About
Technologies
AI Models
Most AI models in Ada run locally
This ensuring data privacy, RGPD compliance, and reducing latency. This approach allows for:
- Control over the models and their versions
- Enhanced data security by keeping all processing on-premises
- Adherence to RGPD (General Data Protection Regulation) requirements
Speech Recognition
- Whisper: State-of-the-art model for transcribing videos into text with high accuracy.
Image Analysis
- Florence-2: Advanced vision model employed to generate detailed descriptions of images extracted from PDFs.
Language Translation
- Areeb123/En-Fr_Translation_Model: Specialized model used for translating Florence-2's English output into French.
PDF Structure Analysis
- Surya: Sophisticated PDF analyzer that:
- Identifies and categorizes text blocks, titles, and images
- Determines the optimal reading order of content blocks
- Enhances document understanding for further processing
Text Embeddings
- Solon: Best open-source model for French semantic search.
Text Generation
- LLaMa 3.1:8b: Large Language model utilized for context-aware automatic quiz generation and text auto-completion.
- groq -> llama-3.3-70b-versatile: Large Language model utilized for .
Core Technological Components
Vector Database
- pgvector: High-performance vector database extension for PostgreSQL chosen for its:
- Fast search capabilities
- Native support within the existing PostgreSQL infrastructure
Processing Backend
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Python: Powerful and versatile programming language used for:
- Serving AI models
- Handling complex data processing pipelines
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FastAPI: Modern, fast (high-performance) web framework for building APIs with Python, chosen for:
- Asynchronous request handling
- Easy integration with AI models
- Typed with Pydantic for automatic data validation and serialization
Web Application Framework
- Next.js: Modern React framework powering both the front-end and back-end of our web application (except for the processing part)
Document Storage
- S3: Object storage solution used to store all original reference documents (PDF, image, video, etc.), offering:
- Scalable and secure storage infrastructure
- Easy integration with existing systems
- Cost-effective storage for large volumes of data
- Compliance with data protection regulations
Deployment
- Docker and Docker Compose: Containerized deployment for easy scaling and management