause more chaos. \n",
|
||||
"\n",
|
||||
"They keep moving. \n",
|
||||
"\n",
|
||||
"And the costs and the threats to America and the world keep rising. \n",
|
||||
"\n",
|
||||
"That’s why the NATO Alliance was created to secure peace and stability in Europe after World War 2. \n",
|
||||
"\n",
|
||||
"The United States is a member along with 29 other nations. \n",
|
||||
"\n",
|
||||
"It matters. American diplomacy matters. American resolve matters. \n",
|
||||
"\n",
|
||||
"Putin’s latest attack on Ukraine was premeditated and unprovoked. \n",
|
||||
"\n",
|
||||
"He rejected repeated efforts at diplomacy. \n",
|
||||
"\n",
|
||||
"He thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did. \n",
|
||||
"\n",
|
||||
"We prepared extensively and carefully. \n",
|
||||
"\n",
|
||||
"We spent months building a coalition of other freedom-loving nations from Europe and the Americas to Asia and Africa to confront Putin. \n",
|
||||
"\n",
|
||||
"I spent countless hours unifying our European allies. We shared with the world in advance what we knew Putin was planning and precisely how he would try to falsely justify his aggression. \n",
|
||||
"\n",
|
||||
"We countered Russia’s lies with truth. \n",
|
||||
"\n",
|
||||
"And now that he has acted the free world is holding him accountable. \n",
|
||||
"\n",
|
||||
"Along with twenty-seven members of the European Union including France, Germany, Italy, as well as countries like the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland. \n",
|
||||
"\n",
|
||||
"We are inflicting pain on Russia and supporting the people of Ukraine. Putin is now isolated from the world more than ever. \n",
|
||||
"\n",
|
||||
"Together with our allies –we are right now enforcing powerful economic sanctions. \n",
|
||||
"\n",
|
||||
"We are cutting off Russia’s largest banks from the international financial system. \n",
|
||||
"\n",
|
||||
"Preventing Russia’s central bank from defending the Russian Ruble making Putin’s $630 Billion “war fund” worthless. \n",
|
||||
"\n",
|
||||
"We are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come. \n",
|
||||
"\n",
|
||||
"Tonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. \n",
|
||||
"\n",
|
||||
"The U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs. \n",
|
||||
"\n",
|
||||
"We are joining with our European allies to find and seize your yachts your luxury apartments your private jets. We are coming for your ill-begotten gains. \n",
|
||||
"\n",
|
||||
"And tonight I am announcing that we will join our allies in closing off American air space to all Russian flights – further isolating Russia – and adding an additional squeeze –on their economy. The Ruble has lost 30% of its value. \n",
|
||||
"\n",
|
||||
"The Russian stock market has lost 40% of its value and trading remains suspended. Russia’s economy is reeling and Putin alone is to blame. \n",
|
||||
"\n",
|
||||
"Together with our allies we are providing support to the Ukrainians in their fight for freedom. Military assistance. Economic assistance. Humanitarian assistance. \n",
|
||||
"\n",
|
||||
"We are giving more than $1 Billion in direct assistance to Ukraine. \n",
|
||||
"\n",
|
||||
"And we will continue to aid the Ukrainian people as they defend their country and to help ease their suffering. \n",
|
||||
"\n",
|
||||
"Let me be clear, our forces are not engaged and will not engage in conflict with Russian forces in Ukraine. \n",
|
||||
"\n",
|
||||
"Our forces are not going to Europe to fight in Ukraine, but to defend our NATO Allies – in the event that Putin decides to keep moving west. \n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"print(texts[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d214aec2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
215
docs/examples/integrations/manifest.ipynb
Normal file
215
docs/examples/integrations/manifest.ipynb
Normal file
@@ -0,0 +1,215 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b4462a94",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Manifest\n",
|
||||
"\n",
|
||||
"This notebook goes over how to use Manifest and LangChain."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "59fcaebc",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"For more detailed information on `manifest`, and how to use it with local hugginface models like in this example, see https://github.com/HazyResearch/manifest"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "04a0170a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from manifest import Manifest\n",
|
||||
"from langchain.llms.manifest import ManifestWrapper"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "de250a6a",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{'model_name': 'bigscience/T0_3B', 'model_path': 'bigscience/T0_3B'}\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"manifest = Manifest(\n",
|
||||
" client_name = \"huggingface\",\n",
|
||||
" client_connection = \"http://127.0.0.1:5000\"\n",
|
||||
")\n",
|
||||
"print(manifest.client.get_model_params())"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "67b719d6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm = ManifestWrapper(client=manifest, llm_kwargs={\"temperature\": 0.001, \"max_tokens\": 256})"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "5af505a8",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Map reduce example\n",
|
||||
"from langchain import PromptTemplate\n",
|
||||
"from langchain.text_splitter import CharacterTextSplitter\n",
|
||||
"from langchain.chains.mapreduce import MapReduceChain\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"_prompt = \"\"\"Write a concise summary of the following:\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"{text}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"CONCISE SUMMARY:\"\"\"\n",
|
||||
"prompt = PromptTemplate(template=_prompt, input_variables=[\"text\"])\n",
|
||||
"\n",
|
||||
"text_splitter = CharacterTextSplitter()\n",
|
||||
"\n",
|
||||
"mp_chain = MapReduceChain.from_params(llm, prompt, text_splitter)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "485b3ec3",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'President Obama delivered his annual State of the Union address on Tuesday night, laying out his priorities for the coming year. Obama said the government will provide free flu vaccines to all Americans, ending the government shutdown and allowing businesses to reopen. The president also said that the government will continue to send vaccines to 112 countries, more than any other nation. \"We have lost so much to COVID-19,\" Trump said. \"Time with one another. And worst of all, so much loss of life.\" He said the CDC is working on a vaccine for kids under 5, and that the government will be ready with plenty of vaccines when they are available. Obama says the new guidelines are a \"great step forward\" and that the virus is no longer a threat. He says the government is launching a \"Test to Treat\" initiative that will allow people to get tested at a pharmacy and get antiviral pills on the spot at no cost. Obama says the new guidelines are a \"great step forward\" and that the virus is no longer a threat. He says the government will continue to send vaccines to 112 countries, more than any other nation. \"We are coming for your'"
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"with open('../state_of_the_union.txt') as f:\n",
|
||||
" state_of_the_union = f.read()\n",
|
||||
"mp_chain.run(state_of_the_union)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6e9d45a8",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Compare HF Models"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "33407ab3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.model_laboratory import ModelLaboratory\n",
|
||||
"\n",
|
||||
"manifest1 = ManifestWrapper(\n",
|
||||
" client=Manifest(\n",
|
||||
" client_name=\"huggingface\",\n",
|
||||
" client_connection=\"http://127.0.0.1:5000\"\n",
|
||||
" ),\n",
|
||||
" llm_kwargs={\"temperature\": 0.01}\n",
|
||||
")\n",
|
||||
"manifest2 = ManifestWrapper(\n",
|
||||
" client=Manifest(\n",
|
||||
" client_name=\"huggingface\",\n",
|
||||
" client_connection=\"http://127.0.0.1:5001\"\n",
|
||||
" ),\n",
|
||||
" llm_kwargs={\"temperature\": 0.01}\n",
|
||||
")\n",
|
||||
"manifest3 = ManifestWrapper(\n",
|
||||
" client=Manifest(\n",
|
||||
" client_name=\"huggingface\",\n",
|
||||
" client_connection=\"http://127.0.0.1:5002\"\n",
|
||||
" ),\n",
|
||||
" llm_kwargs={\"temperature\": 0.01}\n",
|
||||
")\n",
|
||||
"llms = [manifest1, manifest2, manifest3]\n",
|
||||
"model_lab = ModelLaboratory(llms)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "448935c3",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[1mInput:\u001b[0m\n",
|
||||
"What color is a flamingo?\n",
|
||||
"\n",
|
||||
"\u001b[1mManifestWrapper\u001b[0m\n",
|
||||
"Params: {'model_name': 'bigscience/T0_3B', 'model_path': 'bigscience/T0_3B', 'temperature': 0.01}\n",
|
||||
"\u001b[104mpink\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mManifestWrapper\u001b[0m\n",
|
||||
"Params: {'model_name': 'EleutherAI/gpt-neo-125M', 'model_path': 'EleutherAI/gpt-neo-125M', 'temperature': 0.01}\n",
|
||||
"\u001b[103mA flamingo is a small, round\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mManifestWrapper\u001b[0m\n",
|
||||
"Params: {'model_name': 'google/flan-t5-xl', 'model_path': 'google/flan-t5-xl', 'temperature': 0.01}\n",
|
||||
"\u001b[101mpink\u001b[0m\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model_lab.compare(\"What color is a flamingo?\")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "51b9b5b89a4976ad21c8b4273a6c78d700e2954ce7d7452948b7774eb33bbce4"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
254
docs/examples/model_laboratory.ipynb
Normal file
254
docs/examples/model_laboratory.ipynb
Normal file
@@ -0,0 +1,254 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "920a3c1a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Model Laboratory\n",
|
||||
"\n",
|
||||
"This example goes over basic functionality of how to use the ModelLaboratory to test out and try different models."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "ab9e95ad",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import LLMChain, OpenAI, Cohere, HuggingFaceHub, PromptTemplate\n",
|
||||
"from langchain.model_laboratory import ModelLaboratory"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "32cb94e6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llms = [\n",
|
||||
" OpenAI(temperature=0), \n",
|
||||
" Cohere(model=\"command-xlarge-20221108\", max_tokens=20, temperature=0), \n",
|
||||
" HuggingFaceHub(repo_id=\"google/flan-t5-xl\", model_kwargs={\"temperature\":1})\n",
|
||||
"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "14cde09d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model_lab = ModelLaboratory.from_llms(llms)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "f186c741",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[1mInput:\u001b[0m\n",
|
||||
"What color is a flamingo?\n",
|
||||
"\n",
|
||||
"\u001b[1mOpenAI\u001b[0m\n",
|
||||
"Params: {'model': 'text-davinci-002', 'temperature': 0.0, 'max_tokens': 256, 'top_p': 1, 'frequency_penalty': 0, 'presence_penalty': 0, 'n': 1, 'best_of': 1}\n",
|
||||
"\u001b[36;1m\u001b[1;3m\n",
|
||||
"\n",
|
||||
"Flamingos are pink.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mCohere\u001b[0m\n",
|
||||
"Params: {'model': 'command-xlarge-20221108', 'max_tokens': 20, 'temperature': 0.0, 'k': 0, 'p': 1, 'frequency_penalty': 0, 'presence_penalty': 0}\n",
|
||||
"\u001b[33;1m\u001b[1;3m\n",
|
||||
"\n",
|
||||
"Pink\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mHuggingFaceHub\u001b[0m\n",
|
||||
"Params: {'repo_id': 'google/flan-t5-xl', 'temperature': 1}\n",
|
||||
"\u001b[38;5;200m\u001b[1;3mpink\u001b[0m\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model_lab.compare(\"What color is a flamingo?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "248b652a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"prompt = PromptTemplate(template=\"What is the capital of {state}?\", input_variables=[\"state\"])\n",
|
||||
"model_lab_with_prompt = ModelLaboratory.from_llms(llms, prompt=prompt)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "f64377ac",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[1mInput:\u001b[0m\n",
|
||||
"New York\n",
|
||||
"\n",
|
||||
"\u001b[1mOpenAI\u001b[0m\n",
|
||||
"Params: {'model': 'text-davinci-002', 'temperature': 0.0, 'max_tokens': 256, 'top_p': 1, 'frequency_penalty': 0, 'presence_penalty': 0, 'n': 1, 'best_of': 1}\n",
|
||||
"\u001b[36;1m\u001b[1;3m\n",
|
||||
"\n",
|
||||
"The capital of New York is Albany.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mCohere\u001b[0m\n",
|
||||
"Params: {'model': 'command-xlarge-20221108', 'max_tokens': 20, 'temperature': 0.0, 'k': 0, 'p': 1, 'frequency_penalty': 0, 'presence_penalty': 0}\n",
|
||||
"\u001b[33;1m\u001b[1;3m\n",
|
||||
"\n",
|
||||
"The capital of New York is Albany.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mHuggingFaceHub\u001b[0m\n",
|
||||
"Params: {'repo_id': 'google/flan-t5-xl', 'temperature': 1}\n",
|
||||
"\u001b[38;5;200m\u001b[1;3mst john s\u001b[0m\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model_lab_with_prompt.compare(\"New York\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "54336dbf",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain import SelfAskWithSearchChain, SerpAPIChain\n",
|
||||
"\n",
|
||||
"open_ai_llm = OpenAI(temperature=0)\n",
|
||||
"search = SerpAPIChain()\n",
|
||||
"self_ask_with_search_openai = SelfAskWithSearchChain(llm=open_ai_llm, search_chain=search, verbose=True)\n",
|
||||
"\n",
|
||||
"cohere_llm = Cohere(temperature=0, model=\"command-xlarge-20221108\")\n",
|
||||
"search = SerpAPIChain()\n",
|
||||
"self_ask_with_search_cohere = SelfAskWithSearchChain(llm=cohere_llm, search_chain=search, verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "6a50a9f1",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"chains = [self_ask_with_search_openai, self_ask_with_search_cohere]\n",
|
||||
"names = [str(open_ai_llm), str(cohere_llm)]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "d3549e99",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model_lab = ModelLaboratory(chains, names=names)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "362f7f57",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[1mInput:\u001b[0m\n",
|
||||
"What is the hometown of the reigning men's U.S. Open champion?\n",
|
||||
"\n",
|
||||
"\u001b[1mOpenAI\u001b[0m\n",
|
||||
"Params: {'model': 'text-davinci-002', 'temperature': 0.0, 'max_tokens': 256, 'top_p': 1, 'frequency_penalty': 0, 'presence_penalty': 0, 'n': 1, 'best_of': 1}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"What is the hometown of the reigning men's U.S. Open champion?\n",
|
||||
"Are follow up questions needed here:\u001b[32;1m\u001b[1;3m Yes.\n",
|
||||
"Follow up: Who is the reigning men's U.S. Open champion?\u001b[0m\n",
|
||||
"Intermediate answer: \u001b[33;1m\u001b[1;3mCarlos Alcaraz.\u001b[0m\u001b[32;1m\u001b[1;3m\n",
|
||||
"Follow up: Where is Carlos Alcaraz from?\u001b[0m\n",
|
||||
"Intermediate answer: \u001b[33;1m\u001b[1;3mEl Palmar, Spain.\u001b[0m\u001b[32;1m\u001b[1;3m\n",
|
||||
"So the final answer is: El Palmar, Spain\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\u001b[36;1m\u001b[1;3m\n",
|
||||
"So the final answer is: El Palmar, Spain\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1mCohere\u001b[0m\n",
|
||||
"Params: {'model': 'command-xlarge-20221108', 'max_tokens': 256, 'temperature': 0.0, 'k': 0, 'p': 1, 'frequency_penalty': 0, 'presence_penalty': 0}\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new chain...\u001b[0m\n",
|
||||
"What is the hometown of the reigning men's U.S. Open champion?\n",
|
||||
"Are follow up questions needed here:\u001b[32;1m\u001b[1;3m Yes.\n",
|
||||
"Follow up: Who is the reigning men's U.S. Open champion?\u001b[0m\n",
|
||||
"Intermediate answer: \u001b[33;1m\u001b[1;3mCarlos Alcaraz.\u001b[0m\u001b[32;1m\u001b[1;3m\n",
|
||||
"So the final answer is:\n",
|
||||
"\n",
|
||||
"Carlos Alcaraz\u001b[0m\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\u001b[33;1m\u001b[1;3m\n",
|
||||
"So the final answer is:\n",
|
||||
"\n",
|
||||
"Carlos Alcaraz\u001b[0m\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"model_lab.compare(\"What is the hometown of the reigning men's U.S. Open champion?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "94159131",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.7"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
10
docs/examples/prompts.rst
Normal file
10
docs/examples/prompts.rst
Normal file
@@ -0,0 +1,10 @@
|
||||
Prompts
|
||||
=======
|
||||
|
||||
The examples here all highlight how to work with prompts.
