remove run id from hot path

.github/CODEOWNERS

@@ -1,3 +1,2 @@
-/.github/   @baskaryan @ccurme @eyurtsev
-/libs/core/ @eyurtsev
+/.github/   @baskaryan @ccurme
 /libs/packages.yml   @ccurme

.github/CONTRIBUTING.md

@@ -3,8 +3,4 @@
 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/).
-
-## New features
-
-For new features, please start a new [discussion](https://forum.langchain.com/), where the maintainers will help with scoping out the necessary changes.
+To learn how to contribute to LangChain, please follow the [contribution guide here](https://python.langchain.com/docs/contributing/).

.github/DISCUSSION_TEMPLATE/ideas.yml

@@ -0,0 +1,38 @@
+labels: [idea]
+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:
+      required: true
+    attributes:
+      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:
+      required: true
+    attributes:
+      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
+    validations:
+      required: false
+    attributes:
+      label: Proposal (If applicable)
+      description: |
+        If you would like to propose a solution, please describe it here. 

.github/DISCUSSION_TEMPLATE/q-a.yml

@@ -0,0 +1,122 @@
+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, writing documentation or reviewing pull requests.
+
+        By asking questions in a structured way (following this) it will be much easier for us to help you.
+
+        There's a high chance that by following this process, you'll find the solution on your own, eliminating the need to submit a question and wait for an answer. 😎
+
+        As there are many questions submitted every day, 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://python.langchain.com/api_reference/),
+        [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

@@ -1,33 +1,33 @@
 name: "\U0001F41B Bug Report"
-description: Report a bug in LangChain. To report a security issue, please instead use the security option below. For questions, please use the LangChain forum.
-labels: ["bug"]
+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.
+labels: ["02 Bug Report"]
 body:
   - type: markdown
     attributes:
-      value: |
+      value: >
         Thank you for taking the time to file a bug report. 
-
-        Use this to report BUGS in LangChain. For usage questions, feature requests and general design questions, please use the [LangChain Forum](https://forum.langchain.com/).
-
+        
+        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 Forum](https://forum.langchain.com/),
-        * [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
-        * [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        * [LangChain how-to guides](https://python.langchain.com/docs/how_to/),
-        * [API Reference](https://python.langchain.com/api_reference/),
-        * [LangChain ChatBot](https://chat.langchain.com/)
-        * [GitHub search](https://github.com/langchain-ai/langchain),
+        
+        [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
+        [API Reference](https://python.langchain.com/api_reference/),
+        [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: This is a bug, not a usage question. For questions, please use the LangChain Forum (https://forum.langchain.com/).
-          required: true
-        - label: I added a clear and descriptive title that summarizes this issue.
+        - label: I added a very descriptive title to this issue.
           required: true
         - label: I used the GitHub search to find a similar question and didn't find it.
           required: true
@@ -35,8 +35,6 @@ body:
           required: true
         - label: The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package).
           required: true
-        - label: I read what a minimal reproducible example is (https://stackoverflow.com/help/minimal-reproducible-example).
-          required: true
         - label: I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS.
           required: true
   - type: textarea
@@ -47,19 +45,19 @@ body:
       label: Example Code
       description: |
         Please add a self-contained, [minimal, reproducible, example](https://stackoverflow.com/help/minimal-reproducible-example) with your use case.
-
+        
         If a maintainer can copy it, run it, and see it right away, there's a much higher chance that you'll be able to get help.
-
+        
         **Important!** 
-
-        * Avoid screenshots when possible, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.
-        * Reduce your code to the minimum required to reproduce the issue if possible. This makes it much easier for others to help you.
+        
         * Use code tags (e.g., ```python ... ```) to correctly [format your code](https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting).
         * INCLUDE the language label (e.g. `python`) after the first three backticks to enable syntax highlighting. (e.g., ```python rather than ```).
+        * 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: |
         The following code: 
-
+        
         ```python
         from langchain_core.runnables import RunnableLambda
 
@@ -101,18 +99,16 @@ body:
         Please share your system info with us. Do NOT skip this step and please don't trim
         the output. Most users don't include enough information here and it makes it harder
         for us to help you.
-
+        
         Run the following command in your terminal and paste the output here:
-
-        `python -m langchain_core.sys_info`
-
+        
+        python -m langchain_core.sys_info
+        
         or if you have an existing python interpreter running:
-
-        ```python
+        
         from langchain_core import sys_info
         sys_info.print_sys_info()
-        ```
-
+        
         alternatively, put the entire output of `pip freeze` here.
       placeholder: |
         python -m langchain_core.sys_info

.github/ISSUE_TEMPLATE/config.yml

@@ -1,6 +1,12 @@
 blank_issues_enabled: false
 version: 2.1
 contact_links:
-  - name: LangChain Forum
-    url: https://forum.langchain.com/
-    about: General community discussions, support, and feature requests
+  - 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: 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

@@ -1,59 +1,58 @@
 name: Documentation
 description: Report an issue related to the LangChain documentation.
-title: "docs: <Please write a comprehensive title after the 'docs: ' prefix>"
-labels: [documentation]
+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 the [LangChain Forum](https://forum.langchain.com/).
-
-        If you're in the wrong place, here are some helpful links to find a better
-        place to ask your question:
-
-        * [LangChain Forum](https://forum.langchain.com/),
-        * [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
-        * [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        * [LangChain how-to guides](https://python.langchain.com/docs/how_to/),
-        * [API Reference](https://python.langchain.com/api_reference/),
-        * [LangChain ChatBot](https://chat.langchain.com/)
-        * [GitHub search](https://github.com/langchain-ai/langchain),
-  - type: input
-    id: url
-    attributes:
-      label: URL
-      description: URL to documentation
-    validations:
-      required: false
-  - 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.
-  - type: textarea
-    attributes:
-      label: "Idea or request for content:"
-      description: >
-        Please describe as clearly as possible what topics you think are missing
-        from the current documentation.
+- 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://python.langchain.com/api_reference/),
+      [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: input
+  id: url
+  attributes:
+    label: URL
+    description: URL to documentation
+  validations:
+    required: false
+- 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.
+- type: textarea
+  attributes:
+    label: "Idea or request for content:"
+    description: >
+      Please describe as clearly as possible what topics you think are missing
+      from the current documentation.

.github/ISSUE_TEMPLATE/privileged.yml

@@ -5,9 +5,9 @@ body:
     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 on the [LangChain Forum](https://forum.langchain.com/) instead.
-
+        
+        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 pull requests.
   - type: checkboxes

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,32 +1,28 @@
-Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
+Thank you for contributing to LangChain!
+
+- [ ] **PR title**: "package: description"
+  - Where "package" is whichever of langchain, core, etc. is being modified. Use "docs: ..." for purely docs changes, "infra: ..." for CI changes.
+  - Example: "core: add foobar LLM"
 
-- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
-  - Examples:
-    - feat(core): add multi-tenant support
-    - fix(cli): resolve flag parsing error
-    - docs(openai): update API usage examples
-  - Allowed `{TYPE}` values:
-    - feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
-  - Allowed `{SCOPE}` values (optional):
-    - core, cli, langchain, standard-tests, docs, anthropic, chroma, deepseek, exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai, perplexity, prompty, qdrant, xai
-  - Note: the `{DESCRIPTION}` must not start with an uppercase letter.
-  - Once you've written the title, please delete this checklist item; do not include it in the PR.
 
 - [ ] **PR message**: ***Delete this entire checklist*** and replace with
-  - **Description:** a description of the change. Include a [closing keyword](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) if applicable to a relevant issue.
-  - **Issue:** the issue # it fixes, if applicable (e.g. Fixes #123)
-  - **Dependencies:** any dependencies required for this change
-  - **Twitter handle:** if your PR gets announced, and you'd like a mention, we'll gladly shout you out!
+    - **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!
 
-- [ ] **Add tests and docs**: If you're adding a new integration, you must 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.
 
-- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. **We will not consider a PR unless these three are passing in CI.** See [contribution guidelines](https://python.langchain.com/docs/contributing/) for more.
+- [ ] **Add tests and docs**: 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.
+
+
+- [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: https://python.langchain.com/docs/contributing/
 
 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.
+- 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 no one reviews your PR within a few days, please @-mention one of baskaryan, eyurtsev, ccurme, vbarda, hwchase17.

.github/copilot-instructions.md

@@ -1,151 +0,0 @@
-### 1. Avoid Breaking Changes (Stable Public Interfaces)
-
-* Carefully preserve **function signatures**, argument positions, and names for any exported/public methods.
-* Be cautious when **renaming**, **removing**, or **reordering** arguments — even small changes can break downstream consumers.
-* Use keyword-only arguments or clearly mark experimental features to isolate unstable APIs.
-
-Bad:
-
-```python
-def get_user(id, verbose=False):  # Changed from `user_id`
-```
-
-Good:
-
-```python
-def get_user(user_id: str, verbose: bool = False):  # Maintains stable interface
-```
-
-🧠 *Ask yourself:* “Would this change break someone's code if they used it last week?”
-
----
-
-### 2. Simplify Code and Use Clear Variable Names
-
-* Prefer descriptive, **self-explanatory variable names**. Avoid overly short or cryptic identifiers.
-* Break up overly long or deeply nested functions for **readability and maintainability**.
-* Avoid unnecessary abstraction or premature optimization.
-* All generated Python code must include type hints.
-
-Bad:
-
-```python
-def p(u, d):
-    return [x for x in u if x not in d]
-```
-
-Good:
-
-```python
-def filter_unknown_users(users: List[str], known_users: Set[str]) -> List[str]:
-    return [user for user in users if user not in known_users]
-```
-
----
-
-### 3. Ensure Unit Tests Cover New and Updated Functionality
-
-* Every new feature or bugfix should be **covered by a unit test**.
-* Test edge cases and failure conditions.
-* Use `pytest`, `unittest`, or the project’s existing framework consistently.
-
-Checklist:
-
-* [ ] Does the test suite fail if your new logic is broken?
-* [ ] Are all expected behaviors exercised (happy path, invalid input, etc)?
-* [ ] Do tests use fixtures or mocks where needed?
-
----
-
-### 4. Look for Suspicious or Risky Code
-
-* Watch out for:
-
-  * Use of `eval()`, `exec()`, or `pickle` on user-controlled input.
-  * Silent failure modes (`except: pass`).
-  * Unreachable code or commented-out blocks.
-  * Race conditions or resource leaks (file handles, sockets, threads).
-
-Bad:
-
-```python
-def load_config(path):
-    with open(path) as f:
-        return eval(f.read())  # ⚠️ Never eval config
-```
-
-Good:
-
-```python
-import json
-
-def load_config(path: str) -> dict:
-    with open(path) as f:
-        return json.load(f)
-```
-
----
-
-### 5. Use Google-Style Docstrings (with Args section)
-
-* All public functions should include a **Google-style docstring**.
-* Include an `Args:` section where relevant.
-* Types should NOT be written in the docstring — use type hints instead.
-
-Bad:
-
-```python
-def send_email(to, msg):
-    """Send an email to a recipient."""
-```
-
-Good:
-
-```python
-def send_email(to: str, msg: str) -> None:
-    """
-    Sends an email to a recipient.
-
-    Args:
-        to: The email address of the recipient.
-        msg: The message body.
-    """
-```
-
-📌 *Tip:* Keep descriptions concise but clear. Only document return values if non-obvious.
-
----
-
-### 6. Propose Better Designs When Applicable
-
-* If there's a **cleaner**, **more scalable**, or **simpler** design, highlight it.
-* Suggest improvements, even if they require some refactoring — especially if the new code would:
-
-  * Reduce duplication
-  * Make unit testing easier
-  * Improve separation of concerns
-  * Add clarity without adding complexity
-
-Instead of:
-
-```python
-def save(data, db_conn):
-    # manually serializes fields
-```
-
-You might suggest:
-
-```python
-# Suggest using dataclasses or Pydantic for automatic serialization and validation
-```
-
-### 7. Misc
-
-* When suggesting package installation commands, use `uv pip install` as this project uses `uv`.
-* When creating tools for agents, use the @tool decorator from langchain_core.tools. The tool's docstring serves as its functional description for the agent.
-* Avoid suggesting deprecated components, such as the legacy LLMChain.
-* We use Conventional Commits format for pull request titles. Example PR titles:
-    * feat(core): add multi‐tenant support
-    * fix(cli): resolve flag parsing error
-    * docs: update API usage examples
-    * docs(openai): update API usage examples

.github/dependabot.yml

@@ -1,11 +0,0 @@
-# Please see the documentation for all configuration options:
-# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
-# and
-# https://docs.github.com/code-security/dependabot/dependabot-version-updates/configuration-options-for-the-dependabot.yml-file
-
-version: 2
-updates:
-  - package-ecosystem: "github-actions"
-    directory: "/"
-    schedule:
-      interval: "weekly"

.github/scripts/check_diff.py

@@ -37,6 +37,7 @@ IGNORED_PARTNERS = [
 ]
 
 PY_312_MAX_PACKAGES = [
+    "libs/partners/voyageai",
     "libs/partners/chroma", # https://github.com/chroma-core/chroma/issues/4382
 ]
 
@@ -119,9 +120,7 @@ def _get_configs_for_single_dir(job: str, dir_: str) -> List[Dict[str, str]]:
     if job == "test-pydantic":
         return _get_pydantic_test_configs(dir_)
 
-    if job == "codspeed":
-        py_versions = ["3.12"]  # 3.13 is not yet supported
-    elif dir_ == "libs/core":
+    if dir_ == "libs/core":
         py_versions = ["3.9", "3.10", "3.11", "3.12", "3.13"]
     # custom logic for specific directories
     elif dir_ == "libs/partners/milvus":
@@ -212,8 +211,6 @@ def _get_configs_for_multi_dirs(
         )
     elif job == "extended-tests":
         dirs = list(dirs_to_run["extended-test"])
-    elif job == "codspeed":
-        dirs = list(dirs_to_run["codspeed"])
     else:
         raise ValueError(f"Unknown job: {job}")
 
@@ -229,7 +226,6 @@ if __name__ == "__main__":
         "lint": set(),
         "test": set(),
         "extended-test": set(),
-        "codspeed": set(),
     }
     docs_edited = False
 
@@ -253,8 +249,6 @@ if __name__ == "__main__":
             dirs_to_run["extended-test"].update(LANGCHAIN_DIRS)
             dirs_to_run["lint"].add(".")
 
-        if file.startswith("libs/core"):
-            dirs_to_run["codspeed"].add(f"libs/core")
         if any(file.startswith(dir_) for dir_ in LANGCHAIN_DIRS):
             # add that dir and all dirs after in LANGCHAIN_DIRS
             # for extended testing
@@ -293,7 +287,6 @@ if __name__ == "__main__":
                 if not filename.startswith(".")
             ] != ["README.md"]:
                 dirs_to_run["test"].add(f"libs/partners/{partner_dir}")
-                dirs_to_run["codspeed"].add(f"libs/partners/{partner_dir}")
             # Skip if the directory was deleted or is just a tombstone readme
         elif file == "libs/packages.yml":
             continue
@@ -319,7 +312,6 @@ if __name__ == "__main__":
             "compile-integration-tests",
             "dependencies",
             "test-pydantic",
-            "codspeed",
         ]
     }
     map_job_to_configs["test-doc-imports"] = (

.github/workflows/_compile_integration_test.yml

@@ -12,9 +12,6 @@ on:
         type: string
         description: "Python version to use"
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
 

.github/workflows/_integration_test.yml

@@ -1,4 +1,4 @@
-name: Integration Tests
+name: Integration tests
 
 on:
   workflow_dispatch:
@@ -12,9 +12,6 @@ on:
         type: string
         description: "Python version to use"
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
 
@@ -44,8 +41,6 @@ jobs:
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-          ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
-          ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
           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 }}
@@ -72,6 +67,7 @@ jobs:
           ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
           ES_API_KEY: ${{ secrets.ES_API_KEY }}
           MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
+          VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }}
           COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
           UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}

.github/workflows/_lint.yml

@@ -12,9 +12,6 @@ on:
         type: string
         description: "Python version to use"
 
-permissions:
-  contents: read
-
 env:
   WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }}
 

.github/workflows/_release.yml

@@ -1,4 +1,4 @@
-name: Release
+name: release
 run-name: Release ${{ inputs.working-directory }} by @${{ github.actor }}
 on:
   workflow_call:
@@ -64,7 +64,7 @@ jobs:
           name: dist
           path: ${{ inputs.working-directory }}/dist/
 
-      - name: Check version
+      - name: Check Version
         id: check-version
         shell: python
         working-directory: ${{ inputs.working-directory }}
@@ -93,7 +93,7 @@ jobs:
             ${{ inputs.working-directory }}
           ref: ${{ github.ref }} # this scopes to just ref'd branch
           fetch-depth: 0 # this fetches entire commit history
-      - name: Check tags
+      - name: Check Tags
         id: check-tags
         shell: bash
         working-directory: langchain/${{ inputs.working-directory }}
@@ -322,6 +322,7 @@ jobs:
           ES_CLOUD_ID: ${{ secrets.ES_CLOUD_ID }}
           ES_API_KEY: ${{ secrets.ES_API_KEY }}
           MONGODB_ATLAS_URI: ${{ secrets.MONGODB_ATLAS_URI }}
+          VOYAGE_API_KEY: ${{ secrets.VOYAGE_API_KEY }}
           UPSTAGE_API_KEY: ${{ secrets.UPSTAGE_API_KEY }}
           FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
           XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
@@ -340,12 +341,10 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        partner: [openai]
+        partner: [openai, anthropic]
       fail-fast: false  # Continue testing other partners if one fails
     env:
       ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-      ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
-      ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
       OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
       AZURE_OPENAI_API_VERSION: ${{ secrets.AZURE_OPENAI_API_VERSION }}
       AZURE_OPENAI_API_BASE: ${{ secrets.AZURE_OPENAI_API_BASE }}

.github/workflows/_test.yml

@@ -12,9 +12,6 @@ on:
         type: string
         description: "Python version to use"
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
   UV_NO_SYNC: "true"

.github/workflows/_test_doc_imports.yml

@@ -8,9 +8,6 @@ on:
         type: string
         description: "Python version to use"
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
 

.github/workflows/_test_pydantic.yml

@@ -17,9 +17,6 @@ on:
         type: string
         description: "Pydantic version to test."
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
   UV_NO_SYNC: "true"

.github/workflows/api_doc_build.yml

@@ -1,4 +1,4 @@
-name: API Docs Build
+name: API docs build
 
 on:
   workflow_dispatch:
@@ -56,7 +56,7 @@ jobs:
             git clone --depth 1 https://github.com/$repo.git $REPO_NAME
           done
 
-      - name: Setup Python ${{ env.PYTHON_VERSION }}
+      - name: Setup python ${{ env.PYTHON_VERSION }}
         uses: actions/setup-python@v5
         id: setup-python
         with:
@@ -68,7 +68,7 @@ jobs:
           python -m pip install -U uv
           python -m uv pip install --upgrade --no-cache-dir pip setuptools pyyaml
 
-      - name: Move libs
+      - name: Move libs with script
         run: python langchain/.github/scripts/prep_api_docs_build.py
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/check-broken-links.yml

@@ -5,9 +5,6 @@ on:
   schedule:
     - cron:  '0 13 * * *'
 
-permissions:
-  contents: read
-
 jobs:
   check-links:
     if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
@@ -15,7 +12,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Use Node.js 18.x
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v3
         with:
           node-version: 18.x
           cache: "yarn"

.github/workflows/check_core_versions.yml

@@ -1,4 +1,4 @@
-name: Check `core` Version Equality
+name: Check `langchain-core` version equality
 
 on:
   pull_request:
@@ -6,9 +6,6 @@ on:
       - 'libs/core/pyproject.toml'
       - 'libs/core/langchain_core/version.py'
 
-permissions:
-  contents: read
-
 jobs:
   check_version_equality:
     runs-on: ubuntu-latest

.github/workflows/check_diffs.yml

@@ -16,9 +16,6 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
   UV_NO_SYNC: "true"
@@ -32,7 +29,7 @@ jobs:
         with:
           python-version: '3.11'
       - id: files
-        uses: Ana06/get-changed-files@v2.3.0
+        uses: Ana06/get-changed-files@v2.2.0
       - id: set-matrix
         run: |
           python -m pip install packaging requests
@@ -155,7 +152,6 @@ jobs:
           # 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'
-
   ci_success:
     name: "CI Success"
     needs: [build, lint, test, compile-integration-tests, extended-tests, test-doc-imports, test-pydantic]

.github/workflows/check_new_docs.yml

@@ -1,4 +1,4 @@
-name: Integration Docs Lint
+name: Integration docs lint
 
 on:
   push:
@@ -15,9 +15,6 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true
 
-permissions:
-  contents: read
-
 jobs:
   build:
     runs-on: ubuntu-latest
@@ -27,7 +24,7 @@ jobs:
         with:
           python-version: '3.10'
       - id: files
-        uses: Ana06/get-changed-files@v2.3.0
+        uses: Ana06/get-changed-files@v2.2.0
         with:
           filter: |
             *.ipynb

.github/workflows/codspeed.yml

@@ -5,61 +5,40 @@ on:
     branches:
         - master
   pull_request:
+    paths:
+      - 'libs/core/**'
+  # `workflow_dispatch` allows CodSpeed to trigger backtest
+  # performance analysis in order to generate initial data.
   workflow_dispatch:
 
-permissions:
-  contents: read
-
-env:
-  AZURE_OPENAI_CHAT_DEPLOYMENT_NAME: foo
-  AZURE_OPENAI_LEGACY_CHAT_DEPLOYMENT_NAME: foo
-  DEEPSEEK_API_KEY: foo
-  FIREWORKS_API_KEY: foo
-
 jobs:
   codspeed:
     name: Run benchmarks
+    if: (github.event_name == 'pull_request' && contains(github.event.pull_request.labels.*.name, 'run-codspeed-benchmarks')) || github.event_name == 'workflow_dispatch' || github.event_name == 'push'
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        include:
-          - working-directory: libs/core
-            mode: walltime
-          - working-directory: libs/partners/openai
-          - working-directory: libs/partners/anthropic
-          - working-directory: libs/partners/deepseek
-          - working-directory: libs/partners/fireworks
-          - working-directory: libs/partners/xai
-          - working-directory: libs/partners/mistralai
-          - working-directory: libs/partners/groq
-      fail-fast: false
-
     steps:
       - uses: actions/checkout@v4
 
-      # We have to use 3.12 as 3.13 is not yet supported
+      # We have to use 3.12, 3.13 is not yet supported
       - name: Install uv
-        uses: astral-sh/setup-uv@v6
+        uses: astral-sh/setup-uv@v5
         with:
           python-version: "3.12"
 
-      - uses: actions/setup-python@v5
+      # Using this action is still necessary for CodSpeed to work
+      - uses: actions/setup-python@v3
         with:
           python-version: "3.12"
 
-      - name: Install dependencies
+      - name: install deps
         run: uv sync --group test
-        working-directory: ${{ matrix.working-directory }}
+        working-directory: ./libs/core
 
-      - name: Run benchmarks ${{ matrix.working-directory }}
+      - name: Run benchmarks
         uses: CodSpeedHQ/action@v3
         with:
           token: ${{ secrets.CODSPEED_TOKEN }}
           run: |
-            cd ${{ matrix.working-directory }}
-            if [ "${{ matrix.working-directory }}" = "libs/core" ]; then
-              uv run --no-sync pytest ./tests/benchmarks --codspeed
-            else
-              uv run --no-sync pytest ./tests/ --codspeed
-            fi
-          mode: ${{ matrix.mode || 'instrumentation' }}
+            cd libs/core
+            uv run --no-sync pytest ./tests/benchmarks --codspeed
+          mode: walltime

.github/workflows/people.yml

@@ -11,8 +11,7 @@ jobs:
   langchain-people:
     if: github.repository_owner == 'langchain-ai' || github.event_name != 'schedule'
     runs-on: ubuntu-latest
-    permissions:
-      contents: write
+    permissions: write-all
     steps:
       - name: Dump GitHub context
         env:
@@ -24,4 +23,4 @@ jobs:
         run: mkdir -p /home/runner/work/_temp/_github_home && printf "[safe]\n\tdirectory = /github/workspace" > /home/runner/work/_temp/_github_home/.gitconfig
       - uses: ./.github/actions/people
         with:
-          token: ${{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}
+          token: ${{ secrets.LANGCHAIN_PEOPLE_GITHUB_TOKEN }}

.github/workflows/pr_lint.yml

@@ -1,108 +0,0 @@
-# -----------------------------------------------------------------------------
-# PR Title Lint Workflow
-#
-# Purpose:
-#   Enforces Conventional Commits format for pull request titles to maintain a
-#   clear, consistent, and machine-readable change history across our repository.
-#
-# Enforced Commit Message Format (Conventional Commits 1.0.0):
-#   <type>[optional scope]: <description>
-#   [optional body]
-#   [optional footer(s)]
-#
-# Allowed Types:
-#   • feat       — a new feature (MINOR bump)
-#   • fix        — a bug fix (PATCH bump)
-#   • docs       — documentation only changes
-#   • style      — formatting, missing semi-colons, etc.; no code change
-#   • refactor   — code change that neither fixes a bug nor adds a feature
-#   • perf       — code change that improves performance
-#   • test       — adding missing tests or correcting existing tests
-#   • build      — changes that affect the build system or external dependencies
-#   • ci         — continuous integration/configuration changes
-#   • chore      — other changes that don't modify src or test files
-#   • revert     — reverts a previous commit
-#   • release    — prepare a new release
-#
-# Allowed Scopes (optional):
-#   core, cli, langchain, standard-tests, docs, anthropic, chroma, deepseek,
-#   exa, fireworks, groq, huggingface, mistralai, nomic, ollama, openai,
-#   perplexity, prompty, qdrant, xai
-#
-# Rules & Tips for New Committers:
-#   1. Subject (type) must start with a lowercase letter and, if possible, be
-#      followed by a scope wrapped in parenthesis `(scope)`
-#   2. Breaking changes:
-#        – Append "!" after type/scope (e.g., feat!: drop Node 12 support)
-#        – Or include a footer "BREAKING CHANGE: <details>"
-#   3. Example PR titles:
-#        feat(core): add multi‐tenant support
-#        fix(cli): resolve flag parsing error
-#        docs: update API usage examples
-#        docs(openai): update API usage examples
-#
-# Resources:
-#   • Conventional Commits spec: https://www.conventionalcommits.org/en/v1.0.0/
-# -----------------------------------------------------------------------------
-
-name: PR Title Lint
-
-permissions:
-  pull-requests: read
-
-on:
-  pull_request:
-    types: [opened, edited, synchronize]
-
-jobs:
-  lint-pr-title:
-    name: Validate PR Title
-    runs-on: ubuntu-latest
-    steps:
-      - name: Validate PR Title
-        uses: amannn/action-semantic-pull-request@v5
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        with:
-          types: |
-            feat
-            fix
-            docs
-            style
-            refactor
-            perf
-            test
-            build
-            ci
-            chore
-            revert
-            release
-          scopes: |
-            core
-            cli
-            langchain
-            standard-tests
-            text-splitters
-            docs
-            anthropic
-            chroma
-            deepseek
-            exa
-            fireworks
-            groq
-            huggingface
-            mistralai
-            nomic
-            ollama
-            openai
-            perplexity
-            prompty
-            qdrant
-            xai
-            infra
-          requireScope: false
-          disallowScopes: |
-            release
-            [A-Z]+
-          ignoreLabels: |
-            ignore-lint-pr-title

.github/workflows/run_notebooks.yml

@@ -1,4 +1,4 @@
-name: Run Notebooks
+name: Run notebooks
 
 on:
   workflow_dispatch:
@@ -14,9 +14,6 @@ on:
   schedule:
     - cron: '0 13 * * *'
 
-permissions:
-  contents: read
-
 env:
   UV_FROZEN: "true"
 

.github/workflows/scheduled_test.yml

@@ -1,4 +1,4 @@
-name: Scheduled Tests
+name: Scheduled tests
 
 on:
   workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
@@ -12,9 +12,6 @@ on:
   schedule:
     - cron:  '0 13 * * *'
 
-permissions:
-  contents: read
-
 env:
   POETRY_VERSION: "1.8.4"
   UV_FROZEN: "true"
@@ -130,8 +127,6 @@ jobs:
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
           ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
-          ANTHROPIC_FILES_API_IMAGE_ID: ${{ secrets.ANTHROPIC_FILES_API_IMAGE_ID }}
-          ANTHROPIC_FILES_API_PDF_ID: ${{ secrets.ANTHROPIC_FILES_API_PDF_ID }}
           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 }}
@@ -162,7 +157,7 @@ jobs:
             langchain/libs/partners/google-vertexai \
             langchain/libs/partners/aws
 
-      - name: Ensure tests did not create additional files
+      - name: Ensure the tests did not create any additional files
         working-directory: langchain
         run: |
           set -eu

.pre-commit-config.yaml

@@ -103,6 +103,12 @@ repos:
       entry: make -C libs/partners/qdrant format
       files: ^libs/partners/qdrant/
       pass_filenames: false
+    - id: voyageai
+      name: format partners/voyageai
+      language: system
+      entry: make -C libs/partners/voyageai format
+      files: ^libs/partners/voyageai/
+      pass_filenames: false
     - id: root
       name: format docs, cookbook
       language: system

Makefile

@@ -71,6 +71,7 @@ spell_fix:
 lint lint_package lint_tests:
 	uv run --group lint ruff check docs cookbook
 	uv run --group lint ruff format docs cookbook cookbook --diff
+	uv run --group lint ruff check --select I docs cookbook
 	git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0
 	
 	git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \
@@ -80,7 +81,7 @@ lint lint_package lint_tests:
 ## format: Format the project files.
 format format_diff:
 	uv run --group lint ruff format docs cookbook
-	uv run --group lint ruff check --fix docs cookbook
+	uv run --group lint ruff check --select I --fix docs cookbook
 
 update-package-downloads:
 	uv run python docs/scripts/packages_yml_get_downloads.py

README.md

@@ -66,7 +66,7 @@ reliably handle complex tasks with LangGraph, our low-level agent orchestration
 framework. LangGraph offers customizable architecture, long-term memory, and
 human-in-the-loop workflows — and is trusted in production by companies like LinkedIn,
 Uber, Klarna, and GitLab.
-- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/langgraph_platform/) - Deploy
+- [LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform) - Deploy
 and scale agents effortlessly with a purpose-built deployment platform for long
 running, stateful workflows. Discover, reuse, configure, and share agents across
 teams — and iterate quickly with visual prototyping in
@@ -79,6 +79,5 @@ guided examples on getting started with LangChain.
 snippets for topics such as tool calling, RAG use cases, and more.
 - [Conceptual Guides](https://python.langchain.com/docs/concepts/): Explanations of key
 concepts behind the LangChain framework.
-- [LangChain Forum](https://forum.langchain.com/): Connect with the community and share all of your technical questions, ideas, and feedback.
 - [API Reference](https://python.langchain.com/api_reference/): Detailed reference on
 navigating base packages and integrations for LangChain.

SECURITY.md

@@ -7,8 +7,8 @@ LangChain has a large ecosystem of integrations with various external resources
 When building such applications developers should remember to follow good security practices:
 
 * [**Limit Permissions**](https://en.wikipedia.org/wiki/Principle_of_least_privilege): Scope permissions specifically to the application's need. Granting broad or excessive permissions can introduce significant security vulnerabilities. To avoid such vulnerabilities, consider using read-only credentials, disallowing access to sensitive resources, using sandboxing techniques (such as running inside a container), specifying proxy configurations to control external requests, etc. as appropriate for your application.
-* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it's safest to assume that any LLM able to use those credentials may in fact delete data.
-* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It's best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use.
+* **Anticipate Potential Misuse**: Just as humans can err, so can Large Language Models (LLMs). Always assume that any system access or credentials may be used in any way allowed by the permissions they are assigned. For example, if a pair of database credentials allows deleting data, it’s safest to assume that any LLM able to use those credentials may in fact delete data.
+* [**Defense in Depth**](https://en.wikipedia.org/wiki/Defense_in_depth_(computing)): No security technique is perfect. Fine-tuning and good chain design can reduce, but not eliminate, the odds that a Large Language Model (LLM) may make a mistake. It’s best to combine multiple layered security approaches rather than relying on any single layer of defense to ensure security. For example: use both read-only permissions and sandboxing to ensure that LLMs are only able to access data that is explicitly meant for them to use.
 
 Risks of not doing so include, but are not limited to:
 * Data corruption or loss.
@@ -31,13 +31,15 @@ LangChain is partnered with [huntr by Protect AI](https://huntr.com/) to provide
 a bounty program for our open source projects. 
 
 Please report security vulnerabilities associated with the LangChain 
-open source projects [here](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true).
+open source projects by visiting the following link:
+
+[https://huntr.com/bounties/disclose/](https://huntr.com/bounties/disclose/?target=https%3A%2F%2Fgithub.com%2Flangchain-ai%2Flangchain&validSearch=true)
 
 Before reporting a vulnerability, please review:
 
 1) In-Scope Targets and Out-of-Scope Targets below.
 2) The [langchain-ai/langchain](https://python.langchain.com/docs/contributing/repo_structure) monorepo structure.
-3) The [Best Practices](#best-practices) above to
+3) The [Best practicies](#best-practices) above to
    understand what we consider to be a security vulnerability vs. developer
    responsibility.
 
@@ -62,7 +64,7 @@ All out of scope targets defined by huntr as well as:
   bounties. This includes the following directories
   - libs/langchain/langchain/tools
   - libs/community/langchain_community/tools
-  - Please review the [Best Practices](#best-practices)
+  - Please review the [best practices](#best-practices)
     for more details, but generally tools interact with the real world. Developers are
     expected to understand the security implications of their code and are responsible
     for the security of their tools.

cookbook/LLaMA2_sql_chat.ipynb

@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "6a75a5c6-34ee-4ab9-a664-d9b432d812ee",
    "metadata": {},
    "outputs": [
@@ -61,7 +61,7 @@
    ],
    "source": [
     "# Local\n",
-    "from langchain_ollama import ChatOllama\n",
+    "from langchain_community.chat_models import ChatOllama\n",
     "\n",
     "llama2_chat = ChatOllama(model=\"llama2:13b-chat\")\n",
     "llama2_code = ChatOllama(model=\"codellama:7b-instruct\")\n",

cookbook/Multi_modal_RAG_google.ipynb

@@ -185,7 +185,7 @@
     "    )\n",
     "    # Text summary chain\n",
     "    model = VertexAI(\n",
-    "        temperature=0, model_name=\"gemini-2.0-flash-lite-001\", max_tokens=1024\n",
+    "        temperature=0, model_name=\"gemini-pro\", max_tokens=1024\n",
     "    ).with_fallbacks([empty_response])\n",
     "    summarize_chain = {\"element\": lambda x: x} | prompt | model | StrOutputParser()\n",
     "\n",
@@ -254,7 +254,7 @@
     "\n",
     "def image_summarize(img_base64, prompt):\n",
     "    \"\"\"Make image summary\"\"\"\n",
-    "    model = ChatVertexAI(model=\"gemini-2.0-flash\", max_tokens=1024)\n",
+    "    model = ChatVertexAI(model=\"gemini-pro-vision\", max_tokens=1024)\n",
     "\n",
     "    msg = model.invoke(\n",
     "        [\n",
@@ -394,7 +394,7 @@
     "# The vectorstore to use to index the summaries\n",
     "vectorstore = Chroma(\n",
     "    collection_name=\"mm_rag_cj_blog\",\n",
-    "    embedding_function=VertexAIEmbeddings(model_name=\"text-embedding-005\"),\n",
+    "    embedding_function=VertexAIEmbeddings(model_name=\"textembedding-gecko@latest\"),\n",
     ")\n",
     "\n",
     "# Create retriever\n",
@@ -553,7 +553,7 @@
     "    \"\"\"\n",
     "\n",
     "    # Multi-modal LLM\n",
-    "    model = ChatVertexAI(temperature=0, model_name=\"gemini-2.0-flash\", max_tokens=1024)\n",
+    "    model = ChatVertexAI(temperature=0, model_name=\"gemini-pro-vision\", max_tokens=1024)\n",
     "\n",
     "    # RAG pipeline\n",
     "    chain = (\n",

cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb

@@ -204,14 +204,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "523e6ed2-2132-4748-bdb7-db765f20648d",
    "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\n",
-    "from langchain_ollama import ChatOllama"
+    "from langchain_core.prompts import ChatPromptTemplate"
    ]
   },
   {

cookbook/cql_agent.ipynb

@@ -229,9 +229,9 @@
     "    \"smoke\",\n",
     "    \"temp\",\n",
     "]\n",
-    "assert all([column in df.columns for column in expected_columns]), (\n",
-    "    \"DataFrame does not have the expected columns\"\n",
-    ")"
+    "assert all(\n",
+    "    [column in df.columns for column in expected_columns]\n",
+    "), \"DataFrame does not have the expected columns\""
    ]
   },
   {

cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb

@@ -487,7 +487,7 @@
     "        print(\"*\" * 40)\n",
     "        print(\n",
     "            colored(\n",
-    "                f\"After {i + 1} observations, Tommie's summary is:\\n{tommie.get_summary(force_refresh=True)}\",\n",
+    "                f\"After {i+1} observations, Tommie's summary is:\\n{tommie.get_summary(force_refresh=True)}\",\n",
     "                \"blue\",\n",
     "            )\n",
     "        )\n",

cookbook/img-to_img-search_CLIP_ChromaDB.ipynb

@@ -389,7 +389,7 @@
     "        ax = axs[idx]\n",
     "        ax.imshow(img)\n",
     "        # Assuming similarity is not available in the new data, removed sim_score\n",
-    "        ax.title.set_text(f\"\\nProduct ID: {data['id']}\\n Score: {score}\")\n",
+    "        ax.title.set_text(f\"\\nProduct ID: {data[\"id\"]}\\n Score: {score}\")\n",
     "        ax.axis(\"off\")  # Turn off axis\n",
     "\n",
     "    # Hide any remaining empty subplots\n",

cookbook/meta_prompt.ipynb

@@ -148,11 +148,11 @@
     "\n",
     "    instructions = \"None\"\n",
     "    for i in range(max_meta_iters):\n",
-    "        print(f\"[Episode {i + 1}/{max_meta_iters}]\")\n",
+    "        print(f\"[Episode {i+1}/{max_meta_iters}]\")\n",
     "        chain = initialize_chain(instructions, memory=None)\n",
     "        output = chain.predict(human_input=task)\n",
     "        for j in range(max_iters):\n",
-    "            print(f\"(Step {j + 1}/{max_iters})\")\n",
+    "            print(f\"(Step {j+1}/{max_iters})\")\n",
     "            print(f\"Assistant: {output}\")\n",
     "            print(\"Human: \")\n",
     "            human_input = input()\n",

cookbook/multi_player_dnd.ipynb

@@ -183,7 +183,7 @@
    "outputs": [],
    "source": [
     "game_description = f\"\"\"Here is the topic for a Dungeons & Dragons game: {quest}.\n",
-    "        The characters are: {(*character_names,)}.\n",
+    "        The characters are: {*character_names,}.\n",
     "        The story is narrated by the storyteller, {storyteller_name}.\"\"\"\n",
     "\n",
     "player_descriptor_system_message = SystemMessage(\n",
@@ -334,7 +334,7 @@
