First draft

This commit is contained in:
2024-08-25 17:18:49 +02:00
parent 81c591c769
commit 56942b11de
9 changed files with 785 additions and 1 deletions
@@ -0,0 +1,52 @@
"""Groq Cloud API integration."""
import groq
from homeassistant.config_entries import ConfigEntry
from homeassistant.const import CONF_API_KEY, Platform
from homeassistant.core import HomeAssistant
from homeassistant.exceptions import ConfigEntryNotReady
from .const import LOGGER
PLATFORMS = (Platform.CONVERSATION,)
type GroqConfigEntry = ConfigEntry[groq.AsyncClient]
async def async_setup_entry(hass: HomeAssistant, entry: GroqConfigEntry) -> bool:
"""Load entry."""
LOGGER.info("Setting up %s", entry)
client = groq.AsyncGroq(api_key=entry.data[CONF_API_KEY])
try:
await hass.async_add_executor_job(client.with_options(timeout=10.0).models.list)
except groq.AuthenticationError as err:
LOGGER.error("Invalid API key: %s", err)
return False
except groq.GroqError as err:
raise ConfigEntryNotReady(err) from err
entry.runtime_data = client
await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
entry.async_on_unload(entry.add_update_listener(async_update_listener))
return True
async def async_update_listener(hass: HomeAssistant, entry: ConfigEntry):
"""Update entry."""
await hass.config_entries.async_reload(entry.entry_id)
return True
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry."""
LOGGER.info("Unloading %s", entry)
return await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
@@ -0,0 +1,224 @@
"""Config flow for GroqCloud Whisper integration."""
from __future__ import annotations
from typing import Any
from types import MappingProxyType
import groq
import voluptuous as vol
from homeassistant.core import HomeAssistant
from homeassistant.config_entries import (
ConfigEntry,
ConfigFlow,
ConfigFlowResult,
OptionsFlow,
)
from homeassistant.const import CONF_API_KEY, CONF_NAME, CONF_LLM_HASS_API
from homeassistant.helpers import llm
import homeassistant.helpers.config_validation as cv
from homeassistant.helpers.selector import (
NumberSelector,
NumberSelectorConfig,
SelectOptionDict,
SelectSelector,
SelectSelectorConfig,
TemplateSelector,
)
from . import LOGGER
from .const import (
CONF_PROMPT,
CONF_TEMPERATURE,
DEFAULT_NAME,
CONF_CHAT_MODEL,
CONF_MAX_TOKENS,
CONF_PROMPT,
CONF_RECOMMENDED,
CONF_TEMPERATURE,
CONF_TOP_P,
DOMAIN,
RECOMMENDED_CHAT_MODEL,
RECOMMENDED_MAX_TOKENS,
RECOMMENDED_TEMPERATURE,
RECOMMENDED_TOP_P,
)
STEP_USER_DATA_SCHEMA = vol.Schema(
{
vol.Required(CONF_NAME, default=DEFAULT_NAME): cv.string,
vol.Required(CONF_API_KEY): cv.string,
}
)
RECOMMENDED_OPTIONS = {
CONF_RECOMMENDED: True,
CONF_LLM_HASS_API: llm.LLM_API_ASSIST,
CONF_PROMPT: llm.DEFAULT_INSTRUCTIONS_PROMPT,
}
async def validate_input(hass: HomeAssistant, data: dict[str, Any]):
"""Validate the user input allows us to connect.
Data has the keys from STEP_USER_DATA_SCHEMA with values provided by the user.
"""
client = groq.AsyncGroq(api_key=data[CONF_API_KEY])
await hass.async_add_executor_job(client.with_options(timeout=10.0).models.list)
class GroqConfigFlow(ConfigFlow, domain=DOMAIN):
"""Handle UI config flow."""
VERSION = 1
MINOR_VERSION = 0
async def async_step_user(
self,
user_input: dict[str, Any] | None = None,
errors: dict[str, str] | None = None,
) -> ConfigFlowResult:
"""Handle initial step."""
if user_input is None:
return self.async_show_form(
step_id="user", data_schema=STEP_USER_DATA_SCHEMA
)
errors = {}
try:
await validate_input(user_input)
except groq.APIConnectionError:
errors["base"] = "cannot_connect"
except groq.AuthenticationError:
errors["base"] = "invalid_auth"
except Exception:
LOGGER.exception("Unexpected exception")
errors["base"] = "unknown"
else:
return self.async_create_entry(
title="GroqCloud",
data=user_input,
options=RECOMMENDED_OPTIONS,
)
return self.async_show_form(
step_id="user", data_schema=STEP_USER_DATA_SCHEMA, errors=errors
)
@staticmethod
def async_get_options_flow(
config_entry: ConfigEntry,
) -> OptionsFlow:
"""Create the options flow."""
return GroqOptionsFlow(config_entry)
class GroqOptionsFlow(OptionsFlow):
"""Groq Cloud config flow options handler."""
def __init__(self, config_entry: ConfigEntry) -> None:
"""Initialize options flow."""
self.config_entry = config_entry
self.last_rendered_recommended = config_entry.options.get(
CONF_RECOMMENDED, False
)
async def async_step_init(
self, user_input: dict[str, Any] | None = None
) -> ConfigFlowResult:
"""Manage the options."""
options: dict[str, Any] | MappingProxyType[str, Any] = self.config_entry.options
if user_input is not None:
if user_input[CONF_RECOMMENDED] == self.last_rendered_recommended:
if user_input[CONF_LLM_HASS_API] == "none":
user_input.pop(CONF_LLM_HASS_API)
return self.async_create_entry(title="", data=user_input)
# 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[CONF_LLM_HASS_API],
}
schema = groq_config_option_schema(self.hass, options)
return self.async_show_form(
step_id="init",
data_schema=vol.Schema(schema),
)
def groq_config_option_schema(
hass: HomeAssistant,
options: dict[str, Any] | MappingProxyType[str, Any],
) -> dict:
"""Return a schema for Groq Cloud completion options."""
hass_apis: list[SelectOptionDict] = [
SelectOptionDict(
label="No control",
value="none",
)
]
hass_apis.extend(
SelectOptionDict(
label=api.name,
value=api.id,
)
for api in llm.async_get_apis(hass)
)
schema = {
vol.Optional(
CONF_PROMPT,
description={
"suggested_value": options.get(
CONF_PROMPT, