Unable to add dependencies to mlflow.langchain.log_model

[yashshingvi]

Hello,

I'm doing this-

with mlflow.start_run(run_name="run1"):
  logged_chain_info = mlflow.langchain.log_model(
        #   lc_model=os.path.join(os.getcwd(), 'full_chain'), this doesnt work too  
          lc_model='/Workspace/Users/{user_name}/exp/deploy_chain.py',
          model_config="/Workspace/Users/{user_name}/exp/chain_config.yaml", 
          artifact_path="exp_1_artifact",
    
          input_example=input_example,
          example_no_conversion=True,
          code_paths=["/Workspace/Users/{user_name}/exp/example_docs.py"]

      )

But when I do import example_docs in deploy_chain.py it says module not found when I run the above code.

Similarly,

If I try to add a pdf/image file in code_paths and try to access it using relative path it fails on the mlflow run step, If I give absolute path, it fails while serving the endpoint (file not found).

How should I add dependent files to this?