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Python: Upgrade hosting server dependency and add more type support (#5459)

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* Upgrade hosting server dependency and add more type support

* Comments
This commit is contained in:
Tao Chen
2026-04-24 00:27:17 -07:00
committed by GitHub
Unverified
parent 932ceddf95
commit 4adfd244ac
4 changed files with 1492 additions and 56 deletions
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python/packages/foundry_hosting/agent_framework_foundry_hosting/_responses.py
+287 -8
View File
@@ -28,13 +28,35 @@ from azure.ai.agentserver.responses import (
)
from azure.ai.agentserver.responses.hosting import ResponsesAgentServerHost
from azure.ai.agentserver.responses.models import (
ApplyPatchToolCallItemParam,
ApplyPatchToolCallOutputItemParam,
ComputerCallOutputItemParam,
ComputerScreenshotContent,
CreateResponse,
FunctionCallOutputItemParam,
FunctionShellAction,
FunctionShellCallItemParam,
FunctionShellCallOutputContent,
FunctionShellCallOutputExitOutcome,
FunctionShellCallOutputItemParam,
Item,
ItemCodeInterpreterToolCall,
ItemComputerToolCall,
ItemCustomToolCall,
ItemCustomToolCallOutput,
ItemFileSearchToolCall,
ItemFunctionToolCall,
ItemImageGenToolCall,
ItemLocalShellToolCall,
ItemLocalShellToolCallOutput,
ItemMcpApprovalRequest,
ItemMcpToolCall,
ItemMessage,
ItemOutputMessage,
ItemReasoningItem,
ItemWebSearchToolCall,
LocalEnvironmentResource,
MCPApprovalResponse,
MessageContent,
MessageContentInputFileContent,
MessageContentInputImageContent,
@@ -174,9 +196,11 @@ class ResponsesHostServer(ResponsesAgentServerHost):
context: ResponseContext,
) -> AsyncIterable[ResponseStreamEvent | dict[str, Any]]:
"""Handle the creation of a response for a regular (non-workflow) agent."""
input_text = await context.get_input_text()
input_items = await context.get_input_items()
input_messages = _items_to_messages(input_items)
history = await context.get_history()
messages: list[str | Content | Message] = [*_to_messages(history), input_text]
messages: list[str | Content | Message] = [*_output_items_to_messages(history), *input_messages]
chat_options, are_options_set = _to_chat_options(request)
@@ -243,7 +267,9 @@ class ResponsesHostServer(ResponsesAgentServerHost):
The sandbox may be deactivated after some period of inactivity, and only data managed
by the hosting infrastructure or files will be preserved upon deactivation.
"""
input_text = await context.get_input_text()
input_items = await context.get_input_items()
input_messages = _items_to_messages(input_items)
is_streaming_request = self._is_streaming_request(request)
_, are_options_set = _to_chat_options(request)
@@ -296,7 +322,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):
if not is_streaming_request:
# Run the agent in non-streaming mode
response = await self._agent.run(input_text, stream=False, checkpoint_storage=checkpoint_storage)
response = await self._agent.run(input_messages, stream=False, checkpoint_storage=checkpoint_storage)
for message in response.messages:
for content in message.contents:
@@ -308,7 +334,7 @@ class ResponsesHostServer(ResponsesAgentServerHost):
return
# Run the agent in streaming mode
response_stream = self._agent.run(input_text, stream=True, checkpoint_storage=checkpoint_storage)
response_stream = self._agent.run(input_messages, stream=True, checkpoint_storage=checkpoint_storage)
# Track the current active output item builder for streaming;
# lazily created on matching content, closed when a different type arrives.
@@ -532,7 +558,260 @@ def _to_chat_options(request: CreateResponse) -> tuple[ChatOptions, bool]:
# region Input Message Conversion
def _to_messages(history: Sequence[OutputItem]) -> list[Message]:
def _items_to_messages(input_items: Sequence[Item]) -> list[Message]:
"""Converts a sequence of input items to a list of Messages, one per item.
Args:
input_items: The input items to convert.
Returns:
A list of Messages, one per supported input item.
"""
messages: list[Message] = []
for item in input_items:
messages.append(_item_to_message(item))
return messages
def _item_to_message(item: Item) -> Message:
"""Converts an Item to a Message.
Args:
item: The Item to convert.
Returns:
The converted Message.
Raises:
ValueError: If the Item type is not supported.
"""
if item.type == "message":
msg = cast(ItemMessage, item)
if isinstance(msg.content, str):
return Message(role=msg.role, contents=[Content.from_text(msg.content)])
return Message(role=msg.role, contents=[_convert_message_content(part) for part in msg.content])
if item.type == "output_message":
output_msg = cast(ItemOutputMessage, item)
return Message(
role=output_msg.role, contents=[_convert_output_message_content(part) for part in output_msg.content]
)
if item.type == "function_call":
fc = cast(ItemFunctionToolCall, item)
return Message(
role="assistant",
contents=[Content.from_function_call(fc.call_id, fc.name, arguments=fc.arguments)],
)
if item.type == "function_call_output":
fco = cast(FunctionCallOutputItemParam, item)
output = fco.output if isinstance(fco.output, str) else str(fco.output)
return Message(
role="tool",
contents=[Content.from_function_result(fco.call_id, result=output)],
)
if item.type == "reasoning":
reasoning = cast(ItemReasoningItem, item)
reason_contents: list[Content] = []
if reasoning.summary:
for summary in reasoning.summary:
reason_contents.append(Content.from_text(summary.text))
return Message(role="assistant", contents=reason_contents)
if item.type == "mcp_call":
mcp = cast(ItemMcpToolCall, item)
return Message(
role="assistant",
contents=[
Content.from_mcp_server_tool_call(
mcp.id,
mcp.name,
server_name=mcp.server_label,
arguments=mcp.arguments,
)
],
)
if item.type == "mcp_approval_request":
mcp_req = cast(ItemMcpApprovalRequest, item)
mcp_call_content = Content.from_mcp_server_tool_call(
mcp_req.id,
mcp_req.name,
server_name=mcp_req.server_label,
arguments=mcp_req.arguments,
)
return Message(
role="assistant",
contents=[Content.from_function_approval_request(mcp_req.id, mcp_call_content)],
)
if item.type == "mcp_approval_response":
mcp_resp = cast(MCPApprovalResponse, item)
placeholder_content = Content.from_function_call(mcp_resp.approval_request_id, "mcp_approval")
return Message(
role="user",
contents=[
Content.from_function_approval_response(
mcp_resp.approve, mcp_resp.approval_request_id, placeholder_content
)
],
)
if item.type == "code_interpreter_call":
ci = cast(ItemCodeInterpreterToolCall, item)
return Message(
role="assistant",
contents=[Content.from_code_interpreter_tool_call(call_id=ci.id)],
)
if item.type == "image_generation_call":
ig = cast(ItemImageGenToolCall, item)
return Message(
role="assistant",
contents=[Content.from_image_generation_tool_call(image_id=ig.id)],
)
if item.type == "shell_call":
sc = cast(FunctionShellCallItemParam, item)
return Message(
role="assistant",
contents=[
Content.from_shell_tool_call(
call_id=sc.call_id,
commands=sc.action.commands,
status=str(sc.status),
)
],
)
if item.type == "shell_call_output":
sco = cast(FunctionShellCallOutputItemParam, item)
outputs = [
Content.from_shell_command_output(
stdout=out.stdout or "",
stderr=out.stderr or "",
exit_code=getattr(out.outcome, "exit_code", None) if hasattr(out, "outcome") else None,
)
for out in (sco.output or [])
]
return Message(
role="tool",
contents=[
Content.from_shell_tool_result(
call_id=sco.call_id,
outputs=outputs,
max_output_length=sco.max_output_length,
)
],
)
if item.type == "local_shell_call":
lsc = cast(ItemLocalShellToolCall, item)
