🤖 AI Experiments

This repository serves as a collection of experimental AI agents and research projects, focusing on LLM integrations, tool calling, and RAG architectures.

📁 Project Structure

The core experiments are organized within the agents/ directory.

♊ Gemini Experiments

Explorations into Google's Gemini models.

• gemini.py: Implementation of various Gemini-based features.
• Exercises: A set of learning resources and coding exercises to master Gemini API capabilities.
• Documentation: Includes architectural diagrams and specific README for the Gemini module.

🔍 RAG Agent

A sophisticated Retrieval-Augmented Generation (RAG) agent designed for intelligent context retrieval and response generation.

• agent.py: The main agent logic and LangChain integration.
• Results: Performance logs and output examples in results.txt.
• Deep Dive: Detailed documentation on the RAG pipeline and setup.

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Note: This repository is intended for development and research. For specific setup instructions, please refer to the README files within each subdirectory.