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Resolved! streaming llm response
I am deploying an agent that works good withouth streaming:it is using the following packages: "mlflow==2.22.1", "langgraph", "langchain", "pydantic==2.8.2", "langgraph-checkpoint-sqlite", "databricks-langchain", "p...
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To implement streaming output for your agent in Databricks and resolve the error "This model does not support predict_stream method.", the key requirement is that your underlying MLflow model must support the predict_stream method. Most l...
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- 6174 Views
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Resolved! LangGraph MemorySaver checkpointer usage with MLflow
Hi everyone.I am working on a graph that utilizes the MemorySaver class to incorporate short-term memory. This will enable me to maintain a multi-turn conversation with the user by storing the chat history.I am using the MLflow "models from code" fea...
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Hi @moemedina. No, I didn't.I'm considering using ChatModel/ChatAgent class to wrap the graph and be able to move on. However, the MLflow documentation is still referring to ChatModel where Chat Agent is the latest recommendation:MLflow ChatModel Doc...
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- 3364 Views
- 1 replies
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I am struggling on complicated RAG code for Mosaic evaluation deployment
I want to know how I can apply some complicated RAG designs so I can directly deploy on the Mosaic AI evaluation UI. There are two cases:1. two or more index retrieval as independent tools (parallel retrievals)2.two index retrieval processes that dep...
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Interesting use case, would love to know the answer!
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- 2355 Views
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Retrieved Docs in Message History
Hi,I've deployed a Langchain model via MLFlow log model and a deployment agent (following this https://notebooks.databricks.com/demos/llm-rag-chatbot/index.html#)How do I add additional content to the message history for example, I'd like to add retr...
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Hi @davidhuang thanks for pointing to that demo! That implementation of chat history did work in my experience, but it's a little simplistic and could be token-intensive if the history needs to be maintained as a list like that. Has Databricks done a...
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