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Bumps the uv group with 1 update in the /libs/core directory: [setuptools](https://github.com/pypa/setuptools). Updates `setuptools` from 67.8.0 to 78.1.1 <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/pypa/setuptools/blob/main/NEWS.rst">setuptools's changelog</a>.</em></p> <blockquote> <h1>v78.1.1</h1> <h2>Bugfixes</h2> <ul> <li>More fully sanitized the filename in PackageIndex._download. (<a href="https://redirect.github.com/pypa/setuptools/issues/4946">#4946</a>)</li> </ul> <h1>v78.1.0</h1> <h2>Features</h2> <ul> <li>Restore access to _get_vc_env with a warning. (<a href="https://redirect.github.com/pypa/setuptools/issues/4874">#4874</a>)</li> </ul> <h1>v78.0.2</h1> <h2>Bugfixes</h2> <ul> <li>Postponed removals of deprecated dash-separated and uppercase fields in <code>setup.cfg</code>. All packages with deprecated configurations are advised to move before 2026. (<a href="https://redirect.github.com/pypa/setuptools/issues/4911">#4911</a>)</li> </ul> <h1>v78.0.1</h1> <h2>Misc</h2> <ul> <li><a href="https://redirect.github.com/pypa/setuptools/issues/4909">#4909</a></li> </ul> <h1>v78.0.0</h1> <h2>Bugfixes</h2> <ul> <li>Reverted distutils changes that broke the monkey patching of command classes. (<a href="https://redirect.github.com/pypa/setuptools/issues/4902">#4902</a>)</li> </ul> <h2>Deprecations and Removals</h2> <ul> <li>Setuptools no longer accepts options containing uppercase or dash characters in <code>setup.cfg</code>.</li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="8e4868a036"><code>8e4868a</code></a> Bump version: 78.1.0 → 78.1.1</li> <li><a href="100e9a61ad"><code>100e9a6</code></a> Merge pull request <a href="https://redirect.github.com/pypa/setuptools/issues/4951">#4951</a></li> <li><a href="8faf1d7e0c"><code>8faf1d7</code></a> Add news fragment.</li> <li><a href="2ca4a9fe47"><code>2ca4a9f</code></a> Rely on re.sub to perform the decision in one expression.</li> <li><a href="e409e80029"><code>e409e80</code></a> Extract _sanitize method for sanitizing the filename.</li> <li><a href="250a6d1797"><code>250a6d1</code></a> Add a check to ensure the name resolves relative to the tmpdir.</li> <li><a href="d8390feaa9"><code>d8390fe</code></a> Extract _resolve_download_filename with test.</li> <li><a href="4e1e89392d"><code>4e1e893</code></a> Merge <a href="https://github.com/jaraco/skeleton">https://github.com/jaraco/skeleton</a></li> <li><a href="3a3144f0d2"><code>3a3144f</code></a> Fix typo: <code>pyproject.license</code> -> <code>project.license</code> (<a href="https://redirect.github.com/pypa/setuptools/issues/4931">#4931</a>)</li> <li><a href="d751068fd2"><code>d751068</code></a> Fix typo: pyproject.license -> project.license</li> <li>Additional commits viewable in <a href="https://github.com/pypa/setuptools/compare/v67.8.0...v78.1.1">compare view</a></li> </ul> </details> <br /> [](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot merge` will merge this PR after your CI passes on it - `@dependabot squash and merge` will squash and merge this PR after your CI passes on it - `@dependabot cancel merge` will cancel a previously requested merge and block automerging - `@dependabot reopen` will reopen this PR if it is closed - `@dependabot close` will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually - `@dependabot show <dependency name> ignore conditions` will show all of the ignore conditions of the specified dependency - `@dependabot ignore <dependency name> major version` will close this group update PR and stop Dependabot creating any more for the specific dependency's major version (unless you unignore this specific dependency's major version or upgrade to it yourself) - `@dependabot ignore <dependency name> minor version` will close this group update PR and stop Dependabot creating any more for the specific dependency's minor version (unless you unignore this specific dependency's minor version or upgrade to it yourself) - `@dependabot ignore <dependency name>` will close this group update PR and stop Dependabot creating any more for the specific dependency (unless you unignore this specific dependency or upgrade to it yourself) - `@dependabot unignore <dependency name>` will remove all of the ignore conditions of the specified dependency - `@dependabot unignore <dependency name> <ignore condition>` will remove the ignore condition of the specified dependency and ignore conditions You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/langchain-ai/langchain/network/alerts). </details> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
The platform for reliable agents.
LangChain is a framework for building agents and LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development – all while future-proofing decisions as the underlying technology evolves.
pip install langchain
If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.
Documentation:
- docs.langchain.com – Comprehensive documentation, including conceptual overviews and guides
- reference.langchain.com/python – API reference docs for LangChain packages
Discussions: Visit the LangChain Forum to connect with the community and share all of your technical questions, ideas, and feedback.
Note
Looking for the JS/TS library? Check out LangChain.js.
Why use LangChain?
LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
Use LangChain for:
- Real-time data augmentation. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain's vast library of integrations with model providers, tools, vector stores, retrievers, and more.
- Model interoperability. Swap models in and out as your engineering team experiments to find the best choice for your application's needs. As the industry frontier evolves, adapt quickly – LangChain's abstractions keep you moving without losing momentum.
- Rapid prototyping. Quickly build and iterate on LLM applications with LangChain's modular, component-based architecture. Test different approaches and workflows without rebuilding from scratch, accelerating your development cycle.
- Production-ready features. Deploy reliable applications with built-in support for monitoring, evaluation, and debugging through integrations like LangSmith. Scale with confidence using battle-tested patterns and best practices.
- Vibrant community and ecosystem. Leverage a rich ecosystem of integrations, templates, and community-contributed components. Benefit from continuous improvements and stay up-to-date with the latest AI developments through an active open-source community.
- Flexible abstraction layers. Work at the level of abstraction that suits your needs - from high-level chains for quick starts to low-level components for fine-grained control. LangChain grows with your application's complexity.
LangChain ecosystem
While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
To improve your LLM application development, pair LangChain with:
- LangGraph – Build agents that can reliably handle complex tasks with LangGraph, our low-level agent orchestration framework. LangGraph offers customizable architecture, long-term memory, and human-in-the-loop workflows – and is trusted in production by companies like LinkedIn, Uber, Klarna, and GitLab.
- Integrations – List of LangChain integrations, including chat & embedding models, tools & toolkits, and more
- LangSmith – Helpful for agent evals and observability. Debug poor-performing LLM app runs, evaluate agent trajectories, gain visibility in production, and improve performance over time.
- LangSmith Deployment – Deploy and scale agents effortlessly with a purpose-built deployment platform for long-running, stateful workflows. Discover, reuse, configure, and share agents across teams – and iterate quickly with visual prototyping in LangSmith Studio.
- Deep Agents (new!) – Build agents that can plan, use subagents, and leverage file systems for complex tasks
Additional resources
- API Reference – Detailed reference on navigating base packages and integrations for LangChain.
- Contributing Guide – Learn how to contribute to LangChain projects and find good first issues.
- Code of Conduct – Our community guidelines and standards for participation.
- LangChain Academy – Comprehensive, free courses on LangChain libraries and products, made by the LangChain team.