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refactor: remove dead inference API code and clean up imports
Delete ~1,300 lines of dead code from the old bespoke inference API that was replaced by OpenAI-only API. This includes removing unused type conversion functions, dead provider methods, and event_logger.py. Clean up imports across the codebase to remove references to deleted types. This eliminates unnecessary code and dependencies, helping isolate the API package as a self-contained module. This is the last interdependency between the .api package and "exterior" packages, meaning that now every other package in llama stack imports the API, not the other way around. The API is now self contained and can be moved into its own package. Signed-off-by: Charlie Doern <cdoern@redhat.com>
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Charlie Doern
parent
8f4c431370
commit
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18 changed files with 34 additions and 2141 deletions
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import pytest
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from pydantic import ValidationError
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from llama_stack.apis.common.content_types import TextContentItem
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from llama_stack.apis.inference import (
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CompletionMessage,
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OpenAIAssistantMessageParam,
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OpenAIChatCompletionContentPartImageParam,
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OpenAIChatCompletionContentPartTextParam,
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OpenAIDeveloperMessageParam,
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OpenAIImageURL,
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OpenAISystemMessageParam,
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OpenAIToolMessageParam,
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OpenAIUserMessageParam,
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SystemMessage,
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UserMessage,
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)
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from llama_stack.models.llama.datatypes import BuiltinTool, StopReason, ToolCall
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from llama_stack.providers.utils.inference.openai_compat import (
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convert_message_to_openai_dict,
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convert_message_to_openai_dict_new,
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openai_messages_to_messages,
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)
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async def test_convert_message_to_openai_dict():
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message = UserMessage(content=[TextContentItem(text="Hello, world!")], role="user")
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assert await convert_message_to_openai_dict(message) == {
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"role": "user",
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"content": [{"type": "text", "text": "Hello, world!"}],
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}
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# Test convert_message_to_openai_dict with a tool call
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async def test_convert_message_to_openai_dict_with_tool_call():
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message = CompletionMessage(
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content="",
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tool_calls=[ToolCall(call_id="123", tool_name="test_tool", arguments='{"foo": "bar"}')],
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stop_reason=StopReason.end_of_turn,
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)
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openai_dict = await convert_message_to_openai_dict(message)
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assert openai_dict == {
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"role": "assistant",
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"content": [{"type": "text", "text": ""}],
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"tool_calls": [
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{"id": "123", "type": "function", "function": {"name": "test_tool", "arguments": '{"foo": "bar"}'}}
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],
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}
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async def test_convert_message_to_openai_dict_with_builtin_tool_call():
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message = CompletionMessage(
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content="",
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tool_calls=[
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ToolCall(
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call_id="123",
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tool_name=BuiltinTool.brave_search,
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arguments='{"foo": "bar"}',
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)
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],
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stop_reason=StopReason.end_of_turn,
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)
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openai_dict = await convert_message_to_openai_dict(message)
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assert openai_dict == {
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"role": "assistant",
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"content": [{"type": "text", "text": ""}],
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"tool_calls": [
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{"id": "123", "type": "function", "function": {"name": "brave_search", "arguments": '{"foo": "bar"}'}}
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],
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}
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async def test_openai_messages_to_messages_with_content_str():
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openai_messages = [
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OpenAISystemMessageParam(content="system message"),
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OpenAIUserMessageParam(content="user message"),
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OpenAIAssistantMessageParam(content="assistant message"),
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]
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llama_messages = openai_messages_to_messages(openai_messages)
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assert len(llama_messages) == 3
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assert isinstance(llama_messages[0], SystemMessage)
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assert isinstance(llama_messages[1], UserMessage)
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assert isinstance(llama_messages[2], CompletionMessage)
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assert llama_messages[0].content == "system message"
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assert llama_messages[1].content == "user message"
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assert llama_messages[2].content == "assistant message"
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async def test_openai_messages_to_messages_with_content_list():
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openai_messages = [
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OpenAISystemMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="system message")]),
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OpenAIUserMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="user message")]),
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OpenAIAssistantMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="assistant message")]),
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]
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llama_messages = openai_messages_to_messages(openai_messages)
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assert len(llama_messages) == 3
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assert isinstance(llama_messages[0], SystemMessage)
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assert isinstance(llama_messages[1], UserMessage)
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assert isinstance(llama_messages[2], CompletionMessage)
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assert llama_messages[0].content[0].text == "system message"
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assert llama_messages[1].content[0].text == "user message"
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assert llama_messages[2].content[0].text == "assistant message"
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@pytest.mark.parametrize(
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"message_class,kwargs",
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[
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(OpenAISystemMessageParam, {}),
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(OpenAIAssistantMessageParam, {}),
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(OpenAIDeveloperMessageParam, {}),
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(OpenAIUserMessageParam, {}),
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(OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
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],
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)
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def test_message_accepts_text_string(message_class, kwargs):
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"""Test that messages accept string text content."""
