b7ef07dd34
## 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!
47 lines
1.2 KiB
Markdown
47 lines
1.2 KiB
Markdown
# DocuMente - Agentic Retrieval System
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Powered by [datapizza-ai](https://github.com/datapizza-labs/datapizza-ai)
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## Quick Start
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```bash
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# Install dependencies
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pip install datapizza-ai datapizza-ai-clients-openai datapizza-ai-embedders-openai datapizza-ai-vectorstores-qdrant
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# Start Qdrant (vector store)
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docker run -p 6333:6333 qdrant/qdrant
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# Run the API
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python -m agentic_rag.api.main
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```
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## Features
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- 🌐 **Web Interface** - User-friendly UI for document upload and chat
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- 🔌 **REST API** - Full API with Swagger documentation at `/api/docs`
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- 🤖 **Agentic RAG** - Powered by datapizza-ai framework
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- 📄 **Document Processing** - PDF, DOCX, TXT, MD support
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- 🔍 **Semantic Search** - Vector-based retrieval with Qdrant
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- 💬 **Chat Interface** - Conversational AI with context
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## API Endpoints
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- `POST /api/v1/documents` - Upload document
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- `GET /api/v1/documents` - List documents
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- `POST /api/v1/query` - Query knowledge base
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- `POST /api/v1/chat` - Chat endpoint
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- `GET /api/health` - Health check
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- `GET /api/docs` - Swagger UI
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## Architecture
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```
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Web UI (React/Vanilla JS)
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↓
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FastAPI REST API
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↓
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datapizza-ai RAG Pipeline
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↓
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Qdrant Vector Store
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```
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