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This is great @hwchase17 @bryonkuchML Seeing this update, I’m building a tutorial repo around LangChain + Groq + GEPA. The idea is simple: •…
This is great @hwchase17 @bryonkuchML Seeing this update, I’m building a tutorial repo around LangChain + Groq + GEPA. The idea is simple: •LangChain builds the RAG/agent workflow •Groq gives fast inf
This is great @hwchase17 @bryonkuchML Seeing this update, I’m building a tutorial repo around LangChain + Groq + GEPA. The idea is simple: •LangChain builds the RAG/agent workflow •Groq gives fast inference for iteration •GEPA optimizes prompts against evals This is the part most LLM apps eventually need: not just prompting, but a closed-loop system that can actually improve. I’m using a support-copilot style use case because it applies everywhere: docs Q&A, internal copilots, support agents, and tool-using AI systems. #LangChain #Groq #GEPA #AIEngineering #RAG #AIAgents LangChain🤝GEPA shout out to @bryonkuchML for contributing a PR to the GEPA repo to make it work for LangChain! You can now optimize your LangChain chains Docs: https://gepa-ai.github.io/gepa/tutorials/langchain_adapter_pair_sum_product_walkthrough/
Source: Harrison Chase (X) | 2026-06-01