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Merged
merged 1 commit into from
Nov 4, 2025
Merged

Add better tracing for sync_provider #183

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6 changes: 3 additions & 3 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -24,23 +24,23 @@ dependencies = [
"pyyaml>=6.0.2,<7",
"jsonschema>=4.23.0,<5",
"jsonref>=1.1.0,<2",
"temporalio>=1.10.0,<2",
"temporalio>=1.18.2,<2",
"aiohttp>=3.10.10,<4",
"redis>=5.2.0,<6",
"litellm>=1.66.0,<2",
"kubernetes>=25.0.0,<29.0.0",
"jinja2>=3.1.3,<4",
"mcp[cli]>=1.4.1",
"scale-gp>=0.1.0a59",
"openai-agents==0.2.7", # 0.2.3 bug - https://github.com/openai/openai-agents-python/issues/1276
"openai-agents==0.4.2",
"tzlocal>=5.3.1",
"tzdata>=2025.2",
"pytest>=8.4.0",
"json_log_formatter>=1.1.1",
"pytest-asyncio>=1.0.0",
"scale-gp-beta==0.1.0a20",
"ipykernel>=6.29.5",
"openai==1.99.9", # anything higher than 1.99.9 breaks litellm - https://github.com/BerriAI/litellm/issues/13711
"openai>=2.2,<3", # Required by openai-agents 0.4.2; litellm now supports openai 2.x (issue #13711 resolved: https://github.com/BerriAI/litellm/issues/13711)
"cloudpickle>=3.1.1",
"datadog>=0.52.1",
"ddtrace>=3.13.0"
Expand Down
40 changes: 19 additions & 21 deletions requirements-dev.lock
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Original file line number Diff line number Diff line change
Expand Up @@ -113,9 +113,9 @@ httpx==0.27.2
# via mcp
# via openai
# via respx
httpx-aiohttp==0.1.9
# via scale-gp
# via scale-gp-beta
httpx-aiohttp==0.1.9
# via agentex-sdk
httpx-sse==0.4.1
# via mcp
Expand Down Expand Up @@ -191,11 +191,11 @@ nox==2023.4.22
oauthlib==3.3.1
# via kubernetes
# via requests-oauthlib
openai==1.99.9
openai==2.7.1
# via agentex-sdk
# via litellm
# via openai-agents
openai-agents==0.2.7
openai-agents==0.4.2
# via agentex-sdk
opentelemetry-api==1.37.0
# via ddtrace
Expand All @@ -219,20 +219,6 @@ prompt-toolkit==3.0.51
propcache==0.3.1
# via aiohttp
# via yarl
pydantic==2.11.9
# via agentex-sdk
# via agentex-sdk
# via fastapi
# via litellm
# via mcp
# via openai
# via openai-agents
# via pydantic-settings
# via python-on-whales
# via scale-gp
# via scale-gp-beta
pydantic-core==2.33.2
# via pydantic
protobuf==5.29.5
# via ddtrace
# via temporalio
Expand All @@ -247,6 +233,19 @@ pyasn1==0.6.1
# via rsa
pyasn1-modules==0.4.2
# via google-auth
pydantic==2.11.9
# via agentex-sdk
# via fastapi
# via litellm
# via mcp
# via openai
# via openai-agents
# via pydantic-settings
# via python-on-whales
# via scale-gp
# via scale-gp-beta
pydantic-core==2.33.2
# via pydantic
pydantic-settings==2.10.1
# via mcp
pygments==2.18.0
Expand Down Expand Up @@ -340,7 +339,7 @@ stack-data==0.6.3
starlette==0.46.2
