OpenAI’s LangChain

OpenAI’s LangChain is an integration layer that allows LangChain to call OpenAI GPT-4o, GPT-4 Turbo, or GPT-3.5 via a unified LLM or ChatModel interface. With two environment variables — OPENAI_API_KEY and OPENAI_MODEL_NAME — developers can drop an OpenAI model into any chain, agent, or Retrieval-Augmented Generation (RAG) pipeline. Methods like generate, stream, and get_num_tokens handle retries, exponential backoff, and cost tracking, while function invocation support transforms JSON schemas into callable tools. Temperature, top-p, and system hints map directly to OpenAI parameters, so teams can customize creativity without breaking code. Callbacks send token streams and latency metrics to dashboards, and LangChain router chains allow applications to mix OpenAI with Claude or Gemini on the fly. When combined with LangChain vector stores, OpenAI powers chatbots, code assistants, and analytics agents that remain factual and scalable, turning a few lines of Python into enterprise-ready AI services.