Convert Claude to use subentries (#147285)

* Convert Claude to use subentries

* Add latest changes from Google subentries

* Revert accidental change to Google

homeassistant/components/anthropic/__init__.py

@@ -6,11 +6,16 @@ from functools import partial
 
 import anthropic
 
-from homeassistant.config_entries import ConfigEntry
+from homeassistant.config_entries import ConfigEntry, ConfigSubentry
 from homeassistant.const import CONF_API_KEY, Platform
 from homeassistant.core import HomeAssistant
 from homeassistant.exceptions import ConfigEntryNotReady
-from homeassistant.helpers import config_validation as cv
+from homeassistant.helpers import (
+    config_validation as cv,
+    device_registry as dr,
+    entity_registry as er,
+)
+from homeassistant.helpers.typing import ConfigType
 
 from .const import CONF_CHAT_MODEL, DOMAIN, LOGGER, RECOMMENDED_CHAT_MODEL
 
@@ -20,13 +25,24 @@ CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
 type AnthropicConfigEntry = ConfigEntry[anthropic.AsyncClient]
 
 
+async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool:
+    """Set up Anthropic."""
+    await async_migrate_integration(hass)
+    return True
+
+
 async def async_setup_entry(hass: HomeAssistant, entry: AnthropicConfigEntry) -> bool:
     """Set up Anthropic from a config entry."""
     client = await hass.async_add_executor_job(
         partial(anthropic.AsyncAnthropic, api_key=entry.data[CONF_API_KEY])
     )
     try:
-        model_id = entry.options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL)
+        # Use model from first conversation subentry for validation
+        subentries = list(entry.subentries.values())
+        if subentries:
+            model_id = subentries[0].data.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL)
+        else:
+            model_id = RECOMMENDED_CHAT_MODEL
         model = await client.models.retrieve(model_id=model_id, timeout=10.0)
         LOGGER.debug("Anthropic model: %s", model.display_name)
     except anthropic.AuthenticationError as err:
@@ -45,3 +61,68 @@ async def async_setup_entry(hass: HomeAssistant, entry: AnthropicConfigEntry) ->
 async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
     """Unload Anthropic."""
     return await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
+
+
+async def async_migrate_integration(hass: HomeAssistant) -> None:
+    """Migrate integration entry structure."""
+
+    entries = hass.config_entries.async_entries(DOMAIN)
+    if not any(entry.version == 1 for entry in entries):
+        return
+
+    api_keys_entries: dict[str, ConfigEntry] = {}
+    entity_registry = er.async_get(hass)
+    device_registry = dr.async_get(hass)
+
+    for entry in entries:
+        use_existing = False
+        subentry = ConfigSubentry(
+            data=entry.options,
+            subentry_type="conversation",
+            title=entry.title,
+            unique_id=None,
+        )
+        if entry.data[CONF_API_KEY] not in api_keys_entries:
+            use_existing = True
+            api_keys_entries[entry.data[CONF_API_KEY]] = entry
+
+        parent_entry = api_keys_entries[entry.data[CONF_API_KEY]]
+
+        hass.config_entries.async_add_subentry(parent_entry, subentry)
+        conversation_entity = entity_registry.async_get_entity_id(
+            "conversation",
+            DOMAIN,
+            entry.entry_id,
+        )
+        if conversation_entity is not None:
+            entity_registry.async_update_entity(
+                conversation_entity,
+                config_entry_id=parent_entry.entry_id,
+                config_subentry_id=subentry.subentry_id,
+                new_unique_id=subentry.subentry_id,
+            )
+
+        device = device_registry.async_get_device(
+            identifiers={(DOMAIN, entry.entry_id)}
+        )
+        if device is not None:
+            device_registry.async_update_device(
+                device.id,
+                new_identifiers={(DOMAIN, subentry.subentry_id)},
+                add_config_subentry_id=subentry.subentry_id,
+                add_config_entry_id=parent_entry.entry_id,
+            )
+            if parent_entry.entry_id != entry.entry_id:
+                device_registry.async_update_device(
+                    device.id,
+                    remove_config_entry_id=entry.entry_id,
+                )
+
+        if not use_existing:
+            await hass.config_entries.async_remove(entry.entry_id)
+        else:
+            hass.config_entries.async_update_entry(
+                entry,
+                options={},
+                version=2,
+            )

