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Merged
Roopan-Microsoft merged 1 commit into from
Jun 10, 2026
Merged

Revert "fix: enhance message handling and context management in orchestrators" #278

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139 changes: 40 additions & 99 deletions src/processor/src/libs/agent_framework/agent_builder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,6 @@
AgentMiddleware,
BaseChatClient,
ChatMiddleware,
ChatOptions,
ContextProvider,
FunctionTool,
ToolMode,
Expand Down Expand Up @@ -442,61 +441,32 @@ def build(self) -> Agent:
async with agent:
response = await agent.run("Hello!")
"""
# Build default_options from model parameters
options_dict: dict[str, Any] = {}
if self._frequency_penalty is not None:
options_dict["frequency_penalty"] = self._frequency_penalty
if self._logit_bias is not None:
options_dict["logit_bias"] = self._logit_bias
if self._max_tokens is not None:
options_dict["max_tokens"] = self._max_tokens
if self._metadata is not None:
options_dict["metadata"] = self._metadata
if self._model_id is not None:
options_dict["model"] = self._model_id
if self._presence_penalty is not None:
options_dict["presence_penalty"] = self._presence_penalty
if self._response_format is not None:
options_dict["response_format"] = self._response_format
if self._seed is not None:
options_dict["seed"] = self._seed
if self._stop is not None:
options_dict["stop"] = self._stop
if self._store is not None:
options_dict["store"] = self._store
if self._temperature is not None:
options_dict["temperature"] = self._temperature
if self._tool_choice is not None:
options_dict["tool_choice"] = self._tool_choice
if self._top_p is not None:
options_dict["top_p"] = self._top_p
if self._user is not None:
options_dict["user"] = self._user
if self._additional_chat_options:
options_dict.update(self._additional_chat_options)

default_options = ChatOptions(**options_dict) if options_dict else None

# Agent expects context_providers as a Sequence; wrap single instance in a list
ctx_providers = self._context_providers
if ctx_providers is not None and not isinstance(ctx_providers, list):
ctx_providers = [ctx_providers]

# Agent expects middleware as a Sequence; wrap single instance in a list
mw = self._middleware
if mw is not None and not isinstance(mw, list):
mw = [mw]

return Agent(
self._chat_client,
chat_client=self._chat_client,
instructions=self._instructions,
id=self._id,
name=self._name,
description=self._description,
chat_message_store_factory=self._chat_message_store_factory,
conversation_id=self._conversation_id,
context_providers=self._context_providers,
middleware=self._middleware,
frequency_penalty=self._frequency_penalty,
logit_bias=self._logit_bias,
max_tokens=self._max_tokens,
metadata=self._metadata,
model_id=self._model_id,
presence_penalty=self._presence_penalty,
response_format=self._response_format,
seed=self._seed,
stop=self._stop,
store=self._store,
temperature=self._temperature,
tool_choice=self._tool_choice,
tools=self._tools,
default_options=default_options,
context_providers=ctx_providers,
middleware=mw,
top_p=self._top_p,
user=self._user,
additional_chat_options=self._additional_chat_options,
**self._kwargs,
)

Expand Down Expand Up @@ -785,60 +755,31 @@ def create_agent(
``async with`` to ensure proper initialization and cleanup via the Agent's
async context manager protocol.
"""
# Build default_options from model parameters
opts: dict[str, Any] = {}
if frequency_penalty is not None:
opts["frequency_penalty"] = frequency_penalty
if logit_bias is not None:
opts["logit_bias"] = logit_bias
if max_tokens is not None:
opts["max_tokens"] = max_tokens
if metadata is not None:
opts["metadata"] = metadata
if model_id is not None:
opts["model"] = model_id
if presence_penalty is not None:
opts["presence_penalty"] = presence_penalty
if response_format is not None:
opts["response_format"] = response_format
if seed is not None:
opts["seed"] = seed
if stop is not None:
opts["stop"] = stop
if store is not None:
opts["store"] = store
if temperature is not None:
opts["temperature"] = temperature
if tool_choice is not None:
opts["tool_choice"] = tool_choice
if top_p is not None:
opts["top_p"] = top_p
if user is not None:
opts["user"] = user
if additional_chat_options:
opts.update(additional_chat_options)

default_options = ChatOptions(**opts) if opts else None

# Agent expects context_providers as a Sequence; wrap single instance in a list
ctx_providers = context_providers
if ctx_providers is not None and not isinstance(ctx_providers, list):
ctx_providers = [ctx_providers]

# Agent expects middleware as a Sequence; wrap single instance in a list
mw = middleware
if mw is not None and not isinstance(mw, list):
mw = [mw]

return Agent(
chat_client,
chat_client=chat_client,
instructions=instructions,
id=id,
name=name,
description=description,
chat_message_store_factory=chat_message_store_factory,
conversation_id=conversation_id,
context_providers=context_providers,
middleware=middleware,
frequency_penalty=frequency_penalty,
logit_bias=logit_bias,
max_tokens=max_tokens,
metadata=metadata,
model_id=model_id,
presence_penalty=presence_penalty,
response_format=response_format,
seed=seed,
stop=stop,
store=store,
temperature=temperature,
tool_choice=tool_choice,
tools=tools,
default_options=default_options,
context_providers=ctx_providers,
middleware=mw,
top_p=top_p,
user=user,
additional_chat_options=additional_chat_options,
**kwargs,
)
10 changes: 5 additions & 5 deletions src/processor/src/libs/agent_framework/agent_info.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,15 +5,13 @@

from typing import Any, Callable, MutableMapping, Sequence

from agent_framework import FunctionTool, MCPStdioTool, MCPStreamableHTTPTool
from agent_framework import FunctionTool
from jinja2 import Template
from openai import BaseModel
Comment thread
Roopan-Microsoft marked this conversation as resolved.
from pydantic import Field

from .agent_framework_helper import AgentFrameworkHelper, ClientType

ToolType = FunctionTool | MCPStreamableHTTPTool | MCPStdioTool | Callable[..., Any] | MutableMapping[str, Any]


class AgentInfo(BaseModel):
agent_name: str
Expand All @@ -23,8 +21,10 @@ class AgentInfo(BaseModel):
agent_instruction: str | None = Field(default=None)
agent_framework_helper: AgentFrameworkHelper | None = Field(default=None)
tools: (
ToolType
| Sequence[ToolType]
FunctionTool
| Callable[..., Any]
| MutableMapping[str, Any]
| Sequence[FunctionTool | Callable[..., Any] | MutableMapping[str, Any]]
| None
) = Field(default=None)

Expand Down
133 changes: 1 addition & 132 deletions src/processor/src/libs/agent_framework/azure_openai_response_retry.py
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Original file line number Diff line number Diff line change
Expand Up @@ -325,117 +325,6 @@ def _bool(name: str, default: bool) -> bool:
)


def _get_content_items(message: Any) -> list[Any]:
"""Return the list of content items from a message, or empty list."""
contents = None
if isinstance(message, dict):
contents = message.get("contents") or message.get("content")
else:
contents = getattr(message, "contents", None) or getattr(message, "content", None)
if isinstance(contents, list):
return contents
return []


def _remove_orphan_tool_messages(messages: list[Any]) -> list[Any]:
"""Remove messages with orphaned function_call or function_result items.

