GenAI Learning Projects

A hands-on collection of Generative AI projects and experiments covering prompting, RAG, AI agents, workflows, multimodal systems, voice applications, MCP, and local LLM deployment.

Topics & Folders

Folder	Overview
Hello World	Basic API integrations - OpenAI, Gemini, combined examples
Agent sdk	Google Agent Development Kit - tool-based agents, search
Prompts	Prompting techniques - Chain of Thought, Few-shot, Zero-shot, Persona, Styles
RAG	Retrieval-Augmented Generation - indexing, embeddings, vector search
RAG_Queue	RAG with Redis queues - async processing, job management
LangGraph	Workflow orchestration - state management, multi-step workflows
Voice Agent	Voice interactions - speech-to-text, audio processing
Weather Agent	AI agents for domain tasks - specialized agents, API integration
MultiModal Agent	Vision-language models - image analysis, multi-modal input
Ollama_FastAPI	Local LLM deployment - FastAPI, open-source models, no API keys
Memory_agent	Stateful agents - conversation history, persistence
MCP Project	Model Context Protocol - protocol implementation, servers
Hugging Face	HF model integration - model loading, inference
Tokenizer	Token management - counting, encoding, cost analysis

Setup

python -m venv venv
venv\Scripts\activate  # Windows
source venv/bin/activate  # Mac/Linux
pip install -r requirements.txt

Environment Variables

Create .env:

OPENAI_API_KEY=your_key
GEMINI_API_KEY=your_key