LangChain trains custom models for LangSmith Engine with Baseten Loops

LangChain is collaborating with Baseten to train and deploy custom models that power LangSmith Engine, an in-platform agent designed to help users diagnose and improve AI agents autonomously. By fine-tuning open-weight models on agent traces, LangChain can specialize models for tasks such as examining GitHub repositories to identify issue causes and draft related code or prompt changes, while smaller models can be tailored for classification tasks like identifying failure modes or linking traces to open issues. Baseten Loops provides API-based managed infrastructure for supervised fine-tuning, reinforcement learning, long-context workloads, checkpoint evaluation, and direct deployment through Baseten’s inference platform. The partnership aims to shorten the path from model experimentation to production by combining LangChain’s agent evaluation expertise with Baseten’s training and inference infrastructure.

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