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:glob:
|
||||
|
||||
prompts/*
|
||||
@@ -1,5 +1,4 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["input", "output"],
|
||||
"template": "Input: {input}\nOutput: {output}"
|
||||
}
|
||||
306
docs/examples/prompts/few shot examples.ipynb
Normal file
306
docs/examples/prompts/few shot examples.ipynb
Normal file
@@ -0,0 +1,306 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f8b01b97",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Few Shot Prompt examples\n",
|
||||
"Notebook showing off how canonical prompts in LangChain can be recreated as FewShotPrompts"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "18c67cc9",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts.few_shot import FewShotPromptTemplate\n",
|
||||
"from langchain.prompts.prompt import PromptTemplate"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "2a729c9f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Self Ask with Search\n",
|
||||
"\n",
|
||||
"examples = [\n",
|
||||
" {\n",
|
||||
" \"question\": \"Who lived longer, Muhammad Ali or Alan Turing?\",\n",
|
||||
" \"answer\": \"Are follow up questions needed here: Yes.\\nFollow up: How old was Muhammad Ali when he died?\\nIntermediate answer: Muhammad Ali was 74 years old when he died.\\nFollow up: How old was Alan Turing when he died?\\nIntermediate answer: Alan Turing was 41 years old when he died.\\nSo the final answer is: Muhammad Ali\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"When was the founder of craigslist born?\",\n",
|
||||
" \"answer\": \"Are follow up questions needed here: Yes.\\nFollow up: Who was the founder of craigslist?\\nIntermediate answer: Craigslist was founded by Craig Newmark.\\nFollow up: When was Craig Newmark born?\\nIntermediate answer: Craig Newmark was born on December 6, 1952.\\nSo the final answer is: December 6, 1952\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Who was the maternal grandfather of George Washington?\",\n",
|
||||
" \"answer\": \"Are follow up questions needed here: Yes.\\nFollow up: Who was the mother of George Washington?\\nIntermediate answer: The mother of George Washington was Mary Ball Washington.\\nFollow up: Who was the father of Mary Ball Washington?\\nIntermediate answer: The father of Mary Ball Washington was Joseph Ball.\\nSo the final answer is: Joseph Ball\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Are both the directors of Jaws and Casino Royale from the same country?\",\n",
|
||||
" \"answer\": \"Are follow up questions needed here: Yes.\\nFollow up: Who is the director of Jaws?\\nIntermediate Answer: The director of Jaws is Steven Spielberg.\\nFollow up: Where is Steven Spielberg from?\\nIntermediate Answer: The United States.\\nFollow up: Who is the director of Casino Royale?\\nIntermediate Answer: The director of Casino Royale is Martin Campbell.\\nFollow up: Where is Martin Campbell from?\\nIntermediate Answer: New Zealand.\\nSo the final answer is: No\"\n",
|
||||
" }\n",
|
||||
"]\n",
|
||||
"example_prompt = PromptTemplate(input_variables=[\"question\", \"answer\"], template=\"Question: {question}\\n{answer}\")\n",
|
||||
"\n",
|
||||
"prompt = FewShotPromptTemplate(\n",
|
||||
" examples=examples, \n",
|
||||
" example_prompt=example_prompt, \n",
|
||||
" suffix=\"Question: {input}\", \n",
|
||||
" input_variables=[\"input\"]\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "95fc0059",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# ReAct\n",
|
||||
"\n",
|
||||
"examples = [\n",
|
||||
" {\n",
|
||||
" \"question\": \"What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of that area.\\nAction 1: Search[Colorado orogeny]\\nObservation 1: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.\\nThought 2: It does not mention the eastern sector. So I need to look up eastern sector.\\nAction 2: Lookup[eastern sector]\\nObservation 2: (Result 1 / 1) The eastern sector extends into the High Plains and is called the Central Plains orogeny.\\nThought 3: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.\\nAction 3: Search[High Plains]\\nObservation 3: High Plains refers to one of two distinct land regions\\nThought 4: I need to instead search High Plains (United States).\\nAction 4: Search[High Plains (United States)]\\nObservation 4: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]\\nThought 5: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.\\nAction 5: Finish[1,800 to 7,000 ft]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Musician and satirist Allie Goertz wrote a song about the \\\"The Simpsons\\\" character Milhouse, who Matt Groening named after who?\",\n",
|
||||
" \"answer\": \"Thought 1: The question simplifies to \\\"The Simpsons\\\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.\\nAction 1: Search[Milhouse]\\nObservation 1: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.\\nThought 2: The paragraph does not tell who Milhouse is named after, maybe I can look up \\\"named after\\\".\\nAction 2: Lookup[named after]\\nObservation 2: (Result 1 / 1) Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.\\nThought 3: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.\\nAction 3: Finish[Richard Nixon]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Which documentary is about Finnish rock groups, Adam Clayton Powell or The Saimaa Gesture?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Adam Clayton Powell and The Saimaa Gesture, and find which documentary is about Finnish rock groups.\\nAction 1: Search[Adam Clayton Powell]\\nObservation 1 Could not find [Adam Clayton Powell]. Similar: [’Adam Clayton Powell III’, ’Seventh Avenue (Manhattan)’, ’Adam Clayton Powell Jr. State Office Building’, ’Isabel Washington Powell’, ’Adam Powell’, ’Adam Clayton Powell (film)’, ’Giancarlo Esposito’].\\nThought 2: To find the documentary, I can search Adam Clayton Powell (film).\\nAction 2: Search[Adam Clayton Powell (film)]\\nObservation 2: Adam Clayton Powell is a 1989 American documentary film directed by Richard Kilberg. The film is about the rise and fall of influential African-American politician Adam Clayton Powell Jr.[3][4] It was later aired as part of the PBS series The American Experience.\\nThought 3: Adam Clayton Powell (film) is a documentary about an African-American politician, not Finnish rock groups. So the documentary about Finnish rock groups must instead be The Saimaa Gesture.\\nAction 3: Finish[The Saimaa Gesture]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"What profession does Nicholas Ray and Elia Kazan have in common?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Nicholas Ray and Elia Kazan, find their professions, then find the profession they have in common.\\nAction 1: Search[Nicholas Ray]\\nObservation 1: Nicholas Ray (born Raymond Nicholas Kienzle Jr., August 7, 1911 - June 16, 1979) was an American film director, screenwriter, and actor best known for the 1955 film Rebel Without a Cause.\\nThought 2: Professions of Nicholas Ray are director, screenwriter, and actor. I need to search Elia Kazan next and find his professions.\\nAction 2: Search[Elia Kazan]\\nObservation 2: Elia Kazan was an American film and theatre director, producer, screenwriter and actor.\\nThought 3: Professions of Elia Kazan are director, producer, screenwriter, and actor. So profession Nicholas Ray and Elia Kazan have in common is director, screenwriter, and actor.\\nAction 3: Finish[director, screenwriter, actor]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Which magazine was started first Arthur’s Magazine or First for Women?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Arthur’s Magazine and First for Women, and find which was started first.\\nAction 1: Search[Arthur’s Magazine]\\nObservation 1: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.\\nThought 2: Arthur’s Magazine was started in 1844. I need to search First for Women next.\\nAction 2: Search[First for Women]\\nObservation 2: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.\\nThought 3: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.\\nAction 3: Finish[Arthur’s Magazine]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Were Pavel Urysohn and Leonid Levin known for the same type of work?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Pavel Urysohn and Leonid Levin, find their types of work, then find if they are the same.\\nAction 1: Search[Pavel Urysohn]\\nObservation 1: Pavel Samuilovich Urysohn (February 3, 1898 - August 17, 1924) was a Soviet mathematician who is best known for his contributions in dimension theory.\\nThought 2: Pavel Urysohn is a mathematician. I need to search Leonid Levin next and find its type of work.\\nAction 2: Search[Leonid Levin]\\nObservation 2: Leonid Anatolievich Levin is a Soviet-American mathematician and computer scientist.\\nThought 3: Leonid Levin is a mathematician and computer scientist. So Pavel Urysohn and Leonid Levin have the same type of work.\\nAction 3: Finish[yes]\"\n",
|
||||
" }\n",
|
||||
"]\n",
|
||||
"example_prompt = PromptTemplate(input_variables=[\"question\", \"answer\"], template=\"Question: {question}\\n{answer}\")\n",
|
||||
"\n",
|
||||
"prompt = FewShotPromptTemplate(\n",
|
||||
" examples=examples, \n",
|
||||
" example_prompt=example_prompt, \n",
|
||||
" suffix=\"Question: {input}\", \n",
|
||||
" input_variables=[\"input\"]\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "897d4e08",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# LLM Math\n",
|
||||
"examples = [\n",
|
||||
" {\n",
|
||||
" \"question\": \"What is 37593 * 67?\",\n",
|
||||
" \"answer\": \"```python\\nprint(37593 * 67)\\n```\\n```output\\n2518731\\n```\\nAnswer: 2518731\"\n",
|
||||
" }\n",
|
||||
"]\n",
|
||||
"example_prompt = PromptTemplate(input_variables=[\"question\", \"answer\"], template=\"Question: {question}\\n\\n{answer}\")\n",
|
||||
"\n",
|
||||
"prompt = FewShotPromptTemplate(\n",
|
||||
" examples=examples, \n",
|
||||
" example_prompt=example_prompt, \n",
|
||||
" suffix=\"Question: {input}\", \n",
|
||||
" input_variables=[\"input\"]\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "7ab7379f",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# NatBot\n",
|
||||
"example_seperator = \"==================================================\"\n",
|
||||
"content_1 = \"\"\"<link id=1>About</link>\n",
|
||||
"<link id=2>Store</link>\n",
|
||||
"<link id=3>Gmail</link>\n",
|
||||
"<link id=4>Images</link>\n",
|
||||
"<link id=5>(Google apps)</link>\n",
|
||||
"<link id=6>Sign in</link>\n",
|
||||
"<img id=7 alt=\"(Google)\"/>\n",
|
||||
"<input id=8 alt=\"Search\"></input>\n",
|
||||
"<button id=9>(Search by voice)</button>\n",
|
||||
"<button id=10>(Google Search)</button>\n",
|
||||
"<button id=11>(I'm Feeling Lucky)</button>\n",
|
||||
"<link id=12>Advertising</link>\n",
|
||||
"<link id=13>Business</link>\n",
|
||||
"<link id=14>How Search works</link>\n",
|
||||
"<link id=15>Carbon neutral since 2007</link>\n",
|
||||
"<link id=16>Privacy</link>\n",
|
||||
"<link id=17>Terms</link>\n",
|
||||
"<text id=18>Settings</text>\"\"\"\n",
|
||||
"content_2 = \"\"\"<link id=1>About</link>\n",
|
||||
"<link id=2>Store</link>\n",
|
||||
"<link id=3>Gmail</link>\n",
|
||||
"<link id=4>Images</link>\n",
|
||||
"<link id=5>(Google apps)</link>\n",
|
||||
"<link id=6>Sign in</link>\n",
|
||||
"<img id=7 alt=\"(Google)\"/>\n",
|
||||
"<input id=8 alt=\"Search\"></input>\n",
|
||||
"<button id=9>(Search by voice)</button>\n",
|
||||
"<button id=10>(Google Search)</button>\n",
|
||||
"<button id=11>(I'm Feeling Lucky)</button>\n",
|
||||
"<link id=12>Advertising</link>\n",
|
||||
"<link id=13>Business</link>\n",
|
||||
"<link id=14>How Search works</link>\n",
|
||||
"<link id=15>Carbon neutral since 2007</link>\n",
|
||||
"<link id=16>Privacy</link>\n",
|
||||
"<link id=17>Terms</link>\n",
|
||||
"<text id=18>Settings</text>\"\"\"\n",
|
||||
"content_3 = \"\"\"<button id=1>For Businesses</button>\n",
|
||||
"<button id=2>Mobile</button>\n",
|
||||
"<button id=3>Help</button>\n",
|
||||
"<button id=4 alt=\"Language Picker\">EN</button>\n",
|
||||
"<link id=5>OpenTable logo</link>\n",
|
||||
"<button id=6 alt =\"search\">Search</button>\n",
|
||||
"<text id=7>Find your table for any occasion</text>\n",
|
||||
"<button id=8>(Date selector)</button>\n",
|
||||
"<text id=9>Sep 28, 2022</text>\n",
|
||||
"<text id=10>7:00 PM</text>\n",
|
||||
"<text id=11>2 people</text>\n",
|
||||
"<input id=12 alt=\"Location, Restaurant, or Cuisine\"></input>\n",
|
||||
"<button id=13>Let’s go</button>\n",
|
||||
"<text id=14>It looks like you're in Peninsula. Not correct?</text>\n",
|
||||
"<button id=15>Get current location</button>\n",
|
||||
"<button id=16>Next</button>\"\"\"\n",
|
||||
"examples = [\n",
|
||||
" {\n",
|
||||
" \"i\": 1,\n",
|
||||
" \"content\": content_1,\n",
|
||||
" \"objective\": \"Find a 2 bedroom house for sale in Anchorage AK for under $750k\",\n",
|
||||
" \"current_url\": \"https://www.google.com/\",\n",
|
||||
" \"command\": 'TYPESUBMIT 8 \"anchorage redfin\"'\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"i\": 2,\n",
|
||||
" \"content\": content_2,\n",
|
||||
" \"objective\": \"Make a reservation for 4 at Dorsia at 8pm\",\n",
|
||||
" \"current_url\": \"https://www.google.com/\",\n",
|
||||
" \"command\": 'TYPESUBMIT 8 \"dorsia nyc opentable\"'\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"i\": 3,\n",
|
||||
" \"content\": content_3,\n",
|
||||
" \"objective\": \"Make a reservation for 4 for dinner at Dorsia in New York City at 8pm\",\n",
|
||||
" \"current_url\": \"https://www.opentable.com/\",\n",
|
||||
" \"command\": 'TYPESUBMIT 12 \"dorsia new york city\"'\n",
|
||||
" },\n",
|
||||
"]\n",
|
||||
"example_prompt_template=\"\"\"EXAMPLE {i}:\n",
|
||||
"==================================================\n",
|
||||
"CURRENT BROWSER CONTENT:\n",
|
||||
"------------------\n",
|
||||
"{content}\n",
|
||||
"------------------\n",
|
||||
"OBJECTIVE: {objective}\n",
|
||||
"CURRENT URL: {current_url}\n",
|
||||
"YOUR COMMAND:\n",
|
||||
"{command}\"\"\"\n",
|
||||
"example_prompt = PromptTemplate(input_variables=[\"i\", \"content\", \"objective\", \"current_url\", \"command\"], template=example_prompt_template)\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"prefix = \"\"\"\n",
|
||||
"You are an agent controlling a browser. You are given:\n",
|
||||
"\t(1) an objective that you are trying to achieve\n",
|
||||
"\t(2) the URL of your current web page\n",
|
||||
"\t(3) a simplified text description of what's visible in the browser window (more on that below)\n",
|
||||
"You can issue these commands:\n",
|
||||
"\tSCROLL UP - scroll up one page\n",
|
||||
"\tSCROLL DOWN - scroll down one page\n",
|
||||
"\tCLICK X - click on a given element. You can only click on links, buttons, and inputs!\n",
|
||||
"\tTYPE X \"TEXT\" - type the specified text into the input with id X\n",
|
||||
"\tTYPESUBMIT X \"TEXT\" - same as TYPE above, except then it presses ENTER to submit the form\n",
|
||||
"The format of the browser content is highly simplified; all formatting elements are stripped.\n",
|
||||
"Interactive elements such as links, inputs, buttons are represented like this:\n",
|
||||
"\t\t<link id=1>text</link>\n",
|
||||
"\t\t<button id=2>text</button>\n",
|
||||
"\t\t<input id=3>text</input>\n",
|
||||
"Images are rendered as their alt text like this:\n",
|
||||
"\t\t<img id=4 alt=\"\"/>\n",
|
||||
"Based on your given objective, issue whatever command you believe will get you closest to achieving your goal.\n",
|
||||
"You always start on Google; you should submit a search query to Google that will take you to the best page for\n",
|
||||
"achieving your objective. And then interact with that page to achieve your objective.\n",
|
||||
"If you find yourself on Google and there are no search results displayed yet, you should probably issue a command\n",
|
||||
"like \"TYPESUBMIT 7 \"search query\"\" to get to a more useful page.\n",
|
||||
"Then, if you find yourself on a Google search results page, you might issue the command \"CLICK 24\" to click\n",
|
||||
"on the first link in the search results. (If your previous command was a TYPESUBMIT your next command should\n",
|
||||
"probably be a CLICK.)\n",
|
||||
"Don't try to interact with elements that you can't see.\n",
|
||||
"Here are some examples:\n",
|
||||
"\"\"\"\n",
|
||||
"suffix=\"\"\"\n",
|
||||
"The current browser content, objective, and current URL follow. Reply with your next command to the browser.\n",
|
||||
"CURRENT BROWSER CONTENT:\n",
|
||||
"------------------\n",
|
||||
"{browser_content}\n",
|
||||
"------------------\n",
|
||||
"OBJECTIVE: {objective}\n",
|
||||
"CURRENT URL: {url}\n",
|
||||
"PREVIOUS COMMAND: {previous_command}\n",
|
||||
"YOUR COMMAND:\n",
|
||||
"\"\"\"\n",
|
||||
"PROMPT = FewShotPromptTemplate(\n",
|
||||
" examples = examples,\n",
|
||||
" example_prompt=example_prompt,\n",
|
||||
" example_separator=example_seperator,\n",
|
||||
" input_variables=[\"browser_content\", \"url\", \"previous_command\", \"objective\"],\n",
|
||||
" prefix=prefix,\n",
|
||||
" suffix=suffix,\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ce5927c6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -3,7 +3,6 @@
|
||||
"input_variables": ["adjective"],
|
||||
"prefix": "Write antonyms for the following words.",
|
||||
"example_prompt": {
|
||||
"_type": "prompt",
|
||||
"input_variables": ["input", "output"],
|
||||
"template": "Input: {input}\nOutput: {output}"
|
||||
},
|
||||
@@ -4,7 +4,6 @@ input_variables:
|
||||
prefix:
|
||||
Write antonyms for the following words.
|
||||
example_prompt:
|
||||
_type: prompt
|
||||
input_variables:
|
||||
["input", "output"]
|
||||
template:
|
||||
@@ -3,7 +3,6 @@
|
||||
"input_variables": ["adjective"],
|
||||
"prefix": "Write antonyms for the following words.",
|
||||
"example_prompt": {
|
||||
"_type": "prompt",
|
||||
"input_variables": ["input", "output"],
|
||||
"template": "Input: {input}\nOutput: {output}"
|
||||
},
|
||||
161
docs/examples/prompts/generate_examples.ipynb
Normal file
161
docs/examples/prompts/generate_examples.ipynb
Normal file
@@ -0,0 +1,161 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f5d249ee",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%% md\n"
|
||||
}
|
||||
},
|
||||
"source": [
|
||||
"# Generate Examples\n",
|
||||
"\n",
|
||||
"This notebook shows how to use LangChain to generate more examples similar to the ones you already have."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "1685fa2f",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.llms.openai import OpenAI\n",
|
||||
"from langchain.example_generator import generate_example\n",
|
||||
"from langchain.prompts import PromptTemplate"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "334ef4f7",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Use examples from ReAct\n",
|
||||
"examples = [\n",
|
||||
" {\n",
|
||||
" \"question\": \"What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Colorado orogeny, find the area that the eastern sector of the Colorado orogeny extends into, then find the elevation range of that area.\\nAction 1: Search[Colorado orogeny]\\nObservation 1: The Colorado orogeny was an episode of mountain building (an orogeny) in Colorado and surrounding areas.\\nThought 2: It does not mention the eastern sector. So I need to look up eastern sector.\\nAction 2: Lookup[eastern sector]\\nObservation 2: (Result 1 / 1) The eastern sector extends into the High Plains and is called the Central Plains orogeny.\\nThought 3: The eastern sector of Colorado orogeny extends into the High Plains. So I need to search High Plains and find its elevation range.\\nAction 3: Search[High Plains]\\nObservation 3: High Plains refers to one of two distinct land regions\\nThought 4: I need to instead search High Plains (United States).\\nAction 4: Search[High Plains (United States)]\\nObservation 4: The High Plains are a subregion of the Great Plains. From east to west, the High Plains rise in elevation from around 1,800 to 7,000 ft (550 to 2,130 m).[3]\\nThought 5: High Plains rise in elevation from around 1,800 to 7,000 ft, so the answer is 1,800 to 7,000 ft.\\nAction 5: Finish[1,800 to 7,000 ft]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Musician and satirist Allie Goertz wrote a song about the \\\"The Simpsons\\\" character Milhouse, who Matt Groening named after who?\",\n",
|
||||
" \"answer\": \"Thought 1: The question simplifies to \\\"The Simpsons\\\" character Milhouse is named after who. I only need to search Milhouse and find who it is named after.\\nAction 1: Search[Milhouse]\\nObservation 1: Milhouse Mussolini Van Houten is a recurring character in the Fox animated television series The Simpsons voiced by Pamela Hayden and created by Matt Groening.\\nThought 2: The paragraph does not tell who Milhouse is named after, maybe I can look up \\\"named after\\\".\\nAction 2: Lookup[named after]\\nObservation 2: (Result 1 / 1) Milhouse was named after U.S. president Richard Nixon, whose middle name was Milhous.\\nThought 3: Milhouse was named after U.S. president Richard Nixon, so the answer is Richard Nixon.\\nAction 3: Finish[Richard Nixon]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Which documentary is about Finnish rock groups, Adam Clayton Powell or The Saimaa Gesture?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Adam Clayton Powell and The Saimaa Gesture, and find which documentary is about Finnish rock groups.\\nAction 1: Search[Adam Clayton Powell]\\nObservation 1 Could not find [Adam Clayton Powell]. Similar: [’Adam Clayton Powell III’, ’Seventh Avenue (Manhattan)’, ’Adam Clayton Powell Jr. State Office Building’, ’Isabel Washington Powell’, ’Adam Powell’, ’Adam Clayton Powell (film)’, ’Giancarlo Esposito’].\\nThought 2: To find the documentary, I can search Adam Clayton Powell (film).\\nAction 2: Search[Adam Clayton Powell (film)]\\nObservation 2: Adam Clayton Powell is a 1989 American documentary film directed by Richard Kilberg. The film is about the rise and fall of influential African-American politician Adam Clayton Powell Jr.[3][4] It was later aired as part of the PBS series The American Experience.\\nThought 3: Adam Clayton Powell (film) is a documentary about an African-American politician, not Finnish rock groups. So the documentary about Finnish rock groups must instead be The Saimaa Gesture.\\nAction 3: Finish[The Saimaa Gesture]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"What profession does Nicholas Ray and Elia Kazan have in common?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Nicholas Ray and Elia Kazan, find their professions, then find the profession they have in common.\\nAction 1: Search[Nicholas Ray]\\nObservation 1: Nicholas Ray (born Raymond Nicholas Kienzle Jr., August 7, 1911 - June 16, 1979) was an American film director, screenwriter, and actor best known for the 1955 film Rebel Without a Cause.\\nThought 2: Professions of Nicholas Ray are director, screenwriter, and actor. I need to search Elia Kazan next and find his professions.\\nAction 2: Search[Elia Kazan]\\nObservation 2: Elia Kazan was an American film and theatre director, producer, screenwriter and actor.\\nThought 3: Professions of Elia Kazan are director, producer, screenwriter, and actor. So profession Nicholas Ray and Elia Kazan have in common is director, screenwriter, and actor.\\nAction 3: Finish[director, screenwriter, actor]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Which magazine was started first Arthur’s Magazine or First for Women?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Arthur’s Magazine and First for Women, and find which was started first.\\nAction 1: Search[Arthur’s Magazine]\\nObservation 1: Arthur’s Magazine (1844-1846) was an American literary periodical published in Philadelphia in the 19th century.\\nThought 2: Arthur’s Magazine was started in 1844. I need to search First for Women next.\\nAction 2: Search[First for Women]\\nObservation 2: First for Women is a woman’s magazine published by Bauer Media Group in the USA.[1] The magazine was started in 1989.\\nThought 3: First for Women was started in 1989. 1844 (Arthur’s Magazine) < 1989 (First for Women), so Arthur’s Magazine was started first.\\nAction 3: Finish[Arthur’s Magazine]\"\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"question\": \"Were Pavel Urysohn and Leonid Levin known for the same type of work?\",\n",
|
||||
" \"answer\": \"Thought 1: I need to search Pavel Urysohn and Leonid Levin, find their types of work, then find if they are the same.\\nAction 1: Search[Pavel Urysohn]\\nObservation 1: Pavel Samuilovich Urysohn (February 3, 1898 - August 17, 1924) was a Soviet mathematician who is best known for his contributions in dimension theory.\\nThought 2: Pavel Urysohn is a mathematician. I need to search Leonid Levin next and find its type of work.\\nAction 2: Search[Leonid Levin]\\nObservation 2: Leonid Anatolievich Levin is a Soviet-American mathematician and computer scientist.\\nThought 3: Leonid Levin is a mathematician and computer scientist. So Pavel Urysohn and Leonid Levin have the same type of work.\\nAction 3: Finish[yes]\"\n",
|
||||
" }\n",
|
||||
"]\n",
|
||||
"example_template = PromptTemplate(template=\"Question: {question}\\n{answer}\", input_variables=[\"question\", \"answer\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "a7bd36bc",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"new_example = generate_example(examples, OpenAI(), example_template)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "e1efb008",
|
||||
"metadata": {
|
||||
"pycharm": {
|
||||
"name": "#%%\n"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"['',\n",
|
||||
" '',\n",
|
||||
" 'Question: What is the highest mountain peak in North America?',\n",
|
||||
" '',\n",
|
||||
" 'Thought 1: I need to search North America and find the highest mountain peak.',\n",
|
||||
" '',\n",
|
||||
" 'Action 1: Search[North America]',\n",
|
||||
" '',\n",
|
||||
" 'Observation 1: North America is a continent entirely within the Northern Hemisphere and almost all within the Western Hemisphere.',\n",
|
||||
" '',\n",
|
||||
" 'Thought 2: I need to look up \"highest mountain peak\".',\n",
|
||||
" '',\n",
|
||||
" 'Action 2: Lookup[highest mountain peak]',\n",
|
||||
" '',\n",
|
||||
" 'Observation 2: (Result 1 / 1) Denali, formerly Mount McKinley, is the highest mountain peak in North America, with a summit elevation of 20,310 feet (6,190 m) above sea level.',\n",
|
||||
" '',\n",
|
||||
" 'Thought 3: Denali is the highest mountain peak in North America, with a summit elevation of 20,310 feet.',\n",
|
||||
" '',\n",
|
||||
" 'Action 3: Finish[20,310 feet]']"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"new_example.split('\\n')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1ed01ba2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
540
docs/examples/prompts/prompt_management.ipynb
Normal file
540
docs/examples/prompts/prompt_management.ipynb
Normal file
@@ -0,0 +1,540 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "43fb16cb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Prompt Management\n",
|
||||
"\n",
|
||||
"Managing your prompts is annoying and tedious, with everyone writing their own slightly different variants of the same ideas. But it shouldn't be this way. \n",
|
||||
"\n",
|
||||
"LangChain provides a standard and flexible way for specifying and managing all your prompts, as well as clear and specific terminology around them. This notebook goes through the core components of working with prompts, showing how to use them as well as explaining what they do.\n",
|
||||
"\n",
|
||||
"This notebook covers how to work with prompts in Python. If you are interested in how to work with serialized versions of prompts and load them from disk, see [this notebook](prompt_serialization.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "890aad4d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### The BasePromptTemplate Interface\n",
|
||||
"\n",
|
||||
"A prompt template is a mechanism for constructing a prompt to pass to the language model given some user input. Below is the interface that all different types of prompt templates should expose.\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"class BasePromptTemplate(ABC):\n",
|
||||
"\n",
|
||||
" input_variables: List[str]\n",
|
||||
" \"\"\"A list of the names of the variables the prompt template expects.\"\"\"\n",
|
||||
"\n",
|
||||
" @abstractmethod\n",
|
||||
" def format(self, **kwargs: Any) -> str:\n",
|
||||
" \"\"\"Format the prompt with the inputs.\n",
|
||||
"\n",
|
||||
" Args:\n",
|
||||
" kwargs: Any arguments to be passed to the prompt template.\n",
|
||||
"\n",
|
||||
" Returns:\n",
|
||||
" A formatted string.\n",
|
||||
"\n",
|
||||
" Example:\n",
|
||||
"\n",
|
||||
" .. code-block:: python\n",
|
||||
"\n",
|
||||
" prompt.format(variable1=\"foo\")\n",
|
||||
" \"\"\"\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"The only two things that define a prompt are:\n",
|
||||
"\n",
|
||||
"1. `input_variables`: The user inputted variables that are needed to format the prompt.\n",
|
||||
"2. `format`: A method which takes in keyword arguments are returns a formatted prompt. The keys are expected to be the input variables\n",
|
||||
" \n",
|
||||
"The rest of the logic of how the prompt is constructed is left up to different implementations. Let's take a look at some below."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "cddb465e",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### PromptTemplate\n",
|
||||
"\n",
|
||||
"This is the most simple type of prompt template, consisting of a string template that takes any number of input variables. The template should be formatted as a Python f-string, although we will support other formats (Jinja, Mako, etc) in the future. \n",
|
||||
"\n",
|
||||
"If you just want to use a hardcoded prompt template, you should use this implementation.\n",
|
||||
"\n",
|
||||
"Let's walk through a few examples."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "094229f4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts import PromptTemplate"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "ab46bd2a",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Tell me a joke.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example prompt with no input variables\n",
|
||||
"no_input_prompt = PromptTemplate(input_variables=[], template=\"Tell me a joke.\")\n",
|
||||
