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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

Contributing

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

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