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Update anthropic to use the new chatlog API (#138178) 

* Update anthropic to use the new chatlog API

* Remove conversation id logging

* Add back whitespace

* Reduce unnecessary diffs

* Revert diffs to conversation component

* Replace types with union type
pull/135297/merge
Allen Porter 2025-02-09 20:42:15 -08:00 committed by GitHub
parent 29c6a2ec13
commit ae38f89728
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3 changed files with 112 additions and 189 deletions
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258
homeassistant/components/anthropic/conversation.py
View File

@ -16,18 +16,15 @@ from anthropic.types import (
ToolUseBlock,
ToolUseBlockParam,
)
import voluptuous as vol
from voluptuous_openapi import convert
from homeassistant.components import conversation
from homeassistant.components.conversation import trace
from homeassistant.config_entries import ConfigEntry
from homeassistant.const import CONF_LLM_HASS_API, MATCH_ALL
from homeassistant.core import HomeAssistant
from homeassistant.exceptions import HomeAssistantError, TemplateError
from homeassistant.helpers import device_registry as dr, intent, llm, template
from homeassistant.exceptions import HomeAssistantError
from homeassistant.helpers import chat_session, device_registry as dr, intent, llm
from homeassistant.helpers.entity_platform import AddEntitiesCallback
from homeassistant.util import ulid as ulid_util
from . import AnthropicConfigEntry
from .const import (
@ -89,6 +86,44 @@ def _message_convert(
return MessageParam(role=message.role, content=param_content)
def _convert_content(chat_content: conversation.Content) -> MessageParam:
"""Create tool response content."""
if isinstance(chat_content, conversation.ToolResultContent):
return MessageParam(
role="user",
content=[
ToolResultBlockParam(
type="tool_result",
tool_use_id=chat_content.tool_call_id,
content=json.dumps(chat_content.tool_result),
)
],
)
if isinstance(chat_content, conversation.AssistantContent):
return MessageParam(
role="assistant",
content=[
TextBlockParam(type="text", text=chat_content.content or ""),
*[
ToolUseBlockParam(
type="tool_use",
id=tool_call.id,
name=tool_call.tool_name,
input=json.dumps(tool_call.tool_args),
)
for tool_call in chat_content.tool_calls or ()
],
],
)
if isinstance(chat_content, conversation.UserContent):
return MessageParam(
role="user",
content=chat_content.content,
)
# Note: We don't pass SystemContent here as its passed to the API as the prompt
raise ValueError(f"Unexpected content type: {type(chat_content)}")
class AnthropicConversationEntity(
conversation.ConversationEntity, conversation.AbstractConversationAgent
):
@ -100,7 +135,6 @@ class AnthropicConversationEntity(
def __init__(self, entry: AnthropicConfigEntry) -> None:
"""Initialize the agent."""
self.entry = entry
self.history: dict[str, list[MessageParam]] = {}
self._attr_unique_id = entry.entry_id
self._attr_device_info = dr.DeviceInfo(
identifiers={(DOMAIN, entry.entry_id)},
@ -129,110 +163,43 @@ class AnthropicConversationEntity(
self, user_input: conversation.ConversationInput
) -> conversation.ConversationResult:
"""Process a sentence."""
options = self.entry.options
intent_response = intent.IntentResponse(language=user_input.language)
llm_api: llm.APIInstance | None = None
tools: list[ToolParam] | None = None
user_name: str | None = None
llm_context = llm.LLMContext(
platform=DOMAIN,
context=user_input.context,
user_prompt=user_input.text,
language=user_input.language,
assistant=conversation.DOMAIN,
device_id=user_input.device_id,
)
if options.get(CONF_LLM_HASS_API):
try:
llm_api = await llm.async_get_api(
self.hass,
options[CONF_LLM_HASS_API],
llm_context,
)
except HomeAssistantError as err:
LOGGER.error("Error getting LLM API: %s", err)
intent_response.async_set_error(
intent.IntentResponseErrorCode.UNKNOWN,
f"Error preparing LLM API: {err}",
)
return conversation.ConversationResult(
response=intent_response, conversation_id=user_input.conversation_id
)
tools = [
_format_tool(tool, llm_api.custom_serializer) for tool in llm_api.tools
]
if user_input.conversation_id is None:
conversation_id = ulid_util.ulid_now()
messages = []
elif user_input.conversation_id in self.history:
conversation_id = user_input.conversation_id
messages = self.history[conversation_id]
else:
# Conversation IDs are ULIDs. We generate a new one if not provided.
# If an old OLID is passed in, we will generate a new one to indicate
# a new conversation was started. If the user picks their own, they
# want to track a conversation and we respect it.
try:
ulid_util.ulid_to_bytes(user_input.conversation_id)
conversation_id = ulid_util.ulid_now()
except ValueError:
conversation_id = user_input.conversation_id
messages = []
if (
user_input.context
and user_input.context.user_id
and (
user := await self.hass.auth.async_get_user(user_input.context.user_id)
)
with (
chat_session.async_get_chat_session(
