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849987f0e6
Introduce an agent orchestrator service that supports three execution patterns (ReAct, plan-then-execute, supervisor) with LLM-based meta-routing to select the appropriate pattern and task type per request. Update the agent schema to support orchestration fields (correlation, sub-agents, plan steps) and remove legacy response fields (answer, thought, observation).
80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
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from . request_response_spec import RequestResponse, RequestResponseSpec
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from .. schema import AgentRequest, AgentResponse
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from .. knowledge import Uri, Literal
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class AgentClient(RequestResponse):
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async def invoke(self, question, plan=None, state=None,
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history=[], think=None, observe=None, answer_callback=None,
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timeout=300):
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"""
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Invoke the agent with optional streaming callbacks.
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Args:
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question: The question to ask
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plan: Optional plan context
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state: Optional state context
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history: Conversation history
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think: Optional async callback(content, end_of_message) for thought chunks
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observe: Optional async callback(content, end_of_message) for observation chunks
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answer_callback: Optional async callback(content, end_of_message) for answer chunks
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timeout: Request timeout in seconds
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Returns:
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Complete answer text (accumulated from all answer chunks)
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"""
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accumulated_answer = []
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async def recipient(resp):
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if resp.error:
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raise RuntimeError(resp.error.message)
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# Handle thought chunks
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if resp.chunk_type == 'thought':
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if think:
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await think(resp.content, resp.end_of_message)
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return False # Continue receiving
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# Handle observation chunks
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if resp.chunk_type == 'observation':
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if observe:
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await observe(resp.content, resp.end_of_message)
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return False # Continue receiving
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# Handle answer chunks
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if resp.chunk_type == 'answer':
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if resp.content:
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accumulated_answer.append(resp.content)
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if answer_callback:
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await answer_callback(resp.content, resp.end_of_message)
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# Complete when dialog ends
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if resp.end_of_dialog:
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return True
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return False # Continue receiving
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await self.request(
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AgentRequest(
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question = question,
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state = state or "",
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history = history,
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),
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recipient=recipient,
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timeout=timeout,
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)
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return "".join(accumulated_answer)
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class AgentClientSpec(RequestResponseSpec):
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def __init__(
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self, request_name, response_name,
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):
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super(AgentClientSpec, self).__init__(
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request_name = request_name,
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request_schema = AgentRequest,
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response_name = response_name,
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response_schema = AgentResponse,
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impl = AgentClient,
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)
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