From bb7b5b9ccb7fe3a9d97048e7ff25418562f998c4 Mon Sep 17 00:00:00 2001 From: Denis Shulyaka Date: Sun, 16 Mar 2025 20:18:18 +0300 Subject: [PATCH] OpenAI Responses API (#140713) --- .../openai_conversation/__init__.py | 99 ++-- .../openai_conversation/conversation.py | 200 +++---- .../openai_conversation/test_conversation.py | 488 ++++++++++-------- .../openai_conversation/test_init.py | 109 ++-- 4 files changed, 463 insertions(+), 433 deletions(-) diff --git a/homeassistant/components/openai_conversation/__init__.py b/homeassistant/components/openai_conversation/__init__.py index d7fc5205f17..fcf6ab298dc 100644 --- a/homeassistant/components/openai_conversation/__init__.py +++ b/homeassistant/components/openai_conversation/__init__.py @@ -7,21 +7,15 @@ from mimetypes import guess_file_type from pathlib import Path import openai -from openai.types.chat.chat_completion import ChatCompletion -from openai.types.chat.chat_completion_content_part_image_param import ( - ChatCompletionContentPartImageParam, - ImageURL, -) -from openai.types.chat.chat_completion_content_part_param import ( - ChatCompletionContentPartParam, -) -from openai.types.chat.chat_completion_content_part_text_param import ( - ChatCompletionContentPartTextParam, -) -from openai.types.chat.chat_completion_user_message_param import ( - ChatCompletionUserMessageParam, -) from openai.types.images_response import ImagesResponse +from openai.types.responses import ( + EasyInputMessageParam, + Response, + ResponseInputImageParam, + ResponseInputMessageContentListParam, + ResponseInputParam, + ResponseInputTextParam, +) import voluptuous as vol from homeassistant.config_entries import ConfigEntry @@ -44,10 +38,18 @@ from homeassistant.helpers.typing import ConfigType from .const import ( CONF_CHAT_MODEL, CONF_FILENAMES, + CONF_MAX_TOKENS, CONF_PROMPT, + CONF_REASONING_EFFORT, + CONF_TEMPERATURE, + CONF_TOP_P, DOMAIN, LOGGER, RECOMMENDED_CHAT_MODEL, + RECOMMENDED_MAX_TOKENS, + RECOMMENDED_REASONING_EFFORT, + RECOMMENDED_TEMPERATURE, + RECOMMENDED_TOP_P, ) SERVICE_GENERATE_IMAGE = "generate_image" @@ -112,17 +114,14 @@ async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool: translation_placeholders={"config_entry": entry_id}, ) - model: str = entry.data.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL) + model: str = entry.options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL) client: openai.AsyncClient = entry.runtime_data - prompt_parts: list[ChatCompletionContentPartParam] = [ - ChatCompletionContentPartTextParam( - type="text", - text=call.data[CONF_PROMPT], - ) + content: ResponseInputMessageContentListParam = [ + ResponseInputTextParam(type="input_text", text=call.data[CONF_PROMPT]) ] - def append_files_to_prompt() -> None: + def append_files_to_content() -> None: for filename in call.data[CONF_FILENAMES]: if not hass.config.is_allowed_path(filename): raise HomeAssistantError( @@ -138,46 +137,52 @@ async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool: "Only images are supported by the OpenAI API," f"`{filename}` is not an image file" ) - prompt_parts.append( - ChatCompletionContentPartImageParam( - type="image_url", - image_url=ImageURL( - url=f"data:{mime_type};base64,{base64_file}" - ), + content.append( + ResponseInputImageParam( + type="input_image", + file_id=filename, + image_url=f"data:{mime_type};base64,{base64_file}", + detail="auto", ) ) if CONF_FILENAMES in call.data: - await hass.async_add_executor_job(append_files_to_prompt) + await hass.async_add_executor_job(append_files_to_content) - messages: list[ChatCompletionUserMessageParam] = [ - ChatCompletionUserMessageParam( - role="user", - content=prompt_parts, - ) + messages: ResponseInputParam = [ + EasyInputMessageParam(type="message", role="user", content=content) ] try: - response: ChatCompletion = await client.chat.completions.create( - model=model, - messages=messages, - n=1, - response_format={ - "type": "json_object", - }, - ) + model_args = { + "model": model, + "input": messages, + "max_output_tokens": entry.options.get( + CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS + ), + "top_p": entry.options.get(CONF_TOP_P, RECOMMENDED_TOP_P), + "temperature": entry.options.get( + CONF_TEMPERATURE, RECOMMENDED_TEMPERATURE + ), + "user": call.context.user_id, + "store": False, + } + + if model.startswith("o"): + model_args["reasoning"] = { + "effort": entry.options.get( + CONF_REASONING_EFFORT, RECOMMENDED_REASONING_EFFORT + ) + } + + response: Response = await client.responses.create(**model_args) except openai.OpenAIError as err: raise HomeAssistantError(f"Error generating content: {err}") from err except FileNotFoundError as err: raise HomeAssistantError(f"Error generating content: {err}") from err - response_text: str = "" - for response_choice in response.choices: - if response_choice.message.content is not None: - response_text += response_choice.message.content.strip() - - return {"text": response_text} + return {"text": response.output_text} hass.services.async_register( DOMAIN, diff --git a/homeassistant/components/openai_conversation/conversation.py b/homeassistant/components/openai_conversation/conversation.py index d910cf54471..7a8830ffd95 100644 --- a/homeassistant/components/openai_conversation/conversation.py +++ b/homeassistant/components/openai_conversation/conversation.py @@ -2,21 +2,25 @@ from collections.abc import AsyncGenerator, Callable import json -from typing import Any, Literal, cast +from typing import Any, Literal import openai from openai._streaming import AsyncStream -from openai._types import NOT_GIVEN -from openai.types.chat import ( - ChatCompletionAssistantMessageParam, - ChatCompletionChunk, - ChatCompletionMessageParam, - ChatCompletionMessageToolCallParam, - ChatCompletionToolMessageParam, - ChatCompletionToolParam, +from openai.types.responses import ( + EasyInputMessageParam, + FunctionToolParam, + ResponseFunctionCallArgumentsDeltaEvent, + ResponseFunctionCallArgumentsDoneEvent, + ResponseFunctionToolCall, + ResponseFunctionToolCallParam, + ResponseInputParam, + ResponseOutputItemAddedEvent, + ResponseOutputMessage, + ResponseStreamEvent, + ResponseTextDeltaEvent, + ToolParam, ) -from openai.types.chat.chat_completion_message_tool_call_param import Function -from openai.types.shared_params import FunctionDefinition +from openai.types.responses.response_input_param import FunctionCallOutput from voluptuous_openapi import convert from homeassistant.components import assist_pipeline, conversation @@ -60,123 +64,81 @@ async def async_setup_entry( def _format_tool( tool: llm.Tool, custom_serializer: Callable[[Any], Any] | None -) -> ChatCompletionToolParam: +) -> FunctionToolParam: """Format tool specification.""" - tool_spec = FunctionDefinition( + return FunctionToolParam( + type="function", name=tool.name, parameters=convert(tool.parameters, custom_serializer=custom_serializer), + description=tool.description, + strict=False, ) - if tool.description: - tool_spec["description"] = tool.description - return ChatCompletionToolParam(type="function", function=tool_spec) def _convert_content_to_param( content: conversation.Content, -) -> ChatCompletionMessageParam: +) -> ResponseInputParam: """Convert any native chat message for this agent to the native format.""" - if content.role == "tool_result": - assert type(content) is conversation.ToolResultContent - return ChatCompletionToolMessageParam( - role="tool", - tool_call_id=content.tool_call_id, - content=json.dumps(content.tool_result), - ) - if content.role != "assistant" or not content.tool_calls: - role: Literal["system", "user", "assistant", "developer"] = content.role + messages: ResponseInputParam = [] + if isinstance(content, conversation.ToolResultContent): + return [ + FunctionCallOutput( + type="function_call_output", + call_id=content.tool_call_id, + output=json.dumps(content.tool_result), + ) + ] + + if