homeassistant/components/anthropic/config_flow.py

@@ -5,20 +5,21 @@ from __future__ import annotations
 from collections.abc import Mapping
 from functools import partial
 import logging
-from types import MappingProxyType
-from typing import Any
+from typing import Any, cast
 
 import anthropic
 import voluptuous as vol
 
 from homeassistant.config_entries import (
     ConfigEntry,
+    ConfigEntryState,
     ConfigFlow,
     ConfigFlowResult,
-    OptionsFlow,
+    ConfigSubentryFlow,
+    SubentryFlowResult,
 )
-from homeassistant.const import CONF_API_KEY, CONF_LLM_HASS_API
-from homeassistant.core import HomeAssistant
+from homeassistant.const import CONF_API_KEY, CONF_LLM_HASS_API, CONF_NAME
+from homeassistant.core import HomeAssistant, callback
 from homeassistant.helpers import llm
 from homeassistant.helpers.selector import (
     NumberSelector,
@@ -36,6 +37,7 @@ from .const import (
     CONF_RECOMMENDED,
     CONF_TEMPERATURE,
     CONF_THINKING_BUDGET,
+    DEFAULT_CONVERSATION_NAME,
     DOMAIN,
     RECOMMENDED_CHAT_MODEL,
     RECOMMENDED_MAX_TOKENS,
@@ -72,7 +74,7 @@ async def validate_input(hass: HomeAssistant, data: dict[str, Any]) -> None:
 class AnthropicConfigFlow(ConfigFlow, domain=DOMAIN):
     """Handle a config flow for Anthropic."""
 
-    VERSION = 1
+    VERSION = 2
 
     async def async_step_user(
         self, user_input: dict[str, Any] | None = None
@@ -81,6 +83,7 @@ class AnthropicConfigFlow(ConfigFlow, domain=DOMAIN):
         errors = {}
 
         if user_input is not None:
+            self._async_abort_entries_match(user_input)
             try:
                 await validate_input(self.hass, user_input)
             except anthropic.APITimeoutError:
@@ -102,57 +105,93 @@ class AnthropicConfigFlow(ConfigFlow, domain=DOMAIN):
                 return self.async_create_entry(
                     title="Claude",
                     data=user_input,
-                    options=RECOMMENDED_OPTIONS,
+                    subentries=[
+                        {
+                            "subentry_type": "conversation",
+                            "data": RECOMMENDED_OPTIONS,
+                            "title": DEFAULT_CONVERSATION_NAME,
+                            "unique_id": None,
+                        }
+                    ],
                 )
 
         return self.async_show_form(
             step_id="user", data_schema=STEP_USER_DATA_SCHEMA, errors=errors or None
         )
 
-    @staticmethod
-    def async_get_options_flow(
-        config_entry: ConfigEntry,
-    ) -> OptionsFlow:
-        """Create the options flow."""
-        return AnthropicOptionsFlow(config_entry)
+    @classmethod
+    @callback
+    def async_get_supported_subentry_types(
+        cls, config_entry: ConfigEntry
+    ) -> dict[str, type[ConfigSubentryFlow]]:
+        """Return subentries supported by this integration."""
+        return {"conversation": ConversationSubentryFlowHandler}
 
 
-class AnthropicOptionsFlow(OptionsFlow):
-    """Anthropic config flow options handler."""
+class ConversationSubentryFlowHandler(ConfigSubentryFlow):
+    """Flow for managing conversation subentries."""
 
