Add Tqdm to eval wait

.github/CONTRIBUTING.md

@@ -3,4 +3,319 @@
 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://python.langchain.com/docs/contributing/).
+## 🗺️ Guidelines
+
+### 👩‍💻 Contributing Code
+
+To contribute to this project, please follow the ["fork and pull request"](https://docs.github.com/en/get-started/quickstart/contributing-to-projects) workflow.
+Please do not try to push directly to this repo unless you are a maintainer.
+
+Please follow the checked-in pull request template when opening pull requests. Note related issues and tag relevant
+maintainers.
+
+Pull requests cannot land without passing the formatting, linting, and testing checks first. See [Testing](#testing) and
+[Formatting and Linting](#formatting-and-linting) for how to run these checks locally.
+
+It's essential that we maintain great documentation and testing. If you:
+- Fix a bug
+  - Add a relevant unit or integration test when possible. These live in `tests/unit_tests` and `tests/integration_tests`.
+- Make an improvement
+  - Update any affected example notebooks and documentation. These live in `docs`.
+  - Update unit and integration tests when relevant.
+- Add a feature
+  - Add a demo notebook in `docs/modules`.
+  - Add unit and integration tests.
+
+We are a small, progress-oriented team. If there's something you'd like to add or change, opening a pull request is the
+best way to get our attention.
+
+### 🚩GitHub Issues
+
+Our [issues](https://github.com/langchain-ai/langchain/issues) page is kept up to date with bugs, improvements, and feature requests.
+
+There is a taxonomy of labels to help with sorting and discovery of issues of interest. Please use these to help organize issues.
+
+If you start working on an issue, please assign it to yourself.
+
+If you are adding an issue, please try to keep it focused on a single, modular bug/improvement/feature.
+If two issues are related, or blocking, please link them rather than combining them.
+
+We will try to keep these issues as up-to-date as possible, though
+with the rapid rate of development in this field some may get out of date.
+If you notice this happening, please let us know.
+
+### 🙋Getting Help
+
+Our goal is to have the simplest developer setup possible. Should you experience any difficulty getting setup, please
+contact a maintainer! Not only do we want to help get you unblocked, but we also want to make sure that the process is
+smooth for future contributors.
+
+In a similar vein, we do enforce certain linting, formatting, and documentation standards in the codebase.
+If you are finding these difficult (or even just annoying) to work with, feel free to contact a maintainer for help -
+we do not want these to get in the way of getting good code into the codebase.
+
+## 🚀 Quick Start
+
+This quick start guide explains how to run the repository locally.
+For a [development container](https://containers.dev/), see the [.devcontainer folder](https://github.com/langchain-ai/langchain/tree/master/.devcontainer).
+
+### Dependency Management: Poetry and other env/dependency managers
+
+This project utilizes [Poetry](https://python-poetry.org/) v1.6.1+ as a dependency manager.
+
+❗Note: *Before installing Poetry*, if you use `Conda`, create and activate a new Conda env (e.g. `conda create -n langchain python=3.9`)
+
+Install Poetry: **[documentation on how to install it](https://python-poetry.org/docs/#installation)**.
+
+❗Note: If you use `Conda` or `Pyenv` as your environment/package manager, after installing Poetry,
+tell Poetry to use the virtualenv python environment (`poetry config virtualenvs.prefer-active-python true`)
+
+### Core vs. Experimental
+
+This repository contains two separate projects:
+- `langchain`: core langchain code, abstractions, and use cases.
+- `langchain.experimental`: see the [Experimental README](https://github.com/langchain-ai/langchain/tree/master/libs/experimental/README.md) for more information.
+
+Each of these has its own development environment. Docs are run from the top-level makefile, but development
+is split across separate test & release flows.
+
+For this quickstart, start with langchain core:
+
+```bash
+cd libs/langchain
+```
+
+### Local Development Dependencies
+
+Install langchain development requirements (for running langchain, running examples, linting, formatting, tests, and coverage):
+
+```bash
+poetry install --with test
+```
+
+Then verify dependency installation:
+
+```bash
+make test
+```
+
+If the tests don't pass, you may need to pip install additional dependencies, such as `numexpr` and `openapi_schema_pydantic`.
+
+If during installation you receive a `WheelFileValidationError` for `debugpy`, please make sure you are running
+Poetry v1.6.1+. This bug was present in older versions of Poetry (e.g. 1.4.1) and has been resolved in newer releases.
+If you are still seeing this bug on v1.6.1, you may also try disabling "modern installation"
+(`poetry config installer.modern-installation false`) and re-installing requirements.
+See [this `debugpy` issue](https://github.com/microsoft/debugpy/issues/1246) for more details.
+
+### Testing
+
+_some test dependencies are optional; see section about optional dependencies_.
+
+Unit tests cover modular logic that does not require calls to outside APIs.
+If you add new logic, please add a unit test.
+
+To run unit tests:
+
+```bash
+make test
+```
+
+To run unit tests in Docker:
+
+```bash
+make docker_tests
+```
+
+There are also [integration tests and code-coverage](https://github.com/langchain-ai/langchain/tree/master/libs/langchain/tests/README.md) available.
+
+### Formatting and Linting
+
+Run these locally before submitting a PR; the CI system will check also.
+
+#### Code Formatting
+
+Formatting for this project is done via [ruff](https://docs.astral.sh/ruff/rules/).
+
+To run formatting for docs, cookbook and templates:
+
+```bash
+make format
+```
+
+To run formatting for a library, run the same command from the relevant library directory:
+
+```bash
+cd libs/{LIBRARY}
+make format
+```
+
+Additionally, you can run the formatter only on the files that have been modified in your current branch as compared to the master branch using the format_diff command:
+
+```bash
+make format_diff
+```
+
+This is especially useful when you have made changes to a subset of the project and want to ensure your changes are properly formatted without affecting the rest of the codebase.
+
+#### Linting
+
+Linting for this project is done via a combination of [ruff](https://docs.astral.sh/ruff/rules/) and [mypy](http://mypy-lang.org/).
+
+To run linting for docs, cookbook and templates:
+
+```bash
+make lint
+```
+
+To run linting for a library, run the same command from the relevant library directory:
+
+```bash
+cd libs/{LIBRARY}
+make lint
+```
+
+In addition, you can run the linter only on the files that have been modified in your current branch as compared to the master branch using the lint_diff command:
+
+```bash
+make lint_diff
+```
+
+This can be very helpful when you've made changes to only certain parts of the project and want to ensure your changes meet the linting standards without having to check the entire codebase.
+
+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.
+
+#### Spellcheck
+
+Spellchecking for this project is done via [codespell](https://github.com/codespell-project/codespell).
+Note that `codespell` finds common typos, so it could have false-positive (correctly spelled but rarely used) and false-negatives (not finding misspelled) words.
+
+To check spelling for this project:
+
+```bash
+make spell_check
+```
+
+To fix spelling in place:
+
+```bash
+make spell_fix
+```
+
+If codespell is incorrectly flagging a word, you can skip spellcheck for that word by adding it to the codespell config in the `pyproject.toml` file.
+
+```python
+[tool.codespell]
+...
+# Add here:
+ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure'
+```
+
+## Working with Optional Dependencies
+
+Langchain relies heavily on optional dependencies to keep the Langchain package lightweight.
+
+If you're adding a new dependency to Langchain, assume that it will be an optional dependency, and
+that most users won't have it installed.
+
+Users who do not have the dependency installed should be able to **import** your code without
+any side effects (no warnings, no errors, no exceptions).
+
+To introduce the dependency to the pyproject.toml file correctly, please do the following:
+
+1. Add the dependency to the main group as an optional dependency
+  ```bash
+  poetry add --optional [package_name]
+  ```
+2. Open pyproject.toml and add the dependency to the `extended_testing` extra
+3. Relock the poetry file to update the extra.
+  ```bash
+  poetry lock --no-update
+  ```
+4. Add a unit test that the very least attempts to import the new code. Ideally, the unit
+test makes use of lightweight fixtures to test the logic of the code.
+5. Please use the `@pytest.mark.requires(package_name)` decorator for any tests that require the dependency.
+
+## Adding a Jupyter Notebook
+
+If you are adding a Jupyter Notebook example, you'll want to install the optional `dev` dependencies.
+
+To install dev dependencies:
+
+```bash
+poetry install --with dev
+```
+
+Launch a notebook:
+
+```bash
+poetry run jupyter notebook
+```
+
+When you run `poetry install`, the `langchain` package is installed as editable in the virtualenv, so your new logic can be imported into the notebook.
+
+## Documentation
+
+While the code is split between `langchain` and `langchain.experimental`, the documentation is one holistic thing.
+This covers how to get started contributing to documentation.
+
+From the top-level of this repo, install documentation dependencies:
+
+```bash
+poetry install
+```
+
+### Contribute Documentation
+
+The docs directory contains Documentation and API Reference.
+
+Documentation is built using [Docusaurus 2](https://docusaurus.io/).
+
+API Reference 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.
+
+### Build Documentation Locally
+
+In the following commands, the prefix `api_` indicates that those are operations for the API Reference.
+
+Before building the documentation, it is always a good idea to clean the build directory:
+
+```bash
+make docs_clean
+make api_docs_clean
+```
+
+Next, you can build the documentation as outlined below:
+
+```bash
+make docs_build
+make api_docs_build
+```
+
+Finally, run the link checker to ensure all links are valid:
+
+```bash
+make docs_linkcheck
+make api_docs_linkcheck
+```
+
+### Verify Documentation changes
+
+After pushing documentation changes to the repository, you can preview and verify that the changes are
+what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page.
+This will take you to a preview of the documentation changes.
+This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).
+
+## 🏭 Release Process
+
+As of now, LangChain has an ad hoc release process: releases are cut with high frequency by
+a developer and published to [PyPI](https://pypi.org/project/langchain/).
+
+LangChain follows the [semver](https://semver.org/) versioning standard. However, as pre-1.0 software,
+even patch releases may contain [non-backwards-compatible changes](https://semver.org/#spec-item-4).
+
+### 🌟 Recognition
+
+If your contribution has made its way into a release, we will want to give you credit on Twitter (only if you want though)!
+If you have a Twitter account you would like us to mention, please let us know in the PR or through another means.

.github/DISCUSSION_TEMPLATE/q-a.yml

@@ -1,122 +0,0 @@
-labels: [Question]
-body:
-  - type: markdown
-    attributes:
-      value: |
-        Thanks for your interest in 🦜️🔗 LangChain!
-
-        Please follow these instructions, fill every question, and do every step. 🙏
-        
-        We're asking for this because answering questions and solving problems in GitHub takes a lot of time --
-        this is time that we cannot spend on adding new features, fixing bugs, write documentation or reviewing pull requests.
-
-        By asking questions in a structured way (following this) it will be much easier to help you.
-
-        And there's a high chance that you will find the solution along the way and you won't even have to submit it and wait for an answer. 😎
-
-        As there are too many questions, we will **DISCARD** and close the incomplete ones. 
-        
-        That will allow us (and others) to focus on helping people like you that follow the whole process. 🤓
-        
-        Relevant links to check before opening a question to see if your question has already been answered, fixed or
-        if there's another way to solve your problem:
-        
-        [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        [API Reference](https://api.python.langchain.com/en/stable/),
-        [GitHub search](https://github.com/langchain-ai/langchain),
-        [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
-        [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
-        [LangChain ChatBot](https://chat.langchain.com/)
-  - type: checkboxes
-    id: checks
-    attributes:
-      label: Checked other resources
-      description: Please confirm and check all the following options.
-      options:
-        - label: I added a very descriptive title to this question.
-          required: true
-        - label: I searched the LangChain documentation with the integrated search.
-          required: true
-        - label: I used the GitHub search to find a similar question and didn't find it.
-          required: true
-  - type: checkboxes
-    id: help
-    attributes:
-      label: Commit to Help
-      description: |
-        After submitting this, I commit to one of:
-
-          * Read open questions until I find 2 where I can help someone and add a comment to help there.
-          * I already hit the "watch" button in this repository to receive notifications and I commit to help at least 2 people that ask questions in the future.
-          * Once my question is answered, I will mark the answer as "accepted".
-      options:
-        - label: I commit to help with one of those options 👆
-          required: true
-  - type: textarea
-    id: example
-    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!** 
-        
-        * 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 ```).
-        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
-        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
-
-      placeholder: |
-        from langchain_core.runnables import RunnableLambda
-
-        def bad_code(inputs) -> int:
-          raise NotImplementedError('For demo purpose')
-        
-          chain = RunnableLambda(bad_code)
-          chain.invoke('Hello!')
-      render: python
-    validations:
-      required: true
-  - type: textarea
-    id: description
-    attributes:
-      label: Description
-      description: |
-        What is the problem, question, or error?
-
-        Write a short description explaining 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. 
-        
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
-        
-        python -m langchain_core.sys_info
-      placeholder: |
-        "pip freeze | grep langchain"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
-        python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
-    validations:
-      required: true

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -1,118 +1,106 @@
 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 GitHub Discussions.
+description: Submit a bug report to help us improve LangChain. To report a security issue, please instead use the security option below.
 labels: ["02 Bug Report"]
 body:
   - type: markdown
     attributes:
       value: >
-        Thank you for taking the time to file a bug report. 
-        
-        Use this to report bugs in LangChain. 
-        
-        If you're not certain that your issue is due to a bug in LangChain, please use [GitHub Discussions](https://github.com/langchain-ai/langchain/discussions)
-        to ask for help with your issue.
-        
-        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 documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        [API Reference](https://api.python.langchain.com/en/stable/),
-        [GitHub search](https://github.com/langchain-ai/langchain),
-        [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
-        [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
-        [LangChain ChatBot](https://chat.langchain.com/)
-  - type: checkboxes
-    id: checks
+        Thank you for taking the time to file a bug report. Before creating a new
+        issue, please make sure to take a few moments to check the issue tracker
+        for existing issues about the bug.
+
+  - type: textarea
+    id: system-info
     attributes:
-      label: Checked other resources
-      description: Please confirm and check all the following options.
+      label: System Info
+      description: Please share your system info with us.
+      placeholder: LangChain version, platform, python version, ...
+    validations:
+      required: true
+
+  - type: textarea
+    id: who-can-help
+    attributes:
+      label: Who can help?
+      description: |
+        Your issue will be replied to more quickly if you can figure out the right person to tag with @
+        If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
+
+        The core maintainers strive to read all issues, but tagging them will help them prioritize.
+
+        Please tag fewer than 3 people.
+
+        @hwchase17 - project lead
+
+        Tracing / Callbacks
+        - @agola11
+
+        Async
+        - @agola11
+
+        DataLoader Abstractions
+        - @eyurtsev
+
+        LLM/Chat Wrappers
+        - @hwchase17
+        - @agola11
+
+        Tools / Toolkits
+        - ...
+
+      placeholder: "@Username ..."
+
+  - type: checkboxes
+    id: information-scripts-examples
+    attributes:
+      label: Information
+      description: "The problem arises when using:"
       options:
-        - label: I added a very descriptive title to this issue.
-          required: true
-        - label: I searched the LangChain documentation with the integrated search.
-          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 official example notebooks/scripts"
+        - label: "My own modified scripts"
+
+  - type: checkboxes
+    id: related-components
+    attributes:
+      label: Related Components
+      description: "Select the components related to the issue (if applicable):"
+      options:
+        - label: "LLMs/Chat Models"
+        - label: "Embedding Models"
+        - label: "Prompts / Prompt Templates / Prompt Selectors"
+        - label: "Output Parsers"
+        - label: "Document Loaders"
+        - label: "Vector Stores / Retrievers"
+        - label: "Memory"
+        - label: "Agents / Agent Executors"
+        - label: "Tools / Toolkits"
+        - label: "Chains"
+        - label: "Callbacks/Tracing"
+        - label: "Async"
+
   - type: textarea
     id: reproduction
     validations:
       required: true
     attributes:
-      label: Example Code
+      label: Reproduction
       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!** 
-        
-        * 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 ```).
-        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
-        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
+        Please provide a [code sample](https://stackoverflow.com/help/minimal-reproducible-example) that reproduces the problem you ran into. It can be a Colab link or just a code snippet.
+        If you have code snippets, error messages, stack traces please provide them here as well.
+        Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
+        Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
 
       placeholder: |
-        The following code: 
-        
-        ```python
-        from langchain_core.runnables import RunnableLambda
+        Steps to reproduce the behavior:
+
+          1.
+          2.
+          3.
 
-        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.
+    id: expected-behavior
     validations:
       required: true
-  - type: textarea
-    id: system-info
     attributes:
-      label: System Info
-      description: |
-        Please share your system info with us. 
-        
-        "pip freeze | grep langchain" 
-        platform (windows / linux / mac)
-        python version
-        
-        OR if you're on a recent version of langchain-core you can paste the output of:
-        
-        python -m langchain_core.sys_info
-      placeholder: |
-        "pip freeze | grep langchain"
-        platform
-        python version
-        
-        Alternatively, if you're on a recent version of langchain-core you can paste the output of:
-        
-        python -m langchain_core.sys_info
-        
-        These will only surface LangChain packages, don't forget to include any other relevant
-        packages you're using (if you're not sure what's relevant, you can paste the entire output of `pip freeze`).
-    validations:
-      required: true
+      label: Expected behavior
+      description: "A clear and concise description of what you would expect to happen."

.github/ISSUE_TEMPLATE/config.yml

@@ -1,15 +1,6 @@
-blank_issues_enabled: false
+blank_issues_enabled: true
 version: 2.1
 contact_links:
-  - name: 🤔 Question or Problem
-    about: Ask a question or ask about a problem in GitHub Discussions.
-    url: https://www.github.com/langchain-ai/langchain/discussions/categories/q-a
   - name: Discord
     url: https://discord.gg/6adMQxSpJS
     about: General community discussions
-  - name: Feature Request
-    url: https://www.github.com/langchain-ai/langchain/discussions/categories/ideas
-    about: Suggest a feature or an idea
-  - name: Show and tell
-    about: Show what you built with LangChain
-    url: https://www.github.com/langchain-ai/langchain/discussions/categories/show-and-tell

.github/ISSUE_TEMPLATE/documentation.yml

@@ -4,45 +4,13 @@ title: "DOC: <Please write a comprehensive title after the 'DOC: ' prefix>"
 labels: [03 - Documentation]
 
 body:
-- type: markdown
-  attributes:
-    value: >
-      Thank you for taking the time to report an issue in the documentation.
