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Python: Fix AzureAIClient tool call bug for AG-UI use (#3148)

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* Fiz AzureAIClient tool call bug

* Address copilot feedback
This commit is contained in:
Evan Mattson
2026-01-10 03:53:15 +09:00
committed by GitHub
Unverified
parent d28ad2d7df
commit 6445b6b3a6
2 changed files with 67 additions and 15 deletions
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python/packages/ag-ui/agent_framework_ag_ui/_events.py
+1 -1
View File
@@ -160,10 +160,10 @@ class AgentFrameworkEventBridge:
logger.warning(f"FunctionCallContent missing name and call_id. args_length={args_length}")
tool_call_id = self._coalesce_tool_call_id(content)
# Only emit ToolCallStartEvent once per tool call (when it's a new tool call)
if content.name and tool_call_id != self.current_tool_call_id:
self.streaming_tool_args = ""
self.state_delta_count = 0
if content.name:
self.current_tool_call_id = tool_call_id
self.current_tool_call_name = content.name
python/packages/core/agent_framework/openai/_responses_client.py
+66 -14
View File
@@ -1,6 +1,14 @@
# Copyright (c) Microsoft. All rights reserved.
from collections.abc import AsyncIterable, Awaitable, Callable, Mapping, MutableMapping, MutableSequence, Sequence
from collections.abc import (
AsyncIterable,
Awaitable,
Callable,
Mapping,
MutableMapping,
MutableSequence,
Sequence,
)
from datetime import datetime, timezone
from itertools import chain
from typing import Any, TypeVar, cast
@@ -12,7 +20,9 @@ from openai.types.responses.parsed_response import (
ParsedResponse,
)
from openai.types.responses.response import Response as OpenAIResponse
from openai.types.responses.response_stream_event import ResponseStreamEvent as OpenAIResponseStreamEvent
from openai.types.responses.response_stream_event import (
ResponseStreamEvent as OpenAIResponseStreamEvent,
)
from openai.types.responses.response_usage import ResponseUsage
from openai.types.responses.tool_param import (
CodeInterpreter,
@@ -20,7 +30,9 @@ from openai.types.responses.tool_param import (
Mcp,
ToolParam,
)
from openai.types.responses.web_search_tool_param import UserLocation as WebSearchUserLocation
from openai.types.responses.web_search_tool_param import (
UserLocation as WebSearchUserLocation,
)
from openai.types.responses.web_search_tool_param import WebSearchToolParam
from pydantic import BaseModel, ValidationError
@@ -139,13 +151,17 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
if "text_format" not in run_options:
async for chunk in await client.responses.create(stream=True, **run_options):
yield self._parse_chunk_from_openai(
chunk, chat_options=chat_options, function_call_ids=function_call_ids
chunk,
chat_options=chat_options,
function_call_ids=function_call_ids,
)
return
async with client.responses.stream(**run_options) as response:
async for chunk in response:
yield self._parse_chunk_from_openai(
chunk, chat_options=chat_options, function_call_ids=function_call_ids
chunk,
chat_options=chat_options,
function_call_ids=function_call_ids,
)
except BadRequestError as ex:
if ex.code == "content_filter":
@@ -555,7 +571,10 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
if status := props.get("status"):
ret["status"] = status
if reasoning_text := props.get("reasoning_text"):
ret["content"] = {"type": "reasoning_text", "text": reasoning_text}
ret["content"] = {
"type": "reasoning_text",
"text": reasoning_text,
}
if encrypted_content := props.get("encrypted_content"):
ret["encrypted_content"] = encrypted_content
return ret
@@ -601,9 +620,17 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
return file_obj
return {}
case FunctionCallContent():
if not content.call_id:
logger.warning(f"FunctionCallContent missing call_id for function '{content.name}'")
return {}
# Use fc_id from additional_properties if available, otherwise fallback to call_id
fc_id = call_id_to_id.get(content.call_id, content.call_id)
# OpenAI Responses API requires IDs to start with `fc_`
if not fc_id.startswith("fc_"):
fc_id = f"fc_{fc_id}"
return {
"call_id": content.call_id,
"id": call_id_to_id[content.call_id],
"id": fc_id,
"type": "function_call",
"name": content.name,
"arguments": content.arguments,
@@ -739,11 +766,17 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
)
)
case _:
logger.debug("Unparsed annotation type: %s", annotation.type)
logger.debug(
"Unparsed annotation type: %s",
annotation.type,
)
contents.append(text_content)
case "refusal":
contents.append(
TextContent(text=message_content.refusal, raw_representation=message_content)
TextContent(
text=message_content.refusal,
raw_representation=message_content,
)
)
case "reasoning": # ResponseOutputReasoning
if hasattr(item, "content") and item.content:
@@ -769,7 +802,12 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
if item_outputs := getattr(item, "outputs", None):
for code_output in item_outputs:
if getattr(code_output, "type", None) == "logs":
outputs.append(TextContent(text=code_output.logs, raw_representation=code_output))
outputs.append(
TextContent(
text=code_output.logs,
raw_representation=code_output,
)
)
elif getattr(code_output, "type", None) == "image":
outputs.append(
UriContent(
@@ -1008,7 +1046,10 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
# McpApprovalRequest,
# ResponseCustomToolCall,
case "function_call":
function_call_ids[event.output_index] = (event_item.call_id, event_item.name)
function_call_ids[event.output_index] = (
event_item.call_id,
event_item.name,
)
case "mcp_approval_request":
contents.append(
FunctionApprovalRequestContent(
@@ -1061,7 +1102,10 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
for code_output in event_item.outputs:
if getattr(code_output, "type", None) == "logs":
outputs.append(
TextContent(text=cast(Any, code_output).logs, raw_representation=code_output)
TextContent(
text=cast(Any, code_output).logs,
raw_representation=code_output,
)
)
elif getattr(code_output, "type", None) == "image":
outputs.append(
@@ -1075,7 +1119,12 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
contents.append(
CodeInterpreterToolCallContent(
call_id=call_id,
inputs=[TextContent(text=event_item.code, raw_representation=event_item)],
inputs=[
TextContent(
text=event_item.code,
raw_representation=event_item,
)
],
raw_representation=event_item,
)
)
@@ -1113,7 +1162,10 @@ class OpenAIBaseResponsesClient(OpenAIBase, BaseChatClient):
call_id=call_id,
name=name,
arguments=event.delta,
additional_properties={"output_index": event.output_index, "fc_id": event.item_id},
additional_properties={
"output_index": event.output_index,
"fc_id": event.item_id,
},
raw_representation=event,
)
)