-    def __init__(self, config_entry: ConfigEntry) -> None:
-        """Initialize options flow."""
-        self.last_rendered_recommended = config_entry.options.get(
-            CONF_RECOMMENDED, False
-        )
+    last_rendered_recommended = False
 
-    async def async_step_init(
+    @property
+    def _is_new(self) -> bool:
+        """Return if this is a new subentry."""
+        return self.source == "user"
+
+    async def async_step_set_options(
         self, user_input: dict[str, Any] | None = None
-    ) -> ConfigFlowResult:
-        """Manage the options."""
-        options: dict[str, Any] | MappingProxyType[str, Any] = self.config_entry.options
+    ) -> SubentryFlowResult:
+        """Set conversation options."""
+        # abort if entry is not loaded
+        if self._get_entry().state != ConfigEntryState.LOADED:
+            return self.async_abort(reason="entry_not_loaded")
+
         errors: dict[str, str] = {}
 
-        if user_input is not None:
-            if user_input[CONF_RECOMMENDED] == self.last_rendered_recommended:
-                if not user_input.get(CONF_LLM_HASS_API):
-                    user_input.pop(CONF_LLM_HASS_API, None)
-                if user_input.get(
-                    CONF_THINKING_BUDGET, RECOMMENDED_THINKING_BUDGET
-                ) >= user_input.get(CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS):
-                    errors[CONF_THINKING_BUDGET] = "thinking_budget_too_large"
-
-                if not errors:
-                    return self.async_create_entry(title="", data=user_input)
+        if user_input is None:
+            if self._is_new:
+                options = RECOMMENDED_OPTIONS.copy()
             else:
-                # Re-render the options again, now with the recommended options shown/hidden
-                self.last_rendered_recommended = user_input[CONF_RECOMMENDED]
+                # If this is a reconfiguration, we need to copy the existing options
+                # so that we can show the current values in the form.
+                options = self._get_reconfigure_subentry().data.copy()
 
-                options = {
-                    CONF_RECOMMENDED: user_input[CONF_RECOMMENDED],
-                    CONF_PROMPT: user_input[CONF_PROMPT],
-                    CONF_LLM_HASS_API: user_input.get(CONF_LLM_HASS_API),
-                }
+            self.last_rendered_recommended = cast(
+                bool, options.get(CONF_RECOMMENDED, False)
+            )
+
+        elif user_input[CONF_RECOMMENDED] == self.last_rendered_recommended:
+            if not user_input.get(CONF_LLM_HASS_API):
+                user_input.pop(CONF_LLM_HASS_API, None)
+            if user_input.get(
+                CONF_THINKING_BUDGET, RECOMMENDED_THINKING_BUDGET
+            ) >= user_input.get(CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS):
+                errors[CONF_THINKING_BUDGET] = "thinking_budget_too_large"
+
+            if not errors:
+                if self._is_new:
+                    return self.async_create_entry(
+                        title=user_input.pop(CONF_NAME),
+                        data=user_input,
+                    )
+
+                return self.async_update_and_abort(
+                    self._get_entry(),
+                    self._get_reconfigure_subentry(),
+                    data=user_input,
+                )
+
+            options = user_input
+            self.last_rendered_recommended = user_input[CONF_RECOMMENDED]
+        else:
+            # Re-render the options again, now with the recommended options shown/hidden
+            self.last_rendered_recommended = user_input[CONF_RECOMMENDED]
+
+            options = {
+                CONF_RECOMMENDED: user_input[CONF_RECOMMENDED],
+                CONF_PROMPT: user_input[CONF_PROMPT],
+                CONF_LLM_HASS_API: user_input.get(CONF_LLM_HASS_API),
+            }
 
         suggested_values = options.copy()
         if not suggested_values.get(CONF_PROMPT):
@@ -163,19 +202,25 @@ class AnthropicOptionsFlow(OptionsFlow):
             suggested_values[CONF_LLM_HASS_API] = [suggested_llm_apis]
 
         schema = self.add_suggested_values_to_schema(
-            vol.Schema(anthropic_config_option_schema(self.hass, options)),
+            vol.Schema(
+                anthropic_config_option_schema(self.hass, self._is_new, options)
+            ),
             suggested_values,
         )
 
         return self.async_show_form(
-            step_id="init",
+            step_id="set_options",
             data_schema=schema,
             errors=errors or None,
         )
 
