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Python RAG App Code Example

This project has the purpose of showing how to use the RAG model to generate answers for questions based on a given OpenTelemetry Traces.

The chatbot was inspired by Streamlit Chatbot example.

Setting up the project

First of all, you need to have an OpenAI API Key to use the project, you can get one here.

Then, just create a .env file in the root of the project with the following content:

  # add openai api key
  echo "OPENAI_API_KEY={your-open-ai-api-key}" >> .env

Also, I'm considering that you have Python 3.12 and uv installed in your machine. Otherwise, you can download it here:

Creating a virtual env and downloading the dependencies

You will create a virtual env to have a clean environment to run the project, by executing the following commands:

  # create venv and install dependencies
  uv sync

  # activate venv
  source .venv/bin/activate

Running the use cases

To create the VectorStore and run the chatbot you can use the following commands:

  # create vector store
  python ./app/create_vector_store.py --trace-file=$PWD/data/trace.json --preprocessed-trace-file=$PWD/data/trace-description.txt

  # run chatbot
  streamlit run ./app/streamlit_app.py