genpilot 0.0.7

GenPilot streamlines the prototype for single/multi-agent systems powered by Generative AI through an intuitive, user-friendly interface.

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GenPilot

GenPilot streamlines the creation and management of multi-agent systems powered by Generative AI through an intuitive, user-friendly interface. It allows both developers and end-users to efficiently transform concepts and prototypes into fully realized solutions.

Installation

Require Python 3.10 or later.

pip install genpilot

Usage

The client is initialized using litellm. Please refer to the guide for details on different providers.

import genpilot as gp

# 1. User Interface: Also supports Streamlit UI, allowing all agents to share the same chat interface.
terminal = gp.TerminalChat(model_options={"temperature": 0.2, "stream": True})

# 2. Define a Tool to search and summarize information
def search_and_summarize(query):
    """Search for information on the internet and return a summary."""
    return f"Here's the summary for '{query}': [Summarized info]."

# 3. Define an Agent for summarizing search results
info_explorer = gp.Agent(
    name="Information Explorer",
    model="groq:llama-3.3-70b-versatile",
    chat=terminal,
    tools=[search_and_summarize],
    system=(
        "Your role is to search the internet and summarize relevant information for a given query. "
        "Use the search tool to find and condense information for the user, ensuring clarity and relevance."
    ),
)

# 4. Run the Agent with a query
response = info_explorer.run("What's the latest news about AI advancements?")
print(response)

Why GenPilot?

• User-Friendly Interface: GenPilot offers an intuitive interface for prototyping and quick implementation, whether through a web UI or terminal. Get started quickly and seamlessly with minimal effort.

• Enhanced Autonomy: GenPilot can internally register and invoke tools, reducing reliance on external agents and minimizing unnecessary interactions.

• Governed Actions

  

  GenPilot's actions are governed by three permission levels:

  • auto: Permission requested only for system/environment-modifying actions.
  • always: Permission requested for all actions.
  • none: No permission requests.

• Multi-Agent System: Seamlessly scale from single-agent tasks to complex multi-agent workflows, inspired by Routines and Handoffs.

• Memory [PROCESSING]: GenPilot enhances accuracy with customizable memory:

  1. ChatBufferMemory A short-term memory solution designed to retrieve the most recent message along with the current session context.

  2. ChatVectorMemory A long-term memory implementation based on LlamaIndex vector memory.

  MemGPT: Towards LLMs as Operating Systems CLIN: A CONTINUALLY LEARNING LANGUAGE AGENT FOR RAPID TASK ADAPTATION AND GENERALIZATION

  3. ChatPgMemory ...

• RAG Support: GenPilot integrates a retrieval agent that allows local resource or knowledge integration into the multi-agent system. The default implementation leverages LlamaIndex's ChatEngine.

• Typed Prompt and Auto Optimizer

  • https://github.com/stanfordnlp/dspy

  • https://github.com/zou-group/textgrad

Samples

This demo provides advice on what to wear when traveling to a city

This demo uses multi-agent troubleshooting for issues in RedHat ACM

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