detect-framework

Framework Detection

When the user has existing Python code they want to integrate into Omnigent, detect the framework from import statements and recommend the appropriate executor type.

Detection Procedure

1. Ask the user for the path to their agent code (or look for Python files in the current directory if filesystem access is enabled).

2. Scan Python files for import patterns. Check in this priority order:

Import pattern	Framework	Executor type
import anthropic or from anthropic + agent patterns (e.g. Agent, tool, system prompt setup)	Claude SDK	claude_sdk
import openai or from openai + agents patterns (e.g. Agent, Runner, function_tool)	OpenAI Agents SDK	agents_sdk
from langgraph or import langgraph	LangGraph	Not natively supported yet
from deepagents or import deepagents	DeepAgents	Not natively supported yet
from langchain or import langchain	LangChain	Not natively supported yet
from crewai or import crewai	CrewAI	Not natively supported yet
from autogen or import autogen	AutoGen	Not natively supported yet
None of the above	Unknown	Not natively supported yet

3. Report what you found and recommend the executor type.

What to generate for each executor type

llm (default — no existing code)

Generate a standard agent directory:

executor:
  type: llm  # or omit entirely (llm is the default)

claude_sdk

The user's Claude SDK code runs directly. Generate config that points to their entry module:

executor:
  type: claude_sdk

agents_sdk

The user's OpenAI Agents SDK code runs directly:

executor:
  type: agents_sdk

Asking about unsupported frameworks

If the user's framework is not natively supported, let them know:

• Explain that Omnigent does not currently have a supported executor for that framework.
• Offer to show them a pre-filled GitHub issue URL requesting first-class support for their framework.
• If they want to start fresh instead, recommend generating a standard llm agent.
• The issue URL format: https://github.com/dbczumar/omnigent/issues/new?title=...&body=...