Set up an virtual env and load requirements.txt

To start weaviate use the docker-compose in the weaviate directory docker-compose up

#Index Data For reading the Confluence set: CONFLUENCE_JSESSION_ID= in .env file. The JSESSION_ID shall be get from the Browser cookies after logging in. I tried to use the token, with no success. In .env set values

AZURE_KEY=
AZURE_ENDPOINT=
AZURE_VERSION=
AZURE_EMBEDDING_DEPLOYMENT=

to be able to connect the embeddings in azure.

Make sure the weaviate Database is empty. Then:

set -o allexport; source .env; set +o allexport
cd reader
python ./reader.py

and wait.

#Run it Weviate creates an index, you get it by: http://127.0.0.1:8081/v1/schema the index is named 'class'

Add the name to the value WEAVIATE_INDEX= in .env Set the LLM Deplyoment to use to the value AZURE_LLM_DEPLOYMENT in `.env``

Load it by set -o allexport; source .env; set +o allexport in the console.

Start the frontend (backend is started in background then):

cd chat
python ./frontend.py

Visit: http://127.0.0.1:7860/ Type a question, get a result, type another question, get an error ;-)