# via fastapi
# via mcp
temporalio==1.15.0
temporalio==1.18.2
# via agentex-sdk
tiktoken==0.11.0
# via litellm
Expand Down Expand Up @@ -383,16 +382,15 @@ typing-extensions==4.12.2
# via pydantic
# via pydantic-core
# via pyright
# via typing-inspection
typing-inspection==0.4.1
# via pydantic
# via python-on-whales
# via referencing
# via scale-gp
# via scale-gp-beta
# via temporalio
# via typer
# via typing-inspection
typing-inspection==0.4.1
# via pydantic
# via pydantic-settings
tzdata==2025.2
# via agentex-sdk
Expand Down
39 changes: 19 additions & 20 deletions requirements.lock
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -99,12 +99,12 @@ httpcore==1.0.9
httpx==0.27.2
# via agentex-sdk
# via httpx-aiohttp
httpx-aiohttp==0.1.9
# via litellm
# via mcp
# via openai
# via scale-gp
# via scale-gp-beta
httpx-aiohttp==0.1.9
# via agentex-sdk
httpx-sse==0.4.1
# via mcp
Expand Down Expand Up @@ -174,11 +174,11 @@ nexus-rpc==1.1.0
oauthlib==3.3.1
# via kubernetes
# via requests-oauthlib
openai==1.99.9
openai==2.7.1
# via agentex-sdk
# via litellm
# via openai-agents
openai-agents==0.2.7
openai-agents==0.4.2
# via agentex-sdk
opentelemetry-api==1.37.0
# via ddtrace
Expand All @@ -200,19 +200,6 @@ prompt-toolkit==3.0.51
propcache==0.3.1
# via aiohttp
# via yarl
pydantic==2.11.9
# via agentex-sdk
# via fastapi
# via litellm
# via mcp
# via openai
# via openai-agents
# via pydantic-settings
# via python-on-whales
# via scale-gp
# via scale-gp-beta
pydantic-core==2.33.2
# via pydantic
protobuf==5.29.5
# via ddtrace
# via temporalio
Expand All @@ -227,6 +214,19 @@ pyasn1==0.6.1
# via rsa
pyasn1-modules==0.4.2
# via google-auth
pydantic==2.11.9
# via agentex-sdk
# via fastapi
# via litellm
# via mcp
# via openai
# via openai-agents
# via pydantic-settings
# via python-on-whales
# via scale-gp
# via scale-gp-beta
pydantic-core==2.33.2
# via pydantic
pydantic-settings==2.10.1
# via mcp
pygments==2.19.2
Expand Down Expand Up @@ -311,7 +311,7 @@ stack-data==0.6.3
starlette==0.46.2
# via fastapi
# via mcp
temporalio==1.15.0
temporalio==1.18.2
# via agentex-sdk
tiktoken==0.11.0
# via litellm
Expand Down Expand Up @@ -351,16 +351,15 @@ typing-extensions==4.12.2
# via opentelemetry-api
# via pydantic
# via pydantic-core
# via typing-inspection
typing-inspection==0.4.1
# via pydantic
# via python-on-whales
# via referencing
# via scale-gp
# via scale-gp-beta
# via temporalio
# via typer
# via typing-inspection
typing-inspection==0.4.1
# via pydantic
# via pydantic-settings
tzdata==2025.2
# via agentex-sdk
Expand Down
126 changes: 107 additions & 19 deletions src/agentex/lib/adk/providers/_modules/sync_provider.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@
from agents.models.openai_provider import OpenAIProvider

