修改ChatComplete事件的实现
parent
83bb6ad213
commit
cc283b1618
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from __future__ import annotations
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from typing import Any
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from agentkit.context import ConversationContext
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class BaseAgent:
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def __init__(self, config: dict[str, Any]):
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self.config = config
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async def __aenter__(self) -> BaseAgent:
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return self
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async def __aexit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None:
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return None
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async def count_tokens(self, text: str) -> int:
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return len(text.split())
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async def chat_complete(self, context: ConversationContext, stream: bool = False):
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pass
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from __future__ import annotations
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from typing import Any
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from agentkit.base.agent import BaseAgent
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class BaseAgentFactory:
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def __init__(self, props: dict):
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pass
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async def __aenter__(self) -> BaseAgentFactory:
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return self
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async def __aexit__(self, exc_type: Any, exc_val: Any, exc_tb: Any) -> None:
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return None
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async def new_from_id(self, agent_id: str) -> BaseAgent | None:
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"""
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Create agent from agent id.
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"""
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return None
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async def new_from_config(self, agent_type: str, config: dict) -> BaseAgent | None:
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"""
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Create agent from agent type and config.
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"""
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return None
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import logging
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from agentkit.context import ConversationContext
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from agentkit.types import AgentKitFlowStep
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class BreakLoopInterrupt(Exception):
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pass
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class AgentKitFlowExecutor:
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def __init__(self, flow_script: list[AgentKitFlowStep]):
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self.flow = flow_script
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def _execute_step(self, step: AgentKitFlowStep, context: ConversationContext):
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"""
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Execute a single flow step.
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Args:
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step (dict): The step to execute.
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Returns:
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Any: The result of the step execution.
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"""
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step_type = step["type"]
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if step_type == "call":
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return self._execute_call(step, context)
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elif step_type == "if_else":
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return self._execute_if_else(step, context)
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elif step_type == "loop":
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return self._execute_loop(step)
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elif step_type == "break_loop":
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return self._execute_break_loop(step)
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else:
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raise ValueError(f"Unsupported step type: {step_type}")
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def _execute_call(self, step: dict, context: ConversationContext):
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"""
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Execute a 'call' step.
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Args:
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step (dict): The call step configuration.
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Returns:
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Any: The result of the call.
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"""
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func_id = step.get("id")
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config = {k: self._resolve_value(v) for k, v in step.get("config", {}).items()}
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output_map = step.get("output_map", {})
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# Simulate calling a function (replace with actual function calls if needed)
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logging.info(f"Calling function {func_id} with config: {config}")
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result = {key: f"mocked_value_{key}" for key in output_map.keys()} # Mocked output
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# Map outputs to variables
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for key, var_name in output_map.items():
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self.variables[var_name] = result.get(key)
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return result
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def _execute_if_else(self, step: dict, context: ConversationContext):
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"""
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Execute an 'if_else' step.
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Args:
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step (dict): The if_else step configuration.
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Returns:
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Any: The result of the executed branch.
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"""
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condition = step.get("condition")
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condition_input = {k: self._resolve_value(v) for k, v in step.get("condition_input", {}).items()}
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# Evaluate the condition
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condition_result = eval(condition, {}, condition_input)
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# Execute the appropriate branch
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branch = step["true_branch"] if condition_result else step["false_branch"]
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for sub_step in branch:
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self._execute_step(sub_step, context)
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def _execute_loop(self, step: dict, context: ConversationContext):
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"""
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Execute a 'loop' step.
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Args:
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step (dict): The loop step configuration.
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Returns:
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Any: The result of the loop execution.
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"""
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loop_num = step.get("loop_num")
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index_var = step.get("index_var")
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loop_body = step.get("loop_body", [])
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for i in range(loop_num):
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if index_var:
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context.state[index_var] = i
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for sub_step in loop_body:
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self._execute_step(sub_step, context)
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def _execute_break_loop(self):
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"""
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Execute a 'break_loop' step.
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Args:
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step (dict): The break_loop step configuration.
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Returns:
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None
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"""
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raise BreakLoopInterrupt()
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def execute(self, context: ConversationContext):
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"""
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Execute the entire flow.
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Returns:
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None
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"""
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try:
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for step in self.flow:
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self._execute_step(step)
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except BreakLoopInterrupt:
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pass
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from __future__ import annotations
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from typing import Callable
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from type_defs.chat_complete_task import ChatCompleteServiceResponse
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from utils.program import run_listeners
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class ChatCompleteEvent:
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def __init__(self):
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self.on_tool_running: list[Callable[[str, str], None]] = []
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self.on_tool_output: list[Callable[[str], None]] = []
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self.on_message_output: list[Callable[[str], None]] = []
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async def emit_tool_running(self, tool_name: str, running_state: str = "") -> None:
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await run_listeners(self.on_tool_running, tool_name, running_state)
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async def emit_tool_output(self, output: str) -> None:
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await run_listeners(self.on_tool_output, output)
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async def emit_message_output(self, output: str) -> None:
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await run_listeners(self.on_message_output, output)
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class ChatCompleteTaskEvent(ChatCompleteEvent):
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def __init__(self):
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super().__init__()
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self.on_finished: list[Callable[[str | None], None]] = []
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self.on_error: list[Callable[[str], None]] = []
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async def emit_finished(self, result: ChatCompleteServiceResponse | None) -> None:
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await run_listeners(self.on_finished, result)
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async def emit_error(self, ex: Exception) -> None:
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await run_listeners(self.on_error, ex)
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@ -1,3 +0,0 @@
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text2vec>=1.2.9
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--index-url https://download.pytorch.org/whl/cpu
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torch
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from __future__ import annotations
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from typing_extensions import TypedDict
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class ChatCompleteQuestionTooLongException(Exception):
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def __init__(self, tokens_limit: int, tokens_current: int):
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super().__init__(f"Question too long: {tokens_current} > {tokens_limit}")
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self.tokens_limit = tokens_limit
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self.tokens_current = tokens_current
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class ChatCompleteServicePrepareResponse(TypedDict):
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extract_doc: list
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question_tokens: int
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conversation_id: int
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chunk_id: int
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api_id: str
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class ChatCompleteServiceResponse(TypedDict):
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message: str
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message_tokens: int
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total_tokens: int
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finish_reason: str
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question_message_id: str
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response_message_id: str
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delta_data: dict
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@ -0,0 +1,19 @@
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import asyncio
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import sys
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import traceback
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from typing import Coroutine
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async def run_listeners(listeners: list, *args, **kwargs) -> Coroutine[None, None, None]:
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for listener in listeners:
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try:
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res = listener(*args, **kwargs)
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if asyncio.iscoroutine(res):
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await res
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except Exception as ex:
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print(
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"Error while processing callback: %s" % ex,
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file=sys.stderr,
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)
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traceback.print_exc()
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return None
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