This commit removes redundant integration info from details page,
additionally, changing reference from "DigitalOcean GradientAI" to
"DigitalOcean Gradient™ AI" and updating the setup instructions
accordingly.
**Description:**
Two broken links were reported by another LangChain employee. This PR
fixes those links.
Fixed and tested locally.
**Dependencies:**
None
This PR adds documentation for integrating [TrueFoundry’s AI
Gateway](https://www.truefoundry.com/ai-gateway) with Langfuse using the
Langraph OpenAI SDK.
The integration sends requests through TrueFoundry’s AI Gateway for
unified governance, observability, and routing, while Langraph runs on
the client side to capture execution traces and telemetry.
- Issue: N/A
- Dependencies: None
- Twitter - https://x.com/truefoundry
tests - Not applicable
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Thank you for contributing to LangChain!
- [x] **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"
- **Description:** Integrated the Scrapeless package to enable Langchain
users to seamlessly incorporate Scrapeless into their agents.
- **Dependencies:** None
- **Twitter handle:** [Scrapelessteam](https://x.com/Scrapelessteam)
- [x] **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.
- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See [contribution
guidelines](https://python.langchain.com/docs/contributing/) for more.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to `pyproject.toml` files (even
optional ones) unless they are **required** for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
# Description
This PR updates the docs for the
[langchain-anchorbrowser](https://pypi.org/project/langchain-anchorbrowser/)
package. It adds a few tools
[Anchor Browser](https://anchorbrowser.io/?utm=langchain) is the
platform for AI Agentic browser automation, which solves the challenge
of automating workflows for web applications that lack APIs or have
limited API coverage. It simplifies the creation, deployment, and
management of browser-based automations, transforming complex web
interactions into simple API endpoints.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
This PR introduces a new Google partner guide for MCP Toolbox. The
primary goal of this new documentation is to enhance the discoverability
of MCP Toolbox for developers working within the Google ecosystem,
providing them with a clear and direct path to using our tools.
> [!IMPORTANT]
> This PR contains link to a page which is added in #32344. This will
cause deployment failure until that PR is merged.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
This PR introduces a new integration guide for MCP Toolbox. The primary
goal of this new documentation is to enhance the discoverability of MCP
Toolbox for developers working within the LangChain ecosystem, providing
them with a clear and direct path to using our tools.
This approach was chosen to provide users with a practical, hands-on
example that they can easily follow.
> [!NOTE]
> The page added in this PR is linked to from a section in Google
partners page added in #32356.
---------
Co-authored-by: Lauren Hirata Singh <lauren@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
In [Rag Part 1
Tutorial](https://python.langchain.com/docs/tutorials/rag/), when QDrant
vector store is selected, the sample code does not work
It fails with error `ValueError: Collection test not found`
So, this fix is creating that collection and ensuring its dimension size
is matching the selection the embedding size of the selected LLM Model
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
```messages_to_pass = [
HumanMessage(content="What's the capital of France?"),
AIMessage(content="The capital of France is Paris."),
HumanMessage(content="And what about Germany?")
]
formatted_prompt = prompt_template.invoke({"msgs": messages_to_pass})
print(formatted_prompt)```
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
**Description:**
I've added a small clarification to the chatbot tutorial. The tutorial
mentions setting the `LANGSMITH_API_KEY`, but doesn't explain how a new
user can get the key from the website. This change adds a brief note to
guide them to the Settings page.
P.S. This is my first pull request, so I'm excited to learn and
contribute!
**Issue:**
N/A
**Dependencies:**
N/A
**Twitter handle:**
@sohamactive
Co-authored-by: Mason Daugherty <mason@langchain.dev>
**Description:**
In the `docs/docs/how_to/structured_output.ipynb` notebook, an
`AIMessage` within the tool-calling few-shot example was missing the
`name="example_assistant"` parameter. This was inconsistent with the
other `AIMessage` instances in the same list.
This change adds the missing `name` parameter to ensure all examples in
the section are consistent, improving the clarity and correctness of the
documentation.
**Issue:** N/A
**Dependencies:** N/A
While trying the line People.schema got a warning.
```The `schema` method is deprecated; use `model_json_schema` instead```
So made the changes and now working file.
Thank you for contributing to LangChain! Follow these steps to mark your pull request as ready for review. **If any of these steps are not completed, your PR will not be considered for review.**
- [ ] **PR title**: Follows the format: {TYPE}({SCOPE}): {DESCRIPTION}
- Examples:
- feat(core): add multi-tenant support
- fix(cli): resolve flag parsing error
- docs(openai): update API usage examples
- Allowed `{TYPE}` values:
- feat, fix, docs, style, refactor, perf, test, build, ci, chore, revert, release
- Allowed `{SCOPE}` values (optional):
- core, cli, langchain, standard-tests, 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!
- [ ] **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.
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to `pyproject.toml` files (even optional ones) unless they are **required** for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
Description:
Corrected the guide title from "How deal with high cardinality
categoricals" to "How to deal with high-cardinality categoricals".
- Added missing "to" for grammatical correctness.
