Just Agents - Base Package
Project description
just-agents-core
A lightweight, straightforward core library for LLM agents - no over-engineering, just simplicity!
🎯 Core Features
- 🪶 Lightweight and simple implementation
- 📝 Easy-to-understand agent interactions
- 🔧 Customizable prompts using YAML files
- 🤖 Support for various LLM models through litellm
- 🔄 Chain of Thought reasoning with function calls
🏗️ Core Components
BaseAgent
A thin wrapper around litellm for basic LLM interactions. Provides:
- Simple prompt management
- Direct LLM communication
- Memory handling
ChatAgent
The fundamental building block for agent interactions. Here's an example of using multiple chat agents:
from just_agents.base_agent import ChatAgent
from just_agents.llm_options import LLAMA3_3
# Initialize agents with different roles
harris = ChatAgent(
llm_options=LLAMA3_3,
role="You are Kamala Harris in a presidential debate",
goal="Win the debate with clear, concise responses",
task="Respond briefly and effectively to debate questions"
)
trump = ChatAgent(
llm_options=LLAMA3_3,
role="You are Donald Trump in a presidential debate",
goal="Win the debate with your signature style",
task="Respond briefly and effectively to debate questions"
)
moderator = ChatAgent(
llm_options={
"model": "groq/mixtral-8x7b-32768",
"api_base": "https://api.groq.com/openai/v1",
"temperature": 0.0,
"tools": []
},
role="You are a neutral debate moderator",
goal="Ensure a fair and focused debate",
task="Generate clear, specific questions about key political issues"
)
ChainOfThoughtAgent
Extended agent with reasoning capabilities and function calling:
from just_agents.patterns.chain_of_throught import ChainOfThoughtAgent
from just_agents import llm_options
def count_letters(character: str, word: str) -> str:
""" Returns the number of character occurrences in the word. """
count = word.count(character)
return str(count)
# Initialize agent with tools and LLM options
agent = ChainOfThoughtAgent(
tools=[count_letters],
llm_options=llm_options.LLAMA3_3
)
# Get result and reasoning chain
result, chain = agent.think("Count the number of occurrences of the letter 'L' in 'HELLO'.")
📚 Usage
This core package provides the fundamental building blocks for LLM agents. For full usage examples and documentation, please refer to the main repository.
🔧 Installation
pip install just-agents-core
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