9cbb7310e8
Adapters extracted from molecule-monorepo/workspace-template. Uses molecule-ai-workspace-runtime PyPI package for shared infrastructure. - adapter.py — runtime-specific adapter class - requirements.txt — runtime-specific deps + molecule-ai-workspace-runtime - Dockerfile — FROM python:3.11-slim, pip install, COPY adapter, molecule-runtime entrypoint - ADAPTER_MODULE=adapter tells the runtime to load this repo's Adapter class Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
"""LangGraph adapter — Python-based ReAct agent with skills, tools, and plugins."""
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import os
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import logging
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from molecule_runtime.adapters.base import BaseAdapter, AdapterConfig
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from a2a.server.agent_execution import AgentExecutor
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logger = logging.getLogger(__name__)
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class LangGraphAdapter(BaseAdapter):
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@staticmethod
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def name() -> str:
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return "langgraph"
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@staticmethod
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def display_name() -> str:
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return "LangGraph"
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@staticmethod
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def description() -> str:
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return "LangGraph ReAct agent — Python-based with skills, tools, plugins, and peer coordination"
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@staticmethod
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def get_config_schema() -> dict:
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return {
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"model": {"type": "string", "description": "LangChain model string (e.g. openrouter:google/gemini-2.5-flash)"},
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"skills": {"type": "array", "items": {"type": "string"}, "description": "Skill folder names to load"},
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"tools": {"type": "array", "items": {"type": "string"}, "description": "Built-in tools (web_search, filesystem, etc.)"},
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}
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def __init__(self):
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self.loaded_skills = []
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self.all_tools = []
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self.system_prompt = None
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async def setup(self, config: AdapterConfig) -> None:
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result = await self._common_setup(config)
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self.loaded_skills = result.loaded_skills
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self.all_tools = result.langchain_tools
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self.system_prompt = result.system_prompt
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async def create_executor(self, config: AdapterConfig) -> AgentExecutor:
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from agent import create_agent
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from a2a_executor import LangGraphA2AExecutor
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agent = create_agent(config.model, self.all_tools, self.system_prompt)
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return LangGraphA2AExecutor(agent, heartbeat=config.heartbeat, model=config.model)
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