Data & Analytics
SPEC.md · 7 documents
scope
A Python-based tool to download video transcripts and comments from YouTube channels for market research. The goal is to inform a market garden and orchard business plan focused on regenerative agriculture. The system performs a multi-stage AI processing pipeline on the raw data, structuring it into a normalized database of topic-based summaries and atomic insights. A hybrid search system combines full-text search with AI-powered semantic search via vector embeddings for comprehensive data disco
deep-cuts — Media Intelligence Pipeline
Ingests YouTube shows and podcasts, transcribes them, runs LLM analysis to produce structured knowledge (TLDR, keywords, categories, thought threads), stores everything in a searchable database with semantic search, and generates data-driven infographic cards per episode.
Infinite-Context Chat Storage Specification
**Date:** November 2025
Vector Database Shootout - Functional & Technical Specification
A comprehensive benchmarking suite designed to systematically compare the performance characteristics of leading vector databases (Qdrant, Weaviate, pgvector, Milvus, Pinecone) across various dimensions to provide actionable insights for AI application developers.
Logging & Evals
RA-H uses a **trigger-based logging system** that automatically captures all database activity in the `logs` table.
Software Carbon Intensity for AI Specification
This specification extends the Software Carbon Intensity (SCI) methodology to the unique characteristics of Artificial Intelligence (AI) systems. It provides a standardized method for measuring and reporting the carbon emissions associated with AI throughout its lifecycle.
GPU Selection Guide for Large Language Models (LLMs)
This guide helps you choose the right GPU for running Large Language Models, whether you're using them for inference, fine-tuning, or training.