67 lines
2.7 KiB
Python
67 lines
2.7 KiB
Python
import json
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from dataclasses import dataclass
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from typing import Any, Optional
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@dataclass
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class StepOutcome:
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data: Any
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next_prompt: Optional[str] = None
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should_exit: bool = False
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def try_call_generator(func, *args, **kwargs):
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ret = func(*args, **kwargs)
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if hasattr(ret, '__iter__') and not isinstance(ret, (str, bytes, dict, list)):
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ret = yield from ret
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return ret
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class BaseHandler:
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def tool_before_callback(self, tool_name, args, content): pass
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def tool_after_callback(self, tool_name, args, content): pass
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def dispatch(self, tool_name, args, response):
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method_name = f"do_{tool_name}"
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if hasattr(self, method_name):
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_ = yield from try_call_generator(self.tool_before_callback, tool_name, args, response)
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ret = yield from try_call_generator(getattr(self, method_name), args, response)
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_ = yield from try_call_generator(self.tool_after_callback, tool_name, args, response)
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return ret
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else:
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yield f"❌ 未知工具: {tool_name}\n"
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return StepOutcome(None, "未知工具", "ERROR")
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def json_default(o):
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if isinstance(o, set): return list(o)
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return str(o)
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def agent_runner_loop(client, system_prompt, user_input, handler, tools_schema, max_turns=15):
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_input}
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]
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for turn in range(max_turns):
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yield f"\n[🤖 LLM Thinking (Turn {turn+1})] ..."
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response = client.chat(messages=messages, tools=tools_schema)
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if response.thinking: yield '<thinking>' + response.thinking + '</thinking>\n'
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yield response.content
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if not response.tool_calls:
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tool_name, args = 'no_tool', {}
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else:
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tool_call = response.tool_calls[0]
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tool_name = tool_call.function.name
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args = json.loads(tool_call.function.arguments)
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if tool_name == 'no_tool': pass
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else: yield f"\n\n正在调用工具: {tool_name}，参数: {args}\n"
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outcome = yield from handler.dispatch(tool_name, args, response)
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if outcome.next_prompt is None: return {'result': 'CURRENT_TASK_DONE', 'data': outcome.data}
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if outcome.should_exit: return {'result': 'EXITED', 'data': outcome.data}
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next_prompt = ""
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if outcome.data is not None:
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datastr = json.dumps(outcome.data, ensure_ascii=False, default=json_default) if type(outcome.data) in [dict, list] else str(outcome.data)
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next_prompt += f"<tool_result>\n{datastr}\n</tool_result>\n\n"
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next_prompt += outcome.next_prompt
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messages = [{"role": "user", "content": next_prompt}]
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return {'result': 'MAX_TURNS_EXCEEDED'} |