LangChain Llama 3

LangChain Llama 3 is a wrapper that connects Llama 3 models with open Meta weights — 8B, 70B, and 400B-MoE — to LangChain’s unified ChatModel and LLM interfaces. After installing ctransformers or calling an API like Together, Anyscale, or Groq, developers instantiate a Llama3 instance with a model path, context window, and GPU/CPU settings, then place it into chains, agents, or Retrieval-Augmented Generation (RAG) pipelines just like they do with GPT-4. The wrapper supports streaming, function invocation (via JSON mode), and token count estimation to control costs. Quantized GGUF files allow Llama 3 to run locally on a laptop while router chains mix it with Gemini or Claude for hybrid workloads. Because LangChain provides consistent methods — generate, stream, get_num_tokens— teams can compare the open source version of Llama 3 with proprietary models, A/B testing queries, and switch backends with a single line of code, enabling lean, data-sovereign AI without rewriting business logic.