content.content: + role: Literal["user", "assistant", "system", "developer"] = content.role if role == "system": role = "developer" - return cast( - ChatCompletionMessageParam, - {"role": content.role, "content": content.content}, + messages.append( + EasyInputMessageParam(type="message", role=role, content=content.content) ) - # Handle the Assistant content including tool calls. - assert type(content) is conversation.AssistantContent - return ChatCompletionAssistantMessageParam( - role="assistant", - content=content.content, - tool_calls=[ - ChatCompletionMessageToolCallParam( - id=tool_call.id, - function=Function( - arguments=json.dumps(tool_call.tool_args), - name=tool_call.tool_name, - ), - type="function", + if isinstance(content, conversation.AssistantContent) and content.tool_calls: + messages.extend( + # https://github.com/openai/openai-python/issues/2205 + ResponseFunctionToolCallParam( # type: ignore[typeddict-item] + type="function_call", + name=tool_call.tool_name, + arguments=json.dumps(tool_call.tool_args), + call_id=tool_call.id, ) for tool_call in content.tool_calls - ], - ) + ) + return messages async def _transform_stream( - result: AsyncStream[ChatCompletionChunk], + result: AsyncStream[ResponseStreamEvent], ) -> AsyncGenerator[conversation.AssistantContentDeltaDict]: """Transform an OpenAI delta stream into HA format.""" - current_tool_call: dict | None = None + async for event in result: + LOGGER.debug("Received event: %s", event) - async for chunk in result: - LOGGER.debug("Received chunk: %s", chunk) - choice = chunk.choices[0] - - if choice.finish_reason: - if current_tool_call: - yield { - "tool_calls": [ - llm.ToolInput( - id=current_tool_call["id"], - tool_name=current_tool_call["tool_name"], - tool_args=json.loads(current_tool_call["tool_args"]), - ) - ] - } - - break - - delta = chunk.choices[0].delta - - # We can yield delta messages not continuing or starting tool calls - if current_tool_call is None and not delta.tool_calls: - yield { # type: ignore[misc] - key: value - for key in ("role", "content") - if (value := getattr(delta, key)) is not None - } - continue - - # When doing tool calls, we should always have a tool call - # object or we have gotten stopped above with a finish_reason set. - if ( - not delta.tool_calls - or not (delta_tool_call := delta.tool_calls[0]) - or not delta_tool_call.function - ): - raise ValueError("Expected delta with tool call") - - if current_tool_call and delta_tool_call.index == current_tool_call["index"]: - current_tool_call["tool_args"] += delta_tool_call.function.arguments or "" - continue - - # We got tool call with new index, so we need to yield the previous - if current_tool_call: + if isinstance(event, ResponseOutputItemAddedEvent): + if isinstance(event.item, ResponseOutputMessage): + yield {"role": event.item.role} + elif isinstance(event.item, ResponseFunctionToolCall): + current_tool_call = event.item + elif isinstance(event, ResponseTextDeltaEvent): + yield {"content": event.delta} + elif isinstance(event, ResponseFunctionCallArgumentsDeltaEvent): + current_tool_call.arguments += event.delta + elif isinstance(event, ResponseFunctionCallArgumentsDoneEvent): + current_tool_call.status = "completed" yield { "tool_calls": [ llm.ToolInput( - id=current_tool_call["id"], - tool_name=current_tool_call["tool_name"], - tool_args=json.loads(current_tool_call["tool_args"]), + id=current_tool_call.call_id, + tool_name=current_tool_call.name, + tool_args=json.loads(current_tool_call.arguments), ) ] } - current_tool_call = { - "index": delta_tool_call.index, - "id": delta_tool_call.id, - "tool_name": delta_tool_call.function.name, - "tool_args": delta_tool_call.function.arguments or "", - } - class OpenAIConversationEntity( conversation.ConversationEntity, conversation.AbstractConversationAgent @@ -241,7 +203,7 @@ class OpenAIConversationEntity( except conversation.ConverseError