DLI Course 'Building RAG Agents for LLMs' - Assessment Support

Hi team,

I am finishing the final assessment of Deep Learning Institute course ‘Building RAG Agents
for LLMs’.

However, although I successfully launched basic_chat, retriever and generator models to 9012 port and able to generate response locally, when run the evaluation script server_app.py, it could not start Gradio UI, it only shows ‘Starting FastAPI app’.
Therefore, when assess task, it shows ‘it does not look like you completed the assessment yet’.

I need some technical support to debug the issue, in order to pass the assessment.
dli #rag

Best,
Fortuna

Hey Fortuna!

Sorry about the delay! server_app.py is running perpetually in another microservice and the UI should be getting exposed to a port (:8090 I think). From there, you should be hitting the evaluate button to execute the script. Does this help?

Hi,
I have the same problem. Did you manage to do it? I’m going insane :(

Hi @vkudlay, thanks for your reply.

I successfully got Gradio run, and passed all the evaluation questions, as screenshot attached.
The chatbot showed ‘Congrats! You passed the assessment!’.

However, when assessed task, it still showed the same issue.
Could you please to clarify why Gradio UI and environment assess task results are not align?

Best,
Fortuna

Awesome! Did you kickstart the service yourself, or are you using the one perpetually open at <course_url>:8090? If you started it yourself, then the # secret line is still just a comment, hence passing the test does nothing. The running frontend microservice has some actual commands that run in place of that one.

If you’re curious how this is achieved:

  mod: ## Modifier service. Does nothing in dev. Removes solution component in prod
     container_name: modifier
     context: notebooks/docker_router
     dockerfile: Dockerfile
     volumes: 
      - /var/run/docker.sock:/var/run/docker.sock
      - ./notebooks/:/notebooks/
    depends_on: 
      - "frontend"
    command: >
      sed -i -e 's:code_that_does_something():## secret:g' /notebooks/frontend/server_app.py

Example: If your course environment url is http://blablabla.aws.labs.courses.nvidia.com/lab/lab, then frontend should be running on http://blablabla.aws.labs.courses.nvidia.com:8090

Hi I am getting this below error while running server_app.py “Assessment” kindly help…

I have deployed the llms in 9012 port using langserve but still facing this issue unable to complete kindly help.

error logs:

Gradio Stream failed: [{‘loc’: ('root ',), ‘msg’: ‘str type expected’, ‘type’: ‘type_error.str’}, {‘loc’: ('root ', ‘text’), ‘msg’: ‘field required’, ‘type’: ‘value_error.missing’}, {‘loc’: ('root ', ‘messages’), ‘msg’: ‘field required’, ‘type’: ‘value_error.missing’}, {‘loc’: ('root ',), ‘msg’: ‘value is not a valid list’, ‘type’: ‘type_error.list’}]

Heyo! There’s a number of things that could be happening. I’d need more information about the surrounding context to be of much help. The issue is definitely stemming from the fact that the history is getting corrupted (maybe one of your chains is returning none, or maybe your generator chain isn’t quite there). Can you provide some more context?
The tip on the assessment is to check over the frontend code and see what exactly needs to be deployed for your remoterunnable to properly slot into the frontend-side orchestration.