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Update Ollama to use streaming API (#138177)
* Update ollama to use streaming APIs * Remove unnecessary logging * Update ollama to use streaming APIs * Remove unnecessary logging * Update homeassistant/components/ollama/conversation.py Co-authored-by: Paulus Schoutsen <paulus@home-assistant.io> --------- Co-authored-by: Paulus Schoutsen <paulus@home-assistant.io>
This commit is contained in:
Allen Porter
GitHub
parent
ae38f89728
commit
15223b3679
@ -2,7 +2,7 @@
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from __future__ import annotations
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from collections.abc import Callable
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from collections.abc import AsyncGenerator, Callable
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import json
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import logging
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from typing import Any, Literal
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@ -123,7 +123,47 @@ def _convert_content(
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role=MessageRole.SYSTEM.value,
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content=chat_content.content,
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)
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raise ValueError(f"Unexpected content type: {type(chat_content)}")
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raise TypeError(f"Unexpected content type: {type(chat_content)}")
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async def _transform_stream(
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result: AsyncGenerator[ollama.Message],
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) -> AsyncGenerator[conversation.AssistantContentDeltaDict]:
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"""Transform the response stream into HA format.
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An Ollama streaming response may come in chunks like this:
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response: message=Message(role="assistant", content="Paris")
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response: message=Message(role="assistant", content=".")
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response: message=Message(role="assistant", content=""), done: True, done_reason: "stop"
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response: message=Message(role="assistant", tool_calls=[...])
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response: message=Message(role="assistant", content=""), done: True, done_reason: "stop"
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This generator conforms to the chatlog delta stream expectations in that it
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yields deltas, then the role only once the response is done.
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"""
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new_msg = True
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async for response in result:
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_LOGGER.debug("Received response: %s", response)
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response_message = response["message"]
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chunk: conversation.AssistantContentDeltaDict = {}
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if new_msg:
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new_msg = False
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chunk["role"] = "assistant"
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if (tool_calls := response_message.get("tool_calls")) is not None:
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chunk["tool_calls"] = [
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llm.ToolInput(
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tool_name=tool_call["function"]["name"],
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tool_args=_parse_tool_args(tool_call["function"]["arguments"]),
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)
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for tool_call in tool_calls
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]
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if (content := response_message.get("content")) is not None:
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chunk["content"] = content
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if response_message.get("done"):
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new_msg = True
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yield chunk
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class OllamaConversationEntity(
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@ -216,12 +256,12 @@ class OllamaConversationEntity(
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# To prevent infinite loops, we limit the number of iterations
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for _iteration in range(MAX_TOOL_ITERATIONS):
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try:
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response = await client.chat(
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response_generator = await client.chat(
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model=model,
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# Make a copy of the messages because we mutate the list later
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messages=list(message_history.messages),
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tools=tools,
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stream=False,
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stream=True,
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# keep_alive requires specifying unit. In this case, seconds
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keep_alive=f"{settings.get(CONF_KEEP_ALIVE, DEFAULT_KEEP_ALIVE)}s",
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options={CONF_NUM_CTX: settings.get(CONF_NUM_CTX, DEFAULT_NUM_CTX)},
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@ -232,46 +272,25 @@ class OllamaConversationEntity(
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f"Sorry, I had a problem talking to the Ollama server: {err}"
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) from err
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response_message = response["message"]
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content = response_message.get("content")
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tool_calls = response_message.get("tool_calls")
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message_history.messages.append(
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ollama.Message(
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role=response_message["role"],
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content=content,
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tool_calls=tool_calls,
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)
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)
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tool_inputs = [
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llm.ToolInput(
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tool_name=tool_call["function"]["name"],
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tool_args=_parse_tool_args(tool_call["function"]["arguments"]),
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)
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for tool_call in tool_calls or ()
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]
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message_history.messages.extend(
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[
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ollama.Message(
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role=MessageRole.TOOL.value,
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content=json.dumps(tool_response.tool_result),
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)
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async for tool_response in chat_log.async_add_assistant_content(
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conversation.AssistantContent(
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agent_id=user_input.agent_id,
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content=content,
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tool_calls=tool_inputs or None,
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)
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_convert_content(content)
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async for content in chat_log.async_add_delta_content_stream(
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user_input.agent_id, _transform_stream(response_generator)
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)
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]
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)
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if not tool_calls:
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if not chat_log.unresponded_tool_results:
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break
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# Create intent response
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intent_response = intent.IntentResponse(language=user_input.language)
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intent_response.async_set_speech(response_message["content"])
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if not isinstance(chat_log.content[-1], conversation.AssistantContent):
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raise TypeError(
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f"Unexpected last message type: {type(chat_log.content[-1])}"
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)
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intent_response.async_set_speech(chat_log.content[-1].content or "")
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return conversation.ConversationResult(
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response=intent_response, conversation_id=chat_log.conversation_id
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)
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@ -1,5 +1,6 @@
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"""Tests for the Ollama integration."""
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from collections.abc import AsyncGenerator
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from typing import Any
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from unittest.mock import AsyncMock, Mock, patch
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@ -25,6 +26,14 @@ def mock_ulid_tools():
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yield
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async def stream_generator(response: dict | list[dict]) -> AsyncGenerator[dict]:
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"""Generate a response from the assistant."""
