LangChain integrations

LangChain integrations are pluggable adapters that connect the framework’s core abstractions — loaders, embeds, vector stores, chains, agents, and callbacks — to third-party services. Over 100 integrations span LLMs (GPT-4, Claude, Gemini), vector databases (Chroma, Pinecone, Milvus, Weaviate, FAISS), data sources (S3, Google Drive, Notion), observability tools (Weights & Biases, OpenTelemetry), and orchestration layers (Ray, FastAPI, n8n). Each integration implements a unified interface — VectorStore, DocumentLoader, ChatModel — so developers change providers with a single line of code, balancing speed, cost, and compliance. Maturity badges in the documentation mark adapters as community, verified, or enterprise, while semantic versioning ensures compatibility across weekly releases. Callbacks handle latency and token metrics at each integrated layer, turning LangChain integrations into a glue that transforms isolated SaaS APIs into cohesive, ready-to-use pipelines with large language models.