Show HN: GroundCite-An open-source package to fix broken Gemini API citations

1 month ago 6

**GroundCite** is a Python library for adding better grounding and valid Citation support when searching using Gemini with google grounding . It combines web search using Gemini with google grounding with context validation, and structured data parsing using multiple AI providers to deliver accurate and reliable answers to complex questions.

If you’ve ever faced:

Broken citations in Gemini’s outputs,
Irrelevant/Invalid citations pointing to 404 pages or unrelated content, or
No Citations in Structured JSON responses,
Grounding Issues: Gemini disregarding your instructions wrt source of data ( no inclusions or exclusions),
then GroundCite is your solution.

Read more about why we made GroundCite https://www.cennest.com/fix-geminis-broken-citations-with-groundcite-complete-guide/

Playground app for feature testing https://groundcite.cennest.com/

GroundCite in Action https://youtu.be/b1sCCRSgi38

Intelligent Search Integration: Intelligent grounding search with site filtering and content aggregation
AI-Powered Validation: Optional citation validation using advanced AI models
Structured Data Parsing with Citation: Extract structured data with Citations using custom JSON schemas
MultiAgent Graph-Based Pipeline: Consistent output with automatic retry logic and error handling
Comprehensive Logging: Detailed execution metrics and token usage tracking

Command Line Interface (CLI): Feature-rich CLI with rich text formatting
REST API: FastAPI-based web service for HTTP integration
Python Library: Direct integration into Python applications

Retry Logic: Robust error handling with configurable retry mechanisms
Token Usage Tracking: Monitor AI service consumption and costs
Correlation Tracking: End-to-end request tracing and debugging
Configuration Management: Flexible settings with validation
Site Filtering: Include/exclude specific domains in search results

https://www.cennest.com/groundcite-frequently-asked-questions-faq/

Detailed Architecture and usage

-https://github.com/cennest/ground-cite/blob/main/GroundCite/docs/ARCHITECTURE.md
-https://github.com/cennest/ground-cite/blob/main/GroundCite/docs/ARCHITECTURE_LIGHT.md
-https://github.com/cennest/ground-cite/blob/main/GroundCite/docs/USAGE.md

Detailed Documentation: Full documentation

Python: 3.12 or higher
Dependencies: See requirements.txt for full list

langgraph - Graph-based workflow orchestration
google-genai - Google Gemini AI integration
openai - OpenAI API integration
fastapi - REST API framework
click - CLI framework
rich - Enhanced terminal output
pydantic - Data validation and settings

git clone https://github.com/cennest/ground-cite.git cd ground-cite/GroundCite pip install -e .

Using pip (when published)

pip install gemini-groundcite

# Simple query analysis gemini-groundcite analyze -q "What are the latest developments in AI?" --gemini-key your_gemini_key # With validation and parsing gemini-groundcite analyze -q "Company X financials" --validate --parse --gemini-key your_gemini_key # Using OpenAI provider gemini-groundcite analyze -q "Market trends" --provider openai --openai-key your_key --gemini-key your_gemini_key

from gemini_groundcite.config.settings import AppSettings from gemini_groundcite.core.agents import AIAgent # Configure settings settings = AppSettings() settings.ANALYSIS_CONFIG.query = "What are quantum computing breakthroughs?" settings.ANALYSIS_CONFIG.validate = True settings.ANALYSIS_CONFIG.parse = True settings.AI_CONFIG.gemini_ai_key_primary = "your_gemini_key" # Initialize and run analysis agent = AIAgent(settings=settings) results = await agent.analyze_query() print(f"Analysis completed: {results['completed']}") print(f"Results: {results['final_content']}")

# Start the API server python -m gemini_groundcite.main # Make analysis requests curl -X POST "http://localhost:8000/api/v1/analyze" \ -H "Content-Type: application/json" \ -d '{ "query": "Latest AI developments", "config": {"validate": true, "parse": true}, "search_model_name": "gemini-2.5-flash", "api_keys": {"gemini": {"primary": "your_key"}} }'

We welcome contributions! Please reach out to [email protected] or even better send us a PR..

# Clone the repository git clone https://github.com/cennest/ground-cite.git cd ground-cite/GroundCite # Create virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install in development mode pip install -e ".[dev]"

This project is licensed under the MIT License - see the LICENSE file for details.