     "        You are the storyteller, {storyteller_name}.\n",
     "        Please make the quest more specific. Be creative and imaginative.\n",
     "        Please reply with the specified quest in {word_limit} words or less. \n",
-    "        Speak directly to the characters: {(*character_names,)}.\n",
+    "        Speak directly to the characters: {*character_names,}.\n",
     "        Do not add anything else.\"\"\"\n",
     "    ),\n",
     "]\n",

cookbook/multiagent_bidding.ipynb

@@ -200,7 +200,7 @@
    "outputs": [],
    "source": [
     "game_description = f\"\"\"Here is the topic for the presidential debate: {topic}.\n",
-    "The presidential candidates are: {\", \".join(character_names)}.\"\"\"\n",
+    "The presidential candidates are: {', '.join(character_names)}.\"\"\"\n",
     "\n",
     "player_descriptor_system_message = SystemMessage(\n",
     "    content=\"You can add detail to the description of each presidential candidate.\"\n",
@@ -595,7 +595,7 @@
     "        Frame the debate topic as a problem to be solved.\n",
     "        Be creative and imaginative.\n",
     "        Please reply with the specified topic in {word_limit} words or less. \n",
-    "        Speak directly to the presidential candidates: {(*character_names,)}.\n",
+    "        Speak directly to the presidential candidates: {*character_names,}.\n",
     "        Do not add anything else.\"\"\"\n",
     "    ),\n",
     "]\n",

cookbook/nomic_embedding_rag.ipynb

@@ -215,8 +215,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from langchain_community.chat_models import ChatOllama\n",
     "from langchain_core.prompts import ChatPromptTemplate\n",
-    "from langchain_ollama import ChatOllama\n",
     "from langchain_openai import ChatOpenAI\n",
     "\n",
     "# Prompt\n",

cookbook/openai_functions_retrieval_qa.ipynb

@@ -395,7 +395,8 @@
     "prompt_messages = [\n",
     "    SystemMessage(\n",
     "        content=(\n",
-    "            \"You are a world class algorithm to answer questions in a specific format.\"\n",
+    "            \"You are a world class algorithm to answer \"\n",
+    "            \"questions in a specific format.\"\n",
     "        )\n",
     "    ),\n",
     "    HumanMessage(content=\"Answer question using the following context\"),\n",

cookbook/oracleai_demo.ipynb

@@ -25,7 +25,7 @@
     " * [Oracle Blockchain](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_blockchain_table.html#GUID-B469E277-978E-4378-A8C1-26D3FF96C9A6)\n",
     " * [JSON](https://docs.oracle.com/en/database/oracle/oracle-database/23/adjsn/json-in-oracle-database.html)\n",
     "\n",
-    "This guide demonstrates how Oracle AI Vector Search can be used with LangChain to serve an end-to-end RAG pipeline. This guide goes through examples of:\n",
+    "This guide demonstrates how Oracle AI Vector Search can be used with Langchain to serve an end-to-end RAG pipeline. This guide goes through examples of:\n",
     "\n",
     " * Loading the documents from various sources using OracleDocLoader\n",
     " * Summarizing them within/outside the database using OracleSummary\n",
@@ -47,19 +47,7 @@
    "source": [
     "### Prerequisites\n",
     "\n",
-    "Please install the Oracle Database [python-oracledb driver](https://pypi.org/project/oracledb/) to use LangChain with Oracle AI Vector Search:\n",
-    "\n",
-    "```\n",
-    "$ python -m pip install --upgrade oracledb\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Create Demo User\n",
-    "First, connect as a privileged user to create a demo user with all the required privileges. Change the credentials for your environment. Also set the DEMO_PY_DIR path to a directory on the database host where your model file is located:"
+    "Please install Oracle Python Client driver to use Langchain with Oracle AI Vector Search. "
    ]
   },
   {
@@ -68,30 +56,65 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# pip install oracledb"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create Demo User\n",
+    "First, create a demo user with all the required privileges. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Connection successful!\n",
+      "User setup done!\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "\n",
     "import oracledb\n",
     "\n",
-    "# Please update with your SYSTEM (or privileged user) username, password, and database connection string\n",
-    "username = \"SYSTEM\"\n",
+    "# Update with your username, password, hostname, and service_name\n",
+    "username = \"\"\n",
     "password = \"\"\n",
     "dsn = \"\"\n",
     "\n",
-    "with oracledb.connect(user=username, password=password, dsn=dsn) as connection:\n",
+    "try:\n",
+    "    conn = oracledb.connect(user=username, password=password, dsn=dsn)\n",
     "    print(\"Connection successful!\")\n",
     "\n",
-    "    with connection.cursor() as cursor:\n",
+    "    cursor = conn.cursor()\n",
+    "    try:\n",
     "        cursor.execute(\n",
     "            \"\"\"\n",
     "            begin\n",
     "                -- Drop user\n",
-    "                execute immediate 'drop user if exists testuser cascade';\n",
-    "\n",
+    "                begin\n",
+    "                    execute immediate 'drop user testuser cascade';\n",
+    "                exception\n",
+    "                    when others then\n",
+    "                        dbms_output.put_line('Error dropping user: ' || SQLERRM);\n",
+    "                end;\n",
+    "                \n",
     "                -- Create user and grant privileges\n",
     "                execute immediate 'create user testuser identified by testuser';\n",
     "                execute immediate 'grant connect, unlimited tablespace, create credential, create procedure, create any index to testuser';\n",
-    "                execute immediate 'create or replace directory DEMO_PY_DIR as ''/home/yourname/demo/orachain''';\n",
+    "                execute immediate 'create or replace directory DEMO_PY_DIR as ''/scratch/hroy/view_storage/hroy_devstorage/demo/orachain''';\n",
     "                execute immediate 'grant read, write on directory DEMO_PY_DIR to public';\n",
     "                execute immediate 'grant create mining model to testuser';\n",
-    "\n",
+    "                \n",
     "                -- Network access\n",
     "                begin\n",
     "                    DBMS_NETWORK_ACL_ADMIN.APPEND_HOST_ACE(\n",
@@ -104,7 +127,15 @@
     "            end;\n",
     "            \"\"\"\n",
     "        )\n",
-    "        print(\"User setup done!\")"
+    "        print(\"User setup done!\")\n",
+    "    except Exception as e:\n",
+    "        print(f\"User setup failed with error: {e}\")\n",
+    "    finally:\n",
+    "        cursor.close()\n",
+    "    conn.close()\n",
+    "except Exception as e:\n",
+    "    print(f\"Connection failed with error: {e}\")\n",
+    "    sys.exit(1)"
    ]
   },
   {
@@ -112,13 +143,13 @@
    "metadata": {},
    "source": [
     "## Process Documents using Oracle AI\n",
-    "Consider the following scenario: users possess documents stored either in an Oracle Database or a file system and intend to utilize this data with Oracle AI Vector Search powered by LangChain.\n",
+    "Consider the following scenario: users possess documents stored either in an Oracle Database or a file system and intend to utilize this data with Oracle AI Vector Search powered by Langchain.\n",
     "\n",
     "To prepare the documents for analysis, a comprehensive preprocessing workflow is necessary. Initially, the documents must be retrieved, summarized (if required), and chunked as needed. Subsequent steps involve generating embeddings for these chunks and integrating them into the Oracle AI Vector Store. Users can then conduct semantic searches on this data.\n",
     "\n",
-    "The Oracle AI Vector Search LangChain library encompasses a suite of document processing tools that facilitate document loading, chunking, summary generation, and embedding creation.\n",
+    "The Oracle AI Vector Search Langchain library encompasses a suite of document processing tools that facilitate document loading, chunking, summary generation, and embedding creation.\n",
     "\n",
-    "In the sections that follow, we will detail the utilization of Oracle AI LangChain APIs to effectively implement each of these processes."
+    "In the sections that follow, we will detail the utilization of Oracle AI Langchain APIs to effectively implement each of these processes."
    ]
   },
   {
@@ -126,24 +157,38 @@
    "metadata": {},
    "source": [
     "### Connect to Demo User\n",
-    "The following sample code shows how to connect to Oracle Database using the python-oracledb driver. By default, python-oracledb runs in a ‘Thin’ mode which connects directly to Oracle Database. This mode does not need Oracle Client libraries. However, some additional functionality is available when python-oracledb uses them. Python-oracledb is said to be in ‘Thick’ mode when Oracle Client libraries are used. Both modes have comprehensive functionality supporting the Python Database API v2.0 Specification. See the following [guide](https://python-oracledb.readthedocs.io/en/latest/user_guide/appendix_a.html#featuresummary) that talks about features supported in each mode. You can switch to Thick mode if you are unable to use Thin mode."
