I apologize for the confusion in my earlier CLI command. Let me correct the recommendation: The best solution is to modify your deployment configuration to specify the working directory:

python
from prefect.infrastructure import Process

# Create a Process infrastructure with the correct working directory
process_infrastructure = Process(
    working_dir="/root/path/to"  # This should be the directory containing your flow code
)

# Use this when deploying your flow
flow.deploy(
    name="your-deployment",
    infrastructure=process_infrastructure
)

This will ensure that the process worker knows where to find your flow files in the container. The working directory should be the parent directory of your flow file. If you're still having issues, you might want to: 1. Verify the exact path of your flow file in the container (you can do this by running

ls -l /root/path/to/my/entrypoint.py

inside the container) 2. Make sure the process worker has the necessary permissions to read the directory 3. Consider using absolute paths rather than relative paths in your deployment configuration Would you like me to provide more details about any of these aspects or help troubleshoot further?

You can create a process work pool with a specific base job template that includes the working directory configuration:

bash
# Create a process work pool
prefect work-pool create "your-process-pool" \
    --type process \
    --job-configuration '{
        "working_dir": "/root/path/to"
    }'

Then deploy your flow to this work pool:

python
flow.deploy(
    name="your-deployment",
    work_pool_name="your-process-pool"
)

This should resolve the file path issues by ensuring the process worker knows where to find your flow code in the container. The worker will use the specified working directory when executing flows. Would you like me to provide more details about any of these configurations or help troubleshoot further?

Based on the investigation, I think I understand what's happening. The issue appears to be related to how the flow code is being deployed and accessed. Here are a few potential solutions: 1. Use Direct Path in Deployment: Instead of letting Prefect manage the code location, try specifying the exact path in your deployment:

python
   flow.deploy(
       name="your-deployment",
       work_pool_name="your-process-pool",
       path="/root/path/to/my/entrypoint.py"  # Absolute path in the container
   )

2. Mount the Code Directory: Make sure your worker container has the flow code directory mounted correctly. In your docker-compose or container configuration, add:

yaml
   volumes:
     - /root/path/to:/root/path/to

3. Use From Source Deployment: Since the code is already in your container, you can use the

from_source

method:

python
   from prefect.deployments import DeploymentImage
   
   flow.deploy(
       name="your-deployment",
       work_pool_name="your-process-pool",
       image=DeploymentImage(
           name="your-image:tag",
           path="/root/path/to/my/entrypoint.py"
       )
   )

4. Check Work Pool Configuration: Verify your work pool configuration includes:

json
   {
       "working_dir": "/root/path/to",
       "env": {
           "PYTHONPATH": "/root/path/to"
       }
   }

Can you try one of these approaches, particularly the first or third option? Also, it would be helpful to know: 1. How are you currently deploying the flow? 2. Can you share the relevant part of your deployment configuration? 3. Can you confirm the exact path where your flow code exists in the container (maybe by running

ls -l /root/path/to/my/entrypoint.py

inside the container)?