Llama Stack: Meta proposes a unified API spec for the LLM lifecycle
In one sentence Meta announces Llama Stack: an API spec + reference implementations for inference, safety, agents, memory, evals, RAG, and training — meant as 'standard plumbing' for Llama-based applications.
Meta isn't just releasing Llama models — it's also proposing a standard way to build apps on top of them. It's called Llama Stack: an API spec for everything around the model — safety, agents, document search (RAG), memory, evaluation, fine-tuning.
The idea: today if you build an AI app you choose between LangChain, LlamaIndex, Pydantic AI, OpenAI/Anthropic proprietary frameworks. Meta proposes a common API set with open-source reference implementations so different providers can build interchangeable components.
It's not the first attempt to standardize the AI ecosystem (see MCP a few months later) but Meta brings the weight and adoption of the Llama brand.
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