self.hass, user_input.conversation_id
) as session,
conversation.async_get_chat_log(self.hass, session, user_input) as chat_log,
):
user_name = user.name
return await self._async_handle_message(user_input, chat_log)
async def _async_handle_message(
self,
user_input: conversation.ConversationInput,
chat_log: conversation.ChatLog,
) -> conversation.ConversationResult:
"""Call the API."""
options = self.entry.options
try:
prompt_parts = [
template.Template(
llm.BASE_PROMPT
+ options.get(CONF_PROMPT, llm.DEFAULT_INSTRUCTIONS_PROMPT),
self.hass,
).async_render(
{
"ha_name": self.hass.config.location_name,
"user_name": user_name,
"llm_context": llm_context,
},
parse_result=False,
)
await chat_log.async_update_llm_data(
DOMAIN,
user_input,
options.get(CONF_LLM_HASS_API),
options.get(CONF_PROMPT),
)
except conversation.ConverseError as err:
return err.as_conversation_result()
tools: list[ToolParam] | None = None
if chat_log.llm_api:
tools = [
_format_tool(tool, chat_log.llm_api.custom_serializer)
for tool in chat_log.llm_api.tools
]
except TemplateError as err:
LOGGER.error("Error rendering prompt: %s", err)
intent_response.async_set_error(
intent.IntentResponseErrorCode.UNKNOWN,
f"Sorry, I had a problem with my template: {err}",
)
return conversation.ConversationResult(
response=intent_response, conversation_id=conversation_id
)
if llm_api:
prompt_parts.append(llm_api.api_prompt)
prompt = "\n".join(prompt_parts)
# Create a copy of the variable because we attach it to the trace
messages = [*messages, MessageParam(role="user", content=user_input.text)]
LOGGER.debug("Prompt: %s", messages)
LOGGER.debug("Tools: %s", tools)
trace.async_conversation_trace_append(
trace.ConversationTraceEventType.AGENT_DETAIL,
{"system": prompt, "messages": messages},
)
system = chat_log.content[0]
if not isinstance(system, conversation.SystemContent):
raise TypeError("First message must be a system message")
messages = [_convert_content(content) for content in chat_log.content[1:]]
client = self.entry.runtime_data
@ -244,69 +211,62 @@ class AnthropicConversationEntity(
messages=messages,
tools=tools or NOT_GIVEN,
max_tokens=options.get(CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS),
system=prompt,
system=system.content,
temperature=options.get(CONF_TEMPERATURE, RECOMMENDED_TEMPERATURE),
)
except anthropic.AnthropicError as err:
intent_response.async_set_error(
intent.IntentResponseErrorCode.UNKNOWN,
f"Sorry, I had a problem talking to Anthropic: {err}",
)
return conversation.ConversationResult(
response=intent_response, conversation_id=conversation_id
)
raise HomeAssistantError(
f"Sorry, I had a problem talking to Anthropic: {err}"
) from err
LOGGER.debug("Response %s", response)
messages.append(_message_convert(response))
if response.stop_reason != "tool_use" or not llm_api:
break
tool_results: list[ToolResultBlockParam] = []
for tool_call in response.content:
if isinstance(tool_call, TextBlock):
LOGGER.info(tool_call.text)
if not isinstance(tool_call, ToolUseBlock):
continue
tool_input = llm.ToolInput(
text = "".join(
[
content.text
for content in response.content
if isinstance(content, TextBlock)
]
)
tool_inputs = [
llm.ToolInput(
id=tool_call.id,
tool_name=tool_call.name,
tool_args=cast(dict[str, Any], tool_call.input),
)
LOGGER.debug(
"Tool call: %s(%s)", tool_input.tool_name, tool_input.tool_args
for tool_call in response.content
if isinstance(tool_call, ToolUseBlock)
]
tool_results = [
ToolResultBlockParam(
type="tool_result",
tool_use_id=tool_response.tool_call_id,
content=json.dumps(tool_response.tool_result),
)
try:
tool_response = await llm_api.async_call_tool(tool_input)
except (HomeAssistantError, vol.Invalid) as e:
tool_response = {"error": type(e).__name__}
if str(e):
tool_response["error_text"] = str(e)
LOGGER.debug("Tool response: %s", tool_response)
tool_results.append(
ToolResultBlockParam(
type="tool_result",
tool_use_id=tool_call.id,
content=json.dumps(tool_response),
async for tool_response in chat_log.async_add_assistant_content(
conversation.AssistantContent(
agent_id=user_input.agent_id,
content=text,
tool_calls=tool_inputs or None,
)
)
]
if tool_results:
messages.append(MessageParam(role="user", content=tool_results))
messages.append(MessageParam(role="user", content=tool_results))
self.history[conversation_id] = messages
for content in response.content:
if isinstance(content, TextBlock):
intent_response.async_set_speech(content.text)
if not tool_inputs:
break
response_content = chat_log.content[-1]
if not isinstance(response_content, conversation.AssistantContent):
raise TypeError("Last message must be an assistant message")
intent_response = intent.IntentResponse(language=user_input.language)
intent_response.async_set_speech(response_content.content or "")
return conversation.ConversationResult(
response=intent_response, conversation_id=conversation_id
response=intent_response, conversation_id=chat_log.conversation_id
)
async def _async_entry_update_listener(

