Creating tools for LLM so it can call API by itself and finish complex tasks.
Good example of how to play with Agents, Tools, etc.
Python 3.10+
pip install -r requirements.txt
# Fill your credential
cp example.env .env
# Adhoc
python ./utils/api.pyInfrastructure
- OpenAPI document to API Agent
- General API document (e.g. using web crawler)
- Self-building API call function as tool
Learning
- Understand LangGraph
Bug
- Fix agent executor intermediate output exceed max token length limit issue
Tasks
- Spotify Agent
- Basic Spotify API call based on OpenAPI document
- Change it to notebook
- Fix bug
- JSON agent
- Basic Spotify API call based on OpenAPI document
- Financial Agent
- Simple Polygon
- Fix bug
- LangGraph + Polygon
- Simple Polygon
Other
- Build UI to play with each of them (if there is stable playable example)
Tools and Agent (general)
API Agent and Planner
Template
LangGraph: Multi-Agent
- 🦜🕸️LangGraph | 🦜️🔗 Langchain
- LangGraph: Multi-Agent Workflows
- Future of Coding — Multi-Agent LLM Framework using LangGraph | by Anurag Mishra | Mar, 2024 | Medium
- LangGraph
LangServe: Serving
MetaGPT force many packages to be exact version, so you might want to use virtual environment instead of modify all existing packages' version
- geekan/MetaGPT: 🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming (MetaGPT)
- Agent 101 | MetaGPT
- MultiAgent 101 | MetaGPT
- RAG Module | MetaGPT
Agents/Tools (general)
- [2210.03629] ReAct: Synergizing Reasoning and Acting in Language Models
- [2205.00445] MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
API Agent (specific)