as err: return err.as_conversation_result() - tools: list[ChatCompletionToolParam] | None = None + tools: list[ToolParam] | None = None if chat_log.llm_api: tools = [ _format_tool(tool, chat_log.llm_api.custom_serializer) @@ -249,7 +211,11 @@ class OpenAIConversationEntity( ] model = options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL) - messages = [_convert_content_to_param(content) for content in chat_log.content] + messages = [ + m + for content in chat_log.content + for m in _convert_content_to_param(content) + ] client = self.entry.runtime_data @@ -257,24 +223,28 @@ class OpenAIConversationEntity( for _iteration in range(MAX_TOOL_ITERATIONS): model_args = { "model": model, - "messages": messages, - "tools": tools or NOT_GIVEN, - "max_completion_tokens": options.get( + "input": messages, + "max_output_tokens": options.get( CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS ), "top_p": options.get(CONF_TOP_P, RECOMMENDED_TOP_P), "temperature": options.get(CONF_TEMPERATURE, RECOMMENDED_TEMPERATURE), "user": chat_log.conversation_id, + "store": False, "stream": True, } + if tools: + model_args["tools"] = tools if model.startswith("o"): - model_args["reasoning_effort"] = options.get( - CONF_REASONING_EFFORT, RECOMMENDED_REASONING_EFFORT - ) + model_args["reasoning"] = { + "effort": options.get( + CONF_REASONING_EFFORT, RECOMMENDED_REASONING_EFFORT + ) + } try: - result = await client.chat.completions.create(**model_args) + result = await client.responses.create(**model_args) except openai.RateLimitError as err: LOGGER.error("Rate limited by OpenAI: %s", err) raise HomeAssistantError("Rate limited or insufficient funds") from err @@ -282,14 +252,10 @@ class OpenAIConversationEntity( LOGGER.error("Error talking to OpenAI: %s", err) raise HomeAssistantError("Error talking to OpenAI") from err - messages.extend( - [ - _convert_content_to_param(content) - async for content in chat_log.async_add_delta_content_stream( - user_input.agent_id, _transform_stream(result) - ) - ] - ) + async for content in chat_log.async_add_delta_content_stream( + user_input.agent_id, _transform_stream(result) + ): + messages.extend(_convert_content_to_param(content)) if not chat_log.unresponded_tool_results: break diff --git a/tests/components/openai_conversation/test_conversation.py b/tests/components/openai_conversation/test_conversation.py index 238fd5f2d7b..bfcacefb044 100644 --- a/tests/components/openai_conversation/test_conversation.py +++ b/tests/components/openai_conversation/test_conversation.py @@ -3,14 +3,28 @@ from collections.abc import Generator from unittest.mock import AsyncMock, patch -from httpx import Response +import httpx from openai import AuthenticationError, RateLimitError -from openai.types.chat.chat_completion_chunk import ( - ChatCompletionChunk, - Choice, - ChoiceDelta, - ChoiceDeltaToolCall, - ChoiceDeltaToolCallFunction, +from openai.types import ResponseFormatText +from openai.types.responses import ( + Response, + ResponseCompletedEvent, + ResponseContentPartAddedEvent, + ResponseContentPartDoneEvent, + ResponseCreatedEvent, + ResponseFunctionCallArgumentsDeltaEvent, + ResponseFunctionCallArgumentsDoneEvent, + ResponseFunctionToolCall, + ResponseInProgressEvent, + ResponseOutputItemAddedEvent, + ResponseOutputItemDoneEvent, + ResponseOutputMessage, + ResponseOutputText, + ResponseReasoningItem, + ResponseStreamEvent, + ResponseTextConfig, + ResponseTextDeltaEvent, + ResponseTextDoneEvent, ) import pytest from syrupy.assertion import SnapshotAssertion @@ -28,40 +42,65 @@ from tests.components.conversation import ( mock_chat_log, # noqa: F401 ) -ASSIST_RESPONSE_FINISH = ( - # Assistant message - ChatCompletionChunk( - id="chatcmpl-B", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[Choice(index=0, delta=ChoiceDelta(content="Cool"))], - ), - # Finish stream - ChatCompletionChunk( - id="chatcmpl-B", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[Choice(index=0, finish_reason="stop", delta=ChoiceDelta())], - ), -) - @pytest.fixture def mock_create_stream() -> Generator[AsyncMock]: """Mock stream response.""" - async def mock_generator(stream): - for value in stream: + async def mock_generator(events, **kwargs): + response = Response( + id="resp_A", + created_at=1700000000, + error=None, + incomplete_details=None, + instructions=kwargs.get("instructions"), + metadata=kwargs.get("metadata", {}), + model=kwargs.get("model", "gpt-4o-mini"), + object="response", + output=[], + parallel_tool_calls=kwargs.get("parallel_tool_calls", True), + temperature=kwargs.get("temperature", 1.0), + tool_choice=kwargs.get("tool_choice", "auto"), + tools=kwargs.get("tools"), + top_p=kwargs.get("top_p", 1.0), + max_output_tokens=kwargs.get("max_output_tokens", 100000), + previous_response_id=kwargs.get("previous_response_id"), + reasoning=kwargs.get("reasoning"), + status="in_progress", + text=kwargs.get( + "text", ResponseTextConfig(format=ResponseFormatText(type="text")) + ), + truncation=kwargs.get("truncation", "disabled"), + usage=None, + user=kwargs.get("user"), + store=kwargs.get("store", True), + ) + yield ResponseCreatedEvent( + response=response, + type="response.created", + ) + yield ResponseInProgressEvent( + response=response, + type="response.in_progress", + ) + + for value in events: + if isinstance(value, ResponseOutputItemDoneEvent): + response.output.append(value.item) yield value + response.status = "completed" + yield ResponseCompletedEvent( + response=response, + type="response.completed", + ) + with patch( - "openai.resources.chat.completions.AsyncCompletions.create", + "openai.resources.responses.AsyncResponses.create", AsyncMock(), ) as mock_create: mock_create.side_effect = lambda **kwargs: mock_generator( - mock_create.return_value.pop(0) + mock_create.return_value.pop(0), **kwargs ) yield mock_create @@ -99,13 +138,17 @@ async def test_entity( [ ( RateLimitError( - response=Response(status_code=429, request=""), body=None, message=None + response=httpx.Response(status_code=429, request=""), + body=None, + message=None, ), "Rate limited or insufficient funds", ), ( AuthenticationError( - response=Response(status_code=401, request=""), body=None, message=None + response=httpx.Response(status_code=401, request=""), + body=None, + message=None, ), "Error talking to OpenAI", ), @@ -120,7 +163,7 @@ async def test_error_handling( ) -> None: """Test that we handle errors when calling completion API.""" with patch( - "openai.resources.chat.completions.AsyncCompletions.create", + "openai.resources.responses.AsyncResponses.create", new_callable=AsyncMock, side_effect=exception, ): @@ -144,6 +187,165 @@ async def test_conversation_agent( assert agent.supported_languages == "*" +def create_message_item( + id: str, text: str | list[str], output_index: int +) -> list[ResponseStreamEvent]: + """Create a message item.""" + if isinstance(text, str): + text = [text] + + content = ResponseOutputText(annotations=[], text="", type="output_text") + events = [ + ResponseOutputItemAddedEvent( + item=ResponseOutputMessage( + id=id, + content=[], + type="message", + role="assistant", + status="in_progress", + ), + output_index=output_index, + type="response.output_item.added", + ), + ResponseContentPartAddedEvent( + content_index=0, + item_id=id, + output_index=output_index, + part=content, + type="response.content_part.added", + ), + ] + + content.text = "".join(text) + events.extend( + ResponseTextDeltaEvent( + content_index=0, + delta=delta, + item_id=id, + output_index=output_index, + type="response.output_text.delta", + ) + for delta in text + ) + + events.extend( + [ + ResponseTextDoneEvent( + content_index=0, + item_id=id, + output_index=output_index, + text="".join(text), + type="response.output_text.done", + ), + ResponseContentPartDoneEvent( + content_index=0, + item_id=id, + output_index=output_index, + part=content, + type="response.content_part.done", + ), + ResponseOutputItemDoneEvent( + item=ResponseOutputMessage( + id=id, + content=[content], + role="assistant", + status="completed", + type="message", + ), + output_index=output_index, + type="response.output_item.done", + ), + ] + ) + + return events + + +def create_function_tool_call_item( + id: str, arguments: str | list[str], call_id: str, name: str, output_index: int +) -> list[ResponseStreamEvent]: + """Create a function tool call item.""" + if isinstance(arguments, str): + arguments = [arguments] + + events = [ + ResponseOutputItemAddedEvent( + item=ResponseFunctionToolCall( + id=id, + arguments="", + call_id=call_id, + name=name, + type="function_call", + status="in_progress", + ), + output_index=output_index, + type="response.output_item.added", + ) + ] + + events.extend( + ResponseFunctionCallArgumentsDeltaEvent( + delta=delta, + item_id=id, + output_index=output_index, + type="response.function_call_arguments.delta", + ) + for delta in arguments + ) + + events.append( + ResponseFunctionCallArgumentsDoneEvent( + arguments="".join(arguments), + item_id=id, + output_index=output_index, + type="response.function_call_arguments.done", + ) + ) + + events.append( + ResponseOutputItemDoneEvent( + item=ResponseFunctionToolCall( + id=id, + arguments="".join(arguments), + call_id=call_id, + name=name, + type="function_call", + status="completed", + ), + output_index=output_index, + type="response.output_item.done", + ) + ) + + return events + + +def create_reasoning_item(id: str, output_index: int) -> list[ResponseStreamEvent]: + """Create a reasoning item.""" + return [ + ResponseOutputItemAddedEvent( + item=ResponseReasoningItem( + id=id, + summary=[], + type="reasoning", + status=None, + ), + output_index=output_index, + type="response.output_item.added", + ), + ResponseOutputItemDoneEvent( + item=ResponseReasoningItem( + id=id, + summary=[], + type="reasoning", + status=None, + ), + output_index=output_index, + type="response.output_item.done", + ), + ] + + async def test_function_call( hass: HomeAssistant, mock_config_entry_with_assist: MockConfigEntry, @@ -156,111 +358,27 @@ async def test_function_call( mock_create_stream.return_value = [ # Initial conversation ( + # Wait for the model to think + *create_reasoning_item(id="rs_A", output_index=0), # First tool call - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - id="call_call_1", - index=0, - function=ChoiceDeltaToolCallFunction( - name="test_tool", - arguments=None, - ), - ) - ] - ), - ) - ], - ), - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - index=0, - function=ChoiceDeltaToolCallFunction( - name=None, - arguments='{"para', - ), - ) - ] - ), - ) - ], - ), - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - index=0, - function=ChoiceDeltaToolCallFunction( - name=None, - arguments='m1":"call1"}', - ), - ) - ] - ), - ) - ], + *create_function_tool_call_item( + id="fc_1", + arguments=['{"para', 'm1":"call1"}'], + call_id="call_call_1", + name="test_tool", + output_index=1, ), # Second tool call - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - id="call_call_2", - index=1, - function=ChoiceDeltaToolCallFunction( - name="test_tool", - arguments='{"param1":"call2"}', - ), - ) - ] - ), - ) - ], - ), - # Finish stream - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice(index=0, finish_reason="tool_calls", delta=ChoiceDelta()) - ], + *create_function_tool_call_item( + id="fc_2", + arguments='{"param1":"call2"}', + call_id="call_call_2", + name="test_tool", + output_index=2, ), ), # Response after tool responses - ASSIST_RESPONSE_FINISH, + create_message_item(id="msg_A", text="Cool", output_index=0), ] mock_chat_log.mock_tool_results( { @@ -288,99 +406,27 @@ async def test_function_call( ( "Test function call started with missing