topic Re: Facing issues with passing memory checkpointer in lanngraph agents in Machine Learning

Facing issues with passing memory checkpointer in lanngraph agents

kishan_ — Mon, 28 Oct 2024 06:57:18 GMT

Hi,

I am trying to create a simple langgraph agent in Databricks, the agent also uses lanngraph memory checkpoint which enables to store the state of the graph. This is working fine when I am trying it in Databricks notebook, but when I tried to log this as Mlfow model, I couldn't find any documentation on where to pass the memory checkpoint

I want to know if there is way we can pass memory checkpoint when logging langgraph agent in Mlflow

Re: Facing issues with passing memory checkpointer in lanngraph agents

morenoj11 — Mon, 11 Nov 2024 19:04:56 GMT

Facing the same issue here.

Re: Facing issues with passing memory checkpointer in lanngraph agents

morenoj11 — Mon, 11 Nov 2024 19:32:45 GMT

I saw that you can compile the model without checkpointer, register it in MLflow, and then, after loading, assign it after compilation.

```

import mlflow

mlflow.models.set_model(build_graph())

with mlflow.start_run() as run_id:

model_info = mlflow.langchain.log_model(

lc_model="build_graph.py", # Path to our model Python file

artifact_path="langgraph",

)

model_uri = model_info.model_uri

[...]

loaded_model = mlflow.langchain.load_model(model_uri)

loaded_model.checkpointer = checkpointer

loaded_model.invoke(input_state, config) ## config has the thread_id

```

It's not elegant or future-proof, but it might do the trick while we wait for a better solution.

Re: Facing issues with passing memory checkpointer in lanngraph agents

kishan_ — Sun, 12 Jan 2025 08:05:48 GMT

@morenoj11 The solution which you have mentioned, Have you tried to deploy the same in Databricks model serving ?

Re: Facing issues with passing memory checkpointer in lanngraph agents

sebascardonal — Tue, 11 Feb 2025 20:25:38 GMT

Hi all. I have the same issue, could you deploy the graph with the MemorySaver?