+    "The following sample code will show how to connect to Oracle Database. By default, python-oracledb runs in a ‘Thin’ mode which connects directly to Oracle Database. This mode does not need Oracle Client libraries. However, some additional functionality is available when python-oracledb uses them. Python-oracledb is said to be in ‘Thick’ mode when Oracle Client libraries are used. Both modes have comprehensive functionality supporting the Python Database API v2.0 Specification. See the following [guide](https://python-oracledb.readthedocs.io/en/latest/user_guide/appendix_a.html#featuresummary) that talks about features supported in each mode. You might want to switch to thick-mode if you are unable to use thin-mode."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 45,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Connection successful!\n"
+     ]
+    }
+   ],
    "source": [
+    "import sys\n",
+    "\n",
     "import oracledb\n",
     "\n",
-    "# please update with your username, password, and database connection string\n",
-    "username = \"testuser\"\n",
+    "# please update with your username, password, hostname and service_name\n",
+    "username = \"\"\n",
     "password = \"\"\n",
     "dsn = \"\"\n",
     "\n",
-    "connection = oracledb.connect(user=username, password=password, dsn=dsn)\n",
-    "print(\"Connection successful!\")"
+    "try:\n",
+    "    conn = oracledb.connect(user=username, password=password, dsn=dsn)\n",
+    "    print(\"Connection successful!\")\n",
+    "except Exception as e:\n",
+    "    print(\"Connection failed!\")\n",
+    "    sys.exit(1)"
    ]
   },
   {
@@ -156,12 +201,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Table created and populated.\n"
+     ]
+    }
+   ],
    "source": [
-    "with connection.cursor() as cursor:\n",
-    "    drop_table_sql = \"\"\"drop table if exists demo_tab\"\"\"\n",
+    "try:\n",
+    "    cursor = conn.cursor()\n",
+    "\n",
+    "    drop_table_sql = \"\"\"drop table demo_tab\"\"\"\n",
     "    cursor.execute(drop_table_sql)\n",
     "\n",
     "    create_table_sql = \"\"\"create table demo_tab (id number, data clob)\"\"\"\n",
@@ -184,9 +239,15 @@
     "    ]\n",
     "    cursor.executemany(insert_row_sql, rows_to_insert)\n",
     "\n",
-    "connection.commit()\n",
+    "    conn.commit()\n",
     "\n",
-    "print(\"Table created and populated.\")"
+    "    print(\"Table created and populated.\")\n",
+    "    cursor.close()\n",
+    "except Exception as e:\n",
+    "    print(\"Table creation failed.\")\n",
+    "    cursor.close()\n",
+    "    conn.close()\n",
+    "    sys.exit(1)"
    ]
   },
   {
@@ -200,22 +261,30 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Load the ONNX Model\n",
+    "### Load ONNX Model\n",
     "\n",
-    "Oracle accommodates a variety of embedding providers, enabling you to choose between proprietary database solutions and third-party services such as Oracle Generative AI Service and HuggingFace. This selection dictates the methodology for generating and managing embeddings.\n",
+    "Oracle accommodates a variety of embedding providers, enabling users to choose between proprietary database solutions and third-party services such as OCIGENAI and HuggingFace. This selection dictates the methodology for generating and managing embeddings.\n",
     "\n",
-    "***Important*** : Should you opt for the database option, you must upload an ONNX model into the Oracle Database. Conversely, if a third-party provider is selected for embedding generation, uploading an ONNX model to Oracle Database is not required.\n",
+    "***Important*** : Should users opt for the database option, they must upload an ONNX model into the Oracle Database. Conversely, if a third-party provider is selected for embedding generation, uploading an ONNX model to Oracle Database is not required.\n",
     "\n",
-    "A significant advantage of utilizing an ONNX model directly within Oracle Database is the enhanced security and performance it offers by eliminating the need to transmit data to external parties. Additionally, this method avoids the latency typically associated with network or REST API calls.\n",
+    "A significant advantage of utilizing an ONNX model directly within Oracle is the enhanced security and performance it offers by eliminating the need to transmit data to external parties. Additionally, this method avoids the latency typically associated with network or REST API calls.\n",
     "\n",
     "Below is the example code to upload an ONNX model into Oracle Database:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ONNX model loaded.\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_community.embeddings.oracleai import OracleEmbeddings\n",
     "\n",
@@ -225,8 +294,12 @@
     "onnx_file = \"tinybert.onnx\"\n",
     "model_name = \"demo_model\"\n",
     "\n",
-    "OracleEmbeddings.load_onnx_model(connection, onnx_dir, onnx_file, model_name)\n",
-    "print(\"ONNX model loaded.\")"
+    "try:\n",
+    "    OracleEmbeddings.load_onnx_model(conn, onnx_dir, onnx_file, model_name)\n",
+    "    print(\"ONNX model loaded.\")\n",
+    "except Exception as e:\n",
+    "    print(\"ONNX model loading failed!\")\n",
+    "    sys.exit(1)"
    ]
   },
   {
@@ -248,7 +321,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "with connection.cursor() as cursor:\n",
+    "try:\n",
+    "    cursor = conn.cursor()\n",
     "    cursor.execute(\n",
     "        \"\"\"\n",
     "       declare\n",
@@ -275,7 +349,12 @@
     "               params            => json(jo.to_string));\n",
     "       end;\n",
     "       \"\"\"\n",
-    "    )"
+    "    )\n",
+    "    cursor.close()\n",
+    "    print(\"Credentials created.\")\n",
+    "except Exception as ex:\n",
+    "    cursor.close()\n",
+    "    raise"
    ]
   },
   {
@@ -283,24 +362,33 @@
    "metadata": {},
    "source": [
     "### Load Documents\n",
-    "You have the flexibility to load documents from either the Oracle Database, a file system, or both, by appropriately configuring the loader parameters. For comprehensive details on these parameters, please consult the [Oracle AI Vector Search Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-73397E89-92FB-48ED-94BB-1AD960C4EA1F).\n",
+    "Users have the flexibility to load documents from either the Oracle Database, a file system, or both, by appropriately configuring the loader parameters. For comprehensive details on these parameters, please consult the [Oracle AI Vector Search Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-73397E89-92FB-48ED-94BB-1AD960C4EA1F).\n",
     "\n",
     "A significant advantage of utilizing OracleDocLoader is its capability to process over 150 distinct file formats, eliminating the need for multiple loaders for different document types. For a complete list of the supported formats, please refer to the [Oracle Text Supported Document Formats](https://docs.oracle.com/en/database/oracle/oracle-database/23/ccref/oracle-text-supported-document-formats.html).\n",
     "\n",
-    "Below is a sample code snippet that demonstrates how to use OracleDocLoader:"
+    "Below is a sample code snippet that demonstrates how to use OracleDocLoader"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of docs loaded: 3\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_community.document_loaders.oracleai import OracleDocLoader\n",
     "from langchain_core.documents import Document\n",
     "\n",
     "# loading from Oracle Database table\n",
     "# make sure you have the table with this specification\n",
+    "loader_params = {}\n",
     "loader_params = {\n",
     "    \"owner\": \"testuser\",\n",
     "    \"tablename\": \"demo_tab\",\n",
@@ -308,7 +396,7 @@
     "}\n",
     "\n",
     "\"\"\" load the docs \"\"\"\n",
-    "loader = OracleDocLoader(conn=connection, params=loader_params)\n",
+    "loader = OracleDocLoader(conn=conn, params=loader_params)\n",
     "docs = loader.load()\n",
     "\n",
     "\"\"\" verify \"\"\"\n",
@@ -321,23 +409,23 @@
    "metadata": {},
    "source": [
     "### Generate Summary\n",
-    "Now that you have loaded the documents, you may want to generate a summary for each document. The Oracle AI Vector Search LangChain library offers a suite of APIs designed for document summarization. It supports multiple summarization providers such as Database, Oracle Generative AI Service, HuggingFace, among others, allowing you to select the provider that best meets their needs. To utilize these capabilities, you must configure the summary parameters as specified. For detailed information on these parameters, please consult the [Oracle AI Vector Search Guide book](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-EC9DDB58-6A15-4B36-BA66-ECBA20D2CE57)."
+    "Now that the user loaded the documents, they may want to generate a summary for each document. The Oracle AI Vector Search Langchain library offers a suite of APIs designed for document summarization. It supports multiple summarization providers such as Database, OCIGENAI, HuggingFace, among others, allowing users to select the provider that best meets their needs. To utilize these capabilities, users must configure the summary parameters as specified. For detailed information on these parameters, please consult the [Oracle AI Vector Search Guide book](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-EC9DDB58-6A15-4B36-BA66-ECBA20D2CE57)."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "***Note:*** You may need to set proxy if you want to use some 3rd party summary generation providers other than Oracle's in-house and default provider: 'database'. If you don't have proxy, please remove the proxy parameter when you instantiate the OracleSummary."
+    "***Note:*** The users may need to set proxy if they want to use some 3rd party summary generation providers other than Oracle's in-house and default provider: 'database'. If you don't have proxy, please remove the proxy parameter when you instantiate the OracleSummary."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# proxy to be used when we instantiate summary and embedder objects\n",
+    "# proxy to be used when we instantiate summary and embedder object\n",
     "proxy = \"\""
    ]
   },
@@ -345,14 +433,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The following sample code shows how to generate a summary:"
+    "The following sample code will show how to generate summary:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 49,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of Summaries: 3\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_community.utilities.oracleai import OracleSummary\n",
     "from langchain_core.documents import Document\n",
@@ -367,7 +463,7 @@
     "\n",
     "# get the summary instance\n",
     "# Remove proxy if not required\n",
-    "summ = OracleSummary(conn=connection, params=summary_params, proxy=proxy)\n",
+    "summ = OracleSummary(conn=conn, params=summary_params, proxy=proxy)\n",
     "\n",
     "list_summary = []\n",
     "for doc in docs:\n",
@@ -391,9 +487,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of Chunks: 3\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_community.document_loaders.oracleai import OracleTextSplitter\n",
     "from langchain_core.documents import Document\n",
@@ -402,7 +506,7 @@
     "splitter_params = {\"normalize\": \"all\"}\n",
     "\n",
     "\"\"\" get the splitter instance \"\"\"\n",
-    "splitter = OracleTextSplitter(conn=connection, params=splitter_params)\n",
+    "splitter = OracleTextSplitter(conn=conn, params=splitter_params)\n",
     "\n",
     "list_chunks = []\n",
     "for doc in docs:\n",
@@ -419,19 +523,19 @@
    "metadata": {},
    "source": [
     "### Generate Embeddings\n",
-    "Now that the documents are chunked as per requirements, you may want to generate embeddings for these chunks. Oracle AI Vector Search provides multiple methods for generating embeddings, utilizing either locally hosted ONNX models or third-party APIs. For comprehensive instructions on configuring these alternatives, please refer to the [Oracle AI Vector Search Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-C6439E94-4E86-4ECD-954E-4B73D53579DE)."