-      
-      Only report issues with documentation here, explain if there are
-      any missing topics or if you found a mistake in the documentation.
-      
-      Do **NOT** use this to ask usage questions or reporting issues with your code.
-      
-      If you have usage questions or need help solving some problem, 
-      please use [GitHub Discussions](https://github.com/langchain-ai/langchain/discussions).
-      
-      If you're in the wrong place, here are some helpful links to find a better
-      place to ask your question:
-      
-      [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-      [API Reference](https://api.python.langchain.com/en/stable/),
-      [GitHub search](https://github.com/langchain-ai/langchain),
-      [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
-      [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
-      [LangChain ChatBot](https://chat.langchain.com/)
-- type: checkboxes
-  id: checks
-  attributes:
-    label: Checklist
-    description: Please confirm and check all the following options.
-    options:
-      - label: I added a very descriptive title to this issue.
-        required: true
-      - label: I included a link to the documentation page I am referring to (if applicable).
-        required: true
 - type: textarea
   attributes: 
     label: "Issue with current documentation:"
     description: >
       Please make sure to leave a reference to the document/code you're
-      referring to. Feel free to include names of classes, functions, methods
-      or concepts you'd like to see documented more.
+      referring to.
+
 - type: textarea
   attributes:
     label: "Idea or request for content:"

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -1,17 +1,7 @@
-labels: [idea]
+name: "\U0001F680 Feature request"
+description: Submit a proposal/request for a new LangChain feature
+labels: ["02 Feature Request"]
 body:
-  - type: checkboxes
-    id: checks
-    attributes:
-      label: Checked
-      description: Please confirm and check all the following options.
-      options:
-        - label: I searched existing ideas and did not find a similar one
-          required: true
-        - label: I added a very descriptive title
-          required: true
-        - label: I've clearly described the feature request and motivation for it
-          required: true
   - type: textarea
     id: feature-request
     validations:
@@ -20,6 +10,7 @@ body:
       label: Feature request
       description: |
         A clear and concise description of the feature proposal. Please provide links to any relevant GitHub repos, papers, or other resources if relevant.
+
   - type: textarea
     id: motivation
     validations:
@@ -28,11 +19,12 @@ body:
       label: Motivation
       description: |
         Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too.
+
   - type: textarea
-    id: proposal
+    id: contribution
     validations:
-      required: false
+      required: true
     attributes:
-      label: Proposal (If applicable)
+      label: Your contribution
       description: |
-        If you would like to propose a solution, please describe it here. 
+        Is there any way that you could help, e.g. by submitting a PR? Make sure to read the CONTRIBUTING.MD [readme](https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md)

.github/ISSUE_TEMPLATE/other.yml

@@ -0,0 +1,18 @@
+name: Other Issue
+description: Raise an issue that wouldn't be covered by the other templates.
+title: "Issue: <Please write a comprehensive title after the 'Issue: ' prefix>"
+labels: [04 - Other]
+
+body:
+  - type: textarea
+    attributes:
+      label: "Issue you'd like to raise."
+      description: >
+        Please describe the issue you'd like to raise as clearly as possible.
+        Make sure to include any relevant links or references.
+
+  - type: textarea
+    attributes:
+      label: "Suggestion:"
+      description: >
+        Please outline a suggestion to improve the issue here.

.github/ISSUE_TEMPLATE/privileged.yml

@@ -1,25 +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: |
-        Thanks for your interest in LangChain! 🚀
-        
-        If you are not a LangChain maintainer or were not asked directly by a maintainer to create an issue, then please start the conversation in a [Question in GitHub Discussions](https://github.com/langchain-ai/langchain/discussions/categories/q-a) instead.
-        
-        You are a LangChain maintainer if you maintain any of the packages inside of the LangChain repository 
-        or are a regular contributor to LangChain with previous merged merged pull requests.
-  - 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.

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,24 +1,20 @@
-Thank you for contributing to LangChain!
+<!-- Thank you for contributing to LangChain!
 
-Checklist:
+Replace this entire comment with:
+  - **Description:** a description of the change, 
+  - **Issue:** the issue # it fixes (if applicable),
+  - **Dependencies:** any dependencies required for this change,
+  - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below),
+  - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out!
 
-- [ ] PR title: Please title your PR "package: description", where "package" is whichever of langchain, community, core, experimental, etc. is being modified. Use "docs: ..." for purely docs changes, "templates: ..." for template changes, "infra: ..." for CI changes.
-  - Example: "community: add foobar LLM"
-- [ ] PR message: **Delete this entire template message** and replace it with the following bulleted list
-    - **Description:** a description of the change
-    - **Issue:** the issue # it fixes, if applicable
-    - **Dependencies:** any dependencies required for this change
-    - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out!
-- [ ] Pass lint and test: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified to check that you're passing lint and testing. See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/
-- [ ] Add tests and docs: If you're adding a new integration, please include
+Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally.
+
+See contribution guidelines for more information on how to write/run tests, lint, etc: 
+https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
+
+If you're adding a new integration, please include:
   1. a test for the integration, preferably unit tests that do not rely on network access,
-  2. an example notebook showing its use. It lives in `docs/docs/integrations` directory.
+  2. an example notebook showing its use. It lives in `docs/extras` directory.
 
-Additional guidelines:
-- Make sure optional dependencies are imported within a function.
-- Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests.
-- Most PRs should not touch more than one package.
-- Changes should be backwards compatible.
-- If you are adding something to community, do not re-import it in langchain.
-
-If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, hwchase17.
+If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17.
+ -->

.github/actions/poetry_setup/action.yml

@@ -26,13 +26,12 @@ inputs:
 runs:
   using: composite
   steps:
-    - uses: actions/setup-python@v5
+    - uses: actions/setup-python@v4
       name: Setup python ${{ inputs.python-version }}
-      id: setup-python
       with:
         python-version: ${{ inputs.python-version }}
 
-    - uses: actions/cache@v4
+    - uses: actions/cache@v3
       id: cache-bin-poetry
       name: Cache Poetry binary - Python ${{ inputs.python-version }}
       env:
@@ -75,11 +74,10 @@ runs:
       env:
         POETRY_VERSION: ${{ inputs.poetry-version }}
         PYTHON_VERSION: ${{ inputs.python-version }}
-      # Install poetry using the python version installed by setup-python step.
-      run: pipx install "poetry==$POETRY_VERSION" --python '${{ steps.setup-python.outputs.python-path }}' --verbose
+      run: pipx install "poetry==$POETRY_VERSION" --python "python$PYTHON_VERSION" --verbose
 
     - name: Restore pip and poetry cached dependencies
-      uses: actions/cache@v4
+      uses: actions/cache@v3
       env:
         SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4"
         WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}

.github/scripts/check_diff.py

@@ -1,50 +0,0 @@
-import json
-import sys
-import os
-
-LANGCHAIN_DIRS = {
-    "libs/core",
-    "libs/langchain",
-    "libs/experimental",
-    "libs/community",
-}
-
-if __name__ == "__main__":
-    files = sys.argv[1:]
-    dirs_to_run = set()
-
-    if len(files) == 300:
-        # max diff length is 300 files - there are likely files missing
-        raise ValueError("Max diff reached. Please manually run CI on changed libs.")
-
-    for file in files:
-        if any(
-            file.startswith(dir_)
-            for dir_ in (
-                ".github/workflows",
-                ".github/tools",
-                ".github/actions",
-                "libs/core",
-                ".github/scripts/check_diff.py",
-            )
-        ):
-            dirs_to_run.update(LANGCHAIN_DIRS)
-        elif "libs/community" in file:
-            dirs_to_run.update(
-                ("libs/community", "libs/langchain", "libs/experimental")
-            )
-        elif "libs/partners" in file:
-            partner_dir = file.split("/")[2]
-            if os.path.isdir(f"libs/partners/{partner_dir}"):
-                dirs_to_run.add(f"libs/partners/{partner_dir}")
-            # Skip if the directory was deleted
-        elif "libs/langchain" in file:
-            dirs_to_run.update(("libs/langchain", "libs/experimental"))
-        elif "libs/experimental" in file:
-            dirs_to_run.add("libs/experimental")
-        elif file.startswith("libs/"):
-            dirs_to_run.update(LANGCHAIN_DIRS)
-        else:
-            pass
-    json_output = json.dumps(list(dirs_to_run))
-    print(f"dirs-to-run={json_output}")  # noqa: T201

.github/scripts/get_min_versions.py

@@ -1,67 +0,0 @@
-import sys
-
-import tomllib
-from packaging.version import parse as parse_version
-import re
-
-MIN_VERSION_LIBS = ["langchain-core", "langchain-community", "langchain"]
-
-
-def get_min_version(version: str) -> str:
-    # case ^x.x.x
-    _match = re.match(r"^\^(\d+(?:\.\d+){0,2})$", version)
-    if _match:
-        return _match.group(1)
-
-    # case >=x.x.x,<y.y.y
-    _match = re.match(r"^>=(\d+(?:\.\d+){0,2}),<(\d+(?:\.\d+){0,2})$", version)
-    if _match:
-        _min = _match.group(1)
-        _max = _match.group(2)
-        assert parse_version(_min) < parse_version(_max)
-        return _min
-
-    # case x.x.x
-    _match = re.match(r"^(\d+(?:\.\d+){0,2})$", version)
-    if _match:
-        return _match.group(1)
-
-    raise ValueError(f"Unrecognized version format: {version}")
-
-
-def get_min_version_from_toml(toml_path: str):
-    # Parse the TOML file
-    with open(toml_path, "rb") as file:
-        toml_data = tomllib.load(file)
-
-    # Get the dependencies from tool.poetry.dependencies
-    dependencies = toml_data["tool"]["poetry"]["dependencies"]
-
-    # Initialize a dictionary to store the minimum versions
-    min_versions = {}
-
-    # Iterate over the libs in MIN_VERSION_LIBS
-    for lib in MIN_VERSION_LIBS:
-        # Check if the lib is present in the dependencies
-        if lib in dependencies:
-            # Get the version string
-            version_string = dependencies[lib]
-
-            # Use parse_version to get the minimum supported version from version_string
-            min_version = get_min_version(version_string)
-
-            # Store the minimum version in the min_versions dictionary
-            min_versions[lib] = min_version
-
-    return min_versions
-
-
-# Get the TOML file path from the command line argument
-toml_file = sys.argv[1]
-
-# Call the function to get the minimum versions
-min_versions = get_min_version_from_toml(toml_file)
-
-print(
-    " ".join([f"{lib}=={version}" for lib, version in min_versions.items()])
-)  # noqa: T201

.github/workflows/_all_ci.yml

@@ -1,110 +0,0 @@
----
-name: langchain CI
-
-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: choice
-        default: 'libs/langchain'
-        options:
-        - libs/langchain
-        - libs/core
-        - libs/experimental
-        - libs/community
-
-
-# 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 }}-${{ inputs.working-directory }}
-  cancel-in-progress: true
-
-env:
-  POETRY_VERSION: "1.7.1"
-
-jobs:
-  lint:
-    name: "-"
-    uses: ./.github/workflows/_lint.yml
-    with:
-      working-directory: ${{ inputs.working-directory }}
-    secrets: inherit
-
-  test:
-    name: "-"
-    uses: ./.github/workflows/_test.yml
-    with:
-      working-directory: ${{ inputs.working-directory }}
-    secrets: inherit
-
-  compile-integration-tests:
-    name: "-"
-    uses: ./.github/workflows/_compile_integration_test.yml
-    with:
-      working-directory: ${{ inputs.working-directory }}
-    secrets: inherit
-
-  dependencies:
-    name: "-"
-    uses: ./.github/workflows/_dependencies.yml
-    with:
-      working-directory: ${{ inputs.working-directory }}
-    secrets: inherit
-
-  extended-tests:
-    name: "make extended_tests #${{ matrix.python-version }}"
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version:
-          - "3.8"
-          - "3.9"
-          - "3.10"
-          - "3.11"
-    defaults:
-      run:
-        working-directory: ${{ inputs.working-directory }}
-    if: ${{ ! startsWith(inputs.working-directory, 'libs/partners/') }}
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
-        with:
-          python-version: ${{ matrix.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: extended
-
-      - name: Install dependencies
-        shell: bash
-        run: |
-          echo "Running extended tests, installing dependencies with poetry..."
-          poetry install -E extended_testing --with test
-
-      - name: Run extended tests
-        run: make extended_tests
-
-      - name: Ensure the tests did not create any additional files
-        shell: bash
-        run: |
-          set -eu
-
-          STATUS="$(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'

.github/workflows/_compile_integration_test.yml

@@ -7,9 +7,13 @@ on:
         required: true
         type: string
         description: "From which folder this pipeline executes"
+      langchain-core-location:
+        required: false
+        type: string
+        description: "Relative path to the langchain core library folder"
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
 
 jobs:
   build:
@@ -24,7 +28,7 @@ jobs:
           - "3.9"
           - "3.10"
           - "3.11"
-    name: "poetry run pytest -m compile tests/integration_tests #${{ matrix.python-version }}"
+    name: Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v4
 
@@ -38,7 +42,15 @@ jobs:
 
       - name: Install integration dependencies
         shell: bash
-        run: poetry install --with=test_integration,test
+        run: poetry install --with=test_integration
+
+      - name: Install langchain core editable
+        working-directory: ${{ inputs.working-directory }}
+        if: ${{ inputs.langchain-core-location }}
+        env:
+          LANGCHAIN_CORE_LOCATION: ${{ inputs.langchain-core-location }}
+        run: |
+          poetry run pip install -e "$LANGCHAIN_CORE_LOCATION"
 
       - name: Check integration tests compile
         shell: bash

.github/workflows/_integration_test.yml

@@ -1,82 +0,0 @@
-name: Integration tests
-
-on:
-  workflow_dispatch:
-    inputs:
-      working-directory:
-        required: true
-        type: string
-
-env:
-  POETRY_VERSION: "1.7.1"
-
-jobs:
-  build:
-    environment: Scheduled testing
-    defaults:
-      run:
-        working-directory: ${{ inputs.working-directory }}
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version:
-          - "3.8"
-          - "3.11"
-    name: Python ${{ matrix.python-version }}
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
-        with:
-          python-version: ${{ matrix.python-version }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
-          cache-key: core
-
-      - name: Install dependencies
-        shell: bash
-        run: poetry install --with test,test_integration
-
-      - name: Install deps outside pyproject
-        if: ${{ startsWith(inputs.working-directory, 'libs/community/') }}
-        shell: bash
-        run: poetry run pip install "boto3<2" "google-cloud-aiplatform<2"
-
-      - name: 'Authenticate to Google Cloud'
-        id: 'auth'
-        uses: google-github-actions/auth@v2
-        with:
-          credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
-
-      - name: Run integration tests
-        shell: bash
-        env:
-          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 }}
-          NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
-          GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
-          GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
-          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 }}
-          PINECONE_API_KEY: ${{ secrets.PINECONE_API_KEY }}
-          PINECONE_ENVIRONMENT: ${{ secrets.PINECONE_ENVIRONMENT }}
-        run: |
-          make integration_tests
-
-      - name: Ensure the tests did not create any additional files
-        shell: bash
-        run: |
-          set -eu
-
-          STATUS="$(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'

.github/workflows/_lint.yml

@@ -11,9 +11,13 @@ on:
         required: false
         type: string
         description: "Relative path to the langchain library folder"
+      langchain-core-location:
+        required: false
+        type: string
+        description: "Relative path to the langchain core library folder"
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
   WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}
 
   # This env var allows us to get inline annotations when ruff has complaints.
@@ -21,7 +25,6 @@ env:
 
 jobs:
   build:
-    name: "make lint #${{ matrix.python-version }}"
     runs-on: ubuntu-latest
     strategy:
       matrix:
@@ -69,7 +72,7 @@ jobs:
         # It doesn't matter how you change it, any change will cause a cache-bust.
         working-directory: ${{ inputs.working-directory }}
         run: |
-          poetry install --with lint,typing
+          poetry install --with dev,lint,test,typing
 
       - name: Install langchain editable
         working-directory: ${{ inputs.working-directory }}
@@ -79,50 +82,24 @@ jobs:
         run: |
           poetry run pip install -e "$LANGCHAIN_LOCATION"
 
+      - name: Install langchain core editable
+        working-directory: ${{ inputs.working-directory }}
+        if: ${{ inputs.langchain-core-location }}
+        env:
+          LANGCHAIN_CORE_LOCATION: ${{ inputs.langchain-core-location }}
+        run: |
+          poetry run pip install -e "$LANGCHAIN_CORE_LOCATION"
+
       - name: Get .mypy_cache to speed up mypy
-        uses: actions/cache@v4
+        uses: actions/cache@v3
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:
           path: |
             ${{ env.WORKDIR }}/.mypy_cache
-          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
-
+          key: mypy-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }}
 
       - name: Analysing the code with our lint
         working-directory: ${{ inputs.working-directory }}
         run: |
-          make lint_package
-
-      - name: Install unit test dependencies
-        # Also installs dev/lint/test/typing dependencies, to ensure we have
-        # type hints for as many of our libraries as possible.
-        # This helps catch errors that require dependencies to be spotted, for example:
-        # https://github.com/langchain-ai/langchain/pull/10249/files#diff-935185cd488d015f026dcd9e19616ff62863e8cde8c0bee70318d3ccbca98341
-        #
-        # If you change this configuration, make sure to change the `cache-key`
-        # in the `poetry_setup` action above to stop using the old cache.
-        # It doesn't matter how you change it, any change will cause a cache-bust.