"no_input_prompt.format()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "c3ad0fa8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Tell me a funny joke.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example prompt with one input variable\n",
|
||||
"one_input_prompt = PromptTemplate(input_variables=[\"adjective\"], template=\"Tell me a {adjective} joke.\")\n",
|
||||
"one_input_prompt.format(adjective=\"funny\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "ba577dcf",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Tell me a funny joke about chickens.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example prompt with multiple input variables\n",
|
||||
"multiple_input_prompt = PromptTemplate(\n",
|
||||
" input_variables=[\"adjective\", \"content\"], \n",
|
||||
" template=\"Tell me a {adjective} joke about {content}.\"\n",
|
||||
")\n",
|
||||
"multiple_input_prompt.format(adjective=\"funny\", content=\"chickens\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1492b49d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Few Shot Prompts\n",
|
||||
"\n",
|
||||
"A FewShotPromptTemplate is a prompt template that includes some examples. If you have collected some examples of how the task should be done, you can insert them into prompt using this class.\n",
|
||||
"\n",
|
||||
"Examples are datapoints that can be included in the prompt in order to give the model more context what to do. Examples are represented as a dictionary of key-value pairs, with the key being the input (or label) name, and the value being the input (or label) value. \n",
|
||||
"\n",
|
||||
"In addition to the example, we also need to specify how the example should be formatted when it's inserted in the prompt. We can do this using the above `PromptTemplate`!"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "3eb36972",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# These are some examples of a pretend task of creating antonyms.\n",
|
||||
"examples = [\n",
|
||||
" {\"input\": \"happy\", \"output\": \"sad\"},\n",
|
||||
" {\"input\": \"tall\", \"output\": \"short\"},\n",
|
||||
"]\n",
|
||||
"# This how we specify how the example should be formatted.\n",
|
||||
"example_prompt = PromptTemplate(\n",
|
||||
" input_variables=[\"input\",\"output\"],\n",
|
||||
" template=\"Input: {input}\\nOutput: {output}\",\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "80a91d96",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts import FewShotPromptTemplate"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "7931e5f2",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: big\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt_from_string_examples = FewShotPromptTemplate(\n",
|
||||
" # These are the examples we want to insert into the prompt.\n",
|
||||
" examples=examples,\n",
|
||||
" # This is how we want to format the examples when we insert them into the prompt.\n",
|
||||
" example_prompt=example_prompt,\n",
|
||||
" # The prefix is some text that goes before the examples in the prompt.\n",
|
||||
" # Usually, this consists of intructions.\n",
|
||||
" prefix=\"Give the antonym of every input\",\n",
|
||||
" # The suffix is some text that goes after the examples in the prompt.\n",
|
||||
" # Usually, this is where the user input will go\n",
|
||||
" suffix=\"Input: {adjective}\\nOutput:\", \n",
|
||||
" # The input variables are the variables that the overall prompt expects.\n",
|
||||
" input_variables=[\"adjective\"],\n",
|
||||
" # The example_separator is the string we will use to join the prefix, examples, and suffix together with.\n",
|
||||
" example_separator=\"\\n\\n\"\n",
|
||||
" \n",
|
||||
")\n",
|
||||
"print(prompt_from_string_examples.format(adjective=\"big\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "bf038596",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### ExampleSelector\n",
|
||||
"If you have a large number of examples, you may need to select which ones to include in the prompt. The ExampleSelector is the class responsible for doing so. The base interface is defined as below.\n",
|
||||
"\n",
|
||||
"```python\n",
|
||||
"class BaseExampleSelector(ABC):\n",
|
||||
" \"\"\"Interface for selecting examples to include in prompts.\"\"\"\n",
|
||||
"\n",
|
||||
" @abstractmethod\n",
|
||||
" def select_examples(self, input_variables: Dict[str, str]) -> List[dict]:\n",
|
||||
" \"\"\"Select which examples to use based on the inputs.\"\"\"\n",
|
||||
"\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"The only method it needs to expose is a `select_examples` method. This takes in the input variables and then returns a list of examples. It is up to each specific implementation as to how those examples are selected. Let's take a look at some below."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "861a4d1f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### LengthBased ExampleSelector\n",
|
||||
"\n",
|
||||
"This ExampleSelector selects which examples to use based on length. This is useful when you are worried about constructing a prompt that will go over the length of the context window. For longer inputs, it will select fewer examples to include, while for shorter inputs it will select more.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "7c469c95",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts.example_selector import LengthBasedExampleSelector"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "0ec6d950",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# These are a lot of examples of a pretend task of creating antonyms.\n",
|
||||
"examples = [\n",
|
||||
" {\"input\": \"happy\", \"output\": \"sad\"},\n",
|
||||
" {\"input\": \"tall\", \"output\": \"short\"},\n",
|
||||
" {\"input\": \"energetic\", \"output\": \"lethargic\"},\n",
|
||||
" {\"input\": \"sunny\", \"output\": \"gloomy\"},\n",
|
||||
" {\"input\": \"windy\", \"output\": \"calm\"},\n",
|
||||
"]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "207e55f7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"example_selector = LengthBasedExampleSelector(\n",
|
||||
" # These are the examples is has available to choose from.\n",
|
||||
" examples=examples, \n",
|
||||
" # This is the PromptTemplate being used to format the examples.\n",
|
||||
" example_prompt=example_prompt, \n",
|
||||
" # This is the maximum length that the formatted examples should be.\n",
|
||||
" # Length is measured by the get_text_length function below.\n",
|
||||
" max_length=18,\n",
|
||||
" # This is the function used to get the length of a string, which is used\n",
|
||||
" # to determine which examples to include. It is commented out because\n",
|
||||
" # it is provided as a default value if none is specified.\n",
|
||||
" # get_text_length: Callable[[str], int] = lambda x: len(re.split(\"\\n| \", x))\n",
|
||||
")\n",
|
||||
"dynamic_prompt = FewShotPromptTemplate(\n",
|
||||
" # We provide an ExampleSelector instead of examples.\n",
|
||||
" example_selector=example_selector,\n",
|
||||
" example_prompt=example_prompt,\n",
|
||||
" prefix=\"Give the antonym of every input\",\n",
|
||||
" suffix=\"Input: {adjective}\\nOutput:\", \n",
|
||||
" input_variables=[\"adjective\"],\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "d00b4385",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: energetic\n",
|
||||
"Output: lethargic\n",
|
||||
"\n",
|
||||
"Input: sunny\n",
|
||||
"Output: gloomy\n",
|
||||
"\n",
|
||||
"Input: windy\n",
|
||||
"Output: calm\n",
|
||||
"\n",
|
||||
"Input: big\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example with small input, so it selects all examples.\n",
|
||||
"print(dynamic_prompt.format(adjective=\"big\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "878bcde9",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: big and huge and massive and large and gigantic and tall and bigger than everything else\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example with long input, so it selects only one example.\n",
|
||||
"long_string = \"big and huge and massive and large and gigantic and tall and bigger than everything else\"\n",
|
||||
"print(dynamic_prompt.format(adjective=long_string))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2d007b0a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Similarity ExampleSelector\n",
|
||||
"\n",
|
||||
"The SemanticSimilarityExampleSelector selects examples based on which examples are most similar to the inputs. It does this by finding the examples with the embeddings that have the greatest cosine similarity with the inputs.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "241bfe80",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts.example_selector import SemanticSimilarityExampleSelector\n",
|
||||
"from langchain.vectorstores import FAISS\n",
|
||||
"from langchain.embeddings import OpenAIEmbeddings"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "50d0a701",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"example_selector = SemanticSimilarityExampleSelector.from_examples(\n",
|
||||
" # This is the list of examples available to select from.\n",
|
||||
" examples, \n",
|
||||
" # This is the embedding class used to produce embeddings which are used to measure semantic similarity.\n",
|
||||
" OpenAIEmbeddings(), \n",
|
||||
" # This is the VectorStore class that is used to store the embeddings and do a similarity search over.\n",
|
||||
" FAISS, \n",
|
||||
" # This is the number of examples to produce.\n",
|
||||
" k=1\n",
|
||||
")\n",
|
||||
"similar_prompt = FewShotPromptTemplate(\n",
|
||||
" # We provide an ExampleSelector instead of examples.\n",
|
||||
" example_selector=example_selector,\n",
|
||||
" example_prompt=example_prompt,\n",
|
||||
" prefix=\"Give the antonym of every input\",\n",
|
||||
" suffix=\"Input: {adjective}\\nOutput:\", \n",
|
||||
" input_variables=[\"adjective\"],\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "4c8fdf45",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: worried\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Input is a feeling, so should select the happy/sad example\n",
|
||||
"print(similar_prompt.format(adjective=\"worried\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "829af21a",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: fat\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Input is a measurment, so should select the tall/short example\n",
|
||||
"print(similar_prompt.format(adjective=\"fat\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "dbc32551",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Serialization\n",
|
||||
"\n",
|
||||
"PromptTemplates and examples can be serialized and loaded from disk, making it easy to share and store prompts. For a detailed walkthrough on how to do that, see [this notebook](prompt_serialization.ipynb)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1e1e13c6",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Customizability\n",
|
||||
"The above covers all the ways currently supported in LangChain to represent prompts and example selectors. However, due to the simple interface that the base classes (`BasePromptTemplate`, `BaseExampleSelector`) expose, it should be easy to subclass them and write your own implementation in your own codebase. And of course, if you'd like to contribute that back to LangChain, we'd love that :)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "c746d6f4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
542
docs/examples/prompts/prompt_serialization.ipynb
Normal file
542
docs/examples/prompts/prompt_serialization.ipynb
Normal file
@@ -0,0 +1,542 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "43fb16cb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Prompt Serialization\n",
|
||||
"\n",
|
||||
"It is often preferrable to store prompts not as python code but as files. This can make it easy to share, store, and version prompts. This notebook covers how to do that in LangChain, walking through all the different types of prompts and the different serialization options.\n",
|
||||
"\n",
|
||||
"At a high level, the following design principles are applied to serialization:\n",
|
||||
"\n",
|
||||
"1. Both JSON and YAML are supported. We want to support serialization methods are human readable on disk, and YAML and JSON are two of the most popular methods for that. Note that this rule applies to prompts. For other assets, like Examples, different serialization methods may be supported.\n",
|
||||
"\n",
|
||||
"2. We support specifying everything in one file, or storing different components (templates, examples, etc) in different files and referencing them. For some cases, storing everything in file makes the most sense, but for others it is preferrable to split up some of the assets (long templates, large examples, reusable components). LangChain supports both.\n",
|
||||
"\n",
|
||||
"There is also a single entry point to load prompts from disk, making it easy to load any type of prompt."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "2c8d7587",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# All prompts are loaded through the `load_prompt` function.\n",
|
||||
"from langchain.prompts import load_prompt"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "cddb465e",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## PromptTemplate\n",
|
||||
"\n",
|
||||
"This section covers examples for loading a PromptTemplate."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "4d4b40f2",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Loading from YAML\n",
|
||||
"This shows an example of loading a PromptTemplate from YAML."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "2d6e5117",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"input_variables:\r\n",
|
||||
" [\"adjective\", \"content\"]\r\n",
|
||||
"template: \r\n",
|
||||
" Tell me a {adjective} joke about {content}.\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat simple_prompt.yaml"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "4f4ca686",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tell me a funny joke about chickens.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"simple_prompt.yaml\")\n",
|
||||
"print(prompt.format(adjective=\"funny\", content=\"chickens\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "362eadb2",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Loading from JSON\n",
|
||||
"This shows an example of loading a PromptTemplate from JSON."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "510def23",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"input_variables\": [\"adjective\", \"content\"],\r\n",
|
||||
" \"template\": \"Tell me a {adjective} joke about {content}.\"\r\n",
|
||||
"}\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat simple_prompt.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d788a83c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Loading Template from a File\n",
|
||||
"This shows an example of storing the template in a separate file and then referencing it in the config. Notice that the key changes from `template` to `template_path`."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "5547760d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tell me a {adjective} joke about {content}."
