mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-04-08 03:00:28 -04:00
refactor(chat/sdk): remove Langfuse tracing — OpenRouter handles observability
Delete tracing.py (~408 lines) and all TracedSession/hook references from the SDK path. OpenRouter already provides token usage, cost tracking, and request logging, making manual Langfuse integration redundant. This also fixes the broken 'Langfuse' object has no attribute 'trace' warning on every request.
This commit is contained in:
@@ -37,7 +37,6 @@ from .tool_adapter import (
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create_copilot_mcp_server,
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set_execution_context,
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)
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from .tracing import TracedSession, create_tracing_hooks, merge_hooks
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logger = logging.getLogger(__name__)
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config = ChatConfig()
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@@ -356,23 +355,17 @@ async def stream_chat_completion_sdk(
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sdk_model = _resolve_sdk_model()
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# Initialize Langfuse tracing (no-op if not configured)
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tracer = TracedSession(session_id, user_id, system_prompt, model=sdk_model)
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# Merge security hooks with optional tracing hooks
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security_hooks = create_security_hooks(
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user_id,
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sdk_cwd=sdk_cwd,
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max_subtasks=config.claude_agent_max_subtasks,
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)
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tracing_hooks = create_tracing_hooks(tracer)
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combined_hooks = merge_hooks(security_hooks, tracing_hooks)
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options = ClaudeAgentOptions(
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system_prompt=system_prompt,
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mcp_servers={"copilot": mcp_server}, # type: ignore[arg-type]
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allowed_tools=COPILOT_TOOL_NAMES,
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hooks=combined_hooks, # type: ignore[arg-type]
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hooks=security_hooks, # type: ignore[arg-type]
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cwd=sdk_cwd,
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max_buffer_size=config.claude_agent_max_buffer_size,
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# Only pass model/env when OpenRouter is configured
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@@ -382,7 +375,7 @@ async def stream_chat_completion_sdk(
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adapter = SDKResponseAdapter(message_id=message_id)
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adapter.set_task_id(task_id)
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async with tracer, ClaudeSDKClient(options=options) as client:
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async with ClaudeSDKClient(options=options) as client:
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current_message = message or ""
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if not current_message and session.messages:
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last_user = [m for m in session.messages if m.role == "user"]
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@@ -413,7 +406,6 @@ async def stream_chat_completion_sdk(
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f"[SDK] Sending query: {current_message[:80]!r}"
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f" ({len(session.messages)} msgs in session)"
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)
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tracer.log_user_message(current_message)
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await client.query(query_message, session_id=session_id)
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assistant_response = ChatMessage(role="assistant", content="")
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@@ -426,7 +418,6 @@ async def stream_chat_completion_sdk(
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f"[SDK] Received: {type(sdk_msg).__name__} "
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f"{getattr(sdk_msg, 'subtype', '')}"
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)
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tracer.log_sdk_message(sdk_msg)
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for response in adapter.convert_message(sdk_msg):
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if isinstance(response, StreamStart):
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continue
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@@ -1,407 +0,0 @@
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"""Langfuse tracing integration for Claude Agent SDK.
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This module provides modular, non-invasive observability for SDK sessions.
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All tracing is opt-in (only active when Langfuse credentials are configured)
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and designed to not affect the core execution flow.
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Usage::
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async with TracedSession(session_id, user_id) as tracer:
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tracer.log_user_message(message)
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async for sdk_msg in client.receive_messages():
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tracer.log_sdk_message(sdk_msg)
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"""
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from __future__ import annotations
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import logging
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import time
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from dataclasses import dataclass, field
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from typing import TYPE_CHECKING, Any
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from backend.util.settings import Settings
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if TYPE_CHECKING:
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from claude_agent_sdk import Message, ResultMessage
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logger = logging.getLogger(__name__)
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settings = Settings()
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def _is_langfuse_configured() -> bool:
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"""Check if Langfuse credentials are configured."""
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return bool(
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settings.secrets.langfuse_public_key and settings.secrets.langfuse_secret_key
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)
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@dataclass
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class ToolSpan:
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"""Tracks a single tool call for tracing."""
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tool_call_id: str
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tool_name: str
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input: dict[str, Any]
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start_time: float = field(default_factory=time.perf_counter)
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output: str | None = None
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success: bool = True
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end_time: float | None = None
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@dataclass
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class GenerationSpan:
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"""Tracks an LLM generation (text output) for tracing."""
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text: str = ""
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start_time: float = field(default_factory=time.perf_counter)
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end_time: float | None = None
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tool_calls: list[ToolSpan] = field(default_factory=list)
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class TracedSession:
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"""Context manager for tracing a Claude Agent SDK session with Langfuse.
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Automatically creates a trace with:
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- Session-level metadata (user_id, session_id)
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- Generation spans for LLM outputs
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- Tool call spans with input/output
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- Token usage and cost (from ResultMessage)
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If Langfuse is not configured, all methods are no-ops.
