This is a demo app made using Reflex, Llama Index, LangChain, Weaviate, Traceloop and OpenAI.

• OpenAI API key: the app uses OpenAI embedding and chat functionality.
• Traceloop API key: the app traces the function call to OpenAI and export to Traceloop dashboard.
• Weaviate: create a free 14-day cluster and gets the URL and API key to create connection client.

reflex>=0.4.7
reflex-chat
langchain
llama-index
llama-index-vector-stores-weaviate
traceloop-sdk

export TRACELOOP_API_KEY=12345yourkey
export OPENAI_API_KEY=sk-your-key
export WCS_URL=https://your-index-random-numbers.weaviate.network
export WCS_API_KEY=your-key

This demo uses the free 14-day vector database cluster. Go to their website and create an account. After creating the cluster, note the connection information (the URL and the API key).

Set the OPENAI_API_KEY, WC_URL, WC_API_KEY as environment variables, then run the scripts/setup_wcs.py. The setup_wcs.py scripts ingest a directory of markdown files and create an index in the remote Weaviate cluster. In this demo, the folder contains all the markdown files for (a subset of) the reflex documentation.

This app is based on Reflex framework. In the top level directory (this directory has a file named rxconfig.py), run the following commands to run the app:

reflex init
reflex run

Then go to https://localhost:3000 or another URL shown in the terminal when the app is running. Chat and get the results based on the reflex documentation.

Go to the traceloop dashboard, you can see stats such as the tokens and models used for OpenAI calls.