mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-07-29 15:23:51 +00:00
enhance the tracing span utility to make a context manager
This commit is contained in:
Ashwin Bharambe
parent
484dc2e4f5
commit
5d75c2437b
2 changed files with 96 additions and 77 deletions
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@ -26,6 +26,7 @@ from llama_stack.apis.memory import * # noqa: F403
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from llama_stack.apis.safety import * # noqa: F403
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from llama_stack.providers.utils.kvstore import KVStore
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from llama_stack.providers.utils.telemetry import tracing
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from .persistence import AgentPersistence
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from .rag.context_retriever import generate_rag_query
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@ -138,6 +139,7 @@ class ChatAgent(ShieldRunnerMixin):
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async def create_session(self, name: str) -> str:
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return await self.storage.create_session(name)
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@tracing.span("create_and_execute_turn")
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async def create_and_execute_turn(
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self, request: AgentTurnCreateRequest
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) -> AsyncGenerator:
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@ -266,6 +268,7 @@ class ChatAgent(ShieldRunnerMixin):
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yield final_response
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@tracing.span("run_shields")
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async def run_multiple_shields_wrapper(
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self,
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turn_id: str,
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@ -348,9 +351,10 @@ class ChatAgent(ShieldRunnerMixin):
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# TODO: find older context from the session and either replace it
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# or append with a sliding window. this is really a very simplistic implementation
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rag_context, bank_ids = await self._retrieve_context(
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session_id, input_messages, attachments
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)
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with tracing.span("retrieve_rag_context"):
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rag_context, bank_ids = await self._retrieve_context(
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session_id, input_messages, attachments
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)
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step_id = str(uuid.uuid4())
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yield AgentTurnResponseStreamChunk(
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@ -403,55 +407,57 @@ class ChatAgent(ShieldRunnerMixin):
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tool_calls = []
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content = ""
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stop_reason = None
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async for chunk in self.inference_api.chat_completion(
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self.agent_config.model,
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input_messages,
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tools=self._get_tools(),
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tool_prompt_format=self.agent_config.tool_prompt_format,
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stream=True,
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sampling_params=sampling_params,
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):
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event = chunk.event
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if event.event_type == ChatCompletionResponseEventType.start:
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continue
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elif event.event_type == ChatCompletionResponseEventType.complete:
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stop_reason = StopReason.end_of_turn
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continue
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delta = event.delta
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if isinstance(delta, ToolCallDelta):
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if delta.parse_status == ToolCallParseStatus.success:
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tool_calls.append(delta.content)
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with tracing.span("inference"):
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async for chunk in self.inference_api.chat_completion(
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self.agent_config.model,
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input_messages,
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tools=self._get_tools(),
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tool_prompt_format=self.agent_config.tool_prompt_format,
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stream=True,
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sampling_params=sampling_params,
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):
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event = chunk.event
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if event.event_type == ChatCompletionResponseEventType.start:
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continue
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elif event.event_type == ChatCompletionResponseEventType.complete:
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stop_reason = StopReason.end_of_turn
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continue
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if stream:
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.inference.value,
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step_id=step_id,
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model_response_text_delta="",
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tool_call_delta=delta,
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delta = event.delta
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if isinstance(delta, ToolCallDelta):
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if delta.parse_status == ToolCallParseStatus.success:
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tool_calls.append(delta.content)
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if stream:
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.inference.value,
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step_id=step_id,
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model_response_text_delta="",
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tool_call_delta=delta,
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)
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)
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)
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)
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elif isinstance(delta, str):
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content += delta
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if stream and event.stop_reason is None:
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.inference.value,
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step_id=step_id,
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model_response_text_delta=event.delta,
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elif isinstance(delta, str):
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content += delta
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if stream and event.stop_reason is None:
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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payload=AgentTurnResponseStepProgressPayload(
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step_type=StepType.inference.value,
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step_id=step_id,
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model_response_text_delta=event.delta,
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)
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)
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)
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)
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else:
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raise ValueError(f"Unexpected delta type {type(delta)}")
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else:
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raise ValueError(f"Unexpected delta type {type(delta)}")
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if event.stop_reason is not None:
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stop_reason = event.stop_reason
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if event.stop_reason is not None:
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stop_reason = event.stop_reason
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stop_reason = stop_reason or StopReason.out_of_tokens
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message = CompletionMessage(
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@ -528,14 +534,15 @@ class ChatAgent(ShieldRunnerMixin):
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)
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)
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result_messages = await execute_tool_call_maybe(
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self.tools_dict,
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[message],
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)
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assert (
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len(result_messages) == 1
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), "Currently not supporting multiple messages"
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result_message = result_messages[0]
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with tracing.span("tool_execution"):
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result_messages = await execute_tool_call_maybe(
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self.tools_dict,
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[message],
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)
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assert (
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len(result_messages) == 1
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), "Currently not supporting multiple messages"
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result_message = result_messages[0]
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yield AgentTurnResponseStreamChunk(
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event=AgentTurnResponseEvent(
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@ -669,7 +676,8 @@ class ChatAgent(ShieldRunnerMixin):
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)
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for a in attachments
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]
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await self.memory_api.insert_documents(bank_id, documents)
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with tracing.span("insert_documents"):
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await self.memory_api.insert_documents(bank_id, documents)
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else:
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session_info = await self.storage.get_session_info(session_id)
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if session_info.memory_bank_id:
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@ -12,7 +12,7 @@ import threading
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import uuid
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from datetime import datetime
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from functools import wraps
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from typing import Any, Dict, List
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from typing import Any, Callable, Dict, List
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from llama_stack.apis.telemetry import * # noqa: F403
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@ -196,33 +196,42 @@ class TelemetryHandler(logging.Handler):
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pass
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def span(name: str, attributes: Dict[str, Any] = None):
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def decorator(func):
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class SpanContextManager:
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def __init__(self, name: str, attributes: Dict[str, Any] = None):
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self.name = name
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self.attributes = attributes
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def __enter__(self):
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.push_span(self.name, self.attributes)
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return self
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def __exit__(self, exc_type, exc_value, traceback):
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.pop_span()
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async def __aenter__(self):
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return self.__enter__()
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async def __aexit__(self, exc_type, exc_value, traceback):
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self.__exit__(exc_type, exc_value, traceback)
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def __call__(self, func: Callable):
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@wraps(func)
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def sync_wrapper(*args, **kwargs):
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try:
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.push_span(name, attributes)
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result = func(*args, **kwargs)
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finally:
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context.pop_span()
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return result
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print("sync wrapper")
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with self:
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return func(*args, **kwargs)
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@wraps(func)
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async def async_wrapper(*args, **kwargs):
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try:
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global CURRENT_TRACE_CONTEXT
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context = CURRENT_TRACE_CONTEXT
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if context:
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context.push_span(name, attributes)
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result = await func(*args, **kwargs)
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finally:
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context.pop_span()
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return result
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print("async wrapper")
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async with self:
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return await func(*args, **kwargs)
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@wraps(func)
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def wrapper(*args, **kwargs):
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@ -233,4 +242,6 @@ def span(name: str, attributes: Dict[str, Any] = None):
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return wrapper
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return decorator
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def span(name: str, attributes: Dict[str, Any] = None):
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return SpanContextManager(name, attributes)
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