347 lines
10 KiB
Python
347 lines
10 KiB
Python
"""
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CopilotKit Run Loop
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"""
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import asyncio
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import contextvars
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import json
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import traceback
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from typing import Callable
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from pydantic import BaseModel
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from typing_extensions import Any, Dict, Optional, List, TypedDict, cast
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from partialjson.json_parser import JSONParser as PartialJSONParser
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from .protocol import (
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RuntimeEvent,
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RuntimeEventTypes,
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RuntimeMetaEventName,
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emit_runtime_event,
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emit_runtime_events,
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agent_state_message,
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AgentStateMessage,
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PredictStateConfig,
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RuntimeProtocolEvent,
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)
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async def yield_control():
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"""
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Yield control to the event loop.
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"""
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loop = asyncio.get_running_loop()
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future = loop.create_future()
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loop.call_soon(future.set_result, None)
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await future
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class CopilotKitRunExecution(TypedDict):
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"""
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CopilotKit Run Execution
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"""
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thread_id: str
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agent_name: str
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run_id: str
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should_exit: bool
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node_name: str
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is_finished: bool
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predict_state_configuration: Dict[str, PredictStateConfig]
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predicted_state: Dict[str, Any]
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argument_buffer: str
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current_tool_call: Optional[str]
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state: Dict[str, Any]
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_CONTEXT_QUEUE = contextvars.ContextVar("queue", default=None)
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_CONTEXT_EXECUTION = contextvars.ContextVar("execution", default=None)
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def get_context_queue() -> asyncio.Queue:
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"""
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Retrieve the queue from this task's context.
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"""
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q = _CONTEXT_QUEUE.get()
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if q is None:
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raise RuntimeError("No context queue is set!")
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return q
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def set_context_queue(q: asyncio.Queue) -> contextvars.Token:
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"""
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Set the queue in this task's context.
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"""
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token = _CONTEXT_QUEUE.set(cast(Any, q))
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return token
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def reset_context_queue(token: contextvars.Token):
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"""
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Reset the queue in this task's context.
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"""
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_CONTEXT_QUEUE.reset(token)
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def get_context_execution() -> CopilotKitRunExecution:
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"""
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Get the execution from this task's context.
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"""
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return cast(CopilotKitRunExecution, _CONTEXT_EXECUTION.get())
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def set_context_execution(execution: CopilotKitRunExecution) -> contextvars.Token:
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"""
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Set the execution in this task's context.
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"""
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token = _CONTEXT_EXECUTION.set(cast(Any, execution))
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return token
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def reset_context_execution(token: contextvars.Token):
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"""
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Reset the execution in this task's context.
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"""
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_CONTEXT_EXECUTION.reset(token)
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async def queue_put(*events: RuntimeEvent, priority: bool = False):
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"""
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Put an event in the queue.
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"""
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if not priority:
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# yield control so that priority events can be processed first
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await yield_control()
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q = get_context_queue()
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for event in events:
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await q.put(event)
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# yield control so that the reader can process the event
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await yield_control()
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def _to_dict_if_pydantic(obj):
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if isinstance(obj, BaseModel):
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return obj.model_dump()
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return obj
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def _filter_state(
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*, state: Dict[str, Any], exclude_keys: Optional[List[str]] = None
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) -> Dict[str, Any]:
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"""Filter out messages and id from the state"""
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state = _to_dict_if_pydantic(state)
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exclude_keys = exclude_keys or ["messages", "id"]
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return {k: v for k, v in state.items() if k not in exclude_keys}
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async def copilotkit_run(fn: Callable, *, execution: CopilotKitRunExecution):
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"""
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Run a task with a local queue.
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"""
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local_queue = asyncio.Queue()
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token_queue = set_context_queue(local_queue)
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token_execution = set_context_execution(execution)
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task = asyncio.create_task(fn())
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try:
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while True:
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event = await local_queue.get()
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local_queue.task_done()
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json_lines = handle_runtime_event(event=event, execution=execution)
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if json_lines is not None:
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yield json_lines
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if execution["is_finished"]:
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break
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# return control to the containing run loop to send events
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await yield_control()
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await task
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finally:
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reset_context_queue(token_queue)
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reset_context_execution(token_execution)
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def handle_runtime_event(
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*, event: RuntimeEvent, execution: CopilotKitRunExecution
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) -> Optional[str]:
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"""
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Handle a runtime event.
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"""
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if event["type"] in [
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RuntimeEventTypes.TEXT_MESSAGE_START,
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RuntimeEventTypes.TEXT_MESSAGE_CONTENT,
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RuntimeEventTypes.TEXT_MESSAGE_END,
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RuntimeEventTypes.ACTION_EXECUTION_START,
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RuntimeEventTypes.ACTION_EXECUTION_ARGS,
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RuntimeEventTypes.ACTION_EXECUTION_END,
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RuntimeEventTypes.ACTION_EXECUTION_RESULT,
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RuntimeEventTypes.AGENT_STATE_MESSAGE,
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]:
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events: List[RuntimeProtocolEvent] = [cast(RuntimeProtocolEvent, event)]
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if event["type"] in [
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RuntimeEventTypes.ACTION_EXECUTION_START,
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RuntimeEventTypes.ACTION_EXECUTION_ARGS,
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]:
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message = predict_state(
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thread_id=execution["thread_id"],
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agent_name=execution["agent_name"],
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run_id=execution["run_id"],
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event=event,
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execution=execution,
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)
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if message is not None:
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events.append(message)
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return emit_runtime_events(*events)
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if event["type"] == RuntimeEventTypes.META_EVENT:
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if event["name"] == RuntimeMetaEventName.PREDICT_STATE:
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execution["predict_state_configuration"] = event["value"]
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return None
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if event["name"] == RuntimeMetaEventName.EXIT:
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execution["should_exit"] = event["value"]
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return None
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return None
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if event["type"] == RuntimeEventTypes.RUN_STARTED:
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execution["state"] = event["state"]
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return None
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if event["type"] == RuntimeEventTypes.NODE_STARTED:
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execution["node_name"] = event["node_name"]
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execution["state"] = event["state"]
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return emit_runtime_event(
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agent_state_message(
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thread_id=execution["thread_id"],
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agent_name=execution["agent_name"],
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node_name=execution["node_name"],
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run_id=execution["run_id"],
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active=True,
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role="assistant",
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state=json.dumps(_filter_state(state=execution["state"])),
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running=True,
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)
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)
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if event["type"] == RuntimeEventTypes.NODE_FINISHED:
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# reset the predict state configuration at the end of the method execution
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execution["predict_state_configuration"] = {}
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execution["current_tool_call"] = None
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execution["argument_buffer"] = ""
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execution["predicted_state"] = {}
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execution["state"] = event["state"]
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return emit_runtime_event(
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agent_state_message(
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thread_id=execution["thread_id"],
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agent_name=execution["agent_name"],
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node_name=execution["node_name"],
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run_id=execution["run_id"],
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active=False,
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role="assistant",
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state=json.dumps(_filter_state(state=execution["state"])),
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running=True,
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)
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)
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if event["type"] == RuntimeEventTypes.RUN_FINISHED:
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execution["is_finished"] = True
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return None
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if event["type"] == RuntimeEventTypes.RUN_ERROR:
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print("Flow execution error", flush=True)
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error_info = event["error"]
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if isinstance(error_info, Exception):
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# If it's an exception, print the traceback
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print("Exception occurred:", flush=True)
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print(
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"".join(
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traceback.format_exception(
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None, error_info, error_info.__traceback__
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)
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),
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flush=True,
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)
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else:
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# Otherwise, assume it's a string and print it
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print(error_info, flush=True)
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execution["is_finished"] = True
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return None
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def predict_state(
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*,
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thread_id: str,
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agent_name: str,
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run_id: str,
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event: Any,
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execution: CopilotKitRunExecution,
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) -> Optional[AgentStateMessage]:
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"""Predict the state"""
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if event["type"] == RuntimeEventTypes.ACTION_EXECUTION_START:
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execution["current_tool_call"] = event["actionName"]
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execution["argument_buffer"] = ""
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elif event["type"] == RuntimeEventTypes.ACTION_EXECUTION_ARGS:
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execution["argument_buffer"] += event["args"]
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tool_names = [
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config.get("tool_name")
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for config in execution["predict_state_configuration"].values()
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]
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if execution["current_tool_call"] not in tool_names:
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return None
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current_arguments = {}
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try:
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current_arguments = PartialJSONParser().parse(execution["argument_buffer"])
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except: # pylint: disable=bare-except
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return None
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emit_update = False
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for k, v in execution["predict_state_configuration"].items():
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if v["tool_name"] == execution["current_tool_call"]:
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tool_argument = v.get("tool_argument")
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if tool_argument is not None:
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argument_value = current_arguments.get(tool_argument)
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if argument_value is not None:
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execution["predicted_state"][k] = argument_value
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emit_update = True
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else:
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execution["predicted_state"][k] = current_arguments
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emit_update = True
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if emit_update:
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return agent_state_message(
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thread_id=thread_id,
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agent_name=agent_name,
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node_name=execution["node_name"],
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run_id=run_id,
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active=True,
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role="assistant",
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state=json.dumps(
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_filter_state(
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state={
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**(
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execution["state"].model_dump()
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if isinstance(execution["state"], BaseModel)
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else execution["state"]
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),
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**execution["predicted_state"],
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}
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)
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),
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running=True,
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)
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return None
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