The Responses API requires every function_call in the input to have a
corresponding function_call_output (function_result). If context trimming
breaks these pairs, the API rejects the request.
"""
# Collect call_ids for function_calls and function_results
call_ids_with_call: set[str] = set()
call_ids_with_result: set[str] = set()

for m in messages:
for item in _get_content_items(m):
item_type = None
call_id = None
if isinstance(item, dict):
item_type = item.get("type")
call_id = item.get("call_id")
else:
item_type = getattr(item, "type", None)
call_id = getattr(item, "call_id", None)
if not call_id:
continue
if item_type == "function_call":
call_ids_with_call.add(call_id)
elif item_type == "function_result":
call_ids_with_result.add(call_id)

# Identify orphaned call_ids
orphaned_calls = call_ids_with_call - call_ids_with_result
orphaned_results = call_ids_with_result - call_ids_with_call

if not orphaned_calls and not orphaned_results:
return messages

logger.warning(
"[AOAI_CTX_TRIM] removing orphaned tool messages: %d orphaned calls, %d orphaned results",
len(orphaned_calls),
len(orphaned_results),
)

# Remove messages that ONLY contain orphaned tool items
cleaned: list[Any] = []
for m in messages:
items = _get_content_items(m)
if not items:
cleaned.append(m)
continue

has_orphan = False
has_non_orphan = False
for item in items:
item_type = None
call_id = None
if isinstance(item, dict):
item_type = item.get("type")
call_id = item.get("call_id")
else:
item_type = getattr(item, "type", None)
call_id = getattr(item, "call_id", None)
if call_id and item_type == "function_call" and call_id in orphaned_calls:
has_orphan = True
elif call_id and item_type == "function_result" and call_id in orphaned_results:
has_orphan = True
else:
has_non_orphan = True

if has_orphan and not has_non_orphan:
# Message contains ONLY orphaned tool items — drop it entirely
continue
elif has_orphan and has_non_orphan:
# Message has both orphan and non-orphan content.
# Drop orphaned items if possible, keeping the rest.
if isinstance(items, list) and not isinstance(m, dict):
# Filter out orphaned content items from the message
filtered = []
for item in items:
item_type = getattr(item, "type", None)
call_id = getattr(item, "call_id", None)
if call_id and item_type == "function_call" and call_id in orphaned_calls:
continue
if call_id and item_type == "function_result" and call_id in orphaned_results:
continue
filtered.append(item)
if filtered:
try:
m.contents = filtered
except Exception:
pass
cleaned.append(m)
# else: drop message entirely if no content remains
else:
cleaned.append(m)
else:
cleaned.append(m)

return cleaned


def _trim_messages(
messages: MutableSequence[Any], *, cfg: ContextTrimConfig
) -> list[Any]:
Expand Down Expand Up @@ -525,11 +414,6 @@ def _total_chars(msgs: list[Any]) -> int:
break
combined.pop(drop_index)

# Phase final: Remove orphaned tool call / tool result messages.
# The Responses API requires every function_call to have a matching
# function_call_output. Trimming may break these pairs.
combined = _remove_orphan_tool_messages(combined)

return combined


Expand Down Expand Up @@ -655,27 +539,12 @@ def __init__(
# Map legacy params to OpenAIChatClient params
if deployment_name and "model" not in kwargs:
kwargs["model"] = deployment_name
if endpoint and not kwargs.get("azure_endpoint"):
if endpoint and "azure_endpoint" not in kwargs:
kwargs["azure_endpoint"] = endpoint
if ad_token_provider and kwargs.get("credential") is None:
kwargs["credential"] = ad_token_provider

# Remove None-valued keys that would conflict with env-based settings
for k in list(kwargs):
if kwargs[k] is None:
del kwargs[k]

super().__init__(*args, **kwargs)

# OpenAIChatClient appends /v1/ to azure_endpoint but Azure AI Foundry
# endpoints expect /openai/responses (without /v1/). Fix the base URL.
if hasattr(self, "client") and self.client is not None:
base = str(self.client.base_url)
if "/openai/v1/" in base:
import httpx
corrected = base.replace("/openai/v1/", "/openai/")
self.client._base_url = httpx.URL(corrected)

self._retry_config = retry_config or RateLimitRetryConfig.from_env()
self._context_trim_config = ContextTrimConfig.from_env()

Expand Down
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