Fix HF Spaces config: Move Dockerfile to root and add metadata

Dockerfile

@@ -0,0 +1,30 @@
+FROM python:3.9-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    gcc \
+    g++ \
+    postgresql-client \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements and install Python packages
+COPY backend/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code from backend directory
+COPY backend/ ./backend/
+# Main entry point needs to be at root level for some runners, or we point pythonpath
+ENV PYTHONPATH=/app/backend
+
+# Set environment for model caching to /tmp (only writable dir in HF Spaces)
+ENV HF_HOME=/tmp/.cache/huggingface
+ENV FASTEMBED_CACHE_PATH=/tmp/.cache/fastembed
+ENV SENTENCE_TRANSFORMERS_HOME=/tmp/.cache/sentence-transformers
+
+# Expose port 7860 (required by Hugging Face Spaces)
+EXPOSE 7860
+
+# Run FastAPI with uvicorn (pointing to nested app)
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,289 +1,15 @@
-# MEXAR Ultimate 🧠
-
-**Multimodal Explainable AI Reasoning Assistant**
-
-[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
-[![React 18](https://img.shields.io/badge/react-18-61dafb.svg)](https://reactjs.org/)
-[![FastAPI](https://img.shields.io/badge/fastapi-0.109-009688.svg)](https://fastapi.tiangolo.com/)
-[![License: MIT](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)
-
-MEXAR is an explainable AI system that creates domain-specific intelligent agents from your data. It uses **RAG (Retrieval-Augmented Generation)** with source attribution and faithfulness scoring to provide transparent, verifiable answers.
-
----
-
-## ✨ Key Features
-
-| Feature | Description |
-|---------|-------------|
-| 🔍 **Hybrid Search** | Combines semantic (vector) + keyword search with RRF fusion |
-| 🎯 **Cross-Encoder Reranking** | Improves retrieval precision using sentence-transformers |
-| 📊 **Source Attribution** | Inline citations `[1]`, `[2]` linking answers to sources |
-| ✅ **Faithfulness Scoring** | Measures how well answers are grounded in context |
-| 🗣️ **Multimodal Input** | Audio (Whisper), Images (Vision), Video support |
-| 🔐 **Domain Guardrails** | Prevents hallucinations outside knowledge base |
-| 🔊 **Text-to-Speech** | ElevenLabs + Web Speech API support |
-| 📁 **5 File Types** | CSV, PDF, DOCX, JSON, TXT |
-
----
-
-## 🏗️ Architecture
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│                        MEXAR Architecture                        │
-├─────────────────────────────────────────────────────────────────┤
-│                                                                   │
-│   [User] ──► [React Frontend]                                     │
-│                    │                                              │
-│                    ▼                                              │
-│   [FastAPI Backend]                                               │
-│         │                                                         │
-│         ├──► Data Validator (CSV/PDF/DOCX/JSON/TXT)              │
-│         ├──► Prompt Analyzer (LLM-based domain extraction)       │
-│         ├──► Knowledge Compiler (FastEmbed → pgvector)           │
-│         └──► Reasoning Engine                                     │
-│                    │                                              │
-│                    ├──► Hybrid Search (semantic + keyword)        │
-│                    ├──► Reranker (cross-encoder)                  │
-│                    ├──► Source Attribution (inline citations)     │
-│                    └──► Faithfulness Scorer (claim verification)  │
-│                                                                   │
-│   [External Services]                                             │
-│         ├──► Supabase (PostgreSQL + Storage)                     │
-│         ├──► Groq API (LLM + Whisper + Vision)                   │
-│         └──► ElevenLabs (Text-to-Speech)                         │
-└─────────────────────────────────────────────────────────────────┘
-```
-
----
-
-## 🚀 Quick Start
-
-### Prerequisites
-
-- **Python 3.9+** with pip
-- **Node.js 18+** with npm
-- **PostgreSQL** with `pgvector` extension (or use Supabase)
-- **Groq API Key** - Get free at [console.groq.com](https://console.groq.com)
-
-### 1. Backend Setup
-
-```bash
-cd backend
-
-# Create virtual environment
-python -m venv venv
-
-# Activate (Windows)
-.\venv\Scripts\activate
-
-# Activate (macOS/Linux)
-source venv/bin/activate
-
-# Install dependencies
-pip install -r requirements.txt
-```
-
-**Configure Environment Variables:**
-
-Create `backend/.env`:
-```env
-# Required
-GROQ_API_KEY=your_groq_api_key_here
-DATABASE_URL=postgresql://user:password@host:5432/database
-SECRET_KEY=your_secure_secret_key
-
-# Supabase Storage
-SUPABASE_URL=https://your-project.supabase.co
-SUPABASE_KEY=your_supabase_service_role_key
-
-# Optional: ElevenLabs TTS
-ELEVENLABS_API_KEY=your_elevenlabs_api_key_here
-```
-
-**Run Server:**
-```bash
-python -m uvicorn main:app --reload --host 0.0.0.0 --port 8000
-```
-
-### 2. Frontend Setup
-
-```bash
-cd frontend
-
-# Install dependencies
-npm install
-
-# Start development server
-npm start
-```
-
-Open [http://localhost:3000](http://localhost:3000) in your browser.
-
----
-
-## 📁 Project Structure
-
-```
-mexar_ultimate/
-├── backend/
-│   ├── api/                    # REST API endpoints
-│   │   ├── auth.py            # Authentication (JWT)
-│   │   ├── agents.py          # Agent CRUD
-│   │   ├── chat.py            # Chat + multimodal
-│   │   ├── compile.py         # Knowledge compilation
-│   │   └── websocket.py       # Real-time updates
-│   ├── core/                   # Core configuration
-│   │   ├── config.py          # Settings
-│   │   ├── database.py        # SQLAlchemy setup
-│   │   └── security.py        # JWT handling
-│   ├── models/                 # Database models
-│   │   ├── user.py            # User model
-│   │   ├── agent.py           # Agent + CompilationJob
-│   │   ├── chunk.py           # DocumentChunk (pgvector)
-│   │   └── conversation.py    # Chat history
-│   ├── modules/                # Core AI modules
-│   │   ├── data_validator.py  # File parsing
-│   │   ├── prompt_analyzer.py # Domain extraction
-│   │   ├── knowledge_compiler.py # Vector embeddings
-│   │   ├── reasoning_engine.py # RAG pipeline
-│   │   ├── multimodal_processor.py # Audio/Image/Video
-│   │   └── explainability.py  # UI formatting
-│   ├── utils/                  # Utility modules
-│   │   ├── groq_client.py     # Groq API wrapper
-│   │   ├── hybrid_search.py   # RRF search fusion
-│   │   ├── reranker.py        # Cross-encoder
-│   │   ├── faithfulness.py    # Claim verification
-│   │   └── source_attribution.py # Citation extraction
-│   ├── services/               # External services
-│   │   ├── tts_service.py     # Text-to-speech
-│   │   └── storage_service.py # Supabase storage
-│   ├── main.py                 # FastAPI app entry
-│   └── requirements.txt        # Python dependencies
-│
-├── frontend/
-│   ├── src/
-│   │   ├── pages/             # React pages
-│   │   │   ├── Landing.jsx    # Home page
-│   │   │   ├── Login.jsx      # Authentication
-│   │   │   ├── Dashboard.jsx  # User dashboard
-│   │   │   ├── AgentCreation.jsx # Create agent
-│   │   │   ├── CompilationProgress.jsx # Build progress
-│   │   │   └── Chat.jsx       # Chat interface
-│   │   ├── components/        # Reusable UI
-│   │   ├── contexts/          # React contexts
-│   │   ├── api/               # API client
-│   │   └── App.jsx            # Main component
-│   └── package.json           # Node dependencies
-│
-└── README.md
-```
-
----
-
-## 🔧 API Reference
-
-### Authentication
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/api/auth/register` | Register new user |
-| POST | `/api/auth/login` | Login (returns JWT) |
-| GET | `/api/auth/me` | Get current user |
-
-### Agents
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/agents/` | List all agents |
-| GET | `/api/agents/{name}` | Get agent details |
-| DELETE | `/api/agents/{name}` | Delete agent |
-
-### Compilation
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/api/compile/` | Start compilation (multipart) |
-| GET | `/api/compile/{name}/status` | Check compilation status |
-
-### Chat
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/api/chat/` | Send message |
-| POST | `/api/chat/multimodal` | Send with audio/image |
-| GET | `/api/chat/{agent}/history` | Get chat history |
-| POST | `/api/chat/transcribe` | Transcribe audio |
-
----
-
-## 🧪 Technologies
-
-### Backend
-- **FastAPI** - Modern async Python web framework
-- **SQLAlchemy** - ORM for PostgreSQL
-- **pgvector** - Vector similarity search
-- **FastEmbed** - Local embedding generation (BAAI/bge-small-en-v1.5)
-- **sentence-transformers** - Cross-encoder reranking
-- **Groq API** - LLM (Llama 3.1/3.3), Whisper (audio), Vision (images)
-
-### Frontend
-- **React 18** - UI framework
-- **Material-UI** - Component library
-- **React Router** - Navigation
-- **Axios** - HTTP client
-
-### External Services
-- **Supabase** - Managed PostgreSQL + Storage
-- **Groq** - Fast AI inference
-- **ElevenLabs** - Text-to-Speech (optional)
-
----
-
-## 📊 How It Works
-
-### 1. Agent Creation
-```
-User uploads files → DataValidator parses → PromptAnalyzer extracts domain
-                                         → KnowledgeCompiler creates embeddings
-                                         → Stored in pgvector
-```
-
-### 2. Query Processing
-```
-User query → Domain Guardrail check
-          → Hybrid Search (semantic + keyword)
-          → Cross-Encoder Reranking (top 5)
-          → LLM Generation with context
-          → Source Attribution (citations)
-          → Faithfulness Scoring
-          → Explainability formatting
-```
-
-### 3. Confidence Scoring
-Confidence is calculated from:
-- **Retrieval Quality** (35%) - How relevant the retrieved chunks are
-- **Rerank Score** (30%) - Cross-encoder confidence
-- **Faithfulness** (25%) - How grounded the answer is
-- **Base Floor** (10%) - For in-domain queries
-
 ---
-
-## 🌐 Deployment
-
-See [implementation_plan.md](./implementation_plan.md) for detailed deployment instructions covering:
-- GitHub repository setup
-- Vercel (frontend)
-- Render.com (backend)
-- Neon PostgreSQL (database)
-
----
-
-## 📄 License
-
-MIT License - See [LICENSE](LICENSE) for details.
-
+title: Mexar Ultimate
+emoji: 🧠
+colorFrom: blue
+colorTo: purple
+sdk: docker
+app_port: 7860
+app_file: backend/Dockerfile
+pinned: false
+license: mit
 ---
+# MEXAR Ultimate - AI Reasoning Assistant
 
-## 🙏 Acknowledgments
-
-- [Groq](https://groq.com) - Fast AI inference
-- [Supabase](https://supabase.com) - Postgres + Storage
-- [FastEmbed](https://github.com/qdrant/fastembed) - Embeddings
-- [sentence-transformers](https://www.sbert.net) - Reranking models
+This Space hosts the backend API for MEXAR Ultimate.
+Frontend is deployed separately on Vercel.