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StrandsAgentsProcessor: more formatting fixes

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This commit is contained in:
Aleix Conchillo Flaqué
2025-09-23 11:03:43 -07:00
parent 3fc5214c15
commit 17ea0afa6f
1 changed files with 21 additions and 16 deletions
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31
src/pipecat/processors/frameworks/strands_agents.py
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@@ -84,11 +84,11 @@ class StrandsAgentsProcessor(FrameProcessor):
text: The user input text to process through the agent or graph. text: The user input text to process through the agent or graph.
""" """
logger.debug(f"Invoking Strands agent with: {text}") logger.debug(f"Invoking Strands agent with: {text}")
ttfb_tracking = True
try: try:
await self.push_frame(LLMFullResponseStartFrame()) await self.push_frame(LLMFullResponseStartFrame())
await self.start_processing_metrics() await self.start_processing_metrics()
await self.start_ttfb_metrics() await self.start_ttfb_metrics()
ttfb_tracking = True
if self.graph: if self.graph:
# Graph does not stream; await full result then emit assistant text # Graph does not stream; await full result then emit assistant text
@@ -108,9 +108,9 @@ class StrandsAgentsProcessor(FrameProcessor):
await self.push_frame(LLMTextFrame(str(block["text"]))) await self.push_frame(LLMTextFrame(str(block["text"])))
# Update usage metrics # Update usage metrics
await self._report_usage_metrics( await self._report_usage_metrics(
agent_result.metrics.accumulated_usage.get('inputTokens', 0), agent_result.metrics.accumulated_usage.get("inputTokens", 0),
agent_result.metrics.accumulated_usage.get('outputTokens', 0), agent_result.metrics.accumulated_usage.get("outputTokens", 0),
agent_result.metrics.accumulated_usage.get('totalTokens', 0) agent_result.metrics.accumulated_usage.get("totalTokens", 0),
) )
except Exception as parse_err: except Exception as parse_err:
logger.warning(f"Failed to extract messages from GraphResult: {parse_err}") logger.warning(f"Failed to extract messages from GraphResult: {parse_err}")
@@ -125,10 +125,18 @@ class StrandsAgentsProcessor(FrameProcessor):
ttfb_tracking = False ttfb_tracking = False
# Update usage metrics # Update usage metrics
if isinstance(event, dict) and "event" in event and "metadata" in event['event']: if (
if 'usage' in event['event']['metadata']: isinstance(event, dict)
usage = event['event']['metadata']['usage'] and "event" in event
await self._report_usage_metrics(usage.get('inputTokens', 0), usage.get('outputTokens', 0), usage.get('totalTokens', 0)) and "metadata" in event["event"]
):
if "usage" in event["event"]["metadata"]:
usage = event["event"]["metadata"]["usage"]
await self._report_usage_metrics(
usage.get("inputTokens", 0),
usage.get("outputTokens", 0),
usage.get("totalTokens", 0),
)
except GeneratorExit: except GeneratorExit:
logger.warning(f"{self} generator was closed prematurely") logger.warning(f"{self} generator was closed prematurely")
except Exception as e: except Exception as e:
@@ -149,14 +157,11 @@ class StrandsAgentsProcessor(FrameProcessor):
return True return True
async def _report_usage_metrics( async def _report_usage_metrics(
self, self, prompt_tokens: int, completion_tokens: int, total_tokens: int
prompt_tokens: int,
completion_tokens: int,
total_tokens: int
): ):
tokens = LLMTokenUsage( tokens = LLMTokenUsage(
prompt_tokens=prompt_tokens, prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens, completion_tokens=completion_tokens,
total_tokens=total_tokens total_tokens=total_tokens,
) )
await self.start_llm_usage_metrics(tokens) await self.start_llm_usage_metrics(tokens)