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat simple_template.txt"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "9cb13ac5",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"input_variables\": [\"adjective\", \"content\"],\r\n",
|
||||
" \"template_path\": \"simple_template.txt\"\r\n",
|
||||
"}\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat simple_prompt_with_template_file.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "762cb4bf",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tell me a funny joke about chickens.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"simple_prompt_with_template_file.json\")\n",
|
||||
"print(prompt.format(adjective=\"funny\", content=\"chickens\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2ae191cc",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## FewShotPromptTemplate\n",
|
||||
"\n",
|
||||
"This section covers examples for loading few shot prompt templates."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9828f94c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Examples\n",
|
||||
"This shows an example of what examples stored as json might look like."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "b21f5b95",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"[\r\n",
|
||||
" {\"input\": \"happy\", \"output\": \"sad\"},\r\n",
|
||||
" {\"input\": \"tall\", \"output\": \"short\"}\r\n",
|
||||
"]\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat examples.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "8e300335",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Loading from YAML\n",
|
||||
"This shows an example of loading a few shot example from YAML."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "e2bec0fc",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"_type: few_shot\r\n",
|
||||
"input_variables:\r\n",
|
||||
" [\"adjective\"]\r\n",
|
||||
"prefix: \r\n",
|
||||
" Write antonyms for the following words.\r\n",
|
||||
"example_prompt:\r\n",
|
||||
" input_variables:\r\n",
|
||||
" [\"input\", \"output\"]\r\n",
|
||||
" template:\r\n",
|
||||
" \"Input: {input}\\nOutput: {output}\"\r\n",
|
||||
"examples:\r\n",
|
||||
" examples.json\r\n",
|
||||
"suffix:\r\n",
|
||||
" \"Input: {adjective}\\nOutput:\"\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat few_shot_prompt.yaml"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "98c8f356",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Write antonyms for the following words.\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: funny\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"few_shot_prompt.yaml\")\n",
|
||||
"print(prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "4870aa9d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Loading from JSON\n",
|
||||
"This shows an example of loading a few shot example from JSON."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "9d996a86",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"_type\": \"few_shot\",\r\n",
|
||||
" \"input_variables\": [\"adjective\"],\r\n",
|
||||
" \"prefix\": \"Write antonyms for the following words.\",\r\n",
|
||||
" \"example_prompt\": {\r\n",
|
||||
" \"input_variables\": [\"input\", \"output\"],\r\n",
|
||||
" \"template\": \"Input: {input}\\nOutput: {output}\"\r\n",
|
||||
" },\r\n",
|
||||
" \"examples\": \"examples.json\",\r\n",
|
||||
" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
|
||||
"} \r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat few_shot_prompt.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "dd2c10bb",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Write antonyms for the following words.\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: funny\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"few_shot_prompt.json\")\n",
|
||||
"print(prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9d23faf4",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Examples in the Config\n",
|
||||
"This shows an example of referencing the examples directly in the config."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 13,
|
||||
"id": "6cd781ef",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"_type\": \"few_shot\",\r\n",
|
||||
" \"input_variables\": [\"adjective\"],\r\n",
|
||||
" \"prefix\": \"Write antonyms for the following words.\",\r\n",
|
||||
" \"example_prompt\": {\r\n",
|
||||
" \"input_variables\": [\"input\", \"output\"],\r\n",
|
||||
" \"template\": \"Input: {input}\\nOutput: {output}\"\r\n",
|
||||
" },\r\n",
|
||||
" \"examples\": [\r\n",
|
||||
" {\"input\": \"happy\", \"output\": \"sad\"},\r\n",
|
||||
" {\"input\": \"tall\", \"output\": \"short\"}\r\n",
|
||||
" ],\r\n",
|
||||
" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
|
||||
"} \r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat few_shot_prompt_examples_in.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "533ab8a7",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Write antonyms for the following words.\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: funny\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"few_shot_prompt_examples_in.json\")\n",
|
||||
"print(prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2e86139e",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Example Prompt from a File\n",
|
||||
"This shows an example of loading the PromptTemplate that is used to format the examples from a separate file. Note that the key changes from `example_prompt` to `example_prompt_path`."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"id": "0b6dd7b8",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"input_variables\": [\"input\", \"output\"],\r\n",
|
||||
" \"template\": \"Input: {input}\\nOutput: {output}\" \r\n",
|
||||
"}\r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat example_prompt.json"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"id": "76a1065d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"{\r\n",
|
||||
" \"_type\": \"few_shot\",\r\n",
|
||||
" \"input_variables\": [\"adjective\"],\r\n",
|
||||
" \"prefix\": \"Write antonyms for the following words.\",\r\n",
|
||||
" \"example_prompt_path\": \"example_prompt.json\",\r\n",
|
||||
" \"examples\": \"examples.json\",\r\n",
|
||||
" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
|
||||
"} \r\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!cat few_shot_prompt_example_prompt.json "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"id": "744d275d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Write antonyms for the following words.\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: funny\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = load_prompt(\"few_shot_prompt_example_prompt.json\")\n",
|
||||
"print(prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "dcfc7176",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@@ -1,5 +1,4 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template": "Tell me a {adjective} joke about {content}."
|
||||
}
|
||||
@@ -1,7 +1,4 @@
|
||||
_type: prompt
|
||||
input_variables:
|
||||
["adjective"]
|
||||
partial_variables:
|
||||
content: dogs
|
||||
["adjective", "content"]
|
||||
template:
|
||||
Tell me a {adjective} joke about {content}.
|
||||
@@ -1,5 +1,4 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template_path": "simple_template.txt"
|
||||
}
|
||||
723
docs/examples/state_of_the_union.txt
Normal file
723
docs/examples/state_of_the_union.txt
Normal file
@@ -0,0 +1,723 @@
|
||||
Madam Speaker, Madam Vice President, our First Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans.
|
||||
|
||||
Last year COVID-19 kept us apart. This year we are finally together again.
|
||||
|
||||
Tonight, we meet as Democrats Republicans and Independents. But most importantly as Americans.
|
||||
|
||||
With a duty to one another to the American people to the Constitution.
|
||||
|
||||
And with an unwavering resolve that freedom will always triumph over tyranny.
|
||||
|
||||
Six days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated.
|
||||
|
||||
He thought he could roll into Ukraine and the world would roll over. Instead he met a wall of strength he never imagined.
|
||||
|
||||
He met the Ukrainian people.
|
||||
|
||||
From President Zelenskyy to every Ukrainian, their fearlessness, their courage, their determination, inspires the world.
|
||||
|
||||
Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland.
|
||||
|
||||
In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight.
|
||||
|
||||
Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world.
|
||||
|
||||
Please rise if you are able and show that, Yes, we the United States of America stand with the Ukrainian people.
|
||||
|
||||
Throughout our history we’ve learned this lesson when dictators do not pay a price for their aggression they cause more chaos.
|
||||
|
||||
They keep moving.
|
||||
|
||||
And the costs and the threats to America and the world keep rising.
|
||||
|
||||
That’s why the NATO Alliance was created to secure peace and stability in Europe after World War 2.
|
||||
|
||||
The United States is a member along with 29 other nations.
|
||||
|
||||
It matters. American diplomacy matters. American resolve matters.
|
||||
|
||||
Putin’s latest attack on Ukraine was premeditated and unprovoked.
|
||||
|
||||
He rejected repeated efforts at diplomacy.
|
||||
|
||||
He thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did.
|
||||
|
||||
We prepared extensively and carefully.
|
||||
|
||||
We spent months building a coalition of other freedom-loving nations from Europe and the Americas to Asia and Africa to confront Putin.
|
||||
|
||||
I spent countless hours unifying our European allies. We shared with the world in advance what we knew Putin was planning and precisely how he would try to falsely justify his aggression.
|
||||
|
||||
We countered Russia’s lies with truth.
|
||||
|
||||
And now that he has acted the free world is holding him accountable.
|
||||
|
||||
Along with twenty-seven members of the European Union including France, Germany, Italy, as well as countries like the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland.
|
||||
|
||||
We are inflicting pain on Russia and supporting the people of Ukraine. Putin is now isolated from the world more than ever.
|
||||
|
||||
Together with our allies –we are right now enforcing powerful economic sanctions.
|
||||
|
||||
We are cutting off Russia’s largest banks from the international financial system.
|
||||
|
||||
Preventing Russia’s central bank from defending the Russian Ruble making Putin’s $630 Billion “war fund” worthless.
|
||||
|
||||
We are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come.
|
||||
|
||||
Tonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more.
|
||||
|
||||
The U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs.
|
||||
|
||||
We are joining with our European allies to find and seize your yachts your luxury apartments your private jets. We are coming for your ill-begotten gains.
|
||||
|
||||
And tonight I am announcing that we will join our allies in closing off American air space to all Russian flights – further isolating Russia – and adding an additional squeeze –on their economy. The Ruble has lost 30% of its value.
|
||||
|
||||
The Russian stock market has lost 40% of its value and trading remains suspended. Russia’s economy is reeling and Putin alone is to blame.
|
||||
|
||||
Together with our allies we are providing support to the Ukrainians in their fight for freedom. Military assistance. Economic assistance. Humanitarian assistance.
|
||||
|
||||
We are giving more than $1 Billion in direct assistance to Ukraine.
|
||||
|
||||
And we will continue to aid the Ukrainian people as they defend their country and to help ease their suffering.
|
||||
|
||||
Let me be clear, our forces are not engaged and will not engage in conflict with Russian forces in Ukraine.
|
||||
|
||||
Our forces are not going to Europe to fight in Ukraine, but to defend our NATO Allies – in the event that Putin decides to keep moving west.
|
||||
|
||||
For that purpose we’ve mobilized American ground forces, air squadrons, and ship deployments to protect NATO countries including Poland, Romania, Latvia, Lithuania, and Estonia.
|
||||
|
||||
As I have made crystal clear the United States and our Allies will defend every inch of territory of NATO countries with the full force of our collective power.
|
||||
|
||||
And we remain clear-eyed. The Ukrainians are fighting back with pure courage. But the next few days weeks, months, will be hard on them.
|
||||
|
||||
Putin has unleashed violence and chaos. But while he may make gains on the battlefield – he will pay a continuing high price over the long run.
|
||||
|
||||
And a proud Ukrainian people, who have known 30 years of independence, have repeatedly shown that they will not tolerate anyone who tries to take their country backwards.
|
||||
|
||||
To all Americans, I will be honest with you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the world.
|
||||
|
||||
And I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers.
|
||||
|
||||
Tonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world.
|
||||
|
||||
America will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies.
|
||||
|
||||
These steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming.
|
||||
|
||||
But I want you to know that we are going to be okay.
|
||||
|
||||
When the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger.
|
||||
|
||||
While it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly.
|
||||
|
||||
We see the unity among leaders of nations and a more unified Europe a more unified West. And we see unity among the people who are gathering in cities in large crowds around the world even in Russia to demonstrate their support for Ukraine.
|
||||
|
||||
In the battle between democracy and autocracy, democracies are rising to the moment, and the world is clearly choosing the side of peace and security.
|
||||
|
||||
This is a real test. It’s going to take time. So let us continue to draw inspiration from the iron will of the Ukrainian people.
|
||||
|
||||
To our fellow Ukrainian Americans who forge a deep bond that connects our two nations we stand with you.
|
||||
|
||||
Putin may circle Kyiv with tanks, but he will never gain the hearts and souls of the Ukrainian people.
|
||||
|
||||
He will never extinguish their love of freedom. He will never weaken the resolve of the free world.
|
||||
|
||||
We meet tonight in an America that has lived through two of the hardest years this nation has ever faced.
|
||||
|
||||
The pandemic has been punishing.
|
||||
|
||||
And so many families are living paycheck to paycheck, struggling to keep up with the rising cost of food, gas, housing, and so much more.
|
||||
|
||||
I understand.
|
||||
|
||||
I remember when my Dad had to leave our home in Scranton, Pennsylvania to find work. I grew up in a family where if the price of food went up, you felt it.
|
||||
|
||||
That’s why one of the first things I did as President was fight to pass the American Rescue Plan.
|
||||
|
||||
Because people were hurting. We needed to act, and we did.
|
||||
|
||||
Few pieces of legislation have done more in a critical moment in our history to lift us out of crisis.
|
||||
|
||||
It fueled our efforts to vaccinate the nation and combat COVID-19. It delivered immediate economic relief for tens of millions of Americans.
|
||||
|
||||
Helped put food on their table, keep a roof over their heads, and cut the cost of health insurance.
|
||||
|
||||
And as my Dad used to say, it gave people a little breathing room.
|
||||
|
||||
And unlike the $2 Trillion tax cut passed in the previous administration that benefitted the top 1% of Americans, the American Rescue Plan helped working people—and left no one behind.
|
||||
|
||||
And it worked. It created jobs. Lots of jobs.
|
||||
|
||||
In fact—our economy created over 6.5 Million new jobs just last year, more jobs created in one year
|
||||
than ever before in the history of America.
|
||||
|
||||
Our economy grew at a rate of 5.7% last year, the strongest growth in nearly 40 years, the first step in bringing fundamental change to an economy that hasn’t worked for the working people of this nation for too long.
|
||||
|
||||
For the past 40 years we were told that if we gave tax breaks to those at the very top, the benefits would trickle down to everyone else.
|
||||
|
||||
But that trickle-down theory led to weaker economic growth, lower wages, bigger deficits, and the widest gap between those at the top and everyone else in nearly a century.
|
||||
|
||||
Vice President Harris and I ran for office with a new economic vision for America.
|
||||
|
||||
Invest in America. Educate Americans. Grow the workforce. Build the economy from the bottom up
|
||||
and the middle out, not from the top down.
|
||||
|
||||
Because we know that when the middle class grows, the poor have a ladder up and the wealthy do very well.
|
||||
|
||||
America used to have the best roads, bridges, and airports on Earth.
|
||||
|
||||
Now our infrastructure is ranked 13th in the world.
|
||||
|
||||
We won’t be able to compete for the jobs of the 21st Century if we don’t fix that.
|
||||
|
||||
That’s why it was so important to pass the Bipartisan Infrastructure Law—the most sweeping investment to rebuild America in history.
|
||||
|
||||
This was a bipartisan effort, and I want to thank the members of both parties who worked to make it happen.
|
||||
|
||||
We’re done talking about infrastructure weeks.
|
||||
|
||||
We’re going to have an infrastructure decade.
|
||||
|
||||
It is going to transform America and put us on a path to win the economic competition of the 21st Century that we face with the rest of the world—particularly with China.
|
||||
|
||||
As I’ve told Xi Jinping, it is never a good bet to bet against the American people.
|
||||
|
||||
We’ll create good jobs for millions of Americans, modernizing roads, airports, ports, and waterways all across America.
|
||||
|
||||
And we’ll do it all to withstand the devastating effects of the climate crisis and promote environmental justice.
|
||||
|
||||
We’ll build a national network of 500,000 electric vehicle charging stations, begin to replace poisonous lead pipes—so every child—and every American—has clean water to drink at home and at school, provide affordable high-speed internet for every American—urban, suburban, rural, and tribal communities.
|
||||
|
||||
4,000 projects have already been announced.
|
||||
|
||||
And tonight, I’m announcing that this year we will start fixing over 65,000 miles of highway and 1,500 bridges in disrepair.
|
||||
|
||||
When we use taxpayer dollars to rebuild America – we are going to Buy American: buy American products to support American jobs.
|
||||
|
||||
The federal government spends about $600 Billion a year to keep the country safe and secure.
|
||||
|
||||
There’s been a law on the books for almost a century
|
||||
to make sure taxpayers’ dollars support American jobs and businesses.
|
||||
|
||||
Every Administration says they’ll do it, but we are actually doing it.
|
||||
|
||||
We will buy American to make sure everything from the deck of an aircraft carrier to the steel on highway guardrails are made in America.
|
||||
|
||||
But to compete for the best jobs of the future, we also need to level the playing field with China and other competitors.