commands = lsc.action.command if hasattr(lsc.action, "command") and lsc.action.command else []
return Message(
role="assistant",
contents=[
Content.from_shell_tool_call(
call_id=lsc.call_id,
commands=commands,
status=str(lsc.status),
)
],
)
if item.type == "local_shell_call_output":
lsco = cast(ItemLocalShellToolCallOutput, item)
return Message(
role="tool",
contents=[
Content.from_shell_tool_result(
call_id=lsco.id,
outputs=[Content.from_shell_command_output(stdout=lsco.output)],
)
],
)
if item.type == "file_search_call":
fs = cast(ItemFileSearchToolCall, item)
return Message(
role="assistant",
contents=[
Content.from_function_call(
fs.id,
"file_search",
arguments=json.dumps({"queries": fs.queries}),
)
],
)
if item.type == "web_search_call":
ws = cast(ItemWebSearchToolCall, item)
return Message(
role="assistant",
contents=[Content.from_function_call(ws.id, "web_search")],
)
if item.type == "computer_call":
cc = cast(ItemComputerToolCall, item)
return Message(
role="assistant",
contents=[
Content.from_function_call(
cc.call_id,
"computer_use",
arguments=str(cc.action),
)
],
)
if item.type == "computer_call_output":
cco = cast(ComputerCallOutputItemParam, item)
return Message(
role="tool",
contents=[Content.from_function_result(cco.call_id, result=str(cco.output))],
)
if item.type == "custom_tool_call":
ct = cast(ItemCustomToolCall, item)
return Message(
role="assistant",
contents=[Content.from_function_call(ct.call_id, ct.name, arguments=ct.input)],
)
if item.type == "custom_tool_call_output":
cto = cast(ItemCustomToolCallOutput, item)
output = cto.output if isinstance(cto.output, str) else str(cto.output)
return Message(
role="tool",
contents=[Content.from_function_result(cto.call_id, result=output)],
)
if item.type == "apply_patch_call":
ap = cast(ApplyPatchToolCallItemParam, item)
return Message(
role="assistant",
contents=[
Content.from_function_call(
ap.call_id,
"apply_patch",
arguments=str(ap.operation),
)
],
)
if item.type == "apply_patch_call_output":
apo = cast(ApplyPatchToolCallOutputItemParam, item)
return Message(
role="tool",
contents=[Content.from_function_result(apo.call_id, result=apo.output or "")],
)
raise ValueError(f"Unsupported Item type: {item.type}")
def _output_items_to_messages(history: Sequence[OutputItem]) -> list[Message]:
"""Converts a sequence of OutputItem objects to a list of Message objects.
Args:
@@ -543,11 +822,11 @@ def _to_messages(history: Sequence[OutputItem]) -> list[Message]:
"""
messages: list[Message] = []
for item in history:
messages.append(_to_message(item))
messages.append(_output_item_to_message(item))
return messages
def _to_message(item: OutputItem) -> Message:
def _output_item_to_message(item: OutputItem) -> Message:
"""Converts an OutputItem to a Message.
Args:
python/packages/foundry_hosting/pyproject.toml
+4 -4
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@@ -4,7 +4,7 @@ description = "Foundry Hosting integration for Microsoft Agent Framework."
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
readme = "README.md"
requires-python = ">=3.10"
version = "1.0.0a260423"
version = "1.0.0a260424"
license-files = ["LICENSE"]
urls.homepage = "https://aka.ms/agent-framework"
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -24,9 +24,9 @@ classifiers = [
]
dependencies = [
"agent-framework-core>=1.1.1,<2",
"azure-ai-agentserver-core==2.0.0b2",
"azure-ai-agentserver-responses==1.0.0b4",
"azure-ai-agentserver-invocations==1.0.0b2",
"azure-ai-agentserver-core==2.0.0b3",
"azure-ai-agentserver-responses==1.0.0b5",
"azure-ai-agentserver-invocations==1.0.0b3",
]
[tool.uv]
python/packages/foundry_hosting/tests/test_responses.py
+1188 -31
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