LLM Agents: Streamlined AI Agent Development
LLM Agents is an efficient and robust library crafted for constructing AI agents governed by large language models (LLMs). Drawing inspiration from langchain, this initiative aims to streamline the creation and comprehension of AI agents, ensuring accessibility for developers and researchers alike.
Key Features
- Simplified Architecture: Developed with minimal abstraction layers for easy understanding.
- Custom Tools: Includes Python REPL, Google Search, and Hacker News Search functionalities.
- Flexible Integration: Easily expandable with personalized tools and LLM providers.
- Thought-Action-Observation Loop: Implements a cyclical decision-making process.
How It Works
The operation of the LLM Agents library revolves around a simple principle:
- Instruction: The agent receives a task-solving prompt with available tools instruction.
- Tool Utilization: Custom tools are utilized by the agent.
- Decision Loop: The agent engages in a cycle of Thought, Action, Observation.
- Continuous Learning: New insights are integrated, allowing the agent to adapt and improve.
- Final Answer: Upon gathering sufficient data, the agent delivers a conclusive response.
Getting Started
Installation
Clone the repository and run pip install -e . in the project directory.
Environment Setup
Set the following environment variables:
export OPENAI_API_KEY='your-api-key-here'
export SERPAPI_API_KEY='your-serpapi-key-here'Usage
Example of basic usage:
from llm_agents import Agent, ChatLLM, PythonREPLTool, HackerNewsSearchTool, SerpAPITool
agent = Agent(llm=ChatLLM(), tools=[PythonREPLTool(), SerpAPITool(), HackerNewsSearchTool()])
result = agent.run("Your question to the agent")
print(f"Final answer is {result}")Customization
LLM Agents allows for:
- Creating custom tools to enhance the agent's abilities.
- Omitting tools as necessary (e.g., excluding SerpAPI without an API key).
- Experimenting with varied LLM providers or custom prompts.
Benefits
- Educational Value: Gain insights into AI agent structure and functionality.
- Rapid Prototyping: Swiftly construct and test AI agent ideas.
- Customizable: Tailor the agent to specific research requirements.
- Lightweight: Minimal dependencies and simple implementation.
Conclusion
LLM Agents presents a unique avenue to delve into and experiment with AI agent development. Whether you're a researcher, developer, or AI enthusiast, this library establishes a solid base for constructing intelligent, task-driven agents powered by large language models.
Commence your journey with LLM Agents today and unlock the potential of AI-driven problem-solving in your projects!