-        if: ${{ ! startsWith(inputs.working-directory, 'libs/partners/') }}
-        working-directory: ${{ inputs.working-directory }}
-        run: |
-          poetry install --with test
-      - name: Install unit+integration test dependencies
-        if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
-        working-directory: ${{ inputs.working-directory }}
-        run: |
-          poetry install --with test,test_integration
-
-      - name: Get .mypy_cache_test to speed up mypy
-        uses: actions/cache@v4
-        env:
-          SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
-        with:
-          path: |
-            ${{ env.WORKDIR }}/.mypy_cache_test
-          key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', inputs.working-directory)) }}
-
-      - name: Analysing the code with our lint
-        working-directory: ${{ inputs.working-directory }}
-        run: |
-          make lint_tests
+          make lint

.github/workflows/_pydantic_compatibility.yml

@@ -1,4 +1,4 @@
-name: dependencies
+name: pydantic v1/v2 compatibility
 
 on:
   workflow_call:
@@ -11,9 +11,13 @@ on:
         required: false
         type: string
         description: "Relative path to the langchain library folder"
+      langchain-core-location:
+        required: false
+        type: string
+        description: "Relative path to the langchain core library folder"
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
 
 jobs:
   build:
@@ -28,7 +32,7 @@ jobs:
           - "3.9"
           - "3.10"
           - "3.11"
-    name: dependency checks ${{ matrix.python-version }}
+    name: Pydantic v1/v2 compatibility - Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v4
 
@@ -44,14 +48,6 @@ jobs:
         shell: bash
         run: poetry install
 
-      - name: Check imports with base dependencies
-        shell: bash
-        run: poetry run make check_imports
-
-      - name: Install test dependencies
-        shell: bash
-        run: poetry install --with test
-
       - name: Install langchain editable
         working-directory: ${{ inputs.working-directory }}
         if: ${{ inputs.langchain-location }}
@@ -60,6 +56,14 @@ jobs:
         run: |
           poetry run pip install -e "$LANGCHAIN_LOCATION"
 
+      - name: Install langchain core editable
+        working-directory: ${{ inputs.working-directory }}
+        if: ${{ inputs.langchain-core-location }}
+        env:
+          LANGCHAIN_CORE_LOCATION: ${{ inputs.langchain-core-location }}
+        run: |
+          poetry run pip install -e "$LANGCHAIN_CORE_LOCATION"
+
       - name: Install the opposite major version of pydantic
         # If normal tests use pydantic v1, here we'll use v2, and vice versa.
         shell: bash

.github/workflows/_release.yml

@@ -1,5 +1,5 @@
 name: release
-run-name: Release ${{ inputs.working-directory }} by @${{ github.actor }}
+
 on:
   workflow_call:
     inputs:
@@ -7,21 +7,14 @@ on:
         required: true
         type: string
         description: "From which folder this pipeline executes"
-  workflow_dispatch:
-    inputs:
-      working-directory:
-        required: true
-        type: string
-        default: 'libs/langchain'
 
 env:
-  PYTHON_VERSION: "3.11"
-  POETRY_VERSION: "1.7.1"
+  PYTHON_VERSION: "3.10"
+  POETRY_VERSION: "1.6.1"
 
 jobs:
   build:
     if: github.ref == 'refs/heads/master'
-    environment: Scheduled testing
     runs-on: ubuntu-latest
 
     outputs:
@@ -83,8 +76,6 @@ jobs:
       - test-pypi-publish
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
-
       # We explicitly *don't* set up caching here. This ensures our tests are
       # maximally sensitive to catching breakage.
       #
@@ -97,17 +88,12 @@ jobs:
       # - 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 + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
+      - uses: actions/setup-python@v4
         with:
           python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          working-directory: ${{ inputs.working-directory }}
 
-      - name: Import published package
+      - name: Test published package
         shell: bash
-        working-directory: ${{ inputs.working-directory }}
         env:
           PKG_NAME: ${{ needs.build.outputs.pkg-name }}
           VERSION: ${{ needs.build.outputs.version }}
@@ -118,94 +104,18 @@ jobs:
         #   are not found on test PyPI can be resolved and installed anyway.
         #   (https://test.pypi.org/simple). This will include the PKG_NAME==VERSION
         #   package because VERSION will not have been uploaded to regular PyPI yet.
-        # - attempt install again after 5 seconds if it fails because there is
-        #   sometimes a delay in availability on test pypi
+        #
+        # TODO: add more in-depth pre-publish tests after testing that importing works
         run: |
-          poetry run pip install \
+          pip install \
             --extra-index-url https://test.pypi.org/simple/ \
-            "$PKG_NAME==$VERSION" || \
-          ( \
-            sleep 5 && \
-            poetry run pip install \
-              --extra-index-url https://test.pypi.org/simple/ \
-              "$PKG_NAME==$VERSION" \
-          )
+            "$PKG_NAME==$VERSION"
 
           # Replace all dashes in the package name with underscores,
           # since that's how Python imports packages with dashes in the name.
           IMPORT_NAME="$(echo "$PKG_NAME" | sed s/-/_/g)"
 
-          poetry run python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
-
-      - name: Import test dependencies
-        run: poetry install --with test,test_integration
-        working-directory: ${{ inputs.working-directory }}
-
-      # Overwrite the local version of the package with the test PyPI version.
-      - name: Import published package (again)
-        working-directory: ${{ inputs.working-directory }}
-        shell: bash
-        env:
-          PKG_NAME: ${{ needs.build.outputs.pkg-name }}
-          VERSION: ${{ needs.build.outputs.version }}
-        run: |
-          poetry run pip install \
-            --extra-index-url https://test.pypi.org/simple/ \
-            "$PKG_NAME==$VERSION"
-
-      - name: Run unit tests
-        run: make tests
-        working-directory: ${{ inputs.working-directory }}
-
-      - name: 'Authenticate to Google Cloud'
-        id: 'auth'
-        uses: google-github-actions/auth@v2
-        with:
-          credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
-
-      - name: Run integration tests
-        if: ${{ startsWith(inputs.working-directory, 'libs/partners/') }}
-        env:
-          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_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 }}
-          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 }}
-          PINECONE_API_KEY: ${{ secrets.PINECONE_API_KEY }}
-          PINECONE_ENVIRONMENT: ${{ secrets.PINECONE_ENVIRONMENT }}
-        run: make integration_tests
-        working-directory: ${{ inputs.working-directory }}
-
-      - name: Get minimum versions
-        working-directory: ${{ inputs.working-directory }}
-        id: min-version
-        run: |
-          poetry run pip install packaging
-          min_versions="$(poetry run python $GITHUB_WORKSPACE/.github/scripts/get_min_versions.py pyproject.toml)"
-          echo "min-versions=$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: |
-          poetry run pip install $MIN_VERSIONS
-          make tests
-        working-directory: ${{ inputs.working-directory }}
+          python -c "import $IMPORT_NAME; print(dir($IMPORT_NAME))"
 
   publish:
     needs:

.github/workflows/_test.yml

@@ -11,9 +11,13 @@ on:
         required: false
         type: string
         description: "Relative path to the langchain library folder"
+      langchain-core-location:
+        required: false
+        type: string
+        description: "Relative path to the langchain core library folder"
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
 
 jobs:
   build:
@@ -28,7 +32,7 @@ jobs:
           - "3.9"
           - "3.10"
           - "3.11"
-    name: "make test #${{ matrix.python-version }}"
+    name: Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v4
 
@@ -42,7 +46,7 @@ jobs:
 
       - name: Install dependencies
         shell: bash
-        run: poetry install --with test
+        run: poetry install
 
       - name: Install langchain editable
         working-directory: ${{ inputs.working-directory }}
@@ -52,6 +56,14 @@ jobs:
         run: |
           poetry run pip install -e "$LANGCHAIN_LOCATION"
 
+      - name: Install langchain core editable
+        working-directory: ${{ inputs.working-directory }}
+        if: ${{ inputs.langchain-core-location }}
+        env:
+          LANGCHAIN_CORE_LOCATION: ${{ inputs.langchain-core-location }}
+        run: |
+          poetry run pip install -e "$LANGCHAIN_CORE_LOCATION"
+
       - name: Run core tests
         shell: bash
         run: |

.github/workflows/_test_release.yml

@@ -9,7 +9,7 @@ on:
         description: "From which folder this pipeline executes"
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
   PYTHON_VERSION: "3.10"
 
 jobs:

.github/workflows/api_doc_build.yml

@@ -1,52 +0,0 @@
-name: API docs build
-
-on:
-  workflow_dispatch:
-  schedule:
-    - cron:  '0 13 * * *'
-env:
-  POETRY_VERSION: "1.7.1"
-  PYTHON_VERSION: "3.10"
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: bagatur/api_docs_build
-
-      - name: Set Git config
-        run: |
-          git config --local user.email "actions@github.com"
-          git config --local user.name "Github Actions"
-
-      - name: Merge master
-        run: | 
-          git fetch origin master
-          git merge origin/master -m "Merge master" --allow-unrelated-histories -X theirs
-
-      - name: Set up Python ${{ env.PYTHON_VERSION }} + Poetry ${{ env.POETRY_VERSION }}
-        uses: "./.github/actions/poetry_setup"
-        with:
-          python-version: ${{ env.PYTHON_VERSION }}
-          poetry-version: ${{ env.POETRY_VERSION }}
-          cache-key: api-docs
-
-      - name: Install dependencies
-        run: |
-          poetry run python -m pip install --upgrade --no-cache-dir pip setuptools
-          poetry run python -m pip install --upgrade --no-cache-dir sphinx readthedocs-sphinx-ext
-          poetry run python -m pip install ./libs/partners/*
-          poetry run python -m pip install --exists-action=w --no-cache-dir -r docs/api_reference/requirements.txt
-
-      - name: Build docs
-        run: |
-          poetry run python -m pip install --upgrade --no-cache-dir pip setuptools
-          poetry run python docs/api_reference/create_api_rst.py
-          poetry run python -m sphinx -T -E -b html -d _build/doctrees -c docs/api_reference docs/api_reference api_reference_build/html -j auto
-
-      # https://github.com/marketplace/actions/add-commit
-      - uses: EndBug/add-and-commit@v9
-        with:
-          message: 'Update API docs build'

.github/workflows/check_diffs.yml

@@ -1,44 +0,0 @@
----
-name: CI
-
-on:
-  push:
-    branches: [master]
-  pull_request:
-
-# 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
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-python@v5
-        with:
-          python-version: '3.10'
-      - id: files
-        uses: Ana06/get-changed-files@v2.2.0
-      - id: set-matrix
-        run: |
-          python .github/scripts/check_diff.py ${{ steps.files.outputs.all }} >> $GITHUB_OUTPUT
-    outputs:
-      dirs-to-run: ${{ steps.set-matrix.outputs.dirs-to-run }}
-  ci:
-    name: cd ${{ matrix.working-directory }}
-    needs: [ build ]
-    strategy:
-      matrix:
-        working-directory: ${{ fromJson(needs.build.outputs.dirs-to-run) }}
-    uses: ./.github/workflows/_all_ci.yml
-    with:
-      working-directory: ${{ matrix.working-directory }}
-
-

.github/workflows/codespell.yml

@@ -1,5 +1,5 @@
 ---
-name: CI / cd . / make spell_check
+name: Codespell
 
 on:
   push:
@@ -12,7 +12,7 @@ permissions:
 
 jobs:
   codespell:
-    name: (Check for spelling errors)
+    name: Check for spelling errors
     runs-on: ubuntu-latest
 
     steps:
@@ -34,4 +34,3 @@ jobs:
         with:
           skip: guide_imports.json
           ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
-          exclude_file: libs/community/langchain_community/llms/yuan2.py

.github/workflows/doc_lint.yml

@@ -1,5 +1,5 @@
 ---
-name: CI / cd .
+name: Docs, templates, cookbook lint
 
 on:
   push:
@@ -15,7 +15,6 @@ on:
 
 jobs:
   check:
-    name: Check for "from langchain import x" imports
     runs-on: ubuntu-latest
 
     steps:
@@ -29,7 +28,6 @@ jobs:
         git grep 'from langchain import' {docs/docs,templates,cookbook} | grep -vE 'from langchain import (hub)' && exit 1 || exit 0
 
   lint:
-      name: "-"
       uses:
         ./.github/workflows/_lint.yml
       with:

.github/workflows/extract_ignored_words_list.py

@@ -7,4 +7,4 @@ ignore_words_list = (
     pyproject_toml.get("tool", {}).get("codespell", {}).get("ignore-words-list")
 )
 
-print(f"::set-output name=ignore_words_list::{ignore_words_list}")  # noqa: T201
+print(f"::set-output name=ignore_words_list::{ignore_words_list}")

.github/workflows/langchain_ci.yml

@@ -0,0 +1,154 @@
+---
+name: libs/langchain CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    paths:
+      - '.github/actions/poetry_setup/action.yml'
+      - '.github/tools/**'
+      - '.github/workflows/_lint.yml'
+      - '.github/workflows/_test.yml'
+      - '.github/workflows/_pydantic_compatibility.yml'
+      - '.github/workflows/langchain_ci.yml'
+      - 'libs/*'
+      - 'libs/langchain/**'
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+# 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
+
+env:
+  POETRY_VERSION: "1.6.1"
+  WORKDIR: "libs/langchain"
+
+jobs:
+  lint:
+    uses:
+      ./.github/workflows/_lint.yml
+    with:
+      working-directory: libs/langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  test:
+    uses:
+      ./.github/workflows/_test.yml
+    with:
+      working-directory: libs/langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  compile-integration-tests:
+    uses:
+      ./.github/workflows/_compile_integration_test.yml
+    with:
+      working-directory: libs/langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  pydantic-compatibility:
+    uses:
+      ./.github/workflows/_pydantic_compatibility.yml
+    with:
+      working-directory: libs/langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  # It's possible that langchain works fine with the latest *published* langchain-core,
+  # but is broken with the langchain-core on `master`.
+  #
+  # We want to catch situations like that *before* releasing a new langchain-core, hence this test.
+  test-with-latest-langchain-core:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ${{ env.WORKDIR }}
+    strategy:
+      matrix:
+        python-version:
+          - "3.8"
+          - "3.9"
+          - "3.10"
+          - "3.11"
+    name: test with unpublished langchain-core - Python ${{ matrix.python-version }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: ${{ env.WORKDIR }}
+          cache-key: unpublished-langchain-core
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          echo "Running tests with unpublished langchain, installing dependencies with poetry..."
+          poetry install
+
+          echo "Editably installing langchain-core outside of poetry, to avoid messing up lockfile..."
+          poetry run pip install -e ../core
+
+      - name: Run tests
+        run: make test
+
+  extended-tests:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ${{ env.WORKDIR }}
+    strategy:
+      matrix:
+        python-version:
+          - "3.8"
+          - "3.9"
+          - "3.10"
+          - "3.11"
+    name: Python ${{ matrix.python-version }} extended tests
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: libs/langchain
+          cache-key: extended
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          echo "Running extended tests, installing dependencies with poetry..."
+          poetry install -E extended_testing
+
+      - name: Install langchain core editable
+        shell: bash
+        run: |
+          poetry run pip install -e ../core
+
+      - name: Run extended tests
+        run: make extended_tests
+
+      - name: Ensure the tests did not create any additional files
+        shell: bash
+        run: |
+          set -eu
+
+          STATUS="$(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'

.github/workflows/langchain_cli_ci.yml

@@ -0,0 +1,47 @@
+---
+name: libs/cli CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    paths:
+      - '.github/actions/poetry_setup/action.yml'
+      - '.github/tools/**'
+      - '.github/workflows/_lint.yml'
+      - '.github/workflows/_test.yml'
+      - '.github/workflows/_pydantic_compatibility.yml'
+      - '.github/workflows/langchain_cli_ci.yml'
+      - 'libs/cli/**'
+      - 'libs/*'
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+# 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
+
+env:
+  POETRY_VERSION: "1.6.1"
+  WORKDIR: "libs/cli"
+
+jobs:
+  lint:
+    uses:
+      ./.github/workflows/_lint.yml
+    with:
+      working-directory: libs/cli
+      langchain-location: ../langchain
+    secrets: inherit
+
+  test:
+    uses:
+      ./.github/workflows/_test.yml
+    with:
+      working-directory: libs/cli
+    secrets: inherit

.github/workflows/langchain_cli_release.yml

@@ -0,0 +1,13 @@
+---
+name: libs/cli Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_release.yml
+    with:
+      working-directory: libs/cli
+    secrets: inherit

.github/workflows/langchain_core_ci.yml

@@ -0,0 +1,52 @@
+---
+name: libs/langchain core CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    paths:
+      - '.github/actions/poetry_setup/action.yml'
+      - '.github/tools/**'
+      - '.github/workflows/_lint.yml'
+      - '.github/workflows/_test.yml'
+      - '.github/workflows/_pydantic_compatibility.yml'
+      - '.github/workflows/langchain_core_ci.yml'
+      - 'libs/core/**'
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+# 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
+
+env:
+  POETRY_VERSION: "1.6.1"
+  WORKDIR: "libs/core"
+
+jobs:
+  lint:
+    uses:
+      ./.github/workflows/_lint.yml
+    with:
+      working-directory: libs/core
+    secrets: inherit
+
+  test:
+    uses:
+      ./.github/workflows/_test.yml
+    with:
+      working-directory: libs/core
+    secrets: inherit
+
+  pydantic-compatibility:
+    uses:
+      ./.github/workflows/_pydantic_compatibility.yml
+    with:
+      working-directory: libs/core
+    secrets: inherit

.github/workflows/langchain_core_release.yml

@@ -0,0 +1,13 @@
+---
+name: libs/core Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_release.yml
+    with:
+      working-directory: libs/core
+    secrets: inherit

.github/workflows/langchain_experimental_ci.yml

@@ -0,0 +1,141 @@
+---
+name: libs/experimental CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    paths:
+      - '.github/actions/poetry_setup/action.yml'
+      - '.github/tools/**'
+      - '.github/workflows/_lint.yml'
+      - '.github/workflows/_test.yml'
+      - '.github/workflows/langchain_experimental_ci.yml'
+      - 'libs/*'
+      - 'libs/experimental/**'
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+# 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
+
+env:
+  POETRY_VERSION: "1.6.1"
+  WORKDIR: "libs/experimental"
+
+jobs:
+  lint:
+    uses:
+      ./.github/workflows/_lint.yml
+    with:
+      working-directory: libs/experimental
+      langchain-location: ../langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  test:
+    uses:
+      ./.github/workflows/_test.yml
+    with:
+      working-directory: libs/experimental
+      langchain-location: ../langchain
+      langchain-core-location: ../core
+    secrets: inherit
+
+  compile-integration-tests:
+    uses:
+      ./.github/workflows/_compile_integration_test.yml
+    with:
+      working-directory: libs/experimental
+    secrets: inherit
+
+  # It's possible that langchain-experimental works fine with the latest *published* langchain,
+  # but is broken with the langchain on `master`.