|
||||
|
||||
That’s why it is so important to pass the Bipartisan Innovation Act sitting in Congress that will make record investments in emerging technologies and American manufacturing.
|
||||
|
||||
Let me give you one example of why it’s so important to pass it.
|
||||
|
||||
If you travel 20 miles east of Columbus, Ohio, you’ll find 1,000 empty acres of land.
|
||||
|
||||
It won’t look like much, but if you stop and look closely, you’ll see a “Field of dreams,” the ground on which America’s future will be built.
|
||||
|
||||
This is where Intel, the American company that helped build Silicon Valley, is going to build its $20 billion semiconductor “mega site”.
|
||||
|
||||
Up to eight state-of-the-art factories in one place. 10,000 new good-paying jobs.
|
||||
|
||||
Some of the most sophisticated manufacturing in the world to make computer chips the size of a fingertip that power the world and our everyday lives.
|
||||
|
||||
Smartphones. The Internet. Technology we have yet to invent.
|
||||
|
||||
But that’s just the beginning.
|
||||
|
||||
Intel’s CEO, Pat Gelsinger, who is here tonight, told me they are ready to increase their investment from
|
||||
$20 billion to $100 billion.
|
||||
|
||||
That would be one of the biggest investments in manufacturing in American history.
|
||||
|
||||
And all they’re waiting for is for you to pass this bill.
|
||||
|
||||
So let’s not wait any longer. Send it to my desk. I’ll sign it.
|
||||
|
||||
And we will really take off.
|
||||
|
||||
And Intel is not alone.
|
||||
|
||||
There’s something happening in America.
|
||||
|
||||
Just look around and you’ll see an amazing story.
|
||||
|
||||
The rebirth of the pride that comes from stamping products “Made In America.” The revitalization of American manufacturing.
|
||||
|
||||
Companies are choosing to build new factories here, when just a few years ago, they would have built them overseas.
|
||||
|
||||
That’s what is happening. Ford is investing $11 billion to build electric vehicles, creating 11,000 jobs across the country.
|
||||
|
||||
GM is making the largest investment in its history—$7 billion to build electric vehicles, creating 4,000 jobs in Michigan.
|
||||
|
||||
All told, we created 369,000 new manufacturing jobs in America just last year.
|
||||
|
||||
Powered by people I’ve met like JoJo Burgess, from generations of union steelworkers from Pittsburgh, who’s here with us tonight.
|
||||
|
||||
As Ohio Senator Sherrod Brown says, “It’s time to bury the label “Rust Belt.”
|
||||
|
||||
It’s time.
|
||||
|
||||
But with all the bright spots in our economy, record job growth and higher wages, too many families are struggling to keep up with the bills.
|
||||
|
||||
Inflation is robbing them of the gains they might otherwise feel.
|
||||
|
||||
I get it. That’s why my top priority is getting prices under control.
|
||||
|
||||
Look, our economy roared back faster than most predicted, but the pandemic meant that businesses had a hard time hiring enough workers to keep up production in their factories.
|
||||
|
||||
The pandemic also disrupted global supply chains.
|
||||
|
||||
When factories close, it takes longer to make goods and get them from the warehouse to the store, and prices go up.
|
||||
|
||||
Look at cars.
|
||||
|
||||
Last year, there weren’t enough semiconductors to make all the cars that people wanted to buy.
|
||||
|
||||
And guess what, prices of automobiles went up.
|
||||
|
||||
So—we have a choice.
|
||||
|
||||
One way to fight inflation is to drive down wages and make Americans poorer.
|
||||
|
||||
I have a better plan to fight inflation.
|
||||
|
||||
Lower your costs, not your wages.
|
||||
|
||||
Make more cars and semiconductors in America.
|
||||
|
||||
More infrastructure and innovation in America.
|
||||
|
||||
More goods moving faster and cheaper in America.
|
||||
|
||||
More jobs where you can earn a good living in America.
|
||||
|
||||
And instead of relying on foreign supply chains, let’s make it in America.
|
||||
|
||||
Economists call it “increasing the productive capacity of our economy.”
|
||||
|
||||
I call it building a better America.
|
||||
|
||||
My plan to fight inflation will lower your costs and lower the deficit.
|
||||
|
||||
17 Nobel laureates in economics say my plan will ease long-term inflationary pressures. Top business leaders and most Americans support my plan. And here’s the plan:
|
||||
|
||||
First – cut the cost of prescription drugs. Just look at insulin. One in ten Americans has diabetes. In Virginia, I met a 13-year-old boy named Joshua Davis.
|
||||
|
||||
He and his Dad both have Type 1 diabetes, which means they need insulin every day. Insulin costs about $10 a vial to make.
|
||||
|
||||
But drug companies charge families like Joshua and his Dad up to 30 times more. I spoke with Joshua’s mom.
|
||||
|
||||
Imagine what it’s like to look at your child who needs insulin and have no idea how you’re going to pay for it.
|
||||
|
||||
What it does to your dignity, your ability to look your child in the eye, to be the parent you expect to be.
|
||||
|
||||
Joshua is here with us tonight. Yesterday was his birthday. Happy birthday, buddy.
|
||||
|
||||
For Joshua, and for the 200,000 other young people with Type 1 diabetes, let’s cap the cost of insulin at $35 a month so everyone can afford it.
|
||||
|
||||
Drug companies will still do very well. And while we’re at it let Medicare negotiate lower prices for prescription drugs, like the VA already does.
|
||||
|
||||
Look, the American Rescue Plan is helping millions of families on Affordable Care Act plans save $2,400 a year on their health care premiums. Let’s close the coverage gap and make those savings permanent.
|
||||
|
||||
Second – cut energy costs for families an average of $500 a year by combatting climate change.
|
||||
|
||||
Let’s provide investments and tax credits to weatherize your homes and businesses to be energy efficient and you get a tax credit; double America’s clean energy production in solar, wind, and so much more; lower the price of electric vehicles, saving you another $80 a month because you’ll never have to pay at the gas pump again.
|
||||
|
||||
Third – cut the cost of child care. Many families pay up to $14,000 a year for child care per child.
|
||||
|
||||
Middle-class and working families shouldn’t have to pay more than 7% of their income for care of young children.
|
||||
|
||||
My plan will cut the cost in half for most families and help parents, including millions of women, who left the workforce during the pandemic because they couldn’t afford child care, to be able to get back to work.
|
||||
|
||||
My plan doesn’t stop there. It also includes home and long-term care. More affordable housing. And Pre-K for every 3- and 4-year-old.
|
||||
|
||||
All of these will lower costs.
|
||||
|
||||
And under my plan, nobody earning less than $400,000 a year will pay an additional penny in new taxes. Nobody.
|
||||
|
||||
The one thing all Americans agree on is that the tax system is not fair. We have to fix it.
|
||||
|
||||
I’m not looking to punish anyone. But let’s make sure corporations and the wealthiest Americans start paying their fair share.
|
||||
|
||||
Just last year, 55 Fortune 500 corporations earned $40 billion in profits and paid zero dollars in federal income tax.
|
||||
|
||||
That’s simply not fair. That’s why I’ve proposed a 15% minimum tax rate for corporations.
|
||||
|
||||
We got more than 130 countries to agree on a global minimum tax rate so companies can’t get out of paying their taxes at home by shipping jobs and factories overseas.
|
||||
|
||||
That’s why I’ve proposed closing loopholes so the very wealthy don’t pay a lower tax rate than a teacher or a firefighter.
|
||||
|
||||
So that’s my plan. It will grow the economy and lower costs for families.
|
||||
|
||||
So what are we waiting for? Let’s get this done. And while you’re at it, confirm my nominees to the Federal Reserve, which plays a critical role in fighting inflation.
|
||||
|
||||
My plan will not only lower costs to give families a fair shot, it will lower the deficit.
|
||||
|
||||
The previous Administration not only ballooned the deficit with tax cuts for the very wealthy and corporations, it undermined the watchdogs whose job was to keep pandemic relief funds from being wasted.
|
||||
|
||||
But in my administration, the watchdogs have been welcomed back.
|
||||
|
||||
We’re going after the criminals who stole billions in relief money meant for small businesses and millions of Americans.
|
||||
|
||||
And tonight, I’m announcing that the Justice Department will name a chief prosecutor for pandemic fraud.
|
||||
|
||||
By the end of this year, the deficit will be down to less than half what it was before I took office.
|
||||
|
||||
The only president ever to cut the deficit by more than one trillion dollars in a single year.
|
||||
|
||||
Lowering your costs also means demanding more competition.
|
||||
|
||||
I’m a capitalist, but capitalism without competition isn’t capitalism.
|
||||
|
||||
It’s exploitation—and it drives up prices.
|
||||
|
||||
When corporations don’t have to compete, their profits go up, your prices go up, and small businesses and family farmers and ranchers go under.
|
||||
|
||||
We see it happening with ocean carriers moving goods in and out of America.
|
||||
|
||||
During the pandemic, these foreign-owned companies raised prices by as much as 1,000% and made record profits.
|
||||
|
||||
Tonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers.
|
||||
|
||||
And as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up.
|
||||
|
||||
That ends on my watch.
|
||||
|
||||
Medicare is going to set higher standards for nursing homes and make sure your loved ones get the care they deserve and expect.
|
||||
|
||||
We’ll also cut costs and keep the economy going strong by giving workers a fair shot, provide more training and apprenticeships, hire them based on their skills not degrees.
|
||||
|
||||
Let’s pass the Paycheck Fairness Act and paid leave.
|
||||
|
||||
Raise the minimum wage to $15 an hour and extend the Child Tax Credit, so no one has to raise a family in poverty.
|
||||
|
||||
Let’s increase Pell Grants and increase our historic support of HBCUs, and invest in what Jill—our First Lady who teaches full-time—calls America’s best-kept secret: community colleges.
|
||||
|
||||
And let’s pass the PRO Act when a majority of workers want to form a union—they shouldn’t be stopped.
|
||||
|
||||
When we invest in our workers, when we build the economy from the bottom up and the middle out together, we can do something we haven’t done in a long time: build a better America.
|
||||
|
||||
For more than two years, COVID-19 has impacted every decision in our lives and the life of the nation.
|
||||
|
||||
And I know you’re tired, frustrated, and exhausted.
|
||||
|
||||
But I also know this.
|
||||
|
||||
Because of the progress we’ve made, because of your resilience and the tools we have, tonight I can say
|
||||
we are moving forward safely, back to more normal routines.
|
||||
|
||||
We’ve reached a new moment in the fight against COVID-19, with severe cases down to a level not seen since last July.
|
||||
|
||||
Just a few days ago, the Centers for Disease Control and Prevention—the CDC—issued new mask guidelines.
|
||||
|
||||
Under these new guidelines, most Americans in most of the country can now be mask free.
|
||||
|
||||
And based on the projections, more of the country will reach that point across the next couple of weeks.
|
||||
|
||||
Thanks to the progress we have made this past year, COVID-19 need no longer control our lives.
|
||||
|
||||
I know some are talking about “living with COVID-19”. Tonight – I say that we will never just accept living with COVID-19.
|
||||
|
||||
We will continue to combat the virus as we do other diseases. And because this is a virus that mutates and spreads, we will stay on guard.
|
||||
|
||||
Here are four common sense steps as we move forward safely.
|
||||
|
||||
First, stay protected with vaccines and treatments. We know how incredibly effective vaccines are. If you’re vaccinated and boosted you have the highest degree of protection.
|
||||
|
||||
We will never give up on vaccinating more Americans. Now, I know parents with kids under 5 are eager to see a vaccine authorized for their children.
|
||||
|
||||
The scientists are working hard to get that done and we’ll be ready with plenty of vaccines when they do.
|
||||
|
||||
We’re also ready with anti-viral treatments. If you get COVID-19, the Pfizer pill reduces your chances of ending up in the hospital by 90%.
|
||||
|
||||
We’ve ordered more of these pills than anyone in the world. And Pfizer is working overtime to get us 1 Million pills this month and more than double that next month.
|
||||
|
||||
And we’re launching the “Test to Treat” initiative so people can get tested at a pharmacy, and if they’re positive, receive antiviral pills on the spot at no cost.
|
||||
|
||||
If you’re immunocompromised or have some other vulnerability, we have treatments and free high-quality masks.
|
||||
|
||||
We’re leaving no one behind or ignoring anyone’s needs as we move forward.
|
||||
|
||||
And on testing, we have made hundreds of millions of tests available for you to order for free.
|
||||
|
||||
Even if you already ordered free tests tonight, I am announcing that you can order more from covidtests.gov starting next week.
|
||||
|
||||
Second – we must prepare for new variants. Over the past year, we’ve gotten much better at detecting new variants.
|
||||
|
||||
If necessary, we’ll be able to deploy new vaccines within 100 days instead of many more months or years.
|
||||
|
||||
And, if Congress provides the funds we need, we’ll have new stockpiles of tests, masks, and pills ready if needed.
|
||||
|
||||
I cannot promise a new variant won’t come. But I can promise you we’ll do everything within our power to be ready if it does.
|
||||
|
||||
Third – we can end the shutdown of schools and businesses. We have the tools we need.
|
||||
|
||||
It’s time for Americans to get back to work and fill our great downtowns again. People working from home can feel safe to begin to return to the office.
|
||||
|
||||
We’re doing that here in the federal government. The vast majority of federal workers will once again work in person.
|
||||
|
||||
Our schools are open. Let’s keep it that way. Our kids need to be in school.
|
||||
|
||||
And with 75% of adult Americans fully vaccinated and hospitalizations down by 77%, most Americans can remove their masks, return to work, stay in the classroom, and move forward safely.
|
||||
|
||||
We achieved this because we provided free vaccines, treatments, tests, and masks.
|
||||
|
||||
Of course, continuing this costs money.
|
||||
|
||||
I will soon send Congress a request.
|
||||
|
||||
The vast majority of Americans have used these tools and may want to again, so I expect Congress to pass it quickly.
|
||||
|
||||
Fourth, we will continue vaccinating the world.
|
||||
|
||||
We’ve sent 475 Million vaccine doses to 112 countries, more than any other nation.
|
||||
|
||||
And we won’t stop.
|
||||
|
||||
We have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life.
|
||||
|
||||
Let’s use this moment to reset. Let’s stop looking at COVID-19 as a partisan dividing line and see it for what it is: A God-awful disease.
|
||||
|
||||
Let’s stop seeing each other as enemies, and start seeing each other for who we really are: Fellow Americans.
|
||||
|
||||
We can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together.
|
||||
|
||||
I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera.
|
||||
|
||||
They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun.
|
||||
|
||||
Officer Mora was 27 years old.
|
||||
|
||||
Officer Rivera was 22.
|
||||
|
||||
Both Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers.
|
||||
|
||||
I spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves.
|
||||
|
||||
I’ve worked on these issues a long time.
