https://github.com/liteobject/langchain-basics
https://github.com/liteobject/langchain-basics
Last synced: 11 months ago
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- Host: GitHub
- URL: https://github.com/liteobject/langchain-basics
- Owner: LiteObject
- Created: 2024-01-26T04:08:46.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-07-05T03:30:58.000Z (almost 2 years ago)
- Last Synced: 2024-12-29T18:21:19.094Z (over 1 year ago)
- Language: Python
- Size: 662 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# LangChain: Building Powerful Applications with Large Language Models (LLMs) 🦜️🔗
LangChain is an open-source framework designed to simplify the creation of applications powered by Large Language Models (LLMs). It provides a robust set of tools, components, and interfaces that allow developers to seamlessly integrate LLMs with other computational resources and knowledge sources. This enables the development of sophisticated, context-aware applications that go beyond the capabilities of standalone LLMs.
## Key Features and Components
LangChain's ecosystem is built around several core components:
- **LangChain Libraries (Python & JavaScript):**
- **Interfaces and Integrations:** A vast collection of pre-built integrations with various LLMs, vector databases, document loaders, and other tools.
- **Chains and Agents:** A flexible runtime for composing LLM-powered workflows (chains) and autonomous agents that can interact with the environment.
- **Off-the-Shelf Implementations:** Ready-to-use chains and agents for common tasks, accelerating development.
- **LangChain Templates (Python):**
- **Reference Architectures:** A curated collection of deployable application blueprints for a wide range of use cases, providing a solid foundation for your projects.
- **LangServe (Python):**
- **API Deployment:** A streamlined solution for deploying LangChain chains as RESTful APIs, making it easy to integrate your LLM applications into other systems.
- **LangSmith:**
- **Development Platform:** A comprehensive platform for debugging, testing, evaluating, and monitoring LLM applications built with any framework.
- **Seamless LangChain Integration:** Deep integration with LangChain for enhanced observability and control.
- **LangGraph:**
- **Stateful Multi-Actor Applications:** Build complex applications with multiple actors and state management.
- **Graph-Based Architecture:** Model steps as nodes and edges in a graph, enabling robust and flexible workflows.
## LangChain Architecture: A Layered Approach
LangChain's architecture is designed for modularity and extensibility. It can be visualized as a stack:
- **langchain-core:**
- **Foundation:** Provides the fundamental abstractions and the LangChain Expression Language (LCEL).
- **LCEL:** A declarative language for composing chains, enabling efficient and expressive workflow definitions.
- **langchain-community:**
- **Integrations Hub:** A growing collection of third-party integrations, expanding the capabilities of LangChain.
- **langchain:**
- **Application Logic:** Contains the core building blocks for creating LLM applications, including chains, agents, and retrieval strategies.
- **langgraph:**
- **Graph-Based Workflows:** Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph.
- **langserve:**
- **Deployment:** Enables the deployment of LangChain chains as REST APIs.
- **LangSmith:**
- **Observability:** A developer platform for debugging, testing, evaluating, and monitoring LLM applications.
## LangChain Expression Language (LCEL)
[LCEL](https://js.langchain.com/v0.1/docs/get_started/introduction/#langchain-expression-language-lcel) is a powerful declarative way to compose chains. It allows you to define complex workflows in a concise and readable manner.
## Getting Started
Ready to start building with LangChain? Here are some helpful resources:
- **LangChain Introduction:** [https://python.langchain.com/docs/get_started/introduction](https://python.langchain.com/docs/get_started/introduction)
- **LangChain Python Documentation:** [https://python.langchain.com/docs/](https://python.langchain.com/docs/)
- **LangChain JavaScript Documentation:** [https://js.langchain.com/docs/](https://js.langchain.com/docs/)
- **GitHub: langchain-ai/langchain:** [https://github.com/langchain-ai/langchain](https://github.com/langchain-ai/langchain)
- **GitHub: langchain-ai/rag-from-scratch:** [https://github.com/langchain-ai/rag-from-scratch](https://github.com/langchain-ai/rag-from-scratch)