# langchain-ai/langchain

The agent engineering platform.

Repository: https://github.com/langchain-ai/langchain
Canonical: https://ross.abutalabs.com/products/langchain
Homepage: https://docs.langchain.com/langchain/
Language: Python
License: MIT
License Family: permissive
Topics: ai, anthropic, gemini, langchain, llm, openai, python, agents, ai-agents, chatgpt, enterprise, framework, generative-ai, multiagent, open-source, pydantic, rag, deepagents, langgraph, typescript
Last push: 2026-08-26T23:12:17+00:00

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 100
- inputs: {"age_days": 1416, "days_push": 7, "days_rel": 8, "gap_med": 0.0, "n_releases_24m": 787}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 145076, forks 24198 (observed 2026-08-28T04:12:24.337992+00:00)

## What it is
LangChain is an open-source Python framework for building LLM-powered agents and applications, providing a configurable agent harness (create_agent) plus 1000+ provider integrations for chat models, embeddings, tools, and vector stores. It anchors an ecosystem including LangGraph for low-level orchestration, Deep Agents for batteries-included agents, and LangSmith for tracing and evaluation.

## Use cases
- build an ai agent with tool calling in python
- swap between openai, anthropic, and gemini models without changing code
- build a rag chatbot over my documents
- create a multi-agent workflow with planning and subagents
- chain llm calls with custom tools and middleware
- prototype an llm application with vector store integrations
- add tracing and evaluation to my agent app

## When to choose
- you want a model-agnostic framework with a huge integration ecosystem
- you need a customizable agent harness with middleware and tool support
- you want to build RAG pipelines or chatbots quickly in Python
- you plan to scale from simple agents to complex LangGraph workflows

## When to avoid
- you need only raw model API calls without abstractions - use provider SDKs directly
- you want a minimal dependency-free solution for simple LLM usage
- you need a JS/TS-first codebase - use LangChain.js instead
- you require strict control over every prompt token and dislike framework magic

## Facets
- artifact type: framework
- maturity: stable
- function: agent-framework, llm-inference, rag, chatbot, sdk, middleware
- domain: artificial-intelligence, large-language-models, chatbots, developer-tools
- platform: python, cross-platform
- tags: llm, agents, multi-agent, model-agnostic, integrations, langgraph, deep-agents, openai, anthropic, gemini, ai-agents, retrieval-augmented-generation

## Member repositories
- langchain-ai/langchain (main) score 95

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:24.337992+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:11:05.139865+00:00, confidence not recorded.
  - readme: https://github.com/langchain-ai/langchain (fetched 2026-08-28T04:12:24.337992+00:00, sha 6b4aefe74b4e)
  - homepage: https://docs.langchain.com/langchain/ (fetched 2026-08-28T17:25:38.498580+00:00, sha 1068164804a0)
  - site_page: https://docs.langchain.com/ (fetched 2026-08-28T17:25:38.500772+00:00, sha e6cbe67a291c)
  - site_page: https://docs.langchain.com/oss/python/integrations/providers/overview (fetched 2026-08-28T17:25:38.502859+00:00, sha 8260e6c475ce)
  - site_page: https://docs.langchain.com/oss/python/langchain/install (fetched 2026-08-28T17:25:38.505061+00:00, sha f72550dc8995)
  - site_page: https://docs.langchain.com/oss/python/langchain/quickstart (fetched 2026-08-28T17:25:38.506795+00:00, sha 67f67652a75d)
  - site_page: https://docs.langchain.com/oss/python/releases/changelog (fetched 2026-08-28T17:25:38.508953+00:00, sha 048dded673bc)
  - site_page: https://docs.langchain.com/langsmith/trace-with-langchain (fetched 2026-08-28T17:25:38.510874+00:00, sha 32a7ec425016)
  - site_page: https://docs.langchain.com/use-these-docs (fetched 2026-08-28T17:25:38.513067+00:00, sha 5ab7220bb555)
  - site_page: https://changelog.langchain.com/ (fetched 2026-08-28T17:25:38.515032+00:00, sha 3c5994039295)
- Data as of 2026-08-30T08:39:29.467469+00:00.