mirror of
https://github.com/hwchase17/langchain
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a74f3a4979
**Description:** Batch update of alt text and title attributes for images in `md` & `mdx` files across the repo using [alttexter](https://github.com/jonathanalgar/alttexter)/[alttexter-ghclient](https://github.com/jonathanalgar/alttexter-ghclient) (built using LangChain/LangSmith). **Limitation:** cannot update `ipynb` files because of [this issue](https://github.com/langchain-ai/langchain/pull/15357#issuecomment-1885037250). Can revisit when Docusaurus is bumped to v3. I checked all the generated alt texts and titles and didn't find any technical inaccuracies. That's not to say they're _perfect_, but a lot better than what's there currently. [Deployed](https://langchain-819yf1tbk-langchain.vercel.app/docs/modules/model_io/) image example:  You can see LangSmith traces for all the calls out to the LLM in the PRs merged into this one: * https://github.com/jonathanalgar/langchain/pull/6 * https://github.com/jonathanalgar/langchain/pull/4 * https://github.com/jonathanalgar/langchain/pull/3 I didn't add the following files to the PR as the images already have OK alt texts: *27dca2d92f/docs/docs/integrations/providers/argilla.mdx (L3)*27dca2d92f/docs/docs/integrations/providers/apify.mdx (L11)--------- Co-authored-by: github-actions <github-actions@github.com>
58 lines
3.1 KiB
Markdown
58 lines
3.1 KiB
Markdown
# 🦜🍎️ LangChain Core
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[](https://pepy.tech/project/langchain_core)
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[](https://opensource.org/licenses/MIT)
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## Quick Install
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```bash
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pip install langchain-core
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```
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## What is it?
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LangChain Core contains the base abstractions that power the rest of the LangChain ecosystem.
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These abstractions are designed to be as modular and simple as possible.
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Examples of these abstractions include those for language models, document loaders, embedding models, vectorstores, retrievers, and more.
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The benefit of having these abstractions is that any provider can implement the required interface and then easily be used in the rest of the LangChain ecosystem.
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For full documentation see the [API reference](https://api.python.langchain.com/en/stable/core_api_reference.html).
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## What is LangChain Expression Language?
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LangChain Core also contains LangChain Expression Language, or LCEL, a runtime that allows users to compose arbitrary sequences together and get several benefits that are important when building LLM applications.
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We call these sequences “runnables”.
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All runnables expose the same interface with single-invocation, batch, streaming and async methods.
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This design is useful because it is not enough to have a single sync interface when building an LLM application.
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Batch is needed for efficient processing of many inputs.
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Streaming (and streaming of intermediate steps) is needed to show the user that progress is being made.
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Async interfaces are nice when moving into production.
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Rather than having to write multiple implementations for all of those, LCEL allows you to write a runnable once and invoke it in many different ways.
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For more check out the [LCEL docs](https://python.langchain.com/docs/expression_language/).
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## 📕 Releases & Versioning
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`langchain-core` is currently on version `0.1.x`.
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As `langchain-core` contains the base abstractions and runtime for the whole LangChain ecosystem, we will communicate any breaking changes with advance notice and version bumps. The exception for this is anything in `langchain_core.beta`. The reason for `langchain_core.beta` is that given the rate of change of the field, being able to move quickly is still a priority, and this module is our attempt to do so.
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Minor version increases will occur for:
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- Breaking changes for any public interfaces NOT in `langchain_core.beta`
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Patch version increases will occur for:
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- Bug fixes
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- New features
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- Any changes to private interfaces
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- Any changes to `langchain_core.beta`
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## 💁 Contributing
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As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
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For detailed information on how to contribute, see the [Contributing Guide](https://python.langchain.com/docs/contributing/). |