cQubeChat is an intuitive and user-friendly application that allows you to interact with your cQube data using natural language prompts. Type in your questions or requests, and cQubeChat will generate the appropriate SQL query and return the data you need. No more complex SQL queries or digging through tables - cQubeChat makes it easy to access your data!
Features:
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Natural Language Processing: Understands your text queries and displays data in a user-friendly manner.
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Instant Results: Fetches the data from your cQube database and displays the results quickly.
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Data Visualizations: Creates data visualization such as charts and graphs for generating quick insights with data.
- Update OPENAI_API_KEY key in .env file with your own Open Api key and change HASURA_API_URL from
http://hasura:8080
to
http://localhost:8084
- Comment the following lines in docker-compose.yml
chatbot:
image: chatbot
build:
context: .
dockerfile: Dockerfile
ports:
- 8501:8501
- Run the following command to start the postgres database and hasura.
docker compose -f docker-compose.yml up -d
- Once all the containers are up, run the following command to synchronize hasura metadata.
sh import_metadata.sh
-
In the code Create a python virtual environment and install dependencies:
python -m venv cqubechat_venv source cqubechat_venv/bin/activate pip install -r requirements.txt
-
Run the Steamlit app using:
streamlit run cQubeChat.py
This should open up a browser window with the cQubeChat app
-
Update OPENAI_API_KEY key in .env file with your own Open Api key.
-
Run the following command to start the cQubeChat along with the postgres database and hasura.
docker compose -f docker-compose.yml up -d
- Once all the containers are up, run the following command to synchronize hasura metadata.
sh import_metadata.sh
https://drive.google.com/file/d/1WxyGClRnjW3ITVP18iJZux65y0R7N_zc/view?usp=sharing