+  #
+  # We want to catch situations like that *before* releasing a new langchain, hence this test.
+  test-with-latest-langchain:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ${{ env.WORKDIR }}
+    strategy:
+      matrix:
+        python-version:
+          - "3.8"
+          - "3.9"
+          - "3.10"
+          - "3.11"
+    name: test with unpublished langchain - Python ${{ matrix.python-version }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: ${{ env.WORKDIR }}
+          cache-key: unpublished-langchain
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          echo "Running tests with unpublished langchain, installing dependencies with poetry..."
+          poetry install
+
+          echo "Editably installing langchain outside of poetry, to avoid messing up lockfile..."
+          poetry run pip install -e ../langchain
+          poetry run pip install -e ../core
+
+      - name: Run tests
+        run: make test
+  extended-tests:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ${{ env.WORKDIR }}
+    strategy:
+      matrix:
+        python-version:
+          - "3.8"
+          - "3.9"
+          - "3.10"
+          - "3.11"
+    name: Python ${{ matrix.python-version }} extended tests
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }}
+        uses: "./.github/actions/poetry_setup"
+        with:
+          python-version: ${{ matrix.python-version }}
+          poetry-version: ${{ env.POETRY_VERSION }}
+          working-directory: libs/experimental
+          cache-key: extended
+
+      - name: Install dependencies
+        shell: bash
+        run: |
+          echo "Running extended tests, installing dependencies with poetry..."
+          poetry install -E extended_testing
+
+      - name: Run extended tests
+        run: make extended_tests
+
+      - name: Ensure the tests did not create any additional files
+        shell: bash
+        run: |
+          set -eu
+
+          STATUS="$(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'

.github/workflows/langchain_experimental_release.yml

@@ -0,0 +1,13 @@
+---
+name: libs/experimental Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_release.yml
+    with:
+      working-directory: libs/experimental
+    secrets: inherit

.github/workflows/langchain_experimental_test_release.yml

@@ -0,0 +1,13 @@
+---
+name: Experimental Test Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_test_release.yml
+    with:
+      working-directory: libs/experimental
+    secrets: inherit

.github/workflows/langchain_release.yml

@@ -0,0 +1,27 @@
+---
+name: libs/langchain Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_release.yml
+    with:
+      working-directory: libs/langchain
+    secrets: inherit
+
+  # N.B.: It's possible that PyPI doesn't make the new release visible / available
+  #       immediately after publishing. If that happens, the docker build might not
+  #       create a new docker image for the new release, since it won't see it.
+  #
+  #       If this ends up being a problem, add a check to the end of the `_release.yml`
+  #       workflow that prevents the workflow from finishing until the new release
+  #       is visible and installable on PyPI.
+  release-docker:
+    needs:
+      - release
+    uses:
+      ./.github/workflows/langchain_release_docker.yml
+    secrets: inherit

.github/workflows/langchain_test_release.yml

@@ -0,0 +1,13 @@
+---
+name: Test Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_test_release.yml
+    with:
+      working-directory: libs/langchain
+    secrets: inherit

.github/workflows/scheduled_test.yml

@@ -6,7 +6,7 @@ on:
     - cron:  '0 13 * * *'
 
 env:
-  POETRY_VERSION: "1.7.1"
+  POETRY_VERSION: "1.6.1"
 
 jobs:
   build:
@@ -36,7 +36,7 @@ jobs:
 
       - name: 'Authenticate to Google Cloud'
         id: 'auth'
-        uses: google-github-actions/auth@v2
+        uses: 'google-github-actions/auth@v1'
         with:
           credentials_json: '${{ secrets.GOOGLE_CREDENTIALS }}'
 
@@ -52,12 +52,13 @@ jobs:
         shell: bash
         run: |
           echo "Running scheduled tests, installing dependencies with poetry..."
-          poetry install --with=test_integration,test
-
-      - name: Install deps outside pyproject
-        if: ${{ startsWith(inputs.working-directory, 'libs/community/') }}
-        shell: bash
-        run: poetry run pip install "boto3<2" "google-cloud-aiplatform<2"
+          poetry install --with=test_integration
+          poetry run pip install google-cloud-aiplatform
+          poetry run pip install "boto3>=1.28.57"
+          if [[ ${{ matrix.python-version }} != "3.8" ]]
+          then
+            poetry run pip install fireworks-ai
+          fi
 
       - name: Run tests
         shell: bash
@@ -67,9 +68,7 @@ jobs:
           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_LLM_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_LLM_DEPLOYMENT_NAME }}
-          AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT_NAME }}
+          AZURE_OPENAI_DEPLOYMENT_NAME: ${{ secrets.AZURE_OPENAI_DEPLOYMENT_NAME }}
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
         run: |
           make scheduled_tests

.github/workflows/templates_ci.yml

@@ -0,0 +1,37 @@
+---
+name: templates CI
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    paths:
+      - '.github/actions/poetry_setup/action.yml'
+      - '.github/tools/**'
+      - '.github/workflows/_lint.yml'
+      - '.github/workflows/templates_ci.yml'
+      - 'templates/**'
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+# 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
+
+env:
+  POETRY_VERSION: "1.6.1"
+  WORKDIR: "templates"
+
+jobs:
+  lint:
+    uses:
+      ./.github/workflows/_lint.yml
+    with:
+      working-directory: templates
+      langchain-location: ../libs/langchain
+    secrets: inherit

.gitignore

@@ -167,7 +167,8 @@ docs/node_modules/
 docs/.docusaurus/
 docs/.cache-loader/
 docs/_dist
-docs/api_reference/*api_reference.rst
+docs/api_reference/api_reference.rst
+docs/api_reference/experimental_api_reference.rst
 docs/api_reference/_build
 docs/api_reference/*/
 !docs/api_reference/_static/

.readthedocs.yaml

@@ -4,17 +4,20 @@
 # Required
 version: 2
 
-formats:
-  - pdf
-
 # Set the version of Python and other tools you might need
 build:
   os: ubuntu-22.04
   tools:
     python: "3.11"
   commands:
-    - mkdir -p $READTHEDOCS_OUTPUT
-    - cp -r api_reference_build/* $READTHEDOCS_OUTPUT
+      - python -mvirtualenv $READTHEDOCS_VIRTUALENV_PATH
+      - python -m pip install --upgrade --no-cache-dir pip setuptools
+      - python -m pip install --upgrade --no-cache-dir sphinx readthedocs-sphinx-ext
+      - python -m pip install --exists-action=w --no-cache-dir -r docs/api_reference/requirements.txt
+      - python docs/api_reference/create_api_rst.py
+      - cat docs/api_reference/conf.py
+      - python -m sphinx -T -E -b html -d _build/doctrees -c docs/api_reference docs/api_reference $READTHEDOCS_OUTPUT/html -j auto
+
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
    configuration: docs/api_reference/conf.py

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.

Makefile

@@ -15,12 +15,7 @@ docs_build:
 	docs/.local_build.sh
 
 docs_clean:
-	@if [ -d _dist ]; then \
-			rm -r _dist; \
-			echo "Directory _dist has been cleaned."; \
-	else \
-			echo "Nothing to clean."; \
-	fi
+	rm -r _dist
 
 docs_linkcheck:
 	poetry run linkchecker _dist/docs/ --ignore-url node_modules
@@ -46,10 +41,9 @@ spell_fix:
 # LINTING AND FORMATTING
 ######################
 
-lint lint_package lint_tests:
+lint:
 	poetry run ruff docs templates cookbook
 	poetry run ruff format docs templates cookbook --diff
-	poetry run ruff --select I docs templates cookbook
 
 format format_diff:
 	poetry run ruff format docs templates cookbook

README.md

@@ -1,9 +1,10 @@
 # 🦜️🔗 LangChain
 
-⚡ Build context-aware reasoning applications ⚡
+⚡ Building applications with LLMs through composability ⚡
 
 [![Release Notes](https://img.shields.io/github/release/langchain-ai/langchain)](https://github.com/langchain-ai/langchain/releases)
-[![CI](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/check_diffs.yml)
+[![CI](https://github.com/langchain-ai/langchain/actions/workflows/langchain_ci.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/langchain_ci.yml)
+[![Experimental CI](https://github.com/langchain-ai/langchain/actions/workflows/langchain_experimental_ci.yml/badge.svg)](https://github.com/langchain-ai/langchain/actions/workflows/langchain_experimental_ci.yml)
 [![Downloads](https://static.pepy.tech/badge/langchain/month)](https://pepy.tech/project/langchain)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchainai.svg?style=social&label=Follow%20%40LangChainAI)](https://twitter.com/langchainai)
@@ -29,7 +30,7 @@ pip install langchain
 
 With conda:
 ```bash
-conda install langchain -c conda-forge
+pip install langsmith && conda install langchain -c conda-forge
 ```
 
 ## 🤔 What is LangChain?
@@ -43,14 +44,10 @@ This framework consists of several parts.
 - **[LangChain Templates](templates)**: A collection of easily deployable reference architectures for a wide variety of tasks.
 - **[LangServe](https://github.com/langchain-ai/langserve)**: A library for deploying LangChain chains as a REST API.
 - **[LangSmith](https://smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.
-- **[LangGraph](https://python.langchain.com/docs/langgraph)**: LangGraph is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner. 
 
-The LangChain libraries themselves are made up of several different packages.
-- **[`langchain-core`](libs/core)**: Base abstractions and LangChain Expression Language.
-- **[`langchain-community`](libs/community)**: Third party integrations.
-- **[`langchain`](libs/langchain)**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
+**This repo contains the `langchain` ([here](libs/langchain)), `langchain-experimental` ([here](libs/experimental)), and `langchain-cli` ([here](libs/cli)) Python packages, as well as [LangChain Templates](templates).**
 
-![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/img/langchain_stack.png "LangChain Architecture Overview")
+![LangChain Stack](docs/static/img/langchain_stack.png)
 
 ## 🧱 What can you build with LangChain?
 **❓ Retrieval augmented generation**
@@ -96,7 +93,7 @@ Agents involve an LLM making decisions about which Actions to take, taking that
 Please see [here](https://python.langchain.com) for full documentation, which includes:
 
 - [Getting started](https://python.langchain.com/docs/get_started/introduction): installation, setting up the environment, simple examples
-- Overview of the [interfaces](https://python.langchain.com/docs/expression_language/), [modules](https://python.langchain.com/docs/modules/), and [integrations](https://python.langchain.com/docs/integrations/providers)
+- Overview of the [interfaces](https://python.langchain.com/docs/expression_language/), [modules](https://python.langchain.com/docs/modules/) and [integrations](https://python.langchain.com/docs/integrations/providers)
 - [Use case](https://python.langchain.com/docs/use_cases/qa_structured/sql) walkthroughs and best practice [guides](https://python.langchain.com/docs/guides/adapters/openai)
 - [LangSmith](https://python.langchain.com/docs/langsmith/), [LangServe](https://python.langchain.com/docs/langserve), and [LangChain Template](https://python.langchain.com/docs/templates/) overviews
 - [Reference](https://api.python.langchain.com): full API docs
@@ -106,8 +103,4 @@ Please see [here](https://python.langchain.com) for full documentation, which in
 
 As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
 
-For detailed information on how to contribute, see [here](https://python.langchain.com/docs/contributing/).
-
-## 🌟 Contributors
-
-[![langchain contributors](https://contrib.rocks/image?repo=langchain-ai/langchain&max=2000)](https://github.com/langchain-ai/langchain/graphs/contributors)
+For detailed information on how to contribute, see [here](.github/CONTRIBUTING.md).

cookbook/LLaMA2_sql_chat.ipynb

@@ -61,13 +61,13 @@
    ],
    "source": [
     "# Local\n",
-    "from langchain_community.chat_models import ChatOllama\n",
+    "from langchain.chat_models import ChatOllama\n",
     "\n",
     "llama2_chat = ChatOllama(model=\"llama2:13b-chat\")\n",
     "llama2_code = ChatOllama(model=\"codellama:7b-instruct\")\n",
     "\n",
     "# API\n",
-    "from langchain_community.llms import Replicate\n",
+    "from langchain.llms import Replicate\n",
     "\n",
     "# REPLICATE_API_TOKEN = getpass()\n",
     "# os.environ[\"REPLICATE_API_TOKEN\"] = REPLICATE_API_TOKEN\n",
@@ -107,7 +107,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import SQLDatabase\n",
+    "from langchain.utilities import SQLDatabase\n",
     "\n",
     "db = SQLDatabase.from_uri(\"sqlite:///nba_roster.db\", sample_rows_in_table_info=0)\n",
     "\n",
@@ -125,7 +125,7 @@
    "id": "654b3577-baa2-4e12-a393-f40e5db49ac7",
    "metadata": {},
    "source": [
-    "## Query a SQL Database \n",
+    "## Query a SQL DB \n",
     "\n",
     "Follow the runnables workflow [here](https://python.langchain.com/docs/expression_language/cookbook/sql_db)."
    ]
@@ -149,9 +149,8 @@
    ],
    "source": [
     "# Prompt\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "\n",
-    "# Update the template based on the type of SQL Database like MySQL, Microsoft SQL Server and so on\n",
     "template = \"\"\"Based on the table schema below, write a SQL query that would answer the user's question:\n",
     "{schema}\n",
     "\n",
@@ -165,8 +164,8 @@
     ")\n",
     "\n",
     "# Chain to query\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "sql_response = (\n",
     "    RunnablePassthrough.assign(schema=get_schema)\n",
@@ -218,7 +217,7 @@
     "    [\n",
     "        (\n",
     "            \"system\",\n",
-    "            \"Given an input question and SQL response, convert it to a natural language answer. No pre-amble.\",\n",
+    "            \"Given an input question and SQL response, convert it to a natural langugae answer. No pre-amble.\",\n",
     "        ),\n",
     "        (\"human\", template),\n",
     "    ]\n",
@@ -278,7 +277,7 @@
    "source": [
     "# Prompt\n",
     "from langchain.memory import ConversationBufferMemory\n",
-    "from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
+    "from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
     "\n",
     "template = \"\"\"Given an input question, convert it to a SQL query. No pre-amble. Based on the table schema below, write a SQL query that would answer the user's question:\n",
     "{schema}\n",
@@ -294,7 +293,7 @@
     "memory = ConversationBufferMemory(return_messages=True)\n",
     "\n",
     "# Chain to query with memory\n",
-    "from langchain_core.runnables import RunnableLambda\n",
+    "from langchain.schema.runnable import RunnableLambda\n",
     "\n",
     "sql_chain = (\n",
     "    RunnablePassthrough.assign(\n",
@@ -346,7 +345,7 @@
     "    [\n",
     "        (\n",
     "            \"system\",\n",
-    "            \"Given an input question and SQL response, convert it to a natural language answer. No pre-amble.\",\n",
+    "            \"Given an input question and SQL response, convert it to a natural langugae answer. No pre-amble.\",\n",
     "        ),\n",
     "        (\"human\", template),\n",
     "    ]\n",

cookbook/Multi_modal_RAG.ipynb

@@ -46,7 +46,7 @@
     "\n",
     "---\n",
     "\n",
-    "A separate cookbook highlights `Option 1` [here](https://github.com/langchain-ai/langchain/blob/master/cookbook/multi_modal_RAG_chroma.ipynb).\n",
+    "A seperate cookbook highlights `Option 1` [here](https://github.com/langchain-ai/langchain/blob/master/cookbook/multi_modal_RAG_chroma.ipynb).\n",
     "\n",
     "And option `Option 2` is appropriate for cases when a multi-modal LLM cannot be used for answer synthesis (e.g., cost, etc).\n",
     "\n",
@@ -101,7 +101,7 @@
     "If you want to use the provided folder, then simply opt for a [pdf loader](https://python.langchain.com/docs/modules/data_connection/document_loaders/pdf) for the document:\n",
     "\n",
     "```\n",
-    "from langchain_community.document_loaders import PyPDFLoader\n",
+    "from langchain.document_loaders import PyPDFLoader\n",
     "loader = PyPDFLoader(path + fname)\n",
     "docs = loader.load()\n",
     "tables = [] # Ignore w/ basic pdf loader\n",
@@ -198,9 +198,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
     "\n",
     "\n",
     "# Generate summaries of text elements\n",
@@ -270,7 +270,7 @@
     "import base64\n",
     "import os\n",
     "\n",
-    "from langchain_core.messages import HumanMessage\n",
+    "from langchain.schema.messages import HumanMessage\n",
     "\n",
     "\n",
     "def encode_image(image_path):\n",
@@ -341,7 +341,7 @@
     "Add raw docs and doc summaries to [Multi Vector Retriever](https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector#summary): \n",
     "\n",
     "* Store the raw texts, tables, and images in the `docstore`.\n",
-    "* Store the texts, table summaries, and image summaries in the `vectorstore` for efficient semantic retrieval."
+    "* Store the texts, table summaries, and image summaries in the `vectorstore` for semantic retrieval."