|
||||
|
||||
I know what works: Investing in crime preventionand community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety.
|
||||
|
||||
So let’s not abandon our streets. Or choose between safety and equal justice.
|
||||
|
||||
Let’s come together to protect our communities, restore trust, and hold law enforcement accountable.
|
||||
|
||||
That’s why the Justice Department required body cameras, banned chokeholds, and restricted no-knock warrants for its officers.
|
||||
|
||||
That’s why the American Rescue Plan provided $350 Billion that cities, states, and counties can use to hire more police and invest in proven strategies like community violence interruption—trusted messengers breaking the cycle of violence and trauma and giving young people hope.
|
||||
|
||||
We should all agree: The answer is not to Defund the police. The answer is to FUND the police with the resources and training they need to protect our communities.
|
||||
|
||||
I ask Democrats and Republicans alike: Pass my budget and keep our neighborhoods safe.
|
||||
|
||||
And I will keep doing everything in my power to crack down on gun trafficking and ghost guns you can buy online and make at home—they have no serial numbers and can’t be traced.
|
||||
|
||||
And I ask Congress to pass proven measures to reduce gun violence. Pass universal background checks. Why should anyone on a terrorist list be able to purchase a weapon?
|
||||
|
||||
Ban assault weapons and high-capacity magazines.
|
||||
|
||||
Repeal the liability shield that makes gun manufacturers the only industry in America that can’t be sued.
|
||||
|
||||
These laws don’t infringe on the Second Amendment. They save lives.
|
||||
|
||||
The most fundamental right in America is the right to vote – and to have it counted. And it’s under assault.
|
||||
|
||||
In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections.
|
||||
|
||||
We cannot let this happen.
|
||||
|
||||
Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections.
|
||||
|
||||
Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.
|
||||
|
||||
One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.
|
||||
|
||||
And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.
|
||||
|
||||
A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.
|
||||
|
||||
And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system.
|
||||
|
||||
We can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling.
|
||||
|
||||
We’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers.
|
||||
|
||||
We’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster.
|
||||
|
||||
We’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders.
|
||||
|
||||
We can do all this while keeping lit the torch of liberty that has led generations of immigrants to this land—my forefathers and so many of yours.
|
||||
|
||||
Provide a pathway to citizenship for Dreamers, those on temporary status, farm workers, and essential workers.
|
||||
|
||||
Revise our laws so businesses have the workers they need and families don’t wait decades to reunite.
|
||||
|
||||
It’s not only the right thing to do—it’s the economically smart thing to do.
|
||||
|
||||
That’s why immigration reform is supported by everyone from labor unions to religious leaders to the U.S. Chamber of Commerce.
|
||||
|
||||
Let’s get it done once and for all.
|
||||
|
||||
Advancing liberty and justice also requires protecting the rights of women.
|
||||
|
||||
The constitutional right affirmed in Roe v. Wade—standing precedent for half a century—is under attack as never before.
|
||||
|
||||
If we want to go forward—not backward—we must protect access to health care. Preserve a woman’s right to choose. And let’s continue to advance maternal health care in America.
|
||||
|
||||
And for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong.
|
||||
|
||||
As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential.
|
||||
|
||||
While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice.
|
||||
|
||||
And soon, we’ll strengthen the Violence Against Women Act that I first wrote three decades ago. It is important for us to show the nation that we can come together and do big things.
|
||||
|
||||
So tonight I’m offering a Unity Agenda for the Nation. Four big things we can do together.
|
||||
|
||||
First, beat the opioid epidemic.
|
||||
|
||||
There is so much we can do. Increase funding for prevention, treatment, harm reduction, and recovery.
|
||||
|
||||
Get rid of outdated rules that stop doctors from prescribing treatments. And stop the flow of illicit drugs by working with state and local law enforcement to go after traffickers.
|
||||
|
||||
If you’re suffering from addiction, know you are not alone. I believe in recovery, and I celebrate the 23 million Americans in recovery.
|
||||
|
||||
Second, let’s take on mental health. Especially among our children, whose lives and education have been turned upside down.
|
||||
|
||||
The American Rescue Plan gave schools money to hire teachers and help students make up for lost learning.
|
||||
|
||||
I urge every parent to make sure your school does just that. And we can all play a part—sign up to be a tutor or a mentor.
|
||||
|
||||
Children were also struggling before the pandemic. Bullying, violence, trauma, and the harms of social media.
|
||||
|
||||
As Frances Haugen, who is here with us tonight, has shown, we must hold social media platforms accountable for the national experiment they’re conducting on our children for profit.
|
||||
|
||||
It’s time to strengthen privacy protections, ban targeted advertising to children, demand tech companies stop collecting personal data on our children.
|
||||
|
||||
And let’s get all Americans the mental health services they need. More people they can turn to for help, and full parity between physical and mental health care.
|
||||
|
||||
Third, support our veterans.
|
||||
|
||||
Veterans are the best of us.
|
||||
|
||||
I’ve always believed that we have a sacred obligation to equip all those we send to war and care for them and their families when they come home.
|
||||
|
||||
My administration is providing assistance with job training and housing, and now helping lower-income veterans get VA care debt-free.
|
||||
|
||||
Our troops in Iraq and Afghanistan faced many dangers.
|
||||
|
||||
One was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more.
|
||||
|
||||
When they came home, many of the world’s fittest and best trained warriors were never the same.
|
||||
|
||||
Headaches. Numbness. Dizziness.
|
||||
|
||||
A cancer that would put them in a flag-draped coffin.
|
||||
|
||||
I know.
|
||||
|
||||
One of those soldiers was my son Major Beau Biden.
|
||||
|
||||
We don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops.
|
||||
|
||||
But I’m committed to finding out everything we can.
|
||||
|
||||
Committed to military families like Danielle Robinson from Ohio.
|
||||
|
||||
The widow of Sergeant First Class Heath Robinson.
|
||||
|
||||
He was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq.
|
||||
|
||||
Stationed near Baghdad, just yards from burn pits the size of football fields.
|
||||
|
||||
Heath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter.
|
||||
|
||||
But cancer from prolonged exposure to burn pits ravaged Heath’s lungs and body.
|
||||
|
||||
Danielle says Heath was a fighter to the very end.
|
||||
|
||||
He didn’t know how to stop fighting, and neither did she.
|
||||
|
||||
Through her pain she found purpose to demand we do better.
|
||||
|
||||
Tonight, Danielle—we are.
|
||||
|
||||
The VA is pioneering new ways of linking toxic exposures to diseases, already helping more veterans get benefits.
|
||||
|
||||
And tonight, I’m announcing we’re expanding eligibility to veterans suffering from nine respiratory cancers.
|
||||
|
||||
I’m also calling on Congress: pass a law to make sure veterans devastated by toxic exposures in Iraq and Afghanistan finally get the benefits and comprehensive health care they deserve.
|
||||
|
||||
And fourth, let’s end cancer as we know it.
|
||||
|
||||
This is personal to me and Jill, to Kamala, and to so many of you.
|
||||
|
||||
Cancer is the #2 cause of death in America–second only to heart disease.
|
||||
|
||||
Last month, I announced our plan to supercharge
|
||||
the Cancer Moonshot that President Obama asked me to lead six years ago.
|
||||
|
||||
Our goal is to cut the cancer death rate by at least 50% over the next 25 years, turn more cancers from death sentences into treatable diseases.
|
||||
|
||||
More support for patients and families.
|
||||
|
||||
To get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health.
|
||||
|
||||
It’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more.
|
||||
|
||||
ARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s, diabetes, and more.
|
||||
|
||||
A unity agenda for the nation.
|
||||
|
||||
We can do this.
|
||||
|
||||
My fellow Americans—tonight , we have gathered in a sacred space—the citadel of our democracy.
|
||||
|
||||
In this Capitol, generation after generation, Americans have debated great questions amid great strife, and have done great things.
|
||||
|
||||
We have fought for freedom, expanded liberty, defeated totalitarianism and terror.
|
||||
|
||||
And built the strongest, freest, and most prosperous nation the world has ever known.
|
||||
|
||||
Now is the hour.
|
||||
|
||||
Our moment of responsibility.
|
||||
|
||||
Our test of resolve and conscience, of history itself.
|
||||
|
||||
It is in this moment that our character is formed. Our purpose is found. Our future is forged.
|
||||
|
||||
Well I know this nation.
|
||||
|
||||
We will meet the test.
|
||||
|
||||
To protect freedom and liberty, to expand fairness and opportunity.
|
||||
|
||||
We will save democracy.
|
||||
|
||||
As hard as these times have been, I am more optimistic about America today than I have been my whole life.
|
||||
|
||||
Because I see the future that is within our grasp.
|
||||
|
||||
Because I know there is simply nothing beyond our capacity.
|
||||
|
||||
We are the only nation on Earth that has always turned every crisis we have faced into an opportunity.
|
||||
|
||||
The only nation that can be defined by a single word: possibilities.
|
||||
|
||||
So on this night, in our 245th year as a nation, I have come to report on the State of the Union.
|
||||
|
||||
And my report is this: the State of the Union is strong—because you, the American people, are strong.
|
||||
|
||||
We are stronger today than we were a year ago.
|
||||
|
||||
And we will be stronger a year from now than we are today.
|
||||
|
||||
Now is our moment to meet and overcome the challenges of our time.
|
||||
|
||||
And we will, as one people.
|
||||
|
||||
One America.
|
||||
|
||||
The United States of America.
|
||||
|
||||
May God bless you all. May God protect our troops.
|
||||
27
docs/explanation/core_concepts.md
Normal file
27
docs/explanation/core_concepts.md
Normal file
@@ -0,0 +1,27 @@
|
||||
# Core Concepts
|
||||
|
||||
This section goes over the core concepts of LangChain.
|
||||
Understanding these will go a long way in helping you understand the codebase and how to construct chains.
|
||||
|
||||
## PromptTemplates
|
||||
PromptTemplates generically have a `format` method that takes in variables and returns a formatted string.
|
||||
The most simple implementation of this is to have a template string with some variables in it, and then format it with the incoming variables.
|
||||
More complex iterations dynamically construct the template string from few shot examples, etc.
|
||||
|
||||
For a more detailed explanation of how LangChain approaches prompts and prompt templates, see [here](/examples/prompts/prompt_management).
|
||||
|
||||
## LLMs
|
||||
Wrappers around Large Language Models (in particular, the `generate` ability of large language models) are some of the core functionality of LangChain.
|
||||
These wrappers are classes that are callable: they take in an input string, and return the generated output string.
|
||||
|
||||
## Embeddings
|
||||
These classes are very similar to the LLM classes in that they are wrappers around models,
|
||||
but rather than return a string they return an embedding (list of floats). This are particularly useful when
|
||||
implementing semantic search functionality. They expose separate methods for embedding queries versus embedding documents.
|
||||
|
||||
## Vectorstores
|
||||
These are datastores that store documents. They expose a method for passing in a string and finding similar documents.
|
||||
|
||||
## Chains
|
||||
These are pipelines that combine multiple of the above ideas.
|
||||
They vary greatly in complexity and are combination of generic, highly configurable pipelines and more narrow (but usually more complex) pipelines.
|
||||
74
docs/explanation/glossary.md
Normal file
74
docs/explanation/glossary.md
Normal file
@@ -0,0 +1,74 @@
|
||||
# Glossary
|
||||
|
||||
This is a collection of terminology commonly used when developing LLM applications.
|
||||
It contains reference to external papers or sources where the concept was first introduced,
|
||||
as well as to places in LangChain where the concept is used.
|
||||
|
||||
### Chain of Thought Prompting
|
||||
|
||||
A prompting technique used to encourage the model to generate a series of intermediate reasoning steps.
|
||||
A less formal way to induce this behavior is to include “Let’s think step-by-step” in the prompt.
|
||||
|
||||
Resources:
|
||||
- [Chain-of-Thought Paper](https://arxiv.org/pdf/2201.11903.pdf)
|
||||
- [Step-by-Step Paper](https://arxiv.org/abs/2112.00114)
|
||||
|
||||
### Action Plan Generation
|
||||
|
||||
A prompt usage that uses a language model to generate actions to take.
|
||||
The results of these actions can then be fed back into the language model to generate a subsequent action.
|
||||
|
||||
Resources:
|
||||
- [WebGPT Paper](https://arxiv.org/pdf/2112.09332.pdf)
|
||||
- [SayCan Paper](https://say-can.github.io/assets/palm_saycan.pdf)
|
||||
|
||||
### ReAct Prompting
|
||||
|
||||
A prompting technique that combines Chain-of-Thought prompting with action plan generation.
|
||||
This induces the to model to think about what action to take, then take it.
|
||||
|
||||
Resources:
|
||||
- [Paper](https://arxiv.org/pdf/2210.03629.pdf)
|
||||
- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/react.ipynb)
|
||||
|
||||
### Self-ask
|
||||
|
||||
A prompting method that builds on top of chain-of-thought prompting.
|
||||
In this method, the model explicitly asks itself follow-up questions, which are then answered by an external search engine.
|
||||
|
||||
Resources:
|
||||
- [Paper](https://ofir.io/self-ask.pdf)
|
||||
- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/self_ask_with_search.ipynb)
|
||||
|
||||
### Prompt Chaining
|
||||
|
||||
Combining multiple LLM calls together, with the output of one step being the input to the next.
|
||||
|
||||
Resources:
|
||||
- [PromptChainer Paper](https://arxiv.org/pdf/2203.06566.pdf)
|
||||
- [Language Model Cascades](https://arxiv.org/abs/2207.10342)
|
||||
- [ICE Primer Book](https://primer.ought.org/)
|
||||
- [Socratic Models](https://socraticmodels.github.io/)
|
||||
|
||||
### Memetic Proxy
|
||||
|
||||
Encouraging the LLM to respond in a certain way framing the discussion in a context that the model knows of and that will result in that type of response. For example, as a conversation between a student and a teacher.
|
||||
|
||||
Resources:
|
||||
- [Paper](https://arxiv.org/pdf/2102.07350.pdf)
|
||||
|
||||
### Self Consistency
|
||||
|
||||
A decoding strategy that samples a diverse set of reasoning paths and then selects the most consistent answer.
|
||||
Is most effective when combined with Chain-of-thought prompting.
|
||||
|
||||
Resources:
|
||||
- [Paper](https://arxiv.org/pdf/2203.11171.pdf)
|
||||
|
||||
### Inception
|
||||
|
||||
Also called “First Person Instruction”.
|
||||
Encouraging the model to think a certain way by including the start of the model’s response in the prompt.
|
||||
|
||||
Resources:
|
||||
- [Example](https://twitter.com/goodside/status/1583262455207460865?s=20&t=8Hz7XBnK1OF8siQrxxCIGQ)
|
||||
39
docs/getting_started/chains.md
Normal file
39
docs/getting_started/chains.md
Normal file
@@ -0,0 +1,39 @@
|
||||
# Using Chains
|
||||
|
||||
Calling an LLM is a great first step, but it's just the beginning.