+    async_step_user = async_step_set_options
+    async_step_reconfigure = async_step_set_options
+
 
 def anthropic_config_option_schema(
     hass: HomeAssistant,
+    is_new: bool,
     options: Mapping[str, Any],
 ) -> dict:
     """Return a schema for Anthropic completion options."""
@@ -187,15 +232,24 @@ def anthropic_config_option_schema(
         for api in llm.async_get_apis(hass)
     ]
 
-    schema = {
-        vol.Optional(CONF_PROMPT): TemplateSelector(),
-        vol.Optional(
-            CONF_LLM_HASS_API,
-        ): SelectSelector(SelectSelectorConfig(options=hass_apis, multiple=True)),
-        vol.Required(
-            CONF_RECOMMENDED, default=options.get(CONF_RECOMMENDED, False)
-        ): bool,
-    }
+    if is_new:
+        schema: dict[vol.Required | vol.Optional, Any] = {
+            vol.Required(CONF_NAME, default=DEFAULT_CONVERSATION_NAME): str,
+        }
+    else:
+        schema = {}
+
+    schema.update(
+        {
+            vol.Optional(CONF_PROMPT): TemplateSelector(),
+            vol.Optional(
+                CONF_LLM_HASS_API,
+            ): SelectSelector(SelectSelectorConfig(options=hass_apis, multiple=True)),
+            vol.Required(
+                CONF_RECOMMENDED, default=options.get(CONF_RECOMMENDED, False)
+            ): bool,
+        }
+    )
 
     if options.get(CONF_RECOMMENDED):
         return schema

homeassistant/components/anthropic/const.py

@@ -5,6 +5,8 @@ import logging
 DOMAIN = "anthropic"
 LOGGER = logging.getLogger(__package__)
 
+DEFAULT_CONVERSATION_NAME = "Claude conversation"
+
 CONF_RECOMMENDED = "recommended"
 CONF_PROMPT = "prompt"
 CONF_CHAT_MODEL = "chat_model"

homeassistant/components/anthropic/conversation.py

@@ -38,7 +38,7 @@ from anthropic.types import (
 from voluptuous_openapi import convert
 
 from homeassistant.components import conversation
-from homeassistant.config_entries import ConfigEntry
+from homeassistant.config_entries import ConfigEntry, ConfigSubentry
 from homeassistant.const import CONF_LLM_HASS_API, MATCH_ALL
 from homeassistant.core import HomeAssistant
 from homeassistant.exceptions import HomeAssistantError
@@ -72,8 +72,14 @@ async def async_setup_entry(
     async_add_entities: AddConfigEntryEntitiesCallback,
 ) -> None:
     """Set up conversation entities."""
-    agent = AnthropicConversationEntity(config_entry)
-    async_add_entities([agent])
+    for subentry in config_entry.subentries.values():
+        if subentry.subentry_type != "conversation":
+            continue
+
+        async_add_entities(
+            [AnthropicConversationEntity(config_entry, subentry)],
+            config_subentry_id=subentry.subentry_id,
+        )
 
 
 def _format_tool(
@@ -326,21 +332,22 @@ class AnthropicConversationEntity(
 ):
     """Anthropic conversation agent."""
 