- Hyphenated "high-cardinality" for standard compound adjective usage.
Issue:
N/A
Dependencies:
None
Twitter handle:
https://x.com/mishraravibhush
**Description**
Updated the quick setup instructions for JaguarDB in the documentation.
Replaced the outdated Docker image `jaguardb/jaguardb_with_http` with
the current recommended image `jaguardb/jaguardb` for pulling and
running the server.
**Description:** This PR improves the contribution setup guide by adding
comprehensive Windows-specific instructions. The changes address a
common pain point for Windows contributors who don't have `make`
installed by default, making the LangChain contribution process more
accessible across different operating systems.
The main improvements include:
- Added a dedicated "Windows Users" section with multiple installation
options for `make` (Chocolatey, Scoop, WSL)
- Provided direct `uv` commands as alternatives to all `make` commands
throughout the setup guide
- Included Windows-specific instructions for testing, formatting,
linting, and spellchecking
- Enhanced the documentation to be more inclusive for Windows developers
This change makes it easier for Windows users to contribute to LangChain
without requiring additional tool installation, while maintaining the
existing workflow for users who already have `make` available.
**Issue:** This addresses the common barrier Windows users face when
trying to contribute to LangChain due to missing `make` commands.
**Dependencies:** None required - this is purely a documentation
improvement.
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
## **Description:**
Updated incorrect package names across multiple integration docs by
replacing underscores with hyphens to reflect their actual names on
PyPI. This aligns with the actual PyPI package names and prevents
potential confusion or installation issues.
## **Issue:** N/A
## **Dependencies:** None
## **Twitter handle:** N/A
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
langchain-gradientai is Digitalocean's integration with Langchain. It
will help users to build langchain applications using Digitalocean's
GradientAI platform.
---------
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Description:
Fixed minor typos in the `google_imagen.ipynb` integration notebook
related to image generation prompt formatting. No functional changes
were made — just a documentation correction to improve clarity.
## **Description:**
Updated incorrect package names in `FeatureTables.js` by replacing
underscores with hyphens to reflect their actual names on PyPI. This
aligns with the actual PyPI package names and prevents potential
confusion or installation issues.
The following package names were corrected:
- `langchain_aws` ➝ `langchain-aws`
- `langchain_community` ➝ `langchain-community`
- `langchain_elasticsearch` ➝ `langchain-elasticsearch`
- `langchain_google_community` ➝ `langchain-google-community`
## **Issue:** N/A
## **Dependencies:** None
## **Twitter handle:** N/A
Description: Documentation is inconsistent with API docs.
Current documentation implies that to use the integration you must have
credentials configured AND store the path to a service account JSON
file.
API docs explain that you must only complete EITHER of the steps
regarding credentials.
I have updated the docs to make them consistent with the API wording.
## **Description:**
Refactored multiple entries in `kv_store_feat_table.py` to ensure that
all vector store metadata is accurate, consistent, and aligned with
LangChain's latest documentation structure and PyPI naming standards.
**Key improvements across all updated entries:**
- Updated `class` links to point to their respective **docs-based
integration pages** (e.g., `/docs/integrations/stores/...`) instead of
raw API reference URLs.
- Corrected `package` display names to use **hyphenated PyPI-compliant
names** (e.g., `langchain-astradb` instead of `langchain_astradb`).
- Updated `package` links to point to the **specific class-level API
references** (e.g., `/api_reference/.../storage/...ClassName.html`) for
precision.
These improvements enhance:
- Navigation experience for users
- Alignment with PyPI and docs naming conventions
- Clarity across LangChain’s integrations documentation
## **Issue:** N/A
## **Dependencies:** None
## **Twitter handle:** N/A
docs(alpha_vantage): add link for ALPHAVANTAGE_API_KEY generation in
integration notebook
**Description:**
This PR updates the `docs/docs/integrations/tools/alpha_vantage.ipynb`
integration notebook to help users locate the API key registration page
for Alpha Vantage. The following markdown line was added:
---------
Co-authored-by: Mason Daugherty <mason@langchain.dev>
## **Description:**
This PR updates the internal documentation link for the RAG tutorials to
reflect the updated path. Previously, the link pointed to the root
`/docs/tutorials/`, which was generic. It now correctly routes to the
RAG-specific tutorial page for the following vector store docs.
1. AstraDBVectorStore
2. Clickhouse
3. CouchbaseSearchVectorStore
4. DatabricksVectorSearch
5. ElasticsearchStore
6. FAISS
7. Milvus
8. MongoDBAtlasVectorSearch
9. openGauss
10. PGVector
11. PGVectorStore
12. PineconeVectorStore
13. QdrantVectorStore
14. Redis
15. SQLServer
## **Issue:** N/A
## **Dependencies:** None
## **Twitter handle:** N/A
- **Description:** This PR updates the internal documentation link for
the RAG tutorials to reflect the updated path. Previously, the link
pointed to the root `/docs/tutorials/`, which was generic. It now
correctly routes to the RAG-specific tutorial page.
- **Issue:** N/A
- **Dependencies:** None
- **Twitter handle:** N/A
mishraravibhushan