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"""
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def __init__(
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self,
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session_id: str,
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user_id: str | None = None,
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system_prompt: str | None = None,
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model: str | None = None,
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):
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self.session_id = session_id
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self.user_id = user_id
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self.system_prompt = system_prompt
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self.model = model
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self.enabled = _is_langfuse_configured()
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# Internal state
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self._trace: Any = None
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self._langfuse: Any = None
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self._user_message: str | None = None
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self._generations: list[GenerationSpan] = []
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self._current_generation: GenerationSpan | None = None
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self._pending_tools: dict[str, ToolSpan] = {}
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self._start_time: float = 0
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async def __aenter__(self) -> TracedSession:
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"""Start the trace."""
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if not self.enabled:
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return self
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try:
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from langfuse import get_client
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self._langfuse = get_client()
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self._start_time = time.perf_counter()
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# Create the root trace
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self._trace = self._langfuse.trace(
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name="copilot-sdk-session",
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session_id=self.session_id,
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user_id=self.user_id,
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metadata={
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"sdk": "claude-agent-sdk",
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"has_system_prompt": bool(self.system_prompt),
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},
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)
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logger.debug(f"[Tracing] Started trace for session {self.session_id}")
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except Exception as e:
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logger.warning(f"[Tracing] Failed to start trace: {e}")
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self.enabled = False
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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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"""End the trace and flush to Langfuse."""
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if not self.enabled or not self._trace:
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return
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try:
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# Finalize any open generation
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self._finalize_current_generation()
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# Add generations as spans
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for gen in self._generations:
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self._trace.span(
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name="llm-generation",
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start_time=gen.start_time,
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end_time=gen.end_time or time.perf_counter(),
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output=gen.text[:1000] if gen.text else None, # Truncate
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metadata={"tool_calls": len(gen.tool_calls)},
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)
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# Add tool calls as nested spans
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for tool in gen.tool_calls:
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self._trace.span(
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name=f"tool:{tool.tool_name}",
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start_time=tool.start_time,
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end_time=tool.end_time or time.perf_counter(),
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input=tool.input,
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output=tool.output[:500] if tool.output else None,
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metadata={
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"tool_call_id": tool.tool_call_id,
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"success": tool.success,
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},
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)
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# Update trace with final status
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status = "error" if exc_type else "success"
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self._trace.update(
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output=self._generations[-1].text[:500] if self._generations else None,
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metadata={"status": status, "num_generations": len(self._generations)},
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)
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# Flush asynchronously (Langfuse handles this in background)
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logger.debug(
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f"[Tracing] Completed trace for session {self.session_id}, "
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f"{len(self._generations)} generations"
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)
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except Exception as e:
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logger.warning(f"[Tracing] Failed to finalize trace: {e}")
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def log_user_message(self, message: str) -> None:
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"""Log the user's input message."""
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if not self.enabled or not self._trace:
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return
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self._user_message = message
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try:
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self._trace.update(input=message[:1000])
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except Exception as e:
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logger.debug(f"[Tracing] Failed to log user message: {e}")
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def log_sdk_message(self, sdk_message: Message) -> None:
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"""Log an SDK message (automatically categorizes by type)."""
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if not self.enabled:
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return
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try:
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from claude_agent_sdk import (
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AssistantMessage,
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ResultMessage,
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TextBlock,
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ToolResultBlock,
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ToolUseBlock,
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UserMessage,
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)
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if isinstance(sdk_message, AssistantMessage):
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# Start a new generation if needed
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if self._current_generation is None:
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self._current_generation = GenerationSpan()
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self._generations.append(self._current_generation)
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for block in sdk_message.content:
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if isinstance(block, TextBlock) and block.text:
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self._current_generation.text += block.text
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elif isinstance(block, ToolUseBlock):
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tool_span = ToolSpan(
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tool_call_id=block.id,
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tool_name=block.name,
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input=block.input or {},
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)
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self._pending_tools[block.id] = tool_span
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if self._current_generation:
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self._current_generation.tool_calls.append(tool_span)
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elif isinstance(sdk_message, UserMessage):
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# UserMessage carries tool results
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content = sdk_message.content
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blocks = content if isinstance(content, list) else []
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for block in blocks:
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if isinstance(block, ToolResultBlock) and block.tool_use_id:
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tool_span = self._pending_tools.get(block.tool_use_id)
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if tool_span:
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tool_span.end_time = time.perf_counter()
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tool_span.success = not (block.is_error or False)
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tool_span.output = self._extract_tool_output(block.content)
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# After tool results, finalize current generation
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# (SDK will start a new AssistantMessage for continuation)
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self._finalize_current_generation()
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elif isinstance(sdk_message, ResultMessage):
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self._log_result(sdk_message)
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except Exception as e:
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logger.debug(f"[Tracing] Failed to log SDK message: {e}")
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def _log_result(self, result: ResultMessage) -> None:
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"""Log the final result with usage and cost."""