4
tests/components/anthropic/snapshots/test_conversation.ambr
View File

@ -1,7 +1,7 @@
# serializer version: 1
# name: test_unknown_hass_api
dict({
'conversation_id': None,
'conversation_id': '1234',
'response': IntentResponse(
card=dict({
}),
@ -20,7 +20,7 @@
speech=dict({
'plain': dict({
'extra_data': None,
'speech': 'Error preparing LLM API: API non-existing not found',
'speech': 'Error preparing LLM API',
}),
}),
speech_slots=dict({

39
tests/components/anthropic/test_conversation.py
View File

@ -10,7 +10,6 @@ from syrupy.assertion import SnapshotAssertion
import voluptuous as vol
from homeassistant.components import conversation
from homeassistant.components.conversation import trace
from homeassistant.const import CONF_LLM_HASS_API
from homeassistant.core import Context, HomeAssistant
from homeassistant.exceptions import HomeAssistantError
@ -250,42 +249,6 @@ async def test_function_call(
),
)
# Test Conversation tracing
traces = trace.async_get_traces()
assert traces
last_trace = traces[-1].as_dict()
trace_events = last_trace.get("events", [])
assert [event["event_type"] for event in trace_events] == [
trace.ConversationTraceEventType.ASYNC_PROCESS,
trace.ConversationTraceEventType.AGENT_DETAIL,
trace.ConversationTraceEventType.TOOL_CALL,
]
# AGENT_DETAIL event contains the raw prompt passed to the model
detail_event = trace_events[1]
assert "Answer in plain text" in detail_event["data"]["system"]
assert "Today's date is 2024-06-03." in trace_events[1]["data"]["system"]
# Call it again, make sure we have updated prompt
with (
patch(
"anthropic.resources.messages.AsyncMessages.create",
new_callable=AsyncMock,
side_effect=completion_result,
) as mock_create,
freeze_time("2024-06-04 23:00:00"),
):
result = await conversation.async_converse(
hass,
"Please call the test function",
None,
context,
agent_id=agent_id,
)
assert "Today's date is 2024-06-04." in mock_create.mock_calls[1][2]["system"]
# Test old assert message not updated
assert "Today's date is 2024-06-03." in trace_events[1]["data"]["system"]
@patch("homeassistant.components.anthropic.conversation.llm.AssistAPI._async_get_tools")
async def test_function_exception(
@ -448,7 +411,7 @@ async def test_unknown_hass_api(
)
result = await conversation.async_converse(
hass, "hello", None, Context(), agent_id="conversation.claude"
hass, "hello", "1234", Context(), agent_id="conversation.claude"
)
assert result == snapshot