@Marvin Is there an actively maintained

prefect-langchain

or

langchain-prefect

library for handling interaction between langchain and prefect?

✅ thought for 240.0 seconds

no! there is not

Short answer: Not right now. I’m not aware of an officially maintained package named

prefect-langchain

or

langchain-prefect

for Prefect 3.x. There have been occasional mentions in blogs of a potential plugin, but there isn’t a GA, actively maintained integration library published on GitHub or PyPI today. Current guidance is to run LangChain code directly inside Prefect flows—no special adapter required. Typical patterns: - Wrap chains/agents in

@flow

(and

@task

if helpful) for retries, scheduling, and observability. - Manage API keys with Prefect secrets: Store secrets in Prefect - Deploy your app with

prefect deploy

(via prefect.yaml) or programmatically from source: - Deploy with prefect.yaml - Use Prefect logging, artifacts, and events for observability: - Logs API - Artifacts API - Events concept - For LLM-specific tracing (e.g., token/latency at the prompt level), pair LangChain’s callback system with tools like LangSmith or Langfuse alongside Prefect for orchestration. Prefect’s blog context: Keeping your eyes on AI tools. If you share what you’re trying to achieve (e.g., scheduling, retries, cost tracking, callback-based tracing), I can suggest a minimal pattern or starter snippet tailored to your setup.

@Nate thank you! Is there a preferred LLM library that works better with Prefect? Or is the preferred way of interacting with llm libraries just calling them inside a flow?

interacting with llm libraries just calling them inside a flow?

this is what i generally recommend. im biased 🙂 but i prefer `marvin` or the library its built on, `pydantic-ai` but regardless of which agentic while loop you prefer, you can call it from a flow or task