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PAAF (Peter Akande Agentic Framwork) is a simple Agentic framwork built to be used for all my LLM applications.
from paaf.agents.react import ReactAgent
from paaf.llms.openai_llm import OpenAILLM
from paaf.tools.tool_registory import ToolRegistry
from serper import search as serper_search
from wiki import wiki_search
tool_registory = ToolRegistry()
tool_registory.register_tool(serper_search)
tool_registory.register_tool(wiki_search)
@tool_registory.tool()
def my_name() -> str:
"""
Get the name of the user.
Returns:
str: The name of the user.
"""
return "John Doe"
if __name__ == "__main__":
llm = OpenAILLM()
react_agent = ReactAgent(
llm=llm,
tool_registry=tool_registory,
max_iterations=5,
)
response = react_agent.run("Who is older, Cristiano Ronaldo or Lionel Messi?")
print("Response:", response.content)
FAQs
Paaf is an Agent Framework for building AI agents
We found that paaf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Socket now supports pylock.toml, enabling secure, reproducible Python builds with advanced scanning and full alignment with PEP 751's new standard.
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