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rent-management-system/ai_recommendation

Type de record:

software
Créateur:
ren
Hôte:
This microservice provides intelligent property recommendations for tenants within a rental management system, focusing on Ethiopia-specific needs. It leverages FastAPI, PostgreSQL, LangGraph, LangChain, ChromaDB, and Gemini 2.0 Flash to deliver personalized, secure, and scalable recommendations. # AI Recommendation Microservice ## Table of Contents - AI Recommendation Microservice - Table of Contents - 1. Overview - 2. Features - 3. Technologies Used - 4. Architecture Diagram - 5. Folder Structure - 6. Setup Guide - 6.1. Prerequisites - 6.2. Clone the Repository - 6.3. Create Virtual Environment and Install Dependencies - 6.4. Environment Variables - 6.5. Database Setup (Migrations and Seeding) - 6.6. ChromaDB Initialization - 6.7. Running the Application Locally - 7. API Endpoints - 7.1. `POST /api/v1/recommendations` - 7.2. `GET /api/v1/recommendations/{tenant_preference_id}` - 7.3. `POST /api/v1/recommendations/feedback` - 7.4. `POST /api/v1/properties/search` - 8. Testing - 9. Deployment on Hugging Face Spaces - 10. Contributing - 11. License - 12. Contact Information --- ## 1. Overview The AI Recommendation Microservice is a specialized component within a larger rental management system, designed to provide intelligent and personalized property recommendations to tenants. This service is tailored for Ethiopia-specific needs, incorporating local geographical data and language support. It leverages advanced AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), orchestrated by LangGraph, to deliver highly relevant and context-aware suggestions. The core objective is to enhance the tenant's property search experience by considering various factors such as job/school location, salary, preferred house type, family size, and amenities, ultimately suggesting properties that align with their lifestyle and budget. ## 2. Features * **Personalized Property Recommendations**: Generates property recommendations based on a comprehensive tenant profile, including job/school location, salary, house type, family size, and preferred amenities. * **Ethiopia-Specific Context**: Integrates deeply with **Gebeta Maps** for accurate, local-context geocoding and precise minibus route cost estimations within Ethiopia. T …