README.md

metadata

title: Really AI
emoji: 🚀
colorFrom: indigo
colorTo: blue
sdk: docker
app_file: home.py
pinned: false

Really AI

Really AI is an intelligent, direct-access conversational engine designed for technical support, Q&A, and general chat. It combines a sophisticated custom NLP pipeline with real-time system monitoring and secure user authentication.

🌟 Key Features

• Intelligent NLP Pipeline: Advanced Arabic/English text normalization, tokenization, and intent classification.
• Direct Knowledge Access: Real-time search across the data.json knowledge base for consistent and instant responses.
• Real-Time Processing: Visual feedback of the generation process, including steps and progress.
• Performance Metadata: Detailed info for every message, including generation time (duration) and token count.
• Secure & Private: Implements robust password hashing and persistent conversation history.
• System Awareness: Real-time monitoring of CPU/RAM usage and built-in tools for time/date reporting.
• Resilient Design: Data synchronization with Hugging Face Hub, ensuring persistence even in ephemeral deployment environments (e.g., Dockerized Spaces).
• Multi-Tier Model Selection: Five processing tiers balancing speed and depth:
  • Flash Lite (10s): High-speed optimized search.
  • Flash (30s): Standard balanced search.
  • Medium (10m): Deep background processing.
  • Pro (30m): Advanced background analysis.
  • Pro Max (5h): Exhaustive background processing.
• Modern UI: A polished, glassmorphism-based interface with smooth stream-processing and interactive feedback.

🛠 Tech Stack

• Backend: Python 3.9+, Flask, Flask-Session, Werkzeug
• Search/NLP: Custom engine using SequenceMatcher, re, Counter
• Monitoring: psutil
• Integrations: huggingface_hub for dataset/model storage
• Frontend: Vanilla HTML/CSS/JS, FontAwesome, Google Fonts
• Deployment: Docker, optimized for Hugging Face Spaces

🏗 System Architecture

The application operates as an event-driven system:

1. Request Flow: User input is processed via a multi-stage pipeline (Normalization → Direct Data Search → Sentiment Analysis).
2. Streaming: Responses are streamed back via NDJSON for a fluid user experience.
3. Background Tasks: A worker thread handles long-running "Medium", "Pro", and "Pro Max" queries, allowing users to return later for their answers.
4. Sync & Persistence: All state (users, conversations, knowledge data) is persisted in local JSON files and synced to a remote Hugging Face dataset repository.

📜 API Reference

Endpoint	Method	Description
/chat	POST	Main interface; streams AI responses as NDJSON.
/auth/login	POST	Authenticates user and initializes session.
/auth/signup	POST	Registers new user credentials.
/status	GET	Returns real-time system metrics and usage quota.
/tasks	GET	Returns current user's background task status.
/history	GET	Returns current user's conversation history.

🤝 Contribution

Contributions to the NLP core or the UI/UX are highly appreciated. Please open an issue to discuss significant changes before submitting a PR.