|
||||
Normally when you use an LLM in an application, you are not sending user input directly to the LLM.
|
||||
Instead, you are probably taking user input and constructing a prompt, and then sending that to the LLM.
|
||||
|
||||
For example, in the previous example, the text we passed in was hardcoded to ask for a name for a company that made colorful socks.
|
||||
In this imaginary service, what we would want to do is take only the user input describing what the company does, and then format the prompt with that information.
|
||||
|
||||
This is easy to do with LangChain!
|
||||
|
||||
First lets define the prompt:
|
||||
|
||||
```python
|
||||
from langchain.prompts import PromptTemplate
|
||||
|
||||
prompt = PromptTemplate(
|
||||
input_variables=["product"],
|
||||
template="What is a good name for a company that makes {product}?",
|
||||
)
|
||||
```
|
||||
|
||||
We can now create a very simple chain that will take user input, format the prompt with it, and then send it to the LLM:
|
||||
|
||||
```python
|
||||
from langchain.chains import LLMChain
|
||||
chain = LLMChain(llm=llm, prompt=prompt)
|
||||
```
|
||||
|
||||
Now we can run that can only specifying the product!
|
||||
|
||||
```python
|
||||
chain.run("colorful socks")
|
||||
```
|
||||
|
||||
There we go! There's the first chain.
|
||||
|
||||
That is it for the Getting Started example.
|
||||
As a next step, we would suggest checking out the more complex chains in the [Demos section](/examples/demos)
|
||||
37
docs/getting_started/environment.md
Normal file
37
docs/getting_started/environment.md
Normal file
@@ -0,0 +1,37 @@
|
||||
# Setting up your environment
|
||||
|
||||
Using LangChain will usually require integrations with one or more model providers, data stores, apis, etc.
|
||||
There are two components to setting this up, installing the correct python packages and setting the right environment variables.
|
||||
|
||||
## Python packages
|
||||
The python package needed varies based on the integration. See the list of integrations for details.
|
||||
There should also be helpful error messages raised if you try to run an integration and are missing any required python packages.
|
||||
|
||||
## Environment Variables
|
||||
The environment variable needed varies based on the integration. See the list of integrations for details.
|
||||
There should also be helpful error messages raised if you try to run an integration and are missing any required environment variables.
|
||||
|
||||
You can set the environment variable in a few ways.
|
||||
If you are trying to set the environment variable `FOO` to value `bar`, here are the ways you could do so:
|
||||
- From the command line:
|
||||
```
|
||||
export FOO=bar
|
||||
```
|
||||
- From the python notebook/script:
|
||||
```python
|
||||
import os
|
||||
os.environ["FOO"] = "bar"
|
||||
```
|
||||
|
||||
For the Getting Started example, we will be using OpenAI's APIs, so we will first need to install their SDK:
|
||||
|
||||
```
|
||||
pip install openai
|
||||
```
|
||||
|
||||
We will then need to set the environment variable. Let's do this from inside the Jupyter notebook (or Python script).
|
||||
|
||||
```python
|
||||
import os
|
||||
os.environ["OPENAI_API_KEY"] = "..."
|
||||
```
|
||||
11
docs/getting_started/installation.md
Normal file
11
docs/getting_started/installation.md
Normal file
@@ -0,0 +1,11 @@
|
||||
# Installation
|
||||
|
||||
LangChain is available on PyPi, so to it is easily installable with:
|
||||
|
||||
```
|
||||
pip install langchain
|
||||
```
|
||||
|
||||
For more involved installation options, see the [Installation Reference](/installation.md) section.
|
||||
|
||||
That's it! LangChain is now installed. You can now use LangChain from a python script or Jupyter notebook.
|
||||
25
docs/getting_started/llm.md
Normal file
25
docs/getting_started/llm.md
Normal file
@@ -0,0 +1,25 @@
|
||||
# Calling a LLM
|
||||
|
||||
The most basic building block of LangChain is calling an LLM on some input.
|
||||
Let's walk through a simple example of how to do this.
|
||||
For this purpose, let's pretend we are building a service that generates a company name based on what the company makes.
|
||||
|
||||
In order to do this, we first need to import the LLM wrapper.
|
||||
|
||||
```python
|
||||
from langchain.llms import OpenAI
|
||||
```
|
||||
|
||||
We can then initialize the wrapper with any arguments.
|
||||
In this example, we probably want the outputs to be MORE random, so we'll initialize it with a HIGH temperature.
|
||||
|
||||
```python
|
||||
llm = OpenAI(temperature=0.9)
|
||||
```
|
||||
|
||||
We can now call it on some input!
|
||||
|
||||
```python
|
||||
text = "What would be a good company name a company that makes colorful socks?"
|
||||
llm(text)
|
||||
```
|
||||
119
docs/index.rst
Normal file
119
docs/index.rst
Normal file
@@ -0,0 +1,119 @@
|
||||
Welcome to LangChain
|
||||
==========================
|
||||
|
||||
Large language models (LLMs) are emerging as a transformative technology, enabling
|
||||
developers to build applications that they previously could not.
|
||||
But using these LLMs in isolation is often not enough to
|
||||
create a truly powerful app - the real power comes when you are able to
|
||||
combine them with other sources of computation or knowledge.
|
||||
|
||||
This library is aimed at assisting in the development of those types of applications.
|
||||
|
||||
There are three main areas (with a forth coming soon) that LangChain is designed to help with.
|
||||
These are, in increasing order of complexity:
|
||||
1. LLM and Prompt usage
|
||||
2. Chaining LLMs with other tools in a deterministic manner
|
||||
3. Having a router LLM which uses other tools as needed
|
||||
4. (Coming Soon) Memory
|
||||
|
||||
**LLMs and Prompts**
|
||||
|
||||
Calling out to an LLM once is pretty easy, with most of them being behind well documented APIs.
|
||||
However, there are still some challenges going from that to an application running in production that LangChain attempts to address:
|
||||
- Easy switching costs: by exposing a standard interface for all the top LLM providers, LangChain makes it easy to switch from one provider to another, whether it be for production use cases or just for testing stuff out.
|
||||
- Prompt management: managing your prompts is easy when you only have one simple one, but can get tricky when you have a bunch or when they start to get more complex. LangChain provides a standard way for storing, constructing, and referencing prompts.
|
||||
- Prompt optimization: despite the underlying models getting better and better, there is still currently a need for carefully constructing prompts.
|
||||
- More coming soon
|
||||
|
||||
**Chains**
|
||||
|
||||
Using an LLM in isolation is fine for some simple applications, but many more complex ones require chaining LLMs - either with eachother or with other tools.
|
||||
LangChain provides several parts to help with that:
|
||||
- Standard interface for working with Chains
|
||||
- Easy way to construct chains of LLMs
|
||||
- Lots of integrations with other tools that you may want to use in conjunction with LLMs (search, databases, Python REPL, etc)
|
||||
- End-to-end chains for common workflows (database question/answer, recursive summarization, etc)
|
||||
|
||||
**Routing Chains**
|
||||
|
||||
Some applications will require not just a predetermined chain of calls to LLMs/other tools, but potentially an unknown chain that depends on the user input.
|
||||
In these types of chains, there is a "router" LLM chain which has access to a suite of tools.
|
||||
Depending on the user input, the router can then decide which, if any, of these tools to call.
|
||||
To help develop applications like these, LangChain provides:
|
||||
- Standard router and router chain interfaces
|
||||
- Common router LLM chains from literature
|
||||
- Common chains that can be used as tools
|
||||
|
||||
**Memory**
|
||||
Coming soon.
|
||||
|
||||
Documentation Structure
|
||||
=======================
|
||||
The documentation is structured into the following sections:
|
||||
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:caption: Getting Started
|
||||
:name: getting_started
|
||||
|
||||
getting_started/installation.md
|
||||
getting_started/environment.md
|
||||
getting_started/llm.md
|
||||
getting_started/chains.md
|
||||
|
||||
Goes over a simple walk through and tutorial for getting started setting up a simple chain that generates a company name based on what the company makes.
|
||||
Covers installation, environment set up, calling LLMs, and using prompts.
|
||||
Start here if you haven't used LangChain before.
|
||||
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:caption: How-To Examples
|
||||
:name: examples
|
||||
|
||||
examples/demos.rst
|
||||
examples/integrations.rst
|
||||
examples/prompts.rst
|
||||
examples/model_laboratory.ipynb
|
||||
|
||||
More elaborate examples and walk-throughs of particular
|
||||
integrations and use cases. This is the place to look if you have questions
|
||||
about how to integrate certain pieces, or if you want to find examples of
|
||||
common tasks or cool demos.
|
||||
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:caption: Reference
|
||||
:name: reference
|
||||
|
||||
installation.md
|
||||
integrations.md
|
||||
modules/prompt
|
||||
modules/example_selector
|
||||
modules/llms
|
||||
modules/embeddings
|
||||
modules/text_splitter
|
||||
modules/vectorstore
|
||||
modules/chains
|
||||
modules/routing_chains
|
||||
|
||||
|
||||
Full API documentation. This is the place to look if you want to
|
||||
see detailed information about the various classes, methods, and APIs.
|
||||
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 1
|
||||
:caption: Resources
|
||||
:name: resources
|
||||
|
||||
explanation/core_concepts.md
|
||||
explanation/glossary.md
|
||||
Discord <https://discord.gg/6adMQxSpJS>
|
||||
|
||||
Higher level, conceptual explanations of the LangChain components.
|
||||
This is the place to go if you want to increase your high level understanding
|
||||
of the problems LangChain is solving, and how we decided to go about do so.
|
||||
|
||||
24
docs/installation.md
Normal file
24
docs/installation.md
Normal file
@@ -0,0 +1,24 @@
|
||||
# Installation Options
|
||||
|
||||
LangChain is available on PyPi, so to it is easily installable with:
|
||||
|
||||
```
|
||||
pip install langchain
|
||||
```
|
||||
|
||||
That will install the bare minimum requirements of LangChain.
|
||||
A lot of the value of LangChain comes when integrating it with various model providers, datastores, etc.
|
||||
By default, the dependencies needed to do that are NOT installed.
|
||||
However, there are two other ways to install LangChain that do bring in those dependencies.
|
||||
|
||||
To install modules needed for the common LLM providers, run:
|
||||
|
||||
```
|
||||
pip install langchain[llms]
|
||||
```
|
||||
|
||||
To install all modules needed for all integrations, run:
|
||||
|
||||
```
|
||||
pip install langchain[all]
|
||||
```
|
||||
33
docs/integrations.md
Normal file
33
docs/integrations.md
Normal file
@@ -0,0 +1,33 @@
|
||||
# Integration Reference
|
||||
|
||||
Besides the installation of this python package, you will also need to install packages and set environment variables depending on which chains you want to use.
|
||||
|
||||
Note: the reason these packages are not included in the dependencies by default is that as we imagine scaling this package, we do not want to force dependencies that are not needed.
|
||||
|
||||
The following use cases require specific installs and api keys:
|
||||
|
||||
- _OpenAI_:
|
||||
- Install requirements with `pip install openai`
|
||||
- Get an OpenAI api key and either set it as an environment variable (`OPENAI_API_KEY`) or pass it to the LLM constructor as `openai_api_key`.
|
||||
- _Cohere_:
|
||||
- Install requirements with `pip install cohere`
|
||||
- Get a Cohere api key and either set it as an environment variable (`COHERE_API_KEY`) or pass it to the LLM constructor as `cohere_api_key`.
|
||||
- _HuggingFace Hub_
|
||||
- Install requirements with `pip install huggingface_hub`
|
||||
- Get a HuggingFace Hub api token and either set it as an environment variable (`HUGGINGFACEHUB_API_TOKEN`) or pass it to the LLM constructor as `huggingfacehub_api_token`.
|
||||
- _SerpAPI_:
|
||||
- Install requirements with `pip install google-search-results`
|
||||
- Get a SerpAPI api key and either set it as an environment variable (`SERPAPI_API_KEY`) or pass it to the LLM constructor as `serpapi_api_key`.
|
||||
- _NatBot_:
|
||||
- Install requirements with `pip install playwright`
|
||||
- _Wikipedia_:
|
||||
- Install requirements with `pip install wikipedia`
|
||||
- _Elasticsearch_:
|
||||
- Install requirements with `pip install elasticsearch`
|
||||
- Set up Elasticsearch backend. If you want to do locally, [this](https://www.elastic.co/guide/en/elasticsearch/reference/7.17/getting-started.html) is a good guide.
|
||||
- _FAISS_:
|
||||
- Install requirements with `pip install faiss` for Python 3.7 and `pip install faiss-cpu` for Python 3.10+.
|
||||
- _Manifest_:
|
||||
- Install requirements with `pip install manifest-ml` (Note: this is only available in Python 3.8+ currently).
|
||||
|
||||
If you are using the `NLTKTextSplitter` or the `SpacyTextSplitter`, you will also need to install the appropriate models. For example, if you want to use the `SpacyTextSplitter`, you will need to install the `en_core_web_sm` model with `python -m spacy download en_core_web_sm`. Similarly, if you want to use the `NLTKTextSplitter`, you will need to install the `punkt` model with `python -m nltk.downloader punkt`.
|
||||
35
docs/make.bat
Normal file
35
docs/make.bat
Normal file
@@ -0,0 +1,35 @@
|
||||
@ECHO OFF
|
||||
|
||||
pushd %~dp0
|
||||
|
||||
REM Command file for Sphinx documentation
|
||||
|
||||
if "%SPHINXBUILD%" == "" (
|
||||
set SPHINXBUILD=sphinx-build
|
||||
)
|
||||
set SOURCEDIR=.
|
||||
set BUILDDIR=_build
|
||||
|
||||
if "%1" == "" goto help
|
||||
|
||||
%SPHINXBUILD% >NUL 2>NUL
|
||||
if errorlevel 9009 (
|
||||
echo.
|
||||
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
|
||||
echo.installed, then set the SPHINXBUILD environment variable to point
|
||||
echo.to the full path of the 'sphinx-build' executable. Alternatively you
|
||||
echo.may add the Sphinx directory to PATH.
|
||||
echo.
|
||||
echo.If you don't have Sphinx installed, grab it from
|
||||
echo.http://sphinx-doc.org/
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
|
||||
goto end
|
||||
|
||||
:help
|
||||
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
|
||||
|
||||
:end
|
||||
popd
|
||||
7
docs/modules/chains.rst
Normal file
7
docs/modules/chains.rst
Normal file
@@ -0,0 +1,7 @@
|
||||
:mod:`langchain.chains`
|
||||
=======================
|
||||
|
||||
.. automodule:: langchain.chains
|
||||
:members:
|
||||
:undoc-members:
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user