Add all 5 GenAI learning projects from spec#2
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nerdjerry merged 9 commits intocopilot/charming-turtlefrom Feb 26, 2026
Merged
Add all 5 GenAI learning projects from spec#2nerdjerry merged 9 commits intocopilot/charming-turtlefrom
nerdjerry merged 9 commits intocopilot/charming-turtlefrom
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Complete RAG from scratch implementation with: - 6-step pipeline: load → chunk → embed → index → retrieve → generate - HuggingFace all-MiniLM-L6-v2 embeddings (free, local, no API key) - FAISS vector store with disk persistence - OpenAI + Ollama LLM support - argparse CLI with single-question and interactive modes - Heavily commented, beginner-friendly code throughout Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Complete RAG-powered legal contract analysis tool with: - document_parser.py: PDF/DOCX parsing with section detection - indexer.py: FAISS vector indexing (same pattern as Project 1) - summarizer.py: executive summary with structured JSON output - clause_extractor.py: named clause extraction + plain-English translation - risk_analyzer.py: HIGH/MEDIUM/LOW risk scoring with emoji indicators - conflict_detector.py: internal contradiction detection (with disclaimers) - qa_chain.py: grounded RAG Q&A with mandatory section citations - main.py: full CLI pipeline using Rich for formatted output - prompts/: summary, clause, and risk prompt templates - README.md: setup guide, architecture diagram, limitations Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Complete ReAct research agent pipeline including: - paper_parser.py: LLM-based PDF metadata extraction (PaperMetadata Pydantic model) - paper_indexer.py: FAISS vector index with per-paper metadata filtering - tools/search_tool.py: semantic search LangChain Tool - tools/summary_tool.py: paper summary LangChain Tool - tools/compare_tool.py: LLM-powered two-paper comparison Tool - agent.py: ZERO_SHOT_REACT_DESCRIPTION AgentExecutor with verbose ReAct loop - gap_analyzer.py: cross-paper synthesis and research gap identification - report_generator.py: structured Markdown report writer - main.py: CLI with --query, --report, --interactive flags - README.md: agent concepts, ReAct loop, architecture diagram, sample queries Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Three-index multimodal RAG pipeline for PDF documents: - multimodal_parser: pdfplumber extracts text blocks, PNG images, and tables - text_indexer: FAISS index for text chunks (all-MiniLM-L6-v2) - image_processor: GPT-4V base64 captioning with graceful fallback - image_indexer: FAISS index over image captions with image_path metadata - table_processor: LLM converts 2-D tables to prose descriptions + CSV export - table_indexer: FAISS index over table descriptions with csv_path metadata - query_router: LLM classifies query → TEXT / IMAGE / TABLE / ALL - multi_retriever: fetches from relevant indexes, interleaves and de-duplicates - generator: modality-labelled prompt → GPT-4 final answer - main.py: argparse CLI with --skip-images, --skip-tables, --interactive flags Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Complete agentic RAG project with real-time tools: - FAISS knowledge base indexer (reused from Project 1) - Tool registry with 5 tools: RAG, finance (yfinance), Wikipedia, web search (Tavily), weather (OpenWeatherMap) - LangChain agent with OPENAI_FUNCTIONS / ReAct loop - Conversation memory (ConversationBufferWindowMemory k=5) - Response formatter with reasoning trace display - CLI with --query, --interactive, --no-memory, --verbose flags - Mock fallbacks for all optional-key tools - Comprehensive README with architecture diagram, Agentic vs Standard RAG comparison table, custom tool walkthrough, and troubleshooting guide Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: nerdjerry <7092764+nerdjerry@users.noreply.github.com>
Co-authored-by: nerdjerry <7092764+nerdjerry@users.noreply.github.com>
Copilot
AI
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[WIP] Build project according to specifications
Add all 5 GenAI learning projects from spec
Feb 25, 2026
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Pull request overview
This pull request implements a comprehensive educational curriculum for developers learning Generative AI, consisting of five progressively complex projects that demonstrate key concepts from basic RAG to production-grade agentic systems with real-time data integration.
Changes:
- Added 5 self-contained GenAI projects with full documentation and working code
- Added root README.md with learning path, glossary, and setup instructions
- Added .gitignore to exclude generated files and sensitive data
Reviewed changes
Copilot reviewed 69 out of 78 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
| README.md | Project overview with difficulty ratings, learning path, and GenAI glossary |
| .gitignore | Excludes Python artifacts, virtual environments, FAISS indexes, and generated content |
| 01-rag-from-scratch/* | Basic RAG implementation with HuggingFace embeddings and FAISS |
| 02-legal-ai-assistant/* | Domain-specific RAG with clause extraction, risk analysis, and conflict detection |
| 03-research-agent/* | ReAct agent with tools for paper search, summarization, and comparison |
| 04-multimodal-rag/* | Multi-index RAG handling text, images (GPT-4V), and tables |
| 05-agentic-rag-realtime/* | Production agent with 5 tools including live web search, finance, weather, and Wikipedia |
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Co-authored-by: nerdjerry <7092764+nerdjerry@users.noreply.github.com>
nerdjerry
approved these changes
Feb 26, 2026
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.gitignorebase64(stdlib, not pip-installable) from requirements.txt;pdfplumber==0.11.1was already presentwikipedia==1.4.0andrequests==2.31.0were already present in requirements.txtOriginal prompt
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