AIML_Tutorial

# AIML Tutorial Repository A comprehensive collection of tutorials covering **LangChain**, **LangGraph**, **Model Context Protocol (MCP)**, and **Semantic Kernel** frameworks for building AI/ML applications. --- ## Table of Contents - [Overview](#overview) - [Repository Structure](#repository-structure) - [Tutorials Navigation](#tutorials-navigation) - [LangChain](#langchain) - [LangGraph](#langgraph) - [MCP Tutorial](#mcp-tutorial) - [Semantic Kernel](#semantic-kernel) - [Getting Started](#getting-started) - [Prerequisites](#prerequisites) --- ## Overview This repository contains practical tutorials and examples for: - **LangChain**: Building applications with LLM chains, RAG, and agents - **LangGraph**: Creating state-based agentic workflows and multi-step processes - **MCP (Model Context Protocol)**: Implementing servers and semantic kernel integrations - **Semantic Kernel**: Building plugins and AI-powered agents with Microsoft's framework --- --- ## Tutorials Navigation ### LangChain LangChain tutorials covering fundamentals to advanced use cases. #### Fundamentals - Basic model interactions - Getting started with LangChain - Basic conversation setup #### Chat Models - Working with chat models - Model-based conversations #### Prompt Engineering - Basic prompt templates - Chat model prompt templates #### Chains - Basic chain operations - Extended chain functionality - Parallel chain execution - Branching logic in chains #### Advanced Features - Streaming responses - Structured output handling #### RAG (Retrieval-Augmented Generation) - RAG basics - RAG search functionality - RAG with metadata - Metadata-based RAG search - RAG-powered chatbot #### Agents - Basic agent setup - Structured agent outputs - Agent context management - Agent middleware 📁 **Location**: `./Langchain/` --- ### LangGraph LangGraph tutorials for building state machines and agentic workflows. #### Getting Started - Introduction to LangGraph - Basic concepts and setup #### Core Concepts - Routing logic in graphs - State checkpointing - Memory and state management - Working with multiple schemas #### Advanced Topics - Message filtering and trimming - Message summarization - Streaming workflow responses - Interruption handling - Time travel and state replay - Parallel execution - Using subgraphs - Map-reduce patterns - Memory store implementation #### Project Structure | Directory | Purpose | | --------- | -------------------------------- | | `basics/` | Basic project setup and examples | 📁 **Location**: `./Langgraph Tutorial/` --- ### MCP Tutorial Model Context Protocol implementations and integrations. #### Projects - Console-based MCP implementations (SSE and STDIO servers) - Standard MCP server implementation - Integration with Semantic Kernel - Server-Sent Events (SSE) MCP server #### Key Topics - SSE-based server implementation - Standard I/O server implementation - Tool definitions and handlers 📁 **Location**: `./MCPTut/` --- ### Semantic Kernel Microsoft Semantic Kernel tutorials for building AI plugins and agents. #### Fundamentals - Getting started with Semantic Kernel - Using Ollama with Semantic Kernel #### Plugins - Creating and using plugins - Ollama-specific plugins #### Integrations - Azure OpenAI integration - Image-to-text processing #### Advanced Features - Agent framework implementation - Google Search integration #### Additional Projects - Hand digit recognition project - Process framework examples - GitHub models integration 📁 **Location**: `./SemanticKernelTut/` ---