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if not isinstance(response, list):
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response = [response]
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for msg in response:
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yield msg
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@pytest.mark.parametrize("agent_id", [None, "conversation.mock_title"])
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async def test_chat(
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hass: HomeAssistant,
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@ -42,7 +51,9 @@ async def test_chat(
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with patch(
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"ollama.AsyncClient.chat",
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return_value={"message": {"role": "assistant", "content": "test response"}},
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return_value=stream_generator(
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{"message": {"role": "assistant", "content": "test response"}}
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),
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) as mock_chat:
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result = await conversation.async_converse(
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hass,
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@ -81,6 +92,53 @@ async def test_chat(
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assert "Current time is" in detail_event["data"]["messages"][0]["content"]
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async def test_chat_stream(
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hass: HomeAssistant,
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mock_config_entry: MockConfigEntry,
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mock_init_component,
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) -> None:
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"""Test chat messages are assembled across streamed responses."""
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entry = MockConfigEntry()
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entry.add_to_hass(hass)
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with patch(
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"ollama.AsyncClient.chat",
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return_value=stream_generator(
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[
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{"message": {"role": "assistant", "content": "test "}},
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{
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"message": {"role": "assistant", "content": "response"},
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"done": True,
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"done_reason": "stop",
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},
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],
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),
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) as mock_chat:
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result = await conversation.async_converse(
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hass,
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"test message",
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None,
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Context(),
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agent_id=mock_config_entry.entry_id,
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)
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assert mock_chat.call_count == 1
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args = mock_chat.call_args.kwargs
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prompt = args["messages"][0]["content"]
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assert args["model"] == "test model"
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assert args["messages"] == [
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Message(role="system", content=prompt),
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Message(role="user", content="test message"),
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]
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assert result.response.response_type == intent.IntentResponseType.ACTION_DONE, (
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result
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)
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assert result.response.speech["plain"]["speech"] == "test response"
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async def test_template_variables(
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hass: HomeAssistant, mock_config_entry: MockConfigEntry
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) -> None:
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@ -103,7 +161,9 @@ async def test_template_variables(
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patch("ollama.AsyncClient.list"),
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patch(
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"ollama.AsyncClient.chat",
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return_value={"message": {"role": "assistant", "content": "test response"}},
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return_value=stream_generator(
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{"message": {"role": "assistant", "content": "test response"}}
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),
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) as mock_chat,
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patch("homeassistant.auth.AuthManager.async_get_user", return_value=mock_user),
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):
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@ -170,26 +230,30 @@ async def test_function_call(
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def completion_result(*args, messages, **kwargs):
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for message in messages:
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if message["role"] == "tool":
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return {
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"message": {
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"role": "assistant",
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"content": "I have successfully called the function",
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}
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}
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return {
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"message": {
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"role": "assistant",
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"tool_calls": [
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return stream_generator(
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{
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"function": {
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"name": "test_tool",
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"arguments": tool_args,
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"message": {
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"role": "assistant",
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"content": "I have successfully called the function",
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}
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}
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],
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)
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return stream_generator(
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{
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"message": {
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"role": "assistant",
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"tool_calls": [
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{
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"function": {
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"name": "test_tool",
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"arguments": tool_args,
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}
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}
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],
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}
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}
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}
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)
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with patch(
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"ollama.AsyncClient.chat",
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@ -251,26 +315,30 @@ async def test_function_exception(
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def completion_result(*args, messages, **kwargs):
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for message in messages:
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if message["role"] == "tool":
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return {
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"message": {
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"role": "assistant",
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"content": "There was an error calling the function",
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}
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}
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return {
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"message": {
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"role": "assistant",
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"tool_calls": [
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return stream_generator(
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{
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"function": {
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"name": "test_tool",
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"arguments": {"param1": "test_value"},
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"message": {
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"role": "assistant",
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"content": "There was an error calling the function",
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}
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}
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],
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)
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return stream_generator(
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{
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"message": {
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"role": "assistant",
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"tool_calls": [
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{
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"function": {
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"name": "test_tool",
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"arguments": {"param1": "test_value"},
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}
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}
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],
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}
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}
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}
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)
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with patch(
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"ollama.AsyncClient.chat",
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@ -344,7 +412,9 @@ async def test_message_history_trimming(
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def response(*args, **kwargs) -> dict:
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nonlocal response_idx
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response_idx += 1
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return {"message": {"role": "assistant", "content": f"response {response_idx}"}}
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return stream_generator(
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{"message": {"role": "assistant", "content": f"response {response_idx}"}}
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)
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with patch(
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"ollama.AsyncClient.chat",
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@ -438,11 +508,13 @@ async def test_message_history_unlimited(
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"""Test that message history is not trimmed when max_history = 0."""
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conversation_id = "1234"
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def stream(*args, **kwargs) -> AsyncGenerator[dict]:
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return stream_generator(
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{"message": {"role": "assistant", "content": "test response"}}
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)
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with (
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patch(
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"ollama.AsyncClient.chat",
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return_value={"message": {"role": "assistant", "content": "test response"}},
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) as mock_chat,
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patch("ollama.AsyncClient.chat", side_effect=stream) as mock_chat,
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):
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hass.config_entries.async_update_entry(
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mock_config_entry, options={ollama.CONF_MAX_HISTORY: 0}
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@ -559,7 +631,9 @@ async def test_options(
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"""Test that options are passed correctly to ollama client."""
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with patch(
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"ollama.AsyncClient.chat",
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return_value={"message": {"role": "assistant", "content": "test response"}},
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return_value=stream_generator(
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{"message": {"role": "assistant", "content": "test response"}}
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),
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) as mock_chat:
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await conversation.async_converse(
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hass,
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