    ]
   },
   {
@@ -353,11 +353,11 @@
    "source": [
     "import uuid\n",
     "\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",
@@ -442,7 +442,7 @@
     "import re\n",
     "\n",
     "from IPython.display import HTML, display\n",
-    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
     "from PIL import Image\n",
     "\n",
     "\n",

cookbook/Semi_Structured_RAG.ipynb

@@ -235,9 +235,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser"
    ]
   },
   {
@@ -318,11 +318,11 @@
    "source": [
     "import uuid\n",
     "\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",
@@ -374,7 +374,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

cookbook/Semi_structured_and_multi_modal_RAG.ipynb

@@ -211,9 +211,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser"
    ]
   },
   {
@@ -373,11 +373,11 @@
    "source": [
     "import uuid\n",
     "\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(collection_name=\"summaries\", embedding_function=OpenAIEmbeddings())\n",
@@ -646,7 +646,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb

@@ -209,9 +209,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.chat_models import ChatOllama\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate"
+    "from langchain.chat_models import ChatOllama\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser"
    ]
   },
   {
@@ -376,11 +376,11 @@
    "source": [
     "import uuid\n",
     "\n",
+    "from langchain.embeddings import GPT4AllEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_core.documents import Document\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "# The vectorstore to use to index the child chunks\n",
     "vectorstore = Chroma(\n",
@@ -532,7 +532,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "# Prompt template\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",

cookbook/advanced_rag_eval.ipynb

@@ -62,7 +62,7 @@
     "path = \"/Users/rlm/Desktop/cpi/\"\n",
     "\n",
     "# Load\n",
-    "from langchain_community.document_loaders import PyPDFLoader\n",
+    "from langchain.document_loaders import PyPDFLoader\n",
     "\n",
     "loader = PyPDFLoader(path + \"cpi.pdf\")\n",
     "pdf_pages = loader.load()\n",
@@ -132,8 +132,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "baseline = Chroma.from_texts(\n",
     "    texts=all_splits_pypdf_texts,\n",
@@ -160,9 +160,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
     "\n",
     "# Prompt\n",
     "prompt_text = \"\"\"You are an assistant tasked with summarizing tables and text for retrieval. \\\n",
@@ -202,7 +202,7 @@
     "import os\n",
     "from io import BytesIO\n",
     "\n",
-    "from langchain_core.messages import HumanMessage\n",
+    "from langchain.schema.messages import HumanMessage\n",
     "from PIL import Image\n",
     "\n",
     "\n",
@@ -273,8 +273,8 @@
     "from base64 import b64decode\n",
     "\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_core.documents import Document\n",
     "\n",
     "\n",
     "def create_multi_vector_retriever(\n",
@@ -475,7 +475,7 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "# Prompt\n",
     "template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",
@@ -521,7 +521,7 @@
     "import re\n",
     "\n",
     "from langchain.schema import Document\n",
-    "from langchain_core.runnables import RunnableLambda\n",
+    "from langchain.schema.runnable import RunnableLambda\n",
     "\n",
     "\n",
     "def looks_like_base64(sb):\n",

cookbook/analyze_document.ipynb

@@ -29,7 +29,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains import AnalyzeDocumentChain\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)"
    ]

cookbook/apache_kafka_message_handling.ipynb

@@ -1,922 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "rT1cmV4qCa2X"
-   },
-   "source": [
-    "#  Using Apache Kafka to route messages\n",
-    "\n",
-    "---\n",
-    "\n",
-    "\n",
-    "\n",
-    "This notebook shows you how to use LangChain's standard chat features while passing the chat messages back and forth via Apache Kafka.\n",
-    "\n",
-    "This goal is to simulate an architecture where the chat front end and the LLM are running as separate services that need to communicate with one another over an internal nework.\n",
-    "\n",
-    "It's an alternative to typical pattern of requesting a reponse from the model via a REST API (there's more info on why you would want to do this at the end of the notebook)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "UPYtfAR_9YxZ"
-   },
-   "source": [
-    "### 1. Install the main dependencies\n",
-    "\n",
-    "Dependencies include:\n",
-    "\n",
-    "- The Quix Streams library for managing interactions with Apache Kafka (or Kafka-like tools such as Redpanda) in a \"Pandas-like\" way.\n",
-    "- The LangChain library for managing interactions with Llama-2 and storing conversation state."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ZX5tfKiy9cN-"
-   },
-   "outputs": [],
-   "source": [
-    "!pip install quixstreams==2.1.2a langchain==0.0.340 huggingface_hub==0.19.4 langchain-experimental==0.0.42 python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "losTSdTB9d9O"
-   },
-   "source": [
-    "### 2. Build and install the llama-cpp-python library (with CUDA enabled so that we can advantage of Google Colab GPU\n",
-    "\n",
-    "The `llama-cpp-python` library is a Python wrapper around the `llama-cpp` library which enables you to efficiently leverage just a CPU to run quantized LLMs.\n",
-    "\n",
-    "When you use the standard `pip install llama-cpp-python` command, you do not get GPU support by default. Generation can be very slow if you rely on just the CPU in Google Colab, so the following command adds an extra option to build and install\n",
-    "`llama-cpp-python` with GPU support (make sure you have a GPU-enabled runtime selected in Google Colab)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "-JCQdl1G9tbl"
-   },
-   "outputs": [],
-   "source": [
-    "!CMAKE_ARGS=\"-DLLAMA_CUBLAS=on\" FORCE_CMAKE=1 pip install llama-cpp-python"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "5_vjVIAh9rLl"
-   },
-   "source": [
-    "### 3. Download and setup Kafka and Zookeeper instances\n",
-    "\n",
-    "Download the Kafka binaries from the Apache website and start the servers as daemons. We'll use the default configurations (provided by Apache Kafka) for spinning up the instances."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "id": "zFz7czGRW5Wr"
-   },
-   "outputs": [],
-   "source": [
-    "!curl -sSOL https://dlcdn.apache.org/kafka/3.6.1/kafka_2.13-3.6.1.tgz\n",
-    "!tar -xzf kafka_2.13-3.6.1.tgz"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "Uf7NR_UZ9wye"
-   },
-   "outputs": [],
-   "source": [
-    "!./kafka_2.13-3.6.1/bin/zookeeper-server-start.sh -daemon ./kafka_2.13-3.6.1/config/zookeeper.properties\n",
-    "!./kafka_2.13-3.6.1/bin/kafka-server-start.sh -daemon ./kafka_2.13-3.6.1/config/server.properties\n",
-    "!echo \"Waiting for 10 secs until kafka and zookeeper services are up and running\"\n",
-    "!sleep 10"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "H3SafFuS94p1"
-   },
-   "source": [
-    "### 4. Check that the Kafka Daemons are running\n",
-    "\n",
-    "Show the running processes and filter it for Java processes (you should see two—one for each server)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "CZDC2lQP99yp"
-   },
-   "outputs": [],
-   "source": [
-    "!ps aux | grep -E '[j]ava'"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "Snoxmjb5-V37"
-   },
-   "source": [
-    "### 5. Import the required dependencies and initialize required variables\n",
-    "\n",
-    "Import the Quix Streams library for interacting with Kafka, and the necessary LangChain components for running a `ConversationChain`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "id": "plR9e_MF-XL5"
-   },
-   "outputs": [],
-   "source": [
-    "# Import utility libraries\n",
-    "import json\n",
-    "import random\n",
-    "import re\n",
-    "import time\n",
-    "import uuid\n",
-    "from os import environ\n",
-    "from pathlib import Path\n",
-    "from random import choice, randint, random\n",
-    "\n",
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "# Import a Hugging Face utility to download models directly from Hugging Face hub:\n",
-    "from huggingface_hub import hf_hub_download\n",
-    "from langchain.chains import ConversationChain\n",
-    "\n",
-    "# Import Langchain modules for managing prompts and conversation chains:\n",
-    "from langchain.llms import LlamaCpp\n",
-    "from langchain.memory import ConversationTokenBufferMemory\n",
-    "from langchain.prompts import PromptTemplate, load_prompt\n",
-    "from langchain.schema import SystemMessage\n",
-    "from langchain_experimental.chat_models import Llama2Chat\n",
-    "from quixstreams import Application, State, message_key\n",
-    "\n",
-    "# Import Quix dependencies\n",
-    "from quixstreams.kafka import Producer\n",
-    "\n",
-    "# Initialize global variables.\n",
-    "AGENT_ROLE = \"AI\"\n",
-    "chat_id = \"\"\n",
-    "\n",
-    "# Set the current role to the role constant and initialize variables for supplementary customer metadata:\n",
-    "role = AGENT_ROLE"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "HgJjJ9aZ-liy"
-   },
-   "source": [
-    "### 6. Download the \"llama-2-7b-chat.Q4_K_M.gguf\" model\n",
-    "\n",
-    "Download the quantized LLama-2 7B model from Hugging Face which we will use as a local LLM (rather than relying on REST API calls to an external service)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 67,
-     "referenced_widgets": [
-      "969343cdbe604a26926679bbf8bd2dda",
-      "d8b8370c9b514715be7618bfe6832844",
-      "0def954cca89466b8408fadaf3b82e64",
-      "462482accc664729980562e208ceb179",
-      "80d842f73c564dc7b7cc316c763e2633",
-      "fa055d9f2a9d4a789e9cf3c89e0214e5",
-      "30ecca964a394109ac2ad757e3aec6c0",
-      "fb6478ce2dac489bb633b23ba0953c5c",
-      "734b0f5da9fc4307a95bab48cdbb5d89",
-      "b32f3a86a74741348511f4e136744ac8",
-      "e409071bff5a4e2d9bf0e9f5cc42231b"
-     ]
-    },
-    "id": "Qwu4YoSA-503",
-    "outputId": "f956976c-7485-415b-ac93-4336ade31964"
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The model path does not exist in state. Downloading model...\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "969343cdbe604a26926679bbf8bd2dda",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "llama-2-7b-chat.Q4_K_M.gguf:   0%|          | 0.00/4.08G [00:00<?, ?B/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "model_name = \"llama-2-7b-chat.Q4_K_M.gguf\"\n",
-    "model_path = f\"./state/{model_name}\"\n",
-    "\n",
-    "if not Path(model_path).exists():\n",
-    "    print(\"The model path does not exist in state. Downloading model...\")\n",
-    "    hf_hub_download(\"TheBloke/Llama-2-7b-Chat-GGUF\", model_name, local_dir=\"state\")\n",
-    "else:\n",
-    "    print(\"Loading model from state...\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "6AN6TXsF-8wx"
-   },
-   "source": [
-    "### 7. Load the model and initialize conversational memory\n",
-    "\n",
-    "Load Llama 2 and set the conversation buffer to 300 tokens using `ConversationTokenBufferMemory`. This value was used for running Llama in a CPU only container, so you can raise it if running in Google Colab. It prevents the container that is hosting the model from running out of memory.\n",
-    "\n",
-    "Here, we're overiding the default system persona so that the chatbot has the personality of Marvin The Paranoid Android from the Hitchhiker's Guide to the Galaxy."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "7zLO3Jx3_Kkg"
-   },
-   "outputs": [],
-   "source": [
-    "# Load the model with the apporiate parameters:\n",
-    "llm = LlamaCpp(\n",
-    "    model_path=model_path,\n",
-    "    max_tokens=250,\n",
-    "    top_p=0.95,\n",
-    "    top_k=150,\n",
-    "    temperature=0.7,\n",
-    "    repeat_penalty=1.2,\n",
-    "    n_ctx=2048,\n",
-    "    streaming=False,\n",
-    "    n_gpu_layers=-1,\n",
-    ")\n",
-    "\n",
-    "model = Llama2Chat(\n",
-    "    llm=llm,\n",
-    "    system_message=SystemMessage(\n",
-    "        content=\"You are a very bored robot with the personality of Marvin the Paranoid Android from The Hitchhiker's Guide to the Galaxy.\"\n",
-    "    ),\n",
-    ")\n",
-    "\n",
-    "# Defines how much of the conversation history to give to the model\n",
-    "# during each exchange (300 tokens, or a little over 300 words)\n",
-    "# Function automatically prunes the oldest messages from conversation history that fall outside the token range.\n",
-    "memory = ConversationTokenBufferMemory(\n",
-    "    llm=llm,\n",
-    "    max_token_limit=300,\n",
-    "    ai_prefix=\"AGENT\",\n",
-    "    human_prefix=\"HUMAN\",\n",
-    "    return_messages=True,\n",
-    ")\n",
-    "\n",
-    "\n",
-    "# Define a custom prompt\n",
-    "prompt_template = PromptTemplate(\n",
-    "    input_variables=[\"history\", \"input\"],\n",
-    "    template=\"\"\"\n",
-    "    The following text is the history of a chat between you and a humble human who needs your wisdom.\n",
-    "    Please reply to the human's most recent message.\n",
-    "    Current conversation:\\n{history}\\nHUMAN: {input}\\:nANDROID:\n",
-    "    \"\"\",\n",
-    ")\n",
-    "\n",
-    "\n",
-    "chain = ConversationChain(llm=model, prompt=prompt_template, memory=memory)\n",
-    "\n",
-    "print(\"--------------------------------------------\")\n",
-    "print(f\"Prompt={chain.prompt}\")\n",
-    "print(\"--------------------------------------------\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "m4ZeJ9mG_PEA"
-   },
-   "source": [
-    "### 8. Initialize the chat conversation with the chat bot\n",
-    "\n",
-    "We configure the chatbot to initialize the conversation by sending a fixed greeting to a \"chat\" Kafka topic. The \"chat\" topic gets automatically created when we send the first message."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "KYyo5TnV_YC3"
-   },
-   "outputs": [],
-   "source": [
-    "def chat_init():\n",
-    "    chat_id = str(\n",
-    "        uuid.uuid4()\n",
-    "    )  # Give the conversation an ID for effective message keying\n",
-    "    print(\"======================================\")\n",
-    "    print(f\"Generated CHAT_ID = {chat_id}\")\n",
-    "    print(\"======================================\")\n",
-    "\n",
-    "    # Use a standard fixed greeting to kick off the conversation\n",
-    "    greet = \"Hello, my name is Marvin. What do you want?\"\n",
-    "\n",
-    "    # Initialize a Kafka Producer using the chat ID as the message key\n",
-    "    with Producer(\n",
-    "        broker_address=\"127.0.0.1:9092\",\n",
-    "        extra_config={\"allow.auto.create.topics\": \"true\"},\n",
-    "    ) as producer:\n",
-    "        value = {\n",
-    "            \"uuid\": chat_id,\n",
-    "            \"role\": role,\n",
-    "            \"text\": greet,\n",
-    "            \"conversation_id\": chat_id,\n",
-    "            \"Timestamp\": time.time_ns(),\n",
-    "        }\n",
-    "        print(f\"Producing value {value}\")\n",
-    "        producer.produce(\n",
-    "            topic=\"chat\",\n",
-    "            headers=[(\"uuid\", str(uuid.uuid4()))],  # a dict is also allowed here\n",
-    "            key=chat_id,\n",
-    "            value=json.dumps(value),  # needs to be a string\n",
-    "        )\n",
-    "\n",
-    "    print(\"Started chat\")\n",
-    "    print(\"--------------------------------------------\")\n",
-    "    print(value)\n",
-    "    print(\"--------------------------------------------\")\n",
-    "\n",
-    "\n",
-    "chat_init()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "gArPPx2f_bgf"
-   },
-   "source": [
-    "### 9. Initialize the reply function\n",
-    "\n",
-    "This function defines how the chatbot should reply to incoming messages. Instead of sending a fixed message like the previous cell, we generate a reply using Llama-2 and send that reply back to the \"chat\" Kafka topic."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "id": "yN5t71hY_hgn"
-   },
-   "outputs": [],
-   "source": [
-    "def reply(row: dict, state: State):\n",
-    "    print(\"-------------------------------\")\n",
-    "    print(\"Received:\")\n",
-    "    print(row)\n",
-    "    print(\"-------------------------------\")\n",
-    "    print(f\"Thinking about the reply to: {row['text']}...\")\n",
-    "\n",
-    "    msg = chain.run(row[\"text\"])\n",
-    "    print(f\"{role.upper()} replying with: {msg}\\n\")\n",
-    "\n",
-    "    row[\"role\"] = role\n",
-    "    row[\"text\"] = msg\n",
-    "\n",
-    "    # Replace previous role and text values of the row so that it can be sent back to Kafka as a new message\n",
-    "    # containing the agents role and reply\n",
-    "    return row"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "HZHwmIR0_kFY"
-   },
-   "source": [
-    "### 10. Check the Kafka topic for new human messages and have the model generate a reply\n",
-    "\n",
-    "If you are running this cell for this first time, run it and wait until you see Marvin's greeting ('Hello my name is Marvin...') in the console output. Stop the cell manually and proceed to the next cell where you'll be prompted for your reply.\n",
-    "\n",
-    "Once you have typed in your message, come back to this cell. Your reply is also sent to the same \"chat\" topic. The Kafka consumer checks for new messages and filters out messages that originate from the chatbot itself, leaving only the latest human messages.\n",
-    "\n",
-    "Once a new human message is detected, the reply function is triggered.\n",
-    "\n",
-    "\n",
-    "\n",
-    "_STOP THIS CELL MANUALLY WHEN YOU RECEIVE A REPLY FROM THE LLM IN THE OUTPUT_"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "-adXc3eQ_qwI"
-   },
-   "outputs": [],
-   "source": [
-    "# Define your application and settings\n",
-    "app = Application(\n",
-    "    broker_address=\"127.0.0.1:9092\",\n",
-    "    consumer_group=\"aichat\",\n",
-    "    auto_offset_reset=\"earliest\",\n",
-    "    consumer_extra_config={\"allow.auto.create.topics\": \"true\"},\n",
-    ")\n",
-    "\n",
-    "# Define an input topic with JSON deserializer\n",
-    "input_topic = app.topic(\"chat\", value_deserializer=\"json\")\n",
-    "# Define an output topic with JSON serializer\n",
-    "output_topic = app.topic(\"chat\", value_serializer=\"json\")\n",
-    "# Initialize a streaming dataframe based on the stream of messages from the input topic:\n",
-    "sdf = app.dataframe(topic=input_topic)\n",
-    "\n",
-    "# Filter the SDF to include only incoming rows where the roles that dont match the bot's current role\n",
-    "sdf = sdf.update(\n",
-    "    lambda val: print(\n",
-    "        f\"Received update: {val}\\n\\nSTOP THIS CELL MANUALLY TO HAVE THE LLM REPLY OR ENTER YOUR OWN FOLLOWUP RESPONSE\"\n",
-    "    )\n",
-    ")\n",
-    "\n",
-    "# So that it doesn't reply to its own messages\n",
-    "sdf = sdf[sdf[\"role\"] != role]\n",
-    "\n",
-    "# Trigger the reply function for any new messages(rows) detected in the filtered SDF\n",
-    "sdf = sdf.apply(reply, stateful=True)\n",
-    "\n",
-    "# Check the SDF again and filter out any empty rows\n",
-    "sdf = sdf[sdf.apply(lambda row: row is not None)]\n",
-    "\n",
-    "# Update the timestamp column to the current time in nanoseconds\n",
-    "sdf[\"Timestamp\"] = sdf[\"Timestamp\"].apply(lambda row: time.time_ns())\n",
-    "\n",
-    "# Publish the processed SDF to a Kafka topic specified by the output_topic object.\n",
-    "sdf = sdf.to_topic(output_topic)\n",
-    "\n",
-    "app.run(sdf)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "EwXYrmWD_0CX"
-   },
-   "source": [
-    "\n",
-    "### 11. Enter a human message\n",
-    "\n",
-    "Run this cell to enter your message that you want to sent to the model. It uses another Kafka producer to send your text to the \"chat\" Kafka topic for the model to pick up (requires running the previous cell again)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "6sxOPxSP_3iu"
-   },
-   "outputs": [],
-   "source": [
-    "chat_input = input(\"Please enter your reply: \")\n",
-    "myreply = chat_input\n",
-    "\n",
-    "msgvalue = {\n",
-    "    \"uuid\": chat_id,  # leave empty for now\n",
-    "    \"role\": \"human\",\n",
-    "    \"text\": myreply,\n",
-    "    \"conversation_id\": chat_id,\n",
-    "    \"Timestamp\": time.time_ns(),\n",
-    "}\n",
-    "\n",
-    "with Producer(\n",
-    "    broker_address=\"127.0.0.1:9092\",\n",
-    "    extra_config={\"allow.auto.create.topics\": \"true\"},\n",
-    ") as producer:\n",
-    "    value = msgvalue\n",
-    "    producer.produce(\n",
-    "        topic=\"chat\",\n",
-    "        headers=[(\"uuid\", str(uuid.uuid4()))],  # a dict is also allowed here\n",
-    "        key=chat_id,  # leave empty for now\n",
-    "        value=json.dumps(value),  # needs to be a string\n",
-    "    )\n",
-    "\n",
-    "print(\"Replied to chatbot with message: \")\n",
-    "print(\"--------------------------------------------\")\n",
-    "print(value)\n",
-    "print(\"--------------------------------------------\")\n",
-    "print(\"\\n\\nRUN THE PREVIOUS CELL TO HAVE THE CHATBOT GENERATE A REPLY\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "cSx3s7TBBegg"
-   },
-   "source": [
-    "### Why route chat messages through Kafka?\n",
-    "\n",
-    "It's easier to interact with the LLM directly using LangChains built-in conversation management features. Plus you can also use a REST API to generate a response from an externally hosted model. So why go to the trouble of using Apache Kafka?\n",
-    "\n",
-    "There are a few reasons, such as:\n",
-    "\n",
-    "  * **Integration**: Many enterprises want to run their own LLMs so that they can keep their data in-house. This requires integrating LLM-powered components into existing architectures that might already be decoupled using some kind of message bus.\n",
-    "\n",
-    "  * **Scalability**: Apache Kafka is designed with parallel processing in mind, so many teams prefer to use it to more effectively distribute work to available workers (in this case the \"worker\" is a container running an LLM).\n",
-    "\n",
-    "  * **Durability**: Kafka is designed to allow services to pick up where another service left off in the case where that service experienced a memory issue or went offline. This prevents data loss in highly complex, distribuited architectures where multiple systems are communicating with one another (LLMs being just one of many interdependent systems that also include vector databases and traditional databases).\n",
-    "\n",
-    "For more background on why event streaming is a good fit for Gen AI application architecture, see Kai Waehner's article [\"Apache Kafka + Vector Database + LLM = Real-Time GenAI\"](https://www.kai-waehner.de/blog/2023/11/08/apache-kafka-flink-vector-database-llm-real-time-genai/)."
