100x-LLM

100x-LLM

Code snippets and examples from the 100x Applied AI cohort lectures.

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This repository contains code snippets and examples from the 100x Applied AI cohort lectures. It includes implementations of LLM Workflows, RAG (Retrieval Augmented Generation), Agentic Patterns, Chat Completions with various providers, Function Calling, and more. The repository structure consists of core components like LLM Workflows, RAG Implementations, Agentic Patterns, Chat Completions, Function Calling, Hugging Face Integration, and additional components for various agent implementations, presentation generation, Notion API integration, FastAPI-based endpoints, authentication implementations, and LangChain usage examples.

README:

100x Applied AI - Code Snippets

This repository contains code snippets and examples from the 100x Applied AI cohort lectures.

Project Overview

The repository includes implementations of:

  • LLM Workflows and Patterns
  • RAG (Retrieval Augmented Generation)
  • Agentic Patterns
  • Chat Completions with various providers
  • Function Calling
  • And more...

Installation Guide

Prerequisites

  • Python 3.8+
  • pip

Setup

  1. Clone the repository:
    git clone <repository-url>
  2. Create and activate a virtual environment:
    python -m venv venv
    source venv/bin/activate  # On Windows: venv\Scripts\activate
  3. Install dependencies:
    pip install -r requirements.txt
  4. Environment setup:
    • Copy .env_example to .env
    • Add your API keys and configurations

Repository Structure

Core Components

LLM Workflows (llm_workflows/)

  • Prompt Chaining and Orchestration
  • Router-based Workflows
  • Parallel Processing Patterns
  • Code Review Automation
  • Evaluation and Optimization

RAG Implementations (rag/ & rag2/)

  • Different approaches to Retrieval Augmented Generation
  • Integration examples

Agentic Patterns (agentic_patterns/)

  • Implementation of various AI agent patterns
  • Agent orchestration examples

Chat Completions (chat_completions/)

  • OpenAI integration
  • Groq implementation
  • Other LLM providers

Function Calling (function_calling/)

  • Examples of function calling with LLMs
  • Real-world use cases

Hugging Face Integration (huggingface/)

  • Model usage examples
  • Inference API implementations

Additional Components

  • agents/: Various agent implementations
  • presentation_generator/: Automated presentation creation
  • notion_data_integration/: Notion API integration examples
  • api/: FastAPI-based endpoints
  • auth/: Authentication implementations
  • langchain/: LangChain usage examples

Usage

Each directory contains specific examples and implementations. Refer to individual README files within each directory for detailed usage instructions.

Additional Resources

  • Check the prompts/ directory for various prompt engineering examples
  • See llm_workflows/README.md for detailed workflow patterns
  • Explore individual directories for specific implementation details

Environment Variables

Required environment variables (add to .env):

  • OpenAI API keys
  • Hugging Face API tokens
  • Other provider credentials as needed

Contributing

Feel free to contribute by:

  1. Forking the repository
  2. Creating a feature branch
  3. Submitting a pull request

License

This project is licensed under the terms specified in the LICENSE file.

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