arguments", ( - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - id="call_call_1", - index=0, - function=ChoiceDeltaToolCallFunction( - name="test_tool", - arguments=None, - ), - ) - ] - ), - ) - ], - ), - ChatCompletionChunk( - id="chatcmpl-B", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[Choice(index=0, delta=ChoiceDelta(content="Cool"))], + *create_function_tool_call_item( + id="fc_1", + arguments=[], + call_id="call_call_1", + name="test_tool", + output_index=0, ), + *create_message_item(id="msg_A", text="Cool", output_index=1), ), ), ( "Test invalid JSON", ( - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - id="call_call_1", - index=0, - function=ChoiceDeltaToolCallFunction( - name="test_tool", - arguments=None, - ), - ) - ] - ), - ) - ], - ), - ChatCompletionChunk( - id="chatcmpl-A", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta( - tool_calls=[ - ChoiceDeltaToolCall( - index=0, - function=ChoiceDeltaToolCallFunction( - name=None, - arguments='{"para', - ), - ) - ] - ), - ) - ], - ), - ChatCompletionChunk( - id="chatcmpl-B", - created=1700000000, - model="gpt-4-1106-preview", - object="chat.completion.chunk", - choices=[ - Choice( - index=0, - delta=ChoiceDelta(content="Cool"), - finish_reason="tool_calls", - ) - ], + *create_function_tool_call_item( + id="fc_1", + arguments=['{"para'], + call_id="call_call_1", + name="test_tool", + output_index=0, ), + *create_message_item(id="msg_A", text="Cool", output_index=1), ), ), ], @@ -392,7 +438,7 @@ async def test_function_call_invalid( mock_create_stream: AsyncMock, mock_chat_log: MockChatLog, # noqa: F811 description: str, - messages: tuple[ChatCompletionChunk], + messages: tuple[ResponseStreamEvent], ) -> None: """Test function call containing invalid data.""" mock_create_stream.return_value = [messages] @@ -432,7 +478,9 @@ async def test_assist_api_tools_conversion( hass.states.async_set(f"{component}.test", "on") async_expose_entity(hass, "conversation", f"{component}.test", True) - mock_create_stream.return_value = [ASSIST_RESPONSE_FINISH] + mock_create_stream.return_value = [ + create_message_item(id="msg_A", text="Cool", output_index=0) + ] await conversation.async_converse( hass, "hello", None, Context(), agent_id="conversation.openai" diff --git a/tests/components/openai_conversation/test_init.py b/tests/components/openai_conversation/test_init.py index 05a92d0b98e..5aef68841ee 100644 --- a/tests/components/openai_conversation/test_init.py +++ b/tests/components/openai_conversation/test_init.py @@ -2,17 +2,16 @@ from unittest.mock import AsyncMock, mock_open, patch -from httpx import Request, Response +import httpx from openai import ( APIConnectionError, AuthenticationError, BadRequestError, RateLimitError, ) -from openai.types.chat.chat_completion import ChatCompletion, Choice -from openai.types.chat.chat_completion_message import ChatCompletionMessage from openai.types.image import Image from openai.types.images_response import ImagesResponse +from openai.types.responses import Response, ResponseOutputMessage, ResponseOutputText import pytest from homeassistant.components.openai_conversation import CONF_FILENAMES @@ -117,8 +116,8 @@ async def test_generate_image_service_error( patch( "openai.resources.images.AsyncImages.generate", side_effect=RateLimitError( - response=Response( - status_code=500, request=Request(method="GET", url="") + response=httpx.Response( + status_code=500, request=httpx.Request(method="GET", url="") ), body=None, message="Reason", @@ -202,13 +201,13 @@ async def test_invalid_config_entry( ("side_effect", "error"), [ ( - APIConnectionError(request=Request(method="GET", url="test")), + APIConnectionError(request=httpx.Request(method="GET", url="test")), "Connection error", ), ( AuthenticationError( - response=Response( - status_code=500, request=Request(method="GET", url="test") + response=httpx.Response( + status_code=500, request=httpx.Request(method="GET", url="test") ), body=None, message="", @@ -217,8 +216,8 @@ async def