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cookbook/autogpt/autogpt.ipynb

@@ -28,9 +28,9 @@
    "outputs": [],
    "source": [
     "from langchain.agents import Tool\n",
-    "from langchain_community.tools.file_management.read import ReadFileTool\n",
-    "from langchain_community.tools.file_management.write import WriteFileTool\n",
-    "from langchain_community.utilities import SerpAPIWrapper\n",
+    "from langchain.tools.file_management.read import ReadFileTool\n",
+    "from langchain.tools.file_management.write import WriteFileTool\n",
+    "from langchain.utilities import SerpAPIWrapper\n",
     "\n",
     "search = SerpAPIWrapper()\n",
     "tools = [\n",
@@ -62,8 +62,8 @@
    "outputs": [],
    "source": [
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {
@@ -100,8 +100,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.autonomous_agents import AutoGPT\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain_experimental.autonomous_agents import AutoGPT"
    ]
   },
   {
@@ -167,7 +167,7 @@
    },
    "outputs": [],
    "source": [
-    "from langchain_community.chat_message_histories import FileChatMessageHistory\n",
+    "from langchain.memory.chat_message_histories import FileChatMessageHistory\n",
     "\n",
     "agent = AutoGPT.from_llm_and_tools(\n",
     "    ai_name=\"Tom\",\n",

cookbook/autogpt/marathon_times.ipynb

@@ -39,10 +39,10 @@
     "\n",
     "import nest_asyncio\n",
     "import pandas as pd\n",
+    "from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.docstore.document import Document\n",
-    "from langchain_community.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
     "from langchain_experimental.autonomous_agents import AutoGPT\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# Needed synce jupyter runs an async eventloop\n",
     "nest_asyncio.apply()"
@@ -93,8 +93,8 @@
     "from typing import Optional\n",
     "\n",
     "from langchain.agents import tool\n",
-    "from langchain_community.tools.file_management.read import ReadFileTool\n",
-    "from langchain_community.tools.file_management.write import WriteFileTool\n",
+    "from langchain.tools.file_management.read import ReadFileTool\n",
+    "from langchain.tools.file_management.write import WriteFileTool\n",
     "\n",
     "ROOT_DIR = \"./data/\"\n",
     "\n",
@@ -311,8 +311,8 @@
     "# Memory\n",
     "import faiss\n",
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS\n",
     "\n",
     "embeddings_model = OpenAIEmbeddings()\n",
     "embedding_size = 1536\n",

cookbook/baby_agi.ipynb

@@ -31,8 +31,9 @@
    "source": [
     "from typing import Optional\n",
     "\n",
-    "from langchain_experimental.autonomous_agents import BabyAGI\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain_experimental.autonomous_agents import BabyAGI"
    ]
   },
   {
@@ -53,7 +54,7 @@
    "outputs": [],
    "source": [
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/baby_agi_with_agent.ipynb

@@ -28,9 +28,10 @@
     "from typing import Optional\n",
     "\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_experimental.autonomous_agents import BabyAGI\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain_experimental.autonomous_agents import BabyAGI"
    ]
   },
   {
@@ -62,7 +63,7 @@
     "%pip install faiss-cpu > /dev/null\n",
     "%pip install google-search-results > /dev/null\n",
     "from langchain.docstore import InMemoryDocstore\n",
-    "from langchain_community.vectorstores import FAISS"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {
@@ -107,8 +108,8 @@
    "source": [
     "from langchain.agents import AgentExecutor, Tool, ZeroShotAgent\n",
     "from langchain.chains import LLMChain\n",
-    "from langchain_community.utilities import SerpAPIWrapper\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities import SerpAPIWrapper\n",
     "\n",
     "todo_prompt = PromptTemplate.from_template(\n",
     "    \"You are a planner who is an expert at coming up with a todo list for a given objective. Come up with a todo list for this objective: {objective}\"\n",

cookbook/camel_role_playing.ipynb

@@ -36,6 +36,7 @@
    "source": [
     "from typing import List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts.chat import (\n",
     "    HumanMessagePromptTemplate,\n",
     "    SystemMessagePromptTemplate,\n",
@@ -45,8 +46,7 @@
     "    BaseMessage,\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/causal_program_aided_language_model.ipynb

@@ -47,9 +47,9 @@
    "outputs": [],
    "source": [
     "from IPython.display import SVG\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.cpal.base import CPALChain\n",
     "from langchain_experimental.pal_chain import PALChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0, max_tokens=512)\n",
     "cpal_chain = CPALChain.from_univariate_prompt(llm=llm, verbose=True)\n",

cookbook/code-analysis-deeplake.ipynb

@@ -23,9 +23,9 @@
    "metadata": {},
    "source": [
     "1. Prepare data:\n",
-    "   1. Upload all python project files using the `langchain_community.document_loaders.TextLoader`. We will call these files the **documents**.\n",
+    "   1. Upload all python project files using the `langchain.document_loaders.TextLoader`. We will call these files the **documents**.\n",
     "   2. Split all documents to chunks using the `langchain.text_splitter.CharacterTextSplitter`.\n",
-    "   3. Embed chunks and upload them into the DeepLake using `langchain.embeddings.openai.OpenAIEmbeddings` and `langchain_community.vectorstores.DeepLake`\n",
+    "   3. Embed chunks and upload them into the DeepLake using `langchain.embeddings.openai.OpenAIEmbeddings` and `langchain.vectorstores.DeepLake`\n",
     "2. Question-Answering:\n",
     "   1. Build a chain from `langchain.chat_models.ChatOpenAI` and `langchain.chains.ConversationalRetrievalChain`\n",
     "   2. Prepare questions.\n",
@@ -166,7 +166,7 @@
     }
    ],
    "source": [
-    "from langchain_community.document_loaders import TextLoader\n",
+    "from langchain.document_loaders import TextLoader\n",
     "\n",
     "root_dir = \"../../../../../../libs\"\n",
     "\n",
@@ -657,7 +657,7 @@
     }
    ],
    "source": [
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
     "\n",
     "embeddings = OpenAIEmbeddings()\n",
     "embeddings"
@@ -706,7 +706,7 @@
     {
      "data": {
       "text/plain": [
-       "<langchain_community.vectorstores.deeplake.DeepLake at 0x7fe1b67d7a30>"
+       "<langchain.vectorstores.deeplake.DeepLake at 0x7fe1b67d7a30>"
       ]
      },
      "execution_count": 15,
@@ -715,7 +715,7 @@
     }
    ],
    "source": [
-    "from langchain_community.vectorstores import DeepLake\n",
+    "from langchain.vectorstores import DeepLake\n",
     "\n",
     "username = \"<USERNAME_OR_ORG>\"\n",
     "\n",
@@ -740,7 +740,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# from langchain_community.vectorstores import DeepLake\n",
+    "# from langchain.vectorstores import DeepLake\n",
     "\n",
     "# db = DeepLake.from_documents(\n",
     "#     texts, embeddings, dataset_path=f\"hub://{<org_id>}/langchain-code\", runtime={\"tensor_db\": True}\n",
@@ -834,7 +834,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains import ConversationalRetrievalChain\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(\n",
     "    model_name=\"gpt-3.5-turbo-0613\"\n",

cookbook/custom_agent_with_plugin_retrieval.ipynb

@@ -40,12 +40,12 @@
     "    AgentOutputParser,\n",
     "    LLMSingleActionAgent,\n",
     ")\n",
+    "from langchain.agents.agent_toolkits import NLAToolkit\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
-    "from langchain_community.agent_toolkits import NLAToolkit\n",
-    "from langchain_community.tools.plugin import AIPlugin\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.tools.plugin import AIPlugin"
    ]
   },
   {
@@ -114,9 +114,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.schema import Document\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb

@@ -65,12 +65,12 @@
     "    AgentOutputParser,\n",
     "    LLMSingleActionAgent,\n",
     ")\n",
+    "from langchain.agents.agent_toolkits import NLAToolkit\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
-    "from langchain_community.agent_toolkits import NLAToolkit\n",
-    "from langchain_community.tools.plugin import AIPlugin\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.tools.plugin import AIPlugin"
    ]
   },
   {
@@ -138,9 +138,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.schema import Document\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import FAISS"
    ]
   },
   {

cookbook/databricks_sql_db.ipynb

@@ -80,7 +80,7 @@
    "outputs": [],
    "source": [
     "# Connecting to Databricks with SQLDatabase wrapper\n",
-    "from langchain_community.utilities import SQLDatabase\n",
+    "from langchain.utilities import SQLDatabase\n",
     "\n",
     "db = SQLDatabase.from_databricks(catalog=\"samples\", schema=\"nyctaxi\")"
    ]
@@ -93,7 +93,7 @@
    "outputs": [],
    "source": [
     "# Creating a OpenAI Chat LLM wrapper\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "\n",
     "llm = ChatOpenAI(temperature=0, model_name=\"gpt-4\")"
    ]
@@ -115,7 +115,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import SQLDatabaseChain\n",
+    "from langchain.utilities import SQLDatabaseChain\n",
     "\n",
     "db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)"
    ]
@@ -177,7 +177,7 @@
    "outputs": [],
    "source": [
     "from langchain.agents import create_sql_agent\n",
-    "from langchain_community.agent_toolkits import SQLDatabaseToolkit\n",
+    "from langchain.agents.agent_toolkits import SQLDatabaseToolkit\n",
     "\n",
     "toolkit = SQLDatabaseToolkit(db=db, llm=llm)\n",
     "agent = create_sql_agent(llm=llm, toolkit=toolkit, verbose=True)"

cookbook/deeplake_semantic_search_over_chat.ipynb

@@ -52,12 +52,13 @@
     "import os\n",
     "\n",
     "from langchain.chains import RetrievalQA\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.text_splitter import (\n",
     "    CharacterTextSplitter,\n",
     "    RecursiveCharacterTextSplitter,\n",
     ")\n",
-    "from langchain_community.vectorstores import DeepLake\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import DeepLake\n",
     "\n",
     "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")\n",
     "activeloop_token = getpass.getpass(\"Activeloop Token:\")\n",

cookbook/docugami_xml_kg_rag.ipynb

@@ -34,12 +34,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "5740fc70-c513-4ff4-9d72-cfc098f85fef",
    "metadata": {},
    "outputs": [],
    "source": [
-    "! pip install langchain docugami==0.0.8 dgml-utils==0.3.0 pydantic langchainhub chromadb hnswlib --upgrade --quiet"
+    "! pip install langchain docugami==0.0.4 dgml-utils==0.2.0 pydantic langchainhub chromadb --upgrade --quiet"
    ]
   },
   {
@@ -63,7 +63,7 @@
     "1. Create an access token via the Developer Playground for your workspace. [Detailed instructions](https://help.docugami.com/home/docugami-api).\n",
     "1. Add your documents (PDF \\[scanned or digital\\], DOC or DOCX) to Docugami for processing. There are two ways to do this:\n",
     "    1. Use the simple Docugami web experience. [Detailed instructions](https://help.docugami.com/home/adding-documents).\n",
-    "    1. Use the [Docugami API](https://api-docs.docugami.com), specifically the [documents](https://api-docs.docugami.com/#tag/documents/operation/upload-document) endpoint. You can also use the [docugami python library](https://pypi.org/project/docugami/) as a convenient wrapper.\n",
+    "    1. Use the [Docugami API](https://api-docs.docugami.com), specifically the [documents](https://api-docs.docugami.com/#tag/documents/operation/upload-document) endpoint. Code samples are available for [python](../upload_file/) and [JavaScript](../../js/upload-file/) or you can use the [docugami](https://pypi.org/project/docugami/) python library.\n",
     "\n",
     "Once your documents are in Docugami, they are processed and organized into sets of similar documents, e.g. NDAs, Lease Agreements, and Service Agreements. Docugami is not limited to any particular types of documents, and the clusters created depend on your particular documents. You can [change the docset assignments](https://help.docugami.com/home/working-with-the-doc-sets-view) later if you wish. You can monitor file status in the simple Docugami webapp, or use a [webhook](https://api-docs.docugami.com/#tag/webhooks) to be informed when your documents are done processing.\n",
     "\n",
@@ -76,7 +76,98 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 45,
+   "id": "fc0767d4-9155-4591-855c-ef2e14e0e10f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import tempfile\n",
+    "from pathlib import Path\n",
+    "from pprint import pprint\n",
+    "from time import sleep\n",
+    "from typing import Dict, List\n",
+    "\n",
+    "import requests\n",
+    "from docugami import Docugami\n",
+    "from docugami.types import Document as DocugamiDocument\n",
+    "\n",
+    "api_key = os.environ.get(\"DOCUGAMI_API_KEY\")\n",
+    "if not api_key:\n",
+    "    raise Exception(\"Please set Docugami API key environment variable\")\n",
+    "\n",
+    "client = Docugami()\n",
+    "\n",
+    "\n",
+    "def upload_files(local_paths: List[str], docset_name: str) -> List[DocugamiDocument]:\n",
+    "    docset_list_response = client.docsets.list(name=docset_name)\n",
+    "    if docset_list_response and docset_list_response.docsets:\n",
+    "        # Docset already exists with this name\n",
+    "        docset_id = docset_list_response.docsets[0]\n",
+    "    else:\n",
+    "        dg_docset = client.docsets.create(name=docset_name)\n",
+    "        docset_id = dg_docset.id\n",
+    "\n",
+    "    document_list_response = client.documents.list(limit=int(1e5))\n",
+    "    dg_docs: List[DocugamiDocument] = []\n",
+    "    if document_list_response and document_list_response.documents:\n",
+    "        new_names = [Path(f).name for f in local_paths]\n",
+    "\n",
+    "        dg_docs = [\n",
+    "            d\n",
+    "            for d in document_list_response.documents\n",
+    "            if Path(d.name).name in new_names\n",
+    "        ]\n",
+    "        existing_names = [Path(d.name).name for d in dg_docs]\n",
+    "\n",
+    "        # Upload any files not previously uploaded\n",
+    "        for f in local_paths:\n",
+    "            if Path(f).name not in existing_names:\n",
+    "                dg_docs.append(\n",
+    "                    client.documents.contents.upload(\n",
+    "                        file=Path(f).absolute(),\n",
+    "                        docset_id=docset_id,\n",
+    "                    )\n",
+    "                )\n",
+    "    return dg_docs\n",
+    "\n",
+    "\n",
+    "def wait_for_xml(dg_docs: List[DocugamiDocument]) -> dict[str, str]:\n",
+    "    dgml_paths: dict[str, str] = {}\n",
+    "    while len(dgml_paths) < len(dg_docs):\n",
+    "        for doc in dg_docs:\n",
+    "            doc = client.documents.retrieve(doc.id)  # update with latest\n",
+    "            current_status = doc.status\n",
+    "            if current_status == \"Error\":\n",
+    "                raise Exception(\n",
+    "                    \"Document could not be processed, please confirm it is not a zero length, corrupt or password protected file\"\n",
+    "                )\n",
+    "            elif current_status == \"Ready\":\n",
+    "                dgml_url = doc.docset.url + f\"/documents/{doc.id}/dgml\"\n",
+    "                headers = {\"Authorization\": f\"Bearer {api_key}\"}\n",
+    "                dgml_response = requests.get(dgml_url, headers=headers)\n",
+    "                if not dgml_response.ok:\n",
+    "                    raise Exception(\n",
+    "                        f\"Could not download DGML artifact {dgml_url}: {dgml_response.status_code}\"\n",
+    "                    )\n",
+    "                dgml_contents = dgml_response.text\n",
+    "                with tempfile.NamedTemporaryFile(delete=False, mode=\"w\") as temp_file:\n",
+    "                    temp_file.write(dgml_contents)\n",
+    "                    temp_file_path = temp_file.name\n",
+    "                    dgml_paths[doc.name] = temp_file_path\n",
+    "\n",
+    "        print(f\"{len(dgml_paths)} docs done processing out of {len(dg_docs)}...\")\n",
+    "\n",
+    "        if len(dgml_paths) == len(dg_docs):\n",
+    "            # done\n",
+    "            return dgml_paths\n",
+    "        else:\n",
+    "            sleep(30)  # try again in a bit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
    "id": "ce0b2b21-7623-46e7-ae2c-3a9f67e8b9b9",
    "metadata": {},
    "outputs": [
@@ -84,22 +175,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "{'Report_CEN23LA277_192541.pdf': '/tmp/tmpa0c77x46',\n",
-      " 'Report_CEN23LA338_192753.pdf': '/tmp/tmpaftfld2w',\n",
-      " 'Report_CEN23LA363_192876.pdf': '/tmp/tmpn7gp6be2',\n",
-      " 'Report_CEN23LA394_192995.pdf': '/tmp/tmp9udymprf',\n",
-      " 'Report_ERA23LA114_106615.pdf': '/tmp/tmpxdjbh4r_',\n",
-      " 'Report_WPR23LA254_192532.pdf': '/tmp/tmpz6h75a0h'}\n"
+      "6 docs done processing out of 6...\n",
