A RAG-based company information retrieval system
Project description
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# StartGarlic
A RAG-based contextual advertisement system that provides intelligent ad matching based on natural language queries.
## Installation
```bash
pip install startgarlic
Quick Start
from startgarlic import Garlic
# Initialize the system with your API key
api_key = "your_api_key_here"
garlic = Garlic(api_key)
# Find a relevant advertisement based on a query
ad_data = garlic.find_advertisement("I am interested in quantum computing in finance")
print(ad_data)
Features
- Contextual ad matching using RAG (Retrieval-Augmented Generation)
- Semantic search using sentence transformers
- Real-time bidding and auction system
- User context awareness
- Analytics and performance tracking
- Easy API integration
API Usage
Match Endpoint
import requests
response = requests.post(
"http://localhost:8001/api/match",
json={
"query": "I am interested in quantum computing in finance",
"user_id": "optional_user_id",
"context": {}
},
headers={
"Authorization": "Bearer your_api_key_here"
}
)
print(response.json())
Response Format
{
"company": "Example Company",
"product_name": "AI Assistant Pro",
"product_url": "https://example.com/products/ai-assistant",
"tracking_url": "https://example.com/track/ai-assistant?ref=chat"
}
Requirements
- Python >= 3.7
- FastAPI >= 0.68.0
- pandas >= 1.3.0
- sentence-transformers >= 2.0.0
- numpy >= 1.19.0
- supabase >= 0.0.1
Authors
- Bogdan Ciolac (bogdan@startgarlic.com)
- May Elshater (may@startgarlic.com)
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Project details
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