GitHub Issue AI Assistant is an AI-powered application that analyzes GitHub issues and generates structured, actionable insights in JSON format. It helps developers and teams quickly understand issue severity, type, priority, and potential impact using AI.
This application performs the following steps:
Accepts a GitHub issue URL and issue number via a Streamlit web interface
Fetches issue title, description, and comments using the GitHub REST API
Processes the issue data using an LLM-based AI model (Hugging Face Transformers)
Applies a strict structured prompt to ensure valid JSON output
Serves AI analysis through a FastAPI backend
Displays results in a clean, readable UI
Allows users to download the generated JSON output
Saves developer time by summarizing complex GitHub issues
Converts unstructured issue discussions into structured data
Demonstrates real-world LLM integration, API usage, and backend–frontend coordination
Mimics how AI tools are built in modern engineering teams
Backend: FastAPI, Python 3.11
Frontend: Streamlit
AI / LLM: Hugging Face Transformers
APIs: GitHub REST API
Others: Requests, Uvicorn
After extracting the ZIP files, the directory should look like this:
github-issue-ai-assistant/
│ ├── backend/
│ ├── main.py # FastAPI entry point
│ ├── llm.py # AI / LLM logic
│ ├── github.py # GitHub API integration
│ ├── schemas.py # Request & response schemas
│ ├── config.py # Configuration
│ └── init.py │
├── frontend/ │ └── app.py # Streamlit UI │
├── requirements.txt
└── README.md
If ZIP files are not extracted correctly, backend or frontend commands will fail due to missing paths.
Corrected all import paths in main.py to resolve repeated ModuleNotFoundError
Aligned execution commands with the actual extracted folder structure
Ensured backend runs from the project root, not inside subfolders
System Requirements Required Software
Python 3.11 (Recommended strictly : 3.11.9)
Git
Extracted project source files (ZIP)
Follow these steps in order.
git clone https://github.com/kavyaboompur/github-issue-ai-assistant.git
cd github-issue-ai-assistant
python -m venv venv
venv\Scripts\activate
Ensure (venv) appears in the terminal.
pip install -r requirements.txt
Step 5: Start the Backend Server
Check backend folder path first:
cd backend
dir
Run the backend based on extracted structure:
python -m uvicorn backend.main:app --reload --port 8000
If ZIP extraction created nested folders, use:
python -m uvicorn backend.backend.main:app --reload --port 8000
Note:if found error then use crct path
Backend API will be available at:
Keep this terminal open.
Error: ModuleNotFoundError: No module named 'backend'
Root Cause: Python could not resolve module paths because execution was done from the wrong directory
Solution: Identified correct folder hierarchy
Updated imports such as:In main.py of backend folder(beacuse path differs) from backend.backend.llm import IssueAnalyzer, from backend.llm import IssueAnalyzer OR
from llm import IssueAnalyzer
Executed the server from the project root
Step 6: Start the Frontend (New Terminal) cd github-issue-ai-assistant venv\Scripts\activate
If Streamlit is missing:
pip install streamlit
Run the frontend:
streamlit run frontend/app.py (Adjust path if folders differ due to ZIP extraction.)
Click Start
Enter GitHub repository URL
Enter issue number
Click Analyze Issue
Wait for AI processing
View readable summary
Click View Result for JSON
Download JSON output if needed
Screenshots and example outputs are available here: 🔗 https://drive.google.com/file/d/1an2VZ27TGhHyTDghLzRciyoy7-6uZeSl/view
Included Screens:
Application home page
Issue input screen
Processing state
AI-generated summary
Priority score & labels
Full JSON output
Backend & frontend running successfully
Visual execution guide available here: 🔗 https://drive.google.com/file/d/1p0RtVNFa7DPiTowxK4ZMbQQsdTN5I5PQ/view