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## Changes
- Update all references from AgenticRAG to DocuMente
- Update README.md with new project description and structure
- Update LICENSE with new project name
- Update API title and descriptions in main.py
- Update frontend components (Layout, Login, Dashboard, Settings)
- Update static HTML page
- Update all documentation files (prd-v2.md, frontend-plan.md, etc.)
- Update test files with new project name
- Update docker-compose.yml, Dockerfile, requirements.txt
## SEO Benefits
- DocuMente combines 'Documento' and 'Mente' (Italian for Document and Mind)
- Memorable and brandable name
- Reflects the core functionality: AI-powered document intelligence
🎉 Project officially renamed to DocuMente!
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DocuMente - Agentic Retrieval System
Powered by datapizza-ai
Quick Start
# Install dependencies
pip install datapizza-ai datapizza-ai-clients-openai datapizza-ai-embedders-openai datapizza-ai-vectorstores-qdrant
# Start Qdrant (vector store)
docker run -p 6333:6333 qdrant/qdrant
# Run the API
python -m agentic_rag.api.main
Features
- 🌐 Web Interface - User-friendly UI for document upload and chat
- 🔌 REST API - Full API with Swagger documentation at
/api/docs - 🤖 Agentic RAG - Powered by datapizza-ai framework
- 📄 Document Processing - PDF, DOCX, TXT, MD support
- 🔍 Semantic Search - Vector-based retrieval with Qdrant
- 💬 Chat Interface - Conversational AI with context
API Endpoints
POST /api/v1/documents- Upload documentGET /api/v1/documents- List documentsPOST /api/v1/query- Query knowledge basePOST /api/v1/chat- Chat endpointGET /api/health- Health checkGET /api/docs- Swagger UI
Architecture
Web UI (React/Vanilla JS)
↓
FastAPI REST API
↓
datapizza-ai RAG Pipeline
↓
Qdrant Vector Store