Trino Breaking Changes Analyzer

Overview

This project uses AI to analyze Trino release notes and identify breaking changes between different versions. It combines several components:

Architecture

The system consists of multiple services:

• Ollama: Runs the local LLM for text summarization
• Backend: FastAPI service for web scraping
• Agent: Main analysis service using LangGraph
• Gradio UI: Web interface for user interactions

Prerequisites

• Docker and Docker Compose
• Python 3.13
• At least 16GB RAM recommended for running the LLM

Quick Start

1. Clone the repository:

git clone https://github.com/snowsky/langgraph-trino-breaking-changes.git
cd langgraph-trino-breaking-changes

2. Update environment variables for start and end versions:

cp .env.example .env
# Edit .env file or docker-compose.yaml file

2. Start all services using Docker Compose and see live logs:

docker-compose up --build

This will start:

• Ollama LLM service on port 11434
• Ollama Web UI on port 8080 (accessible at http://localhost:8080)
• Backend service on port 8000
• Agent service for analysis

Manual Setup

If you prefer to run services separately:

1. Create and activate virtual environment:

python3 -m venv venv
source venv/bin/activate

2. Install dependencies:

pip install -r my_agent/requirements.txt

3. Start the backend service:

cd backend
uvicorn app:app --host 0.0.0.0 --port 8000

Start the Gradio interface:

pip install -r gradio/requirements.txt
python gradio/gradio_trino_changes.py

Once the Gradio interface is running, open your browser and navigate to http://localhost:7860 to access the UI. After each analysis run, you can copy the results directly from the interface for further use.

Test drive

python run_agent.py

Output files

Example summary and markdown files can be found under output folder.

Environment Variables

Key environment variables (configured in docker-compose.yaml):

COLLECTION_NAME=my_collection
BACKEND_CRAWLSVC_URL=http://backend:8000 
TRINO_RELEASE_URL=https://trino.io/docs/current/release.html
OLLAMA_MODEL_NAME=llama3.2
OLLAMA_BASE_URL=http://ollama:11434
OLLAMA_NUM_CTX=8192

Project Structure

├── backend/               # FastAPI web scraping service
├── gradio/                # Gradio web interface
├── my_agent/              # Main analysis logic
├── ollama/                # Ollama model configurations
└── docker-compose.yaml    # Service orchestration

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is Apache licensed.