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msg = message_class(content="Test message", **kwargs)
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assert msg.content == "Test message"
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@pytest.mark.parametrize(
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"message_class,kwargs",
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[
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(OpenAISystemMessageParam, {}),
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(OpenAIAssistantMessageParam, {}),
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(OpenAIDeveloperMessageParam, {}),
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(OpenAIUserMessageParam, {}),
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(OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
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],
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)
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def test_message_accepts_text_list(message_class, kwargs):
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"""Test that messages accept list of text content parts."""
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content_list = [OpenAIChatCompletionContentPartTextParam(text="Test message")]
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msg = message_class(content=content_list, **kwargs)
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assert len(msg.content) == 1
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assert msg.content[0].text == "Test message"
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@pytest.mark.parametrize(
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"message_class,kwargs",
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[
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(OpenAISystemMessageParam, {}),
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(OpenAIAssistantMessageParam, {}),
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(OpenAIDeveloperMessageParam, {}),
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(OpenAIToolMessageParam, {"tool_call_id": "call_123"}),
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],
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)
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def test_message_rejects_images(message_class, kwargs):
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"""Test that system, assistant, developer, and tool messages reject image content."""
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with pytest.raises(ValidationError):
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message_class(
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content=[
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OpenAIChatCompletionContentPartImageParam(image_url=OpenAIImageURL(url="http://example.com/image.jpg"))
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],
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**kwargs,
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)
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def test_user_message_accepts_images():
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"""Test that user messages accept image content (unlike other message types)."""
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# List with images should work
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msg = OpenAIUserMessageParam(
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content=[
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OpenAIChatCompletionContentPartTextParam(text="Describe this image:"),
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OpenAIChatCompletionContentPartImageParam(image_url=OpenAIImageURL(url="http://example.com/image.jpg")),
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]
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)
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assert len(msg.content) == 2
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assert msg.content[0].text == "Describe this image:"
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assert msg.content[1].image_url.url == "http://example.com/image.jpg"
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async def test_convert_message_to_openai_dict_new_user_message():
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"""Test convert_message_to_openai_dict_new with UserMessage."""
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message = UserMessage(content="Hello, world!", role="user")
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result = await convert_message_to_openai_dict_new(message)
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assert result["role"] == "user"
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assert result["content"] == "Hello, world!"
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async def test_convert_message_to_openai_dict_new_completion_message_with_tool_calls():
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"""Test convert_message_to_openai_dict_new with CompletionMessage containing tool calls."""
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message = CompletionMessage(
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content="I'll help you find the weather.",
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tool_calls=[
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ToolCall(
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call_id="call_123",
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tool_name="get_weather",
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arguments='{"city": "Sligo"}',
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)
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],
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stop_reason=StopReason.end_of_turn,
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)
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result = await convert_message_to_openai_dict_new(message)
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# This would have failed with "Cannot instantiate typing.Union" before the fix
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assert result["role"] == "assistant"
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assert result["content"] == "I'll help you find the weather."
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assert "tool_calls" in result
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assert result["tool_calls"] is not None
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assert len(result["tool_calls"]) == 1
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tool_call = result["tool_calls"][0]
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assert tool_call.id == "call_123"
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assert tool_call.type == "function"
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assert tool_call.function.name == "get_weather"
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assert tool_call.function.arguments == '{"city": "Sligo"}'
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