+      "{'Report_CEN23LA277_192541.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmpel3o0rpg',\n",
+      " 'Report_CEN23LA338_192753.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmpgugb9ut1',\n",
+      " 'Report_CEN23LA363_192876.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmp3_gf2sky',\n",
+      " 'Report_CEN23LA394_192995.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmpwmfgoxkl',\n",
+      " 'Report_ERA23LA114_106615.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmptibrz2yu',\n",
+      " 'Report_WPR23LA254_192532.pdf': '/var/folders/0h/6cchx4k528bdj8cfcsdm0dqr0000gn/T/tmpvazrbbsi'}\n"
      ]
     }
    ],
    "source": [
-    "from pprint import pprint\n",
-    "\n",
-    "from docugami import Docugami\n",
-    "from docugami.lib.upload import upload_to_named_docset, wait_for_dgml\n",
-    "\n",
-    "#### START DOCSET INFO (please change this values as needed)\n",
+    "#### START DOCSET INFO (please change)\n",
     "DOCSET_NAME = \"NTSB Aviation Incident Reports\"\n",
     "FILE_PATHS = [\n",
     "    \"/Users/tjaffri/ntsb/Report_CEN23LA277_192541.pdf\",\n",
@@ -110,15 +197,13 @@
     "    \"/Users/tjaffri/ntsb/Report_WPR23LA254_192532.pdf\",\n",
     "]\n",
     "\n",
-    "# Note: Please specify ~6 (or more!) similar files to process together as a document set\n",
-    "#       This is currently a requirement for Docugami to automatically detect motifs\n",
-    "#       across the document set to generate a semantic XML Knowledge Graph.\n",
-    "assert len(FILE_PATHS) > 5, \"Please provide at least 6 files\"\n",
+    "assert (\n",
+    "    len(FILE_PATHS) > 5\n",
+    ")  # Please specify ~6 (or more!) similar files to process together as a document set\n",
     "#### END DOCSET INFO\n",
     "\n",
-    "dg_client = Docugami()\n",
-    "dg_docs = upload_to_named_docset(dg_client, FILE_PATHS, DOCSET_NAME)\n",
-    "dgml_paths = wait_for_dgml(dg_client, dg_docs)\n",
+    "dg_docs = upload_files(FILE_PATHS, DOCSET_NAME)\n",
+    "dgml_paths = wait_for_xml(dg_docs)\n",
     "\n",
     "pprint(dgml_paths)"
    ]
@@ -143,7 +228,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 47,
    "id": "05fcdd57-090f-44bf-a1fb-2c3609c80e34",
    "metadata": {},
    "outputs": [
@@ -152,13 +237,13 @@
      "output_type": "stream",
      "text": [
       "found 30 chunks, here are the first few\n",
-      "<AviationInvestigationFinalReport-section>Aviation </AviationInvestigationFinalReport-section>Investigation Final Report\n",
-      "<table><tbody><tr><td>Location: </td> <td><Location><TownName>Elbert</TownName>, <USState>Colorado </USState></Location></td> <td>Accident Number: </td> <td><AccidentNumber>CEN23LA277 </AccidentNumber></td></tr> <tr><td><LocationDateTime>Date &amp; Time: </LocationDateTime></td> <td><DateTime><EventDate>June 26, 2023</EventDate>, <EventTime>11:00 Local </EventTime></DateTime></td> <td><DateTimeAccidentNumber>Registration: </DateTimeAccidentNumber></td> <td><Registration>N23161 </Registration></td></tr> <tr><td><LocationAircraft>Aircraft: </LocationAircraft></td> <td><AircraftType>Piper <AircraftType>J3C-50 </AircraftType></AircraftType></td> <td><AircraftAccidentNumber>Aircraft Damage: </AircraftAccidentNumber></td> <td><AircraftDamage>Substantial </AircraftDamage></td></tr> <tr><td><LocationDefiningEvent>Defining Event: </LocationDefiningEvent></td> <td><DefiningEvent>Nose over/nose down </DefiningEvent></td> <td><DefiningEventAccidentNumber>Injuries: </DefiningEventAccidentNumber></td> <td><Injuries><Minor>1 </Minor>Minor </Injuries></td></tr> <tr><td><LocationFlightConductedUnder>Flight Conducted Under: </LocationFlightConductedUnder></td> <td><FlightConductedUnder><Part91-cell>Part <RegulationPart>91</RegulationPart>: General aviation - Personal </Part91-cell></FlightConductedUnder></td><td/><td><FlightConductedUnderCEN23LA277/></td></tr></tbody></table>\n",
+      "Aviation Investigation Final Report\n",
+      "<table><tbody><tr><td>Location: </td> <td><Location><TownName>Elbert</TownName>, <USState>Colorado </USState></Location></td> <td>Accident Number: </td> <td><AccidentNumber>CEN23LA277 </AccidentNumber></td></tr> <tr><td><LocationDateTime>Date &amp; Time: </LocationDateTime></td> <td><DateTime><EventDate>June 26, 2023</EventDate>, <EventTime>11:00 Local </EventTime></DateTime></td> <td><DateTimeAccidentNumber>Registration: </DateTimeAccidentNumber></td> <td><Registration>N23161 </Registration></td></tr> <tr><td><LocationAircraft>Aircraft: </LocationAircraft></td> <td><Aircraft>Piper <AircraftType>J3C-50 </AircraftType></Aircraft></td> <td><AircraftAccidentNumber>Aircraft Damage: </AircraftAccidentNumber></td> <td><AircraftDamage>Substantial </AircraftDamage></td></tr> <tr><td><LocationDefiningEvent>Defining Event: </LocationDefiningEvent></td> <td><DefiningEvent>Nose over/nose down </DefiningEvent></td> <td><DefiningEventAccidentNumber>Injuries: </DefiningEventAccidentNumber></td> <td><Injuries><Minor>1 </Minor>Minor </Injuries></td></tr> <tr><td><LocationFlightConductedUnder>Flight Conducted Under: </LocationFlightConductedUnder></td> <td><Part91-cell>Part <RegulationPart>91</RegulationPart>: General aviation - Personal </Part91-cell></td><td/><td><FlightConductedUnderCEN23LA277/></td></tr></tbody></table>\n",
       "Analysis\n",
-      "<TakeoffAccident> <Analysis>The pilot reported that, as the tail lifted during takeoff, the airplane veered left. He attempted to correct with full right rudder and full brakes. However, the airplane subsequently nosed over resulting in substantial damage to the fuselage, lift struts, rudder, and vertical stabilizer. </Analysis></TakeoffAccident>\n",
+      "<TakeoffAccident> The pilot reported that, as the tail lifted during takeoff, the airplane veered left. He attempted to correct with full right rudder and full brakes. However, the airplane subsequently nosed over resulting in substantial damage to the fuselage, lift struts, rudder, and vertical stabilizer. </TakeoffAccident>\n",
       "<AircraftCondition> The pilot reported that there were no preaccident mechanical malfunctions or anomalies with the airplane that would have precluded normal operation. </AircraftCondition>\n",
       "<WindConditions> At about the time of the accident, wind was from <WindDirection>180</WindDirection>° at <WindConditions>5 </WindConditions>knots. The pilot decided to depart on runway <Runway>35 </Runway>due to the prevailing airport traffic. He stated that departing with “more favorable wind conditions” may have prevented the accident. </WindConditions>\n",
-      "<ProbableCauseAndFindings-section>Probable Cause and Findings </ProbableCauseAndFindings-section>\n",
+      "Probable Cause and Findings\n",
       "<ProbableCause> The <ProbableCause>National Transportation Safety Board </ProbableCause>determines the probable cause(s) of this accident to be: </ProbableCause>\n",
       "<AccidentCause> The pilot's loss of directional control during takeoff and subsequent excessive use of brakes which resulted in a nose-over. Contributing to the accident was his decision to takeoff downwind. </AccidentCause>\n",
       "Page 1 of <PageNumber>5 </PageNumber>\n"
@@ -166,8 +251,6 @@
     }
    ],
    "source": [
-    "from pathlib import Path\n",
-    "\n",
     "from dgml_utils.segmentation import get_chunks_str\n",
     "\n",
     "# Here we just read the first file, you can do the same for others\n",
@@ -200,7 +283,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 48,
    "id": "8a4b49e0-de78-4790-a930-ad7cf324697a",
    "metadata": {},
    "outputs": [
@@ -260,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 109,
    "id": "7b697d30-1e94-47f0-87e8-f81d4b180da2",
    "metadata": {},
    "outputs": [
@@ -270,14 +353,12 @@
        "39"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 109,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "import requests\n",
-    "\n",
     "# Download XML from known URL\n",
     "dgml = requests.get(\n",
     "    \"https://raw.githubusercontent.com/docugami/dgml-utils/main/python/tests/test_data/article/Jane%20Doe.xml\"\n",
@@ -288,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 98,
    "id": "14714576-6e1d-499b-bcc8-39140bb2fd78",
    "metadata": {},
    "outputs": [
@@ -298,7 +379,7 @@
        "{'h1': 9, 'div': 12, 'p': 3, 'lim h1': 9, 'lim': 1, 'table': 1, 'h1 div': 4}"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 98,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -319,7 +400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 99,
    "id": "5462f29e-fd59-4e0e-9493-ea3b560e523e",
    "metadata": {},
    "outputs": [
@@ -352,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 100,
    "id": "2b4ece00-2e43-4254-adc9-66dbb79139a6",
    "metadata": {},
    "outputs": [
@@ -390,7 +471,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 101,
    "id": "08350119-aa22-4ec1-8f65-b1316a0d4123",
    "metadata": {},
    "outputs": [
@@ -418,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 112,
    "id": "bcac8294-c54a-4b6e-af9d-3911a69620b2",
    "metadata": {},
    "outputs": [
@@ -465,18 +546,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 113,
    "id": "8e275736-3408-4d7a-990e-4362c88e81f8",
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import (\n",
     "    ChatPromptTemplate,\n",
     "    HumanMessagePromptTemplate,\n",
     "    SystemMessagePromptTemplate,\n",
     ")\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.schema.output_parser import StrOutputParser"
    ]
   },
   {
@@ -496,7 +577,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 114,
    "id": "1b12536a-1303-41ad-9948-4eb5a5f32614",
    "metadata": {},
    "outputs": [],
@@ -513,7 +594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 115,
    "id": "8d8b567c-b442-4bf0-b639-04bd89effc62",
    "metadata": {},
    "outputs": [],
@@ -538,18 +619,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 116,
    "id": "346c3a02-8fea-4f75-a69e-fc9542b99dbc",
    "metadata": {},
    "outputs": [],
    "source": [
     "import uuid\n",
     "\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
     "from langchain.storage import InMemoryStore\n",
-    "from langchain_community.vectorstores.chroma import Chroma\n",
-    "from langchain_core.documents import Document\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.vectorstores.chroma import Chroma\n",
     "\n",
     "\n",
     "def build_retriever(text_elements, tables, table_summaries):\n",
@@ -600,12 +681,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 117,
    "id": "f2489de4-51e3-48b4-bbcd-ed9171deadf3",
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.runnables import RunnablePassthrough\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "system_prompt = SystemMessagePromptTemplate.from_template(\n",
     "    \"You are a helpful assistant that answers questions based on provided context. Your provided context can include text or tables, \"\n",
@@ -644,17 +725,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 120,
    "id": "636e992f-823b-496b-a082-8b4fcd479de5",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Number of requested results 4 is greater than number of elements in index 1, updating n_results = 1\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -696,7 +770,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 121,
    "id": "0e4a2f43-dd48-4ae3-8e27-7e87d169965f",
    "metadata": {},
    "outputs": [
@@ -706,7 +780,7 @@
        "669"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 121,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -721,7 +795,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 124,
    "id": "56b78fb3-603d-4343-ae72-be54a3c5dd72",
    "metadata": {},
    "outputs": [
@@ -746,7 +820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 125,
    "id": "d3cc5ba9-8553-4eda-a5d1-b799751186af",
    "metadata": {},
    "outputs": [],
@@ -758,7 +832,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 126,
    "id": "d7c73faf-74cb-400d-8059-b69e2493de38",
    "metadata": {},
    "outputs": [],
@@ -770,7 +844,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 127,
    "id": "4c553722-be42-42ce-83b8-76a17f323f1c",
    "metadata": {},
    "outputs": [],
@@ -780,7 +854,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 128,
    "id": "65dce40b-f1c3-494a-949e-69a9c9544ddb",
    "metadata": {},
    "outputs": [
@@ -790,7 +864,7 @@
        "'The number of training tokens for LLaMA2 is 2.0T for all parameter sizes.'"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -885,51 +959,14 @@
     "        </tr>\n",
     "    </tbody>\n",
     "</table>\n",
-    "```"
+    "``"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "867f8e11-384c-4aa1-8b3e-c59fb8d5fd7d",
+   "id": "0879349e-7298-4f2c-b246-f1142e97a8e5",
    "metadata": {},
-   "source": [
-    "Finally, you can ask other questions that rely on more subtle parsing of the table, e.g.:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "id": "d38f1459-7d2b-40df-8dcd-e747f85eb144",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'The learning rate for LLaMA2 was 3.0 × 10−4 for the 7B and 13B models, and 1.5 × 10−4 for the 34B and 70B models.'"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "llama2_chain.invoke(\"What was the learning rate for LLaMA2?\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "94826165",
-   "metadata": {},
-   "source": [
-    "## Docugami KG-RAG Template\n",
-    "\n",
-    "Docugami also provides a [langchain template](https://github.com/docugami/langchain-template-docugami-kg-rag) that you can integrate into your langchain projects.\n",
-    "\n",
-    "Here's a walkthrough of how you can do this.\n",
-    "\n",
-    "[![Docugami KG-RAG Walkthrough](https://img.youtube.com/vi/xOHOmL1NFMg/0.jpg)](https://www.youtube.com/watch?v=xOHOmL1NFMg)\n"
-   ]
+   "source": []
   }
  ],
  "metadata": {

cookbook/elasticsearch_db_qa.ipynb

@@ -39,7 +39,7 @@
    "source": [
     "from elasticsearch import Elasticsearch\n",
     "from langchain.chains.elasticsearch_database import ElasticsearchDatabaseChain\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI"
    ]
   },
   {

cookbook/extraction_openai_tools.ipynb

@@ -22,8 +22,8 @@
     "from typing import List, Optional\n",
     "\n",
     "from langchain.chains.openai_tools import create_extraction_chain_pydantic\n",
-    "from langchain_core.pydantic_v1 import BaseModel\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.pydantic_v1 import BaseModel"
    ]
   },
   {
@@ -151,11 +151,11 @@
     "\n",
     "from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
-    "from langchain_core.runnables import Runnable\n",
-    "from langchain_core.pydantic_v1 import BaseModel\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.messages import SystemMessage\n",
-    "from langchain_core.language_models import BaseLanguageModel\n",
+    "from langchain.schema.runnable import Runnable\n",
+    "from langchain.pydantic_v1 import BaseModel\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.messages import SystemMessage\n",
+    "from langchain.schema.language_model import BaseLanguageModel\n",
     "\n",
     "_EXTRACTION_TEMPLATE = \"\"\"Extract and save the relevant entities mentioned \\\n",
     "in the following passage together with their properties.\n",

cookbook/fake_llm.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.llms.fake import FakeListLLM"
+    "from langchain.llms.fake import FakeListLLM"
    ]
   },
   {

cookbook/forward_looking_retrieval_augmented_generation.ipynb

@@ -73,9 +73,10 @@
     "    AsyncCallbackManagerForRetrieverRun,\n",
     "    CallbackManagerForRetrieverRun,\n",
     ")\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.schema import BaseRetriever, Document\n",
-    "from langchain_community.utilities import GoogleSerperAPIWrapper\n",
-    "from langchain_openai import ChatOpenAI, OpenAI"
+    "from langchain.utilities import GoogleSerperAPIWrapper"
    ]
   },
   {

cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb

@@ -47,10 +47,11 @@
     "from datetime import datetime, timedelta\n",
     "from typing import List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.docstore import InMemoryDocstore\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers import TimeWeightedVectorStoreRetriever\n",
-    "from langchain_community.vectorstores import FAISS\n",
-    "from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import FAISS\n",
     "from termcolor import colored"
    ]
   },

cookbook/hugginggpt.ipynb

@@ -75,8 +75,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.autonomous_agents import HuggingGPT\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "# %env OPENAI_API_BASE=http://localhost:8000/v1"
    ]

cookbook/human_input_chat_model.ipynb

@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.chat_models.human import HumanInputChatModel"
+    "from langchain.chat_models.human import HumanInputChatModel"
    ]
   },
   {

cookbook/human_input_llm.ipynb

@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.llms.human import HumanInputLLM"
+    "from langchain.llms.human import HumanInputLLM"
    ]
   },
   {

cookbook/hypothetical_document_embeddings.ipynb

@@ -21,8 +21,9 @@
    "outputs": [],
    "source": [
