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SOFIA: Simple Orchestrated Flow Intelligence Agent

Project description

👩‍💼 SOFIA: Simple Orchestrated Flow Intelligence Agent

SOFIA is an open-source, configurable multi-step agent framework for building advanced LLM-powered assistants. Define your agent's persona, tools, and step-by-step flows in Python or YAML—perfect for conversational, workflow, and automation use cases.

Features

  • Step-based agent flows: Define agent behavior as a sequence of steps, each with its own tools and transitions.
  • Persona-driven: Easily set the agent's persona for consistent, branded responses.
  • Tool integration: Register Python functions as tools for the agent to call.
  • YAML or Python config: Configure agents via code or declarative YAML.
  • OpenAI and custom LLM support
  • Session management: Save and resume conversations.
  • Extensible: Build your own tools, steps, and integrations.
  • Interactive CLI: Bootstrap new agents with sofia init (install with [cli] extra).

Installation

From PyPI (coming soon)

pip install sofia-agent

With CLI support

pip install sofia-agent[cli]

From Source

git clone https://github.com/chandralegend/sofia.git
cd sofia
poetry install

Usage

CLI: Bootstrap a New Agent

sofia init

This will interactively guide you to create a config YAML and starter Python file for your agent.

Python API Example

from sofia_agent import *
from sofia_agent.llms import OpenAIChatLLM

def get_time():
    from datetime import datetime
    return f"Current time: {datetime.now()}"

steps = [
    Step(
        step_id="start",
        description="Greet and offer to tell the time.",
        available_tools=["get_time"],
        routes=[Route(target="end", condition="User is done")],
    ),
    Step(
        step_id="end",
        description="Say goodbye.",
    ),
]

llm = OpenAIChatLLM()
agent = Sofia(
    name="clockbot",
    llm=llm,
    steps=steps,
    start_step_id="start",
    tools=[get_time],
    persona="You are a friendly clock assistant.",
)
sess = agent.create_session()
# ... interact with sess.next(user_input)

YAML Config Example

See examples/config.barista.yaml for a full-featured barista agent.

Configuration

  • Persona: Set in YAML or Python for consistent agent style.
  • Steps: Each step defines available tools, description, and routes to other steps.
  • Tools: Python functions registered with the agent.

Example: Barista Agent

A full example is provided in examples/barista.py and examples/config.barista.yaml.

Contributing

Contributions are welcome! Please open issues or pull requests on GitHub.

License

MIT License. See LICENSE.

Acknowledgements

  • Inspired by the open-source LLM community.
  • Built with ❤️ by contributors.

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