chatbot: A Python repository from gavincapriola

Files Overview

app.py: This file sets up the Beam application, specifying the resources it requires and the Python packages it depends on. It also defines the REST API trigger for the application.
run.py: This file is responsible for:
- Loading documents from the ./data directory.
- Splitting the texts from the documents.
- Generating embeddings for the split texts using the OpenAI API.
- Creating a FAISS vector store from the embeddings.
- Setting up a RetrievalQA system using langchain.
- Defining a handler function that takes a query and returns a response from the QA system.

Ensure you've set the openai_api_key variable in run.py to your OpenAI API key.
Run the Beam application.
Once the application is running, you can make a REST API call to the endpoint with a query, and the system will return a predicted response.

For example, calling the handler with the query "What is the meaning of life?" will return a response from the RetrievalQA system.

Please ensure that the data directory (./data) contains your .txt files to be loaded by the DirectoryLoader.
The openai_api_key should be kept confidential. Consider using environment variables or a configuration file to securely store and retrieve it.

Contributions are welcome! Please make sure to test your changes before submitting a pull request.