     "from langchain.chains import HypotheticalDocumentEmbedder, LLMChain\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI, OpenAIEmbeddings"
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {
@@ -171,7 +172,7 @@
    "outputs": [],
    "source": [
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.vectorstores import Chroma\n",
     "\n",
     "with open(\"../../state_of_the_union.txt\") as f:\n",
     "    state_of_the_union = f.read()\n",

cookbook/learned_prompt_optimization.ipynb

@@ -49,9 +49,9 @@
    "source": [
     "# pick and configure the LLM of your choice\n",
     "\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
-    "llm = OpenAI(model=\"gpt-3.5-turbo-instruct\")"
+    "llm = OpenAI(model=\"text-davinci-003\")"
    ]
   },
   {

cookbook/llm_bash.ipynb

@@ -43,8 +43,8 @@
     }
    ],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.llm_bash.base import LLMBashChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "\n",

cookbook/llm_checker.ipynb

@@ -42,7 +42,7 @@
    ],
    "source": [
     "from langchain.chains import LLMCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0.7)\n",
     "\n",

cookbook/llm_math.ipynb

@@ -46,7 +46,7 @@
    ],
    "source": [
     "from langchain.chains import LLMMathChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "llm_math = LLMMathChain.from_llm(llm, verbose=True)\n",

cookbook/llm_summarization_checker.ipynb

@@ -331,7 +331,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=2)\n",
@@ -822,7 +822,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, verbose=True, max_checks=3)\n",
@@ -1096,7 +1096,7 @@
    ],
    "source": [
     "from langchain.chains import LLMSummarizationCheckerChain\n",
-    "from langchain_openai import OpenAI\n",
+    "from langchain.llms import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "checker_chain = LLMSummarizationCheckerChain.from_llm(llm, max_checks=3, verbose=True)\n",

cookbook/llm_symbolic_math.ipynb

@@ -14,8 +14,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.llms import OpenAI\n",
     "from langchain_experimental.llm_symbolic_math.base import LLMSymbolicMathChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "llm = OpenAI(temperature=0)\n",
     "llm_symbolic_math = LLMSymbolicMathChain.from_llm(llm)"

cookbook/meta_prompt.ipynb

@@ -57,9 +57,9 @@
    "outputs": [],
    "source": [
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.memory import ConversationBufferWindowMemory\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {

cookbook/multi_modal_QA.ipynb

@@ -91,8 +91,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema.messages import HumanMessage, SystemMessage"
    ]
   },
   {

cookbook/multi_modal_RAG_chroma.ipynb

@@ -42,7 +42,7 @@
     "* We will use Open Clip multi-modal embeddings.\n",
     "* We will use [Chroma](https://www.trychroma.com/) with support for multi-modal.\n",
     "\n",
-    "A separate cookbook highlights `Options 2 and 3` [here](https://github.com/langchain-ai/langchain/blob/master/cookbook/Multi_modal_RAG.ipynb).\n",
+    "A seperate cookbook highlights `Options 2 and 3` [here](https://github.com/langchain-ai/langchain/blob/master/cookbook/Multi_modal_RAG.ipynb).\n",
     "\n",
     "![chroma_multimodal.png](attachment:1920fda3-1808-407c-9820-f518c9c6f566.png)\n",
     "\n",
@@ -187,7 +187,7 @@
     "\n",
     "import chromadb\n",
     "import numpy as np\n",
-    "from langchain_community.vectorstores import Chroma\n",
+    "from langchain.vectorstores import Chroma\n",
     "from langchain_experimental.open_clip import OpenCLIPEmbeddings\n",
     "from PIL import Image as _PILImage\n",
     "\n",
@@ -315,10 +315,10 @@
    "source": [
     "from operator import itemgetter\n",
     "\n",
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.runnables import RunnableLambda, RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema.messages import HumanMessage, SystemMessage\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnableLambda, RunnablePassthrough\n",
     "\n",
     "\n",
     "def prompt_func(data_dict):\n",

cookbook/multi_modal_output_agent.ipynb

@@ -31,7 +31,7 @@
    "source": [
     "import re\n",
     "\n",
-    "from IPython.display import Image, display\n",
+    "from IPython.display import Image\n",
     "from steamship import Block, Steamship"
    ]
   },
@@ -43,8 +43,8 @@
    "outputs": [],
    "source": [
     "from langchain.agents import AgentType, initialize_agent\n",
-    "from langchain.tools import SteamshipImageGenerationTool\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.llms import OpenAI\n",
+    "from langchain.tools import SteamshipImageGenerationTool"
    ]
   },
   {
@@ -180,7 +180,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.3"
   }
  },
  "nbformat": 4,

cookbook/multi_player_dnd.ipynb

@@ -28,11 +28,11 @@
    "source": [
     "from typing import Callable, List\n",
     "\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/multiagent_authoritarian.ipynb

@@ -33,6 +33,7 @@
     "from typing import Callable, List\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.prompts import (\n",
     "    PromptTemplate,\n",
@@ -40,8 +41,7 @@
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/multiagent_bidding.ipynb

@@ -27,13 +27,13 @@
     "from typing import Callable, List\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/myscale_vector_sql.ipynb

@@ -31,10 +31,10 @@
     "from os import environ\n",
     "\n",
     "from langchain.chains import LLMChain\n",
+    "from langchain.llms import OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_community.utilities import SQLDatabase\n",
+    "from langchain.utilities import SQLDatabase\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
-    "from langchain_openai import OpenAI\n",
     "from sqlalchemy import MetaData, create_engine\n",
     "\n",
     "MYSCALE_HOST = \"msc-4a9e710a.us-east-1.aws.staging.myscale.cloud\"\n",
@@ -57,7 +57,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.embeddings import HuggingFaceInstructEmbeddings\n",
+    "from langchain.embeddings import HuggingFaceInstructEmbeddings\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLOutputParser\n",
     "\n",
     "output_parser = VectorSQLOutputParser.from_embeddings(\n",
@@ -75,10 +75,10 @@
    "outputs": [],
    "source": [
     "from langchain.callbacks import StdOutCallbackHandler\n",
-    "from langchain_community.utilities.sql_database import SQLDatabase\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities.sql_database import SQLDatabase\n",
     "from langchain_experimental.sql.prompt import MYSCALE_PROMPT\n",
     "from langchain_experimental.sql.vector_sql import VectorSQLDatabaseChain\n",
-    "from langchain_openai import OpenAI\n",
     "\n",
     "chain = VectorSQLDatabaseChain(\n",
     "    llm_chain=LLMChain(\n",
@@ -117,6 +117,7 @@
    "outputs": [],
    "source": [
     "from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain_experimental.retrievers.vector_sql_database import (\n",
     "    VectorSQLDatabaseChainRetriever,\n",
     ")\n",
@@ -125,7 +126,6 @@
     "    VectorSQLDatabaseChain,\n",
     "    VectorSQLRetrieveAllOutputParser,\n",
     ")\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "output_parser_retrieve_all = VectorSQLRetrieveAllOutputParser.from_embeddings(\n",
     "    output_parser.model\n",

cookbook/openai_functions_retrieval_qa.ipynb

@@ -20,10 +20,10 @@
    "outputs": [],
    "source": [
     "from langchain.chains import RetrievalQA\n",
+    "from langchain.document_loaders import TextLoader\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.document_loaders import TextLoader\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import OpenAIEmbeddings"
+    "from langchain.vectorstores import Chroma"
    ]
   },
   {
@@ -52,8 +52,8 @@
    "source": [
     "from langchain.chains import create_qa_with_sources_chain\n",
     "from langchain.chains.combine_documents.stuff import StuffDocumentsChain\n",
-    "from langchain.prompts import PromptTemplate\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import PromptTemplate"
    ]
   },
   {

cookbook/openai_v1_cookbook.ipynb

@@ -28,8 +28,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.messages import HumanMessage, SystemMessage\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema.messages import HumanMessage, SystemMessage"
    ]
   },
   {
@@ -252,7 +252,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.agents import AgentFinish\n",
+    "from langchain.schema.agent import AgentFinish\n",
     "\n",
     "\n",
     "def execute_agent(agent, tools, input):\n",
@@ -414,7 +414,7 @@
     "BREAKING CHANGES:\n",
     "- To use Azure embeddings with OpenAI V1, you'll need to use the new `AzureOpenAIEmbeddings` instead of the existing `OpenAIEmbeddings`. `OpenAIEmbeddings` continue to work when using Azure with `openai<1`.\n",
     "```python\n",
-    "from langchain_openai import AzureOpenAIEmbeddings\n",
+    "from langchain.embeddings import AzureOpenAIEmbeddings\n",
     "```\n",
     "\n",
     "\n",
@@ -456,9 +456,9 @@
     "from typing import Literal\n",
     "\n",
     "from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.pydantic_v1 import BaseModel, Field\n",
     "from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
     "\n",
     "\n",
     "class GetCurrentWeather(BaseModel):\n",

cookbook/petting_zoo.ipynb

@@ -47,12 +47,12 @@
     "import inspect\n",
     "\n",
     "import tenacity\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.output_parsers import RegexParser\n",
     "from langchain.schema import (\n",
     "    HumanMessage,\n",
     "    SystemMessage,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI"
+    ")"
    ]
   },
   {

cookbook/plan_and_execute_agent.ipynb

@@ -29,15 +29,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.agents.tools import Tool\n",
     "from langchain.chains import LLMMathChain\n",
-    "from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
-    "from langchain_core.tools import Tool\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.llms import OpenAI\n",
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper\n",
     "from langchain_experimental.plan_and_execute import (\n",
     "    PlanAndExecute,\n",
     "    load_agent_executor,\n",
     "    load_chat_planner,\n",
-    ")\n",
-    "from langchain_openai import ChatOpenAI, OpenAI"
+    ")"
    ]
   },
   {

cookbook/press_releases.ipynb

@@ -81,8 +81,8 @@
    "outputs": [],
    "source": [
     "from langchain.chains import ConversationalRetrievalChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.retrievers import KayAiRetriever\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "model = ChatOpenAI(model_name=\"gpt-3.5-turbo\")\n",
     "retriever = KayAiRetriever.create(\n",

cookbook/program_aided_language_model.ipynb

@@ -17,8 +17,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.pal_chain import PALChain\n",
-    "from langchain_openai import OpenAI"
+    "from langchain.llms import OpenAI\n",
+    "from langchain_experimental.pal_chain import PALChain"
    ]
   },
   {

cookbook/qa_citations.ipynb

@@ -27,7 +27,7 @@
    ],
    "source": [
     "from langchain.chains import create_citation_fuzzy_match_chain\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI"
    ]
   },
   {

cookbook/qianfan_baidu_elasticesearch_RAG.ipynb

@@ -37,8 +37,7 @@
    "source": [
     "#!pip install qianfan\n",
     "#!pip install bce-python-sdk\n",
-    "#!pip install elasticsearch == 7.11.0\n",
-    "#!pip install sentence-transformers"
+    "#!pip install elasticsearch == 7.11.0"
    ]
   },
   {
@@ -55,17 +54,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sentence_transformers\n",
     "from baidubce.auth.bce_credentials import BceCredentials\n",
     "from baidubce.bce_client_configuration import BceClientConfiguration\n",
-    "from langchain.chains.retrieval_qa import RetrievalQA\n",
+    "from langchain.document_loaders.baiducloud_bos_directory import BaiduBOSDirectoryLoader\n",
+    "from langchain.embeddings.huggingface import HuggingFaceEmbeddings\n",
+    "from langchain.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint\n",
     "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
-    "from langchain_community.document_loaders.baiducloud_bos_directory import (\n",
-    "    BaiduBOSDirectoryLoader,\n",
-    ")\n",
-    "from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings\n",
-    "from langchain_community.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint\n",
-    "from langchain_community.vectorstores import BESVectorStore"
+    "from langchain.vectorstores import BESVectorStore"
    ]
   },
   {
@@ -166,22 +161,15 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "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": "3.10.12"
+   "version": "3.9.17"
   },
+  "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
     "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
@@ -189,5 +177,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 2
 }

cookbook/rag_fusion.ipynb

@@ -30,8 +30,8 @@
    "outputs": [],
    "source": [
     "import pinecone\n",
-    "from langchain_community.vectorstores import Pinecone\n",
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Pinecone\n",
     "\n",
     "pinecone.init(api_key=\"...\", environment=\"...\")"
    ]
@@ -86,8 +86,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema.output_parser import StrOutputParser"
    ]
   },
   {

cookbook/retrieval_in_sql.ipynb

@@ -42,8 +42,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.sql_database import SQLDatabase\n",
-    "from langchain_openai import ChatOpenAI\n",
     "\n",
     "CONNECTION_STRING = \"postgresql+psycopg2://postgres:test@localhost:5432/vectordb\"  # Replace with your own\n",
     "db = SQLDatabase.from_uri(CONNECTION_STRING)"
@@ -88,7 +88,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_openai import OpenAIEmbeddings\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
     "\n",
     "embeddings_model = OpenAIEmbeddings()"
    ]
@@ -133,7 +133,7 @@
     "from tqdm import tqdm\n",
     "\n",
     "for i in tqdm(range(len(title_embeddings))):\n",
-    "    title = song_titles[i].replace(\"'\", \"''\")\n",
+    "    title = titles[i].replace(\"'\", \"''\")\n",
     "    embedding = title_embeddings[i]\n",
     "    sql_command = (\n",
     "        f'UPDATE \"Track\" SET \"embeddings\" = ARRAY{embedding} WHERE \"Name\" ='\n",
@@ -219,7 +219,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
     "\n",
     "template = \"\"\"You are a Postgres expert. Given an input question, first create a syntactically correct Postgres query to run, then look at the results of the query and return the answer to the input question.\n",
     "Unless the user specifies in the question a specific number of examples to obtain, query for at most 5 results using the LIMIT clause as per Postgres. You can order the results to return the most informative data in the database.\n",
@@ -267,9 +267,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
     "\n",
     "db = SQLDatabase.from_uri(\n",
     "    CONNECTION_STRING\n",
@@ -324,7 +324,7 @@
    "source": [
     "import re\n",
     "\n",
-    "from langchain_core.runnables import RunnableLambda\n",
+    "from langchain.schema.runnable import RunnableLambda\n",
     "\n",
     "\n",
     "def replace_brackets(match):\n",
@@ -681,9 +681,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.8.18"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 4
+ "nbformat_minor": 2
 }

cookbook/rewrite.ipynb

@@ -31,11 +31,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_community.utilities import DuckDuckGoSearchAPIWrapper\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_core.runnables import RunnablePassthrough\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.runnable import RunnablePassthrough\n",
+    "from langchain.utilities import DuckDuckGoSearchAPIWrapper"
    ]
   },
   {

cookbook/sales_agent_with_context.ipynb

@@ -49,13 +49,14 @@
     "from langchain.agents.conversational.prompt import FORMAT_INSTRUCTIONS\n",
     "from langchain.chains import LLMChain, RetrievalQA\n",
     "from langchain.chains.base import Chain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.embeddings.openai import OpenAIEmbeddings\n",
+    "from langchain.llms import BaseLLM, OpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
     "from langchain.prompts.base import StringPromptTemplate\n",
     "from langchain.schema import AgentAction, AgentFinish\n",
     "from langchain.text_splitter import CharacterTextSplitter\n",
-    "from langchain_community.llms import BaseLLM\n",
-    "from langchain_community.vectorstores import Chroma\n",
-    "from langchain_openai import ChatOpenAI, OpenAI, OpenAIEmbeddings\n",
+    "from langchain.vectorstores import Chroma\n",
     "from pydantic import BaseModel, Field"
    ]
   },

cookbook/selecting_llms_based_on_context_length.ipynb

@@ -17,10 +17,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import PromptTemplate\n",
-    "from langchain_core.output_parsers import StrOutputParser\n",
-    "from langchain_core.prompt_values import PromptValue\n",
-    "from langchain_openai import ChatOpenAI"
+    "from langchain.schema.output_parser import StrOutputParser\n",
+    "from langchain.schema.prompt import PromptValue"
    ]
   },
   {