-    _attr_has_entity_name = True
-    _attr_name = None
     _attr_supports_streaming = True
 
-    def __init__(self, entry: AnthropicConfigEntry) -> None:
+    def __init__(self, entry: AnthropicConfigEntry, subentry: ConfigSubentry) -> None:
         """Initialize the agent."""
         self.entry = entry
-        self._attr_unique_id = entry.entry_id
+        self.subentry = subentry
+        self._attr_name = subentry.title
+        self._attr_unique_id = subentry.subentry_id
         self._attr_device_info = dr.DeviceInfo(
-            identifiers={(DOMAIN, entry.entry_id)},
+            identifiers={(DOMAIN, subentry.subentry_id)},
+            name=subentry.title,
             manufacturer="Anthropic",
             model="Claude",
             entry_type=dr.DeviceEntryType.SERVICE,
         )
-        if self.entry.options.get(CONF_LLM_HASS_API):
+        if self.subentry.data.get(CONF_LLM_HASS_API):
             self._attr_supported_features = (
                 conversation.ConversationEntityFeature.CONTROL
             )
@@ -363,7 +370,7 @@ class AnthropicConversationEntity(
         chat_log: conversation.ChatLog,
     ) -> conversation.ConversationResult:
         """Call the API."""
-        options = self.entry.options
+        options = self.subentry.data
 
         try:
             await chat_log.async_provide_llm_data(
@@ -393,7 +400,7 @@ class AnthropicConversationEntity(
         chat_log: conversation.ChatLog,
     ) -> None:
         """Generate an answer for the chat log."""
-        options = self.entry.options
+        options = self.subentry.data
 
         tools: list[ToolParam] | None = None
         if chat_log.llm_api:

homeassistant/components/anthropic/strings.json

@@ -12,28 +12,44 @@
       "timeout_connect": "[%key:common::config_flow::error::timeout_connect%]",
       "authentication_error": "[%key:common::config_flow::error::invalid_auth%]",
       "unknown": "[%key:common::config_flow::error::unknown%]"
+    },
+    "abort": {
+      "already_configured": "[%key:common::config_flow::abort::already_configured_service%]"
     }
   },
-  "options": {
-    "step": {
-      "init": {
-        "data": {
-          "prompt": "Instructions",
-          "chat_model": "[%key:common::generic::model%]",
-          "max_tokens": "Maximum tokens to return in response",
-          "temperature": "Temperature",
-          "llm_hass_api": "[%key:common::config_flow::data::llm_hass_api%]",
-          "recommended": "Recommended model settings",
-          "thinking_budget_tokens": "Thinking budget"
-        },
-        "data_description": {
-          "prompt": "Instruct how the LLM should respond. This can be a template.",
-          "thinking_budget_tokens": "The number of tokens the model can use to think about the response out of the total maximum number of tokens. Set to 1024 or greater to enable extended thinking."
+  "config_subentries": {
+    "conversation": {
+      "initiate_flow": {
+        "user": "Add conversation agent",
+        "reconfigure": "Reconfigure conversation agent"
+      },
+      "entry_type": "Conversation agent",
+
+      "step": {
+        "set_options": {
+          "data": {
+            "name": "[%key:common::config_flow::data::name%]",
+            "prompt": "Instructions",
+            "chat_model": "[%key:common::generic::model%]",
+            "max_tokens": "Maximum tokens to return in response",
+            "temperature": "Temperature",
+            "llm_hass_api": "[%key:common::config_flow::data::llm_hass_api%]",
+            "recommended": "Recommended model settings",
+            "thinking_budget_tokens": "Thinking budget"
+          },
+          "data_description": {
+            "prompt": "Instruct how the LLM should respond. This can be a template.",
+            "thinking_budget_tokens": "The number of tokens the model can use to think about the response out of the total maximum number of tokens. Set to 1024 or greater to enable extended thinking."
+          }
         }
+      },
+      "abort": {
+        "reconfigure_successful": "[%key:common::config_flow::abort::reconfigure_successful%]",
+        "entry_not_loaded": "Cannot add things while the configuration is disabled."
+      },
+      "error": {
+        "thinking_budget_too_large": "Maximum tokens must be greater than the thinking budget."
       }
-    },
-    "error": {
-      "thinking_budget_too_large": "Maximum tokens must be greater than the thinking budget."
     }
   }
 }