test_invalid_config_entry( ), ( BadRequestError( - response=Response( - status_code=500, request=Request(method="GET", url="test") + response=httpx.Response( + status_code=500, request=httpx.Request(method="GET", url="test") ), body=None, message="", @@ -250,11 +249,11 @@ async def test_init_error( ( {"prompt": "Picture of a dog", "filenames": []}, { - "messages": [ + "input": [ { "content": [ { - "type": "text", + "type": "input_text", "text": "Picture of a dog", }, ], @@ -266,18 +265,18 @@ async def test_init_error( ( {"prompt": "Picture of a dog", "filenames": ["/a/b/c.jpg"]}, { - "messages": [ + "input": [ { "content": [ { - "type": "text", + "type": "input_text", "text": "Picture of a dog", }, { - "type": "image_url", - "image_url": { - "url": "data:image/jpeg;base64,BASE64IMAGE1", - }, + "type": "input_image", + "image_url": "data:image/jpeg;base64,BASE64IMAGE1", + "detail": "auto", + "file_id": "/a/b/c.jpg", }, ], }, @@ -291,24 +290,24 @@ async def test_init_error( "filenames": ["/a/b/c.jpg", "d/e/f.jpg"], }, { - "messages": [ + "input": [ { "content": [ { - "type": "text", + "type": "input_text", "text": "Picture of a dog", }, { - "type": "image_url", - "image_url": { - "url": "data:image/jpeg;base64,BASE64IMAGE1", - }, + "type": "input_image", + "image_url": "data:image/jpeg;base64,BASE64IMAGE1", + "detail": "auto", + "file_id": "/a/b/c.jpg", }, { - "type": "image_url", - "image_url": { - "url": "data:image/jpeg;base64,BASE64IMAGE2", - }, + "type": "input_image", + "image_url": "data:image/jpeg;base64,BASE64IMAGE2", + "detail": "auto", + "file_id": "d/e/f.jpg", }, ], }, @@ -329,13 +328,17 @@ async def test_generate_content_service( """Test generate content service.""" service_data["config_entry"] = mock_config_entry.entry_id expected_args["model"] = "gpt-4o-mini" - expected_args["n"] = 1 - expected_args["response_format"] = {"type": "json_object"} - expected_args["messages"][0]["role"] = "user" + expected_args["max_output_tokens"] = 150 + expected_args["top_p"] = 1.0 + expected_args["temperature"] = 1.0 + expected_args["user"] = None + expected_args["store"] = False + expected_args["input"][0]["type"] = "message" + expected_args["input"][0]["role"] = "user" with ( patch( - "openai.resources.chat.completions.AsyncCompletions.create", + "openai.resources.responses.AsyncResponses.create", new_callable=AsyncMock, ) as mock_create, patch( @@ -345,19 +348,27 @@ async def test_generate_content_service( patch("pathlib.Path.exists", return_value=True), patch.object(hass.config, "is_allowed_path", return_value=True), ): - mock_create.return_value = ChatCompletion( - id="", - model="", - created=1700000000, - object="chat.completion", - choices=[ - Choice( - index=0, - finish_reason="stop", - message=ChatCompletionMessage( - role="assistant", - content="This is the response", - ), + mock_create.return_value = Response( + object="response", + id="resp_A", + created_at=1700000000, + model="gpt-4o-mini", + parallel_tool_calls=True, + tool_choice="auto", + tools=[], + output=[ + ResponseOutputMessage( + type="message", + id="msg_A", + content=[ + ResponseOutputText( + type="output_text", + text="This is the response", + annotations=[], + ) + ], + role="assistant", + status="completed", ) ], ) @@ -427,7 +438,7 @@ async def test_generate_content_service_invalid( with ( patch( - "openai.resources.chat.completions.AsyncCompletions.create", + "openai.resources.responses.AsyncResponses.create", new_callable=AsyncMock, ) as mock_create, patch( @@ -459,10 +470,10 @@ async def test_generate_content_service_error( """Test generate content service handles errors.""" with ( patch( - "openai.resources.chat.completions.AsyncCompletions.create", + "openai.resources.responses.AsyncResponses.create", side_effect=RateLimitError( - response=Response( - status_code=417, request=Request(method="GET", url="") + response=httpx.Response( + status_code=417, request=httpx.Request(method="GET", url="") ), body=None, message="Reason",