https://github.com/notyusheng/infojoe
AI-powered natural language interface for PostgreSQL databases. Allows users to query and explore structured data using plain English.
https://github.com/notyusheng/infojoe
docker docker-compose fastapi lm-studio postgres qwen2-5 streamlit
Last synced: about 1 month ago
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AI-powered natural language interface for PostgreSQL databases. Allows users to query and explore structured data using plain English.
- Host: GitHub
- URL: https://github.com/notyusheng/infojoe
- Owner: NotYuSheng
- License: mit
- Created: 2025-04-02T13:01:48.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-04-11T13:22:09.000Z (about 1 month ago)
- Last Synced: 2025-04-11T13:46:22.134Z (about 1 month ago)
- Topics: docker, docker-compose, fastapi, lm-studio, postgres, qwen2-5, streamlit
- Language: Python
- Homepage:
- Size: 125 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# InfoJOE
**InfoJOE** is an AI-powered natural language interface for PostgreSQL databases. It allows users to explore and query structured data using plain English, powered by [Qwen 2.5](https://huggingface.co/Qwen/Qwen1.5-72B-Chat) running via [LM Studio](https://lmstudio.ai/).
Full Page Sample
---
## Getting Started
### Start the Application
Run the following command to build and start the containers:
```docker compose up -d```
This will:
1. Build the Docker images for the FastAPI and Streamlit services.
2. Start the containers and serve the application.
---
## Features
- **Auto Table Discovery**:
Automatically detects all tables in your connected PostgreSQL database.
- **Interactive Table Selection**:
Easily select tables using a click-to-select interface.
- **LLM-Generated Data Dictionary**:
Generates a clear, human-readable data dictionary for any selected table using Qwen 2.5.
- **Diverse Data Sampling**:
Previews a representative sample of rows to reflect different value distributions and data types, not just the top rows.
- **Natural Language to SQL**:
Translate natural language queries into SQL commands using Qwen 2.5.
---
## Prerequisites
Before you start, ensure the following tools are installed on your system:
- Docker
- Docker Compose
---
## Access the Application
- **FastAPI Backend**:
Visit to access the API.
Documentation is available at
- **Streamlit Frontend**:
Visit to interact with the frontend.
---
## Development Workflow
### Stopping the Application
To stop the application, press `Ctrl+C` or run the following command:
docker-compose down
This will stop and remove the containers, but the built images will remain.
---
## Directory Structure
The project structure is as follows:
```shell
.
├── backend/ # FastAPI application
│ ├── db.py # Handles database connection and queries (e.g., to PostgreSQL or SQLite)
│ ├── main.py # FastAPI entrypoint
│ ├── requirements.txt # Python dependencies for FastAPI
│ └── Dockerfile # Dockerfile for FastAPI
├── frontend/ # Streamlit application
│ ├── app.py # Streamlit entrypoint
│ ├── Dockerfile # Dockerfile for Streamlit
│ └── requirements.txt # Python dependencies for streamlit
├── postgres/ # PostgreSQL setup folder
│ └── init.sql # SQL script to initialize the database (e.g., table creation, seed data)
├── shared_utils/ # Shared Python utilities used by both frontend and backend
│ └── functions.py # Streamlit entrypoint
├── docker-compose.yml # Docker Compose configuration
└── README.md # Project documentation
```
---
## Troubleshooting
- Ensure Docker and Docker Compose are installed and running on your system.
- Verify that the required ports (8000 and 8080) are not in use by other
applications.
---
## License
This project is licensed under the MIT License. See the LICENSE file for details.