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11-11-2024 11:32 AM
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.
