Building AI Applications - Examples¶
This section provides practical examples and frameworks for building AI applications, from development tools to production implementations.
Development and Code Generation¶
DevOpsGPT
Framework for automated development:
- Implements requirement analysis and planning
- Features code generation and optimization
- Includes deployment automation
Process overview:
GPT Engineer
Code generation and project development framework: - Available in two implementations: - AntonOsika/gpt-engineer - gpt-engineer-org/gpt-engineer - Focuses on end-to-end project generation - Includes project structure and documentation
Tool Creation and Enhancement¶
Large Language Models as Tool Makers
Framework for tool creation and reuse:
- Enables tool creation by larger models
- Supports tool reuse by lightweight models
- GitHub: ctlllll/llm-toolmaker
CREATOR: Tool Creation Framework
Disentangles abstract and concrete reasoning:
- Implements structured tool creation process
- Features cognitive architecture for reasoning
Chrome-GPT
Browser automation framework: - Automates Chrome browser interactions - Enables web-based task automation - Built on AutoGPT architecture
AgentForge
Low-code framework for agent development: - Supports rapid prototyping - Enables cognitive architecture testing - Features comprehensive testing tools - Focuses on AI-powered autonomous agents
Application Examples¶
Document Processing and Q&A¶
askFSDL
Demonstration of a retrieval-augmented Q&A application: - Part of LLM full stack - Technology stack: - OpenAI API - Pinecone vector database - MongoDB - Modal (serverless) - Discord bot (AWS)
Local LLM Document Q&A
Running open-source LLMs locally for document Q&A: - Focuses on CPU inference - Uses Llama 2 and other open models - Optimized for document processing
Model Optimization¶
UniversalNER
Model distillation framework: - Demonstrates effective knowledge transfer - Achieves high accuracy with smaller models - GitHub: universal-ner/universal-ner
Additional Resources¶
For more examples and implementations, explore: - Agent Examples for agent-specific implementations - Commercial Solutions for production-ready platforms - System Examples for multi-agent implementations