from agentex import AsyncAgentex
from agentex.lib.utils.logging import make_logger
from agentex.lib.core.tracing.tracer import AsyncTracer
from agentex.types.task_message_delta import TextDelta
from agentex.types.task_message_update import (
Expand All @@ -40,6 +41,44 @@
from agentex.types.tool_request_content import ToolRequestContent
from agentex.types.tool_response_content import ToolResponseContent

logger = make_logger(__name__)


def _serialize_item(item: Any) -> dict[str, Any]:
"""
Universal serializer for any item type from OpenAI Agents SDK.

Uses model_dump() for Pydantic models, otherwise extracts attributes manually.
Filters out internal Pydantic fields that can't be serialized.
"""
if hasattr(item, 'model_dump'):
# Pydantic model - use model_dump for proper serialization
try:
return item.model_dump(mode='json', exclude_unset=True)
except Exception:
# Fallback to dict conversion
return dict(item) if hasattr(item, '__iter__') else {}
else:
# Not a Pydantic model - extract attributes manually
item_dict = {}
for attr_name in dir(item):
if not attr_name.startswith('_') and attr_name not in ('model_fields', 'model_config', 'model_computed_fields'):
try:
attr_value = getattr(item, attr_name, None)
# Skip methods and None values
if attr_value is not None and not callable(attr_value):
# Convert to JSON-serializable format
if hasattr(attr_value, 'model_dump'):
item_dict[attr_name] = attr_value.model_dump()
elif isinstance(attr_value, (str, int, float, bool, list, dict)):
item_dict[attr_name] = attr_value
else:
item_dict[attr_name] = str(attr_value)
except Exception:
# Skip attributes that can't be accessed
pass
return item_dict


class SyncStreamingModel(Model):
"""Simple model wrapper that adds logging to stream_response and supports tracing."""
Expand Down Expand Up @@ -109,10 +148,38 @@ async def get_response(

response = await self.original_model.get_response(**kwargs)

# Set span output
if span:
# Set span output with structured data
if span and response:
new_items = []
final_output = None

# Extract final output text from response
response_final_output = getattr(response, 'final_output', None)
if response_final_output:
final_output = response_final_output

# Extract items from the response output
response_output = getattr(response, 'output', None)
if response_output:
output_items = response_output if isinstance(response_output, list) else [response_output]

for item in output_items:
item_dict = _serialize_item(item)
if item_dict:
new_items.append(item_dict)

# Extract final_output from message type if available
if item_dict.get('type') == 'message' and not final_output:
content = item_dict.get('content', [])
if content and isinstance(content, list):
for content_part in content:
if isinstance(content_part, dict) and 'text' in content_part:
final_output = content_part['text']
break

span.output = {
"response": str(response) if response else None,
"new_items": new_items,
"final_output": final_output,
}

return response
Expand Down Expand Up @@ -160,7 +227,9 @@ async def stream_response(
# Wrap the streaming in a tracing span if tracer is available
if self.tracer and self.trace_id:
trace = self.tracer.trace(self.trace_id)
async with trace.span(

# Manually start the span instead of using context manager
span = await trace.start_span(
parent_id=self.parent_span_id,
name="run_agent_streamed",
input={
Expand All @@ -172,7 +241,9 @@ async def stream_response(
"handoffs": [str(h) for h in handoffs] if handoffs else [],
"previous_response_id": previous_response_id,
},
) as span:
)

try:
# Get the stream from the original model
stream_kwargs = {
"system_instructions": system_instructions,
Expand All @@ -193,23 +264,40 @@ async def stream_response(
# Get the stream response from the original model and yield each event
stream_response = self.original_model.stream_response(**stream_kwargs)

# Pass through each event from the original stream
event_count = 0
final_output = None
# Pass through each event from the original stream and track items
new_items = []
final_response_text = ""

async for event in stream_response:
event_count += 1
# Track the final output if available
if hasattr(event, 'type') and event.type == 'raw_response_event':
if hasattr(event.data, 'output'):
final_output = event.data.output
event_type = getattr(event, 'type', 'no-type')

# Handle response.output_item.done events which contain completed items
if event_type == 'response.output_item.done':
item = getattr(event, 'item', None)
if item is not None:
item_dict = _serialize_item(item)
if item_dict:
new_items.append(item_dict)

# Update final_response_text from message type if available
if item_dict.get('type') == 'message':
content = item_dict.get('content', [])
if content and isinstance(content, list):
for content_part in content:
if isinstance(content_part, dict) and 'text' in content_part:
final_response_text = content_part['text']
break

yield event

# Set span output
if span:
span.output = {
"event_count": event_count,
"final_output": str(final_output) if final_output else None,
}
# Set span output with structured data including tool calls and final response
span.output = {
"new_items": new_items,
"final_output": final_response_text if final_response_text else None,
}
finally:
# End the span after all events have been yielded
await trace.end_span(span)
else:
# No tracing, just stream normally
# Get the stream from the original model
Expand Down