+    "Now that the documents are chunked as per requirements, the users may want to generate embeddings for these chunks. Oracle AI Vector Search provides multiple methods for generating embeddings, utilizing either locally hosted ONNX models or third-party APIs. For comprehensive instructions on configuring these alternatives, please refer to the [Oracle AI Vector Search Guide](https://docs.oracle.com/en/database/oracle/oracle-database/23/arpls/dbms_vector_chain1.html#GUID-C6439E94-4E86-4ECD-954E-4B73D53579DE)."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "***Note:*** You may need to configure a proxy to utilize third-party embedding generation providers, excluding the 'database' provider that utilizes an ONNX model."
+    "***Note:*** Users may need to configure a proxy to utilize third-party embedding generation providers, excluding the 'database' provider that utilizes an ONNX model."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -443,14 +547,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The following sample code shows how to generate embeddings:"
+    "The following sample code will show how to generate embeddings:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of embeddings: 3\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_community.embeddings.oracleai import OracleEmbeddings\n",
     "from langchain_core.documents import Document\n",
@@ -460,7 +572,7 @@
     "\n",
     "# get the embedding instance\n",
     "# Remove proxy if not required\n",
-    "embedder = OracleEmbeddings(conn=connection, params=embedder_params, proxy=proxy)\n",
+    "embedder = OracleEmbeddings(conn=conn, params=embedder_params, proxy=proxy)\n",
     "\n",
     "embeddings = []\n",
     "for doc in docs:\n",
@@ -479,19 +591,19 @@
    "metadata": {},
    "source": [
     "## Create Oracle AI Vector Store\n",
-    "Now that you know how to use Oracle AI LangChain library APIs individually to process the documents, let us show how to integrate with Oracle AI Vector Store to facilitate the semantic searches."
+    "Now that you know how to use Oracle AI Langchain library APIs individually to process the documents, let us show how to integrate with Oracle AI Vector Store to facilitate the semantic searches."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "First, let's import all the dependencies:"
+    "First, let's import all the dependencies."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -514,80 +626,100 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Next, let's combine all document processing stages together. Here is the sample code:"
+    "Next, let's combine all document processing stages together. Here is the sample code below:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 53,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Connection successful!\n",
+      "ONNX model loaded.\n",
+      "Number of total chunks with metadata: 3\n"
+     ]
+    }
+   ],
    "source": [
     "\"\"\"\n",
-    "In this sample example, we will use 'database' provider for both summary and embeddings\n",
-    "so, we don't need to do the following:\n",
+    "In this sample example, we will use 'database' provider for both summary and embeddings.\n",
+    "So, we don't need to do the followings:\n",
     "    - set proxy for 3rd party providers\n",
     "    - create credential for 3rd party providers\n",
     "\n",
-    "If you choose to use 3rd party provider, please follow the necessary steps for proxy and credential.\n",
+    "If you choose to use 3rd party provider, \n",
+    "please follow the necessary steps for proxy and credential.\n",
     "\"\"\"\n",
     "\n",
-    "# please update with your username, password, and database connection string\n",
+    "# oracle connection\n",
+    "# please update with your username, password, hostname, and service_name\n",
     "username = \"\"\n",
     "password = \"\"\n",
     "dsn = \"\"\n",
     "\n",
-    "with oracledb.connect(user=username, password=password, dsn=dsn) as connection:\n",
+    "try:\n",
+    "    conn = oracledb.connect(user=username, password=password, dsn=dsn)\n",
     "    print(\"Connection successful!\")\n",
+    "except Exception as e:\n",
+    "    print(\"Connection failed!\")\n",
+    "    sys.exit(1)\n",
     "\n",
-    "    # load onnx model\n",
-    "    # please update with your related information\n",
-    "    onnx_dir = \"DEMO_PY_DIR\"\n",
-    "    onnx_file = \"tinybert.onnx\"\n",
-    "    model_name = \"demo_model\"\n",
-    "    OracleEmbeddings.load_onnx_model(connection, onnx_dir, onnx_file, model_name)\n",
+    "\n",
+    "# load onnx model\n",
+    "# please update with your related information\n",
+    "onnx_dir = \"DEMO_PY_DIR\"\n",
+    "onnx_file = \"tinybert.onnx\"\n",
+    "model_name = \"demo_model\"\n",
+    "try:\n",
+    "    OracleEmbeddings.load_onnx_model(conn, onnx_dir, onnx_file, model_name)\n",
     "    print(\"ONNX model loaded.\")\n",
+    "except Exception as e:\n",
+    "    print(\"ONNX model loading failed!\")\n",
+    "    sys.exit(1)\n",
     "\n",
-    "    # params\n",
-    "    # please update necessary fields with related information\n",
-    "    loader_params = {\n",
-    "        \"owner\": \"testuser\",\n",
-    "        \"tablename\": \"demo_tab\",\n",
-    "        \"colname\": \"data\",\n",
-    "    }\n",
-    "    summary_params = {\n",
-    "        \"provider\": \"database\",\n",
-    "        \"glevel\": \"S\",\n",
-    "        \"numParagraphs\": 1,\n",
-    "        \"language\": \"english\",\n",
-    "    }\n",
-    "    splitter_params = {\"normalize\": \"all\"}\n",
-    "    embedder_params = {\"provider\": \"database\", \"model\": \"demo_model\"}\n",
     "\n",
-    "    # instantiate loader, summary, splitter, and embedder\n",
-    "    loader = OracleDocLoader(conn=connection, params=loader_params)\n",
-    "    summary = OracleSummary(conn=connection, params=summary_params)\n",
-    "    splitter = OracleTextSplitter(conn=connection, params=splitter_params)\n",
-    "    embedder = OracleEmbeddings(conn=connection, params=embedder_params)\n",
+    "# params\n",
+    "# please update necessary fields with related information\n",
+    "loader_params = {\n",
+    "    \"owner\": \"testuser\",\n",
+    "    \"tablename\": \"demo_tab\",\n",
+    "    \"colname\": \"data\",\n",
+    "}\n",
+    "summary_params = {\n",
+    "    \"provider\": \"database\",\n",
+    "    \"glevel\": \"S\",\n",
+    "    \"numParagraphs\": 1,\n",
+    "    \"language\": \"english\",\n",
+    "}\n",
+    "splitter_params = {\"normalize\": \"all\"}\n",
+    "embedder_params = {\"provider\": \"database\", \"model\": \"demo_model\"}\n",
     "\n",
-    "    # process the documents\n",
-    "    chunks_with_mdata = []\n",
-    "    for id, doc in enumerate(docs, start=1):\n",
-    "        summ = summary.get_summary(doc.page_content)\n",
-    "        chunks = splitter.split_text(doc.page_content)\n",
-    "        for ic, chunk in enumerate(chunks, start=1):\n",
-    "            chunk_metadata = doc.metadata.copy()\n",
-    "            chunk_metadata[\"id\"] = (\n",
-    "                chunk_metadata[\"_oid\"] + \"$\" + str(id) + \"$\" + str(ic)\n",
-    "            )\n",
-    "            chunk_metadata[\"document_id\"] = str(id)\n",
-    "            chunk_metadata[\"document_summary\"] = str(summ[0])\n",
-    "            chunks_with_mdata.append(\n",
-    "                Document(page_content=str(chunk), metadata=chunk_metadata)\n",
-    "            )\n",
+    "# instantiate loader, summary, splitter, and embedder\n",
+    "loader = OracleDocLoader(conn=conn, params=loader_params)\n",
+    "summary = OracleSummary(conn=conn, params=summary_params)\n",
+    "splitter = OracleTextSplitter(conn=conn, params=splitter_params)\n",
+    "embedder = OracleEmbeddings(conn=conn, params=embedder_params)\n",
     "\n",
-    "    \"\"\" verify \"\"\"\n",
-    "    print(f\"Number of total chunks with metadata: {len(chunks_with_mdata)}\")"
+    "# process the documents\n",
+    "chunks_with_mdata = []\n",
+    "for id, doc in enumerate(docs, start=1):\n",
+    "    summ = summary.get_summary(doc.page_content)\n",
+    "    chunks = splitter.split_text(doc.page_content)\n",
+    "    for ic, chunk in enumerate(chunks, start=1):\n",
+    "        chunk_metadata = doc.metadata.copy()\n",
+    "        chunk_metadata[\"id\"] = chunk_metadata[\"_oid\"] + \"$\" + str(id) + \"$\" + str(ic)\n",
+    "        chunk_metadata[\"document_id\"] = str(id)\n",
+    "        chunk_metadata[\"document_summary\"] = str(summ[0])\n",
+    "        chunks_with_mdata.append(\n",
+    "            Document(page_content=str(chunk), metadata=chunk_metadata)\n",
+    "        )\n",
+    "\n",
+    "\"\"\" verify \"\"\"\n",
+    "print(f\"Number of total chunks with metadata: {len(chunks_with_mdata)}\")"
    ]
   },
   {
@@ -601,15 +733,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Vector Store Table: oravs\n"
+     ]
+    }
+   ],
    "source": [
     "# create Oracle AI Vector Store\n",
     "vectorstore = OracleVS.from_documents(\n",
     "    chunks_with_mdata,\n",
     "    embedder,\n",
-    "    client=connection,\n",
+    "    client=conn,\n",
     "    table_name=\"oravs\",\n",
     "    distance_strategy=DistanceStrategy.DOT_PRODUCT,\n",
     ")\n",
@@ -638,12 +778,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
     "oraclevs.create_index(\n",
-    "    connection, vectorstore, params={\"idx_name\": \"hnsw_oravs\", \"idx_type\": \"HNSW\"}\n",
+    "    conn, vectorstore, params={\"idx_name\": \"hnsw_oravs\", \"idx_type\": \"HNSW\"}\n",
     ")\n",
     "\n",
     "print(\"Index created.\")"
@@ -653,7 +793,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This example demonstrates the creation of a default HNSW index on embeddings within the 'oravs' table. You may adjust various parameters according to your specific needs. For detailed information on these parameters, please consult the [Oracle AI Vector Search Guide book](https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/manage-different-categories-vector-indexes.html).\n",
+    "This example demonstrates the creation of a default HNSW index on embeddings within the 'oravs' table. Users may adjust various parameters according to their specific needs. For detailed information on these parameters, please consult the [Oracle AI Vector Search Guide book](https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/manage-different-categories-vector-indexes.html).\n",
     "\n",
     "Additionally, various types of vector indices can be created to meet diverse requirements. More details can be found in our [comprehensive guide](https://python.langchain.com/v0.1/docs/integrations/vectorstores/oracle/).\n"
    ]
@@ -665,16 +805,29 @@
     "## Perform Semantic Search\n",
     "All set!\n",
     "\n",
-    "You have successfully processed the documents and stored them in the vector store, followed by the creation of an index to enhance query performance. You are now prepared to proceed with semantic searches.\n",
+    "We have successfully processed the documents and stored them in the vector store, followed by the creation of an index to enhance query performance. We are now prepared to proceed with semantic searches.\n",
     "\n",
     "Below is the sample code for this process:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 58,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[Document(page_content='The database stores LOBs differently from other data types. Creating a LOB column implicitly creates a LOB segment and a LOB index. The tablespace containing the LOB segment and LOB index, which are always stored together, may be different from the tablespace containing the table. Sometimes the database can store small amounts of LOB data in the table itself rather than in a separate LOB segment.', metadata={'_oid': '662f2f257677f3c2311a8ff999fd34e5', '_rowid': 'AAAR/xAAEAAAAAnAAC', 'id': '662f2f257677f3c2311a8ff999fd34e5$3$1', 'document_id': '3', 'document_summary': 'Sometimes the database can store small amounts of LOB data in the table itself rather than in a separate LOB segment.\\n\\n'})]\n",
+      "[]\n",
+      "[(Document(page_content='The database stores LOBs differently from other data types. Creating a LOB column implicitly creates a LOB segment and a LOB index. The tablespace containing the LOB segment and LOB index, which are always stored together, may be different from the tablespace containing the table. Sometimes the database can store small amounts of LOB data in the table itself rather than in a separate LOB segment.', metadata={'_oid': '662f2f257677f3c2311a8ff999fd34e5', '_rowid': 'AAAR/xAAEAAAAAnAAC', 'id': '662f2f257677f3c2311a8ff999fd34e5$3$1', 'document_id': '3', 'document_summary': 'Sometimes the database can store small amounts of LOB data in the table itself rather than in a separate LOB segment.\\n\\n'}), 0.055675752460956573)]\n",
+      "[]\n",
+      "[Document(page_content='If the answer to any preceding questions is yes, then the database stops the search and allocates space from the specified tablespace; otherwise, space is allocated from the database default shared temporary tablespace.', metadata={'_oid': '662f2f253acf96b33b430b88699490a2', '_rowid': 'AAAR/xAAEAAAAAnAAA', 'id': '662f2f253acf96b33b430b88699490a2$1$1', 'document_id': '1', 'document_summary': 'If the answer to any preceding questions is yes, then the database stops the search and allocates space from the specified tablespace; otherwise, space is allocated from the database default shared temporary tablespace.\\n\\n'})]\n",
+      "[Document(page_content='If the answer to any preceding questions is yes, then the database stops the search and allocates space from the specified tablespace; otherwise, space is allocated from the database default shared temporary tablespace.', metadata={'_oid': '662f2f253acf96b33b430b88699490a2', '_rowid': 'AAAR/xAAEAAAAAnAAA', 'id': '662f2f253acf96b33b430b88699490a2$1$1', 'document_id': '1', 'document_summary': 'If the answer to any preceding questions is yes, then the database stops the search and allocates space from the specified tablespace; otherwise, space is allocated from the database default shared temporary tablespace.\\n\\n'})]\n"
+     ]
+    }
+   ],
    "source": [
     "query = \"What is Oracle AI Vector Store?\"\n",
     "filter = {\"document_id\": [\"1\"]}\n",
@@ -719,7 +872,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.3"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

cookbook/rag_with_quantized_embeddings.ipynb

@@ -53,7 +53,7 @@
    "id": "f5ccda4e-7af5-4355-b9c4-25547edf33f9",
    "metadata": {},
    "source": [
-    "Let's first load up this paper, and split into text chunks of size 1000."
+    "Lets first load up this paper, and split into text chunks of size 1000."
    ]
   },
   {
@@ -241,7 +241,7 @@
    "id": "360b2837-8024-47e0-a4ba-592505a9a5c8",
    "metadata": {},
    "source": [
-    "With our embedder in place, let's define our retriever:"
+    "With our embedder in place, lets define our retriever:"
    ]
   },
   {
@@ -312,7 +312,7 @@
    "id": "d84ea8f4-a5de-4d76-b44d-85e56583f489",
    "metadata": {},
    "source": [
-    "Let's write our documents into our new store. This will use our embedder on each document."
+    "Lets write our documents into our new store. This will use our embedder on each document."
    ]
   },
   {
@@ -339,7 +339,7 @@
    "id": "580bc212-8ecd-4d28-8656-b96fcd0d7eb6",
    "metadata": {},
    "source": [
-    "Great! Our retriever is good to go. Let's load up an LLM, that will reason over the retrieved documents:"
+    "Great! Our retriever is good to go. Lets load up an LLM, that will reason over the retrieved documents:"
    ]
   },
   {
@@ -430,7 +430,7 @@
    "id": "3bc53602-86d6-420f-91b1-fc2effa7e986",
    "metadata": {},
    "source": [
-    "Excellent! Let's ask it a question.\n",
+    "Excellent! lets ask it a question.\n",
     "We will also use a verbose and debug, to check which documents were used by the model to produce the answer."
    ]
   },

cookbook/two_agent_debate_tools.ipynb

@@ -227,7 +227,7 @@
    "outputs": [],
    "source": [
     "conversation_description = f\"\"\"Here is the topic of conversation: {topic}\n",
-    "The participants are: {\", \".join(names.keys())}\"\"\"\n",
+    "The participants are: {', '.join(names.keys())}\"\"\"\n",
     "\n",
     "agent_descriptor_system_message = SystemMessage(\n",
     "    content=\"You can add detail to the description of the conversation participant.\"\n",
@@ -396,7 +396,7 @@
     "        You are the moderator.\n",
     "        Please make the topic more specific.\n",
     "        Please reply with the specified quest in {word_limit} words or less. \n",
-    "        Speak directly to the participants: {(*names,)}.\n",
+    "        Speak directly to the participants: {*names,}.\n",
     "        Do not add anything else.\"\"\"\n",
     "    ),\n",
     "]\n",

docs/api_reference/_extensions/gallery_directive.py

@@ -108,7 +108,7 @@ class GalleryGridDirective(SphinxDirective):
 
         # Parse the template with Sphinx Design to create an output container
         # Prep the options for the template grid
-        class_ = "gallery-directive" + f" {self.options.get('class-container', '')}"
+        class_ = "gallery-directive" + f' {self.options.get("class-container", "")}'
         options = {"gutter": 2, "class-container": class_}
         options_str = "\n".join(f":{k}: {v}" for k, v in options.items())
 

docs/api_reference/create_api_rst.py

@@ -267,7 +267,7 @@ def _construct_doc(
 .. _{package_namespace}:
 
 ======================================
-{package_namespace.replace("_", "-")}: {package_version}
+{package_namespace.replace('_', '-')}: {package_version}
 ======================================
 
 .. automodule:: {package_namespace}
@@ -325,7 +325,7 @@ def _construct_doc(
 
         index_autosummary += f"""
 :ref:`{package_namespace}_{module}`
-{"^" * (len(package_namespace) + len(module) + 8)}
+{'^' * (len(package_namespace) + len(module) + 8)}
 """
 
         if classes:
@@ -364,7 +364,7 @@ def _construct_doc(
     
 """
                 index_autosummary += f"""
-    {class_["qualified_name"]}
+    {class_['qualified_name']}
 """
 
         if functions:
@@ -427,7 +427,7 @@ def _construct_doc(
 
 """
                 index_autosummary += f"""
-    {class_["qualified_name"]}
+    {class_['qualified_name']}
 """
 
         if deprecated_functions:
@@ -663,7 +663,6 @@ def main(dirs: Optional[list] = None) -> None:
             dir_
             for dir_ in os.listdir(ROOT_DIR / "libs")
             if dir_ not in ("cli", "partners", "packages.yml")
-            and "pyproject.toml" in os.listdir(ROOT_DIR / "libs" / dir_)
         ]
         dirs += [
             dir_

docs/cassettes/agents_114ba50d.msgpack.zlib

@@ -1 +1 @@
-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

docs/cassettes/agents_24460239.msgpack.zlib

@@ -1 +1 @@
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docs/cassettes/agents_482ce13d.msgpack.zlib

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docs/cassettes/agents_532d6557.msgpack.zlib

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docs/cassettes/agents_56d8028b-5dbc-40b2-86f5-ed60631d86a3.msgpack.zlib

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docs/cassettes/agents_688b465d.msgpack.zlib

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docs/cassettes/agents_76a02d36-6ea2-4e62-88b4-6c480dd9c04f.msgpack.zlib

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docs/cassettes/agents_7ab50503-d09f-4ff4-9080-5afe297ccc38.msgpack.zlib

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docs/cassettes/agents_a13462d0-2d02-4474-921e-15a1ba1fa274.msgpack.zlib

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docs/cassettes/agents_a3fb262c.msgpack.zlib

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docs/cassettes/agents_b6a7e925.msgpack.zlib

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docs/cassettes/agents_c96c960b.msgpack.zlib

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docs/cassettes/chatbots_tools_10.msgpack.zlib

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docs/cassettes/chatbots_tools_14.msgpack.zlib

@@ -1 +1 @@
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docs/cassettes/chatbots_tools_17.msgpack.zlib

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docs/cassettes/chatbots_tools_19.msgpack.zlib

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docs/cassettes/qa_chat_history_4fbca953-970d-4271-be30-6c7799893dd1.msgpack.zlib

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docs/cassettes/qa_chat_history_how_to_e59541dd-405b-4032-847f-73becf6aefd0.msgpack.zlib

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