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if not self.enabled or not self._trace:
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return
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try:
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# Extract usage info
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usage = result.usage or {}
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metadata: dict[str, Any] = {
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"duration_ms": result.duration_ms,
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"duration_api_ms": result.duration_api_ms,
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"num_turns": result.num_turns,
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"is_error": result.is_error,
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}
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if result.total_cost_usd is not None:
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metadata["cost_usd"] = result.total_cost_usd
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if usage:
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metadata["usage"] = usage
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self._trace.update(metadata=metadata)
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# Log as a generation for proper Langfuse cost/usage tracking
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if usage or result.total_cost_usd:
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self._trace.generation(
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name="claude-sdk-completion",
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model=self.model or "claude-sonnet-4-20250514",
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usage=(
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{
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"input": usage.get("input_tokens", 0),
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"output": usage.get("output_tokens", 0),
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"total": usage.get("input_tokens", 0)
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+ usage.get("output_tokens", 0),
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}
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if usage
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else None
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),
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metadata={"cost_usd": result.total_cost_usd},
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)
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logger.debug(
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f"[Tracing] Logged result: {result.num_turns} turns, "
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f"${result.total_cost_usd:.4f} cost"
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if result.total_cost_usd
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else f"[Tracing] Logged result: {result.num_turns} turns"
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)
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except Exception as e:
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logger.debug(f"[Tracing] Failed to log result: {e}")
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def _finalize_current_generation(self) -> None:
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"""Mark the current generation as complete."""
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if self._current_generation:
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self._current_generation.end_time = time.perf_counter()
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self._current_generation = None
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@staticmethod
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def _extract_tool_output(content: str | list[dict[str, str]] | None) -> str:
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"""Extract string output from tool result content."""
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts = [
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item.get("text", "") for item in content if item.get("type") == "text"
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]
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return "".join(parts) if parts else str(content)
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return str(content) if content else ""
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def create_tracing_hooks(tracer: TracedSession) -> dict[str, Any]:
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"""Create SDK hooks for fine-grained Langfuse tracing.
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These hooks capture precise timing for tool executions and failures
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that may not be visible in the message stream.
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Designed to be merged with security hooks:
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hooks = {**security_hooks, **create_tracing_hooks(tracer)}
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Args:
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tracer: The active TracedSession instance
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Returns:
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Hooks configuration dict for ClaudeAgentOptions
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"""
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if not tracer.enabled:
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return {}
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try:
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from claude_agent_sdk import HookMatcher
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from claude_agent_sdk.types import HookContext, HookInput, SyncHookJSONOutput
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async def trace_pre_tool_use(
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input_data: HookInput,
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tool_use_id: str | None,
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context: HookContext,
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) -> SyncHookJSONOutput:
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"""Record tool start time for accurate duration tracking."""
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_ = context
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if not tool_use_id:
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return {}
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tool_name = str(input_data.get("tool_name", "unknown"))
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tool_input = input_data.get("tool_input", {})
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# Record start time in pending tools
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tracer._pending_tools[tool_use_id] = ToolSpan(
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tool_call_id=tool_use_id,
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tool_name=tool_name,
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input=tool_input if isinstance(tool_input, dict) else {},
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)
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return {}
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async def trace_post_tool_use(
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input_data: HookInput,
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tool_use_id: str | None,
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context: HookContext,
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) -> SyncHookJSONOutput:
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"""Record tool completion for duration calculation."""
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_ = context
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if tool_use_id and tool_use_id in tracer._pending_tools:
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tracer._pending_tools[tool_use_id].end_time = time.perf_counter()
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tracer._pending_tools[tool_use_id].success = True
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return {}
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async def trace_post_tool_failure(
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input_data: HookInput,
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tool_use_id: str | None,
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context: HookContext,
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) -> SyncHookJSONOutput:
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"""Record tool failures for error tracking."""
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_ = context
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if tool_use_id and tool_use_id in tracer._pending_tools:
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tracer._pending_tools[tool_use_id].end_time = time.perf_counter()
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tracer._pending_tools[tool_use_id].success = False
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error = input_data.get("error", "Unknown error")
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tracer._pending_tools[tool_use_id].output = f"ERROR: {error}"
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return {}
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return {
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"PreToolUse": [HookMatcher(matcher="*", hooks=[trace_pre_tool_use])],
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"PostToolUse": [HookMatcher(matcher="*", hooks=[trace_post_tool_use])],
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"PostToolUseFailure": [
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HookMatcher(matcher="*", hooks=[trace_post_tool_failure])
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],
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}
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except ImportError:
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logger.debug("[Tracing] SDK not available for hook-based tracing")
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return {}
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def merge_hooks(*hook_dicts: dict[str, Any]) -> dict[str, Any]:
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"""Merge multiple hook configurations into one.
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Combines hook matchers for the same event type, allowing both
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security and tracing hooks to coexist.
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Usage:
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combined = merge_hooks(security_hooks, tracing_hooks)
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"""
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result: dict[str, list[Any]] = {}
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for hook_dict in hook_dicts:
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for event_name, matchers in hook_dict.items():
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if event_name not in result:
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result[event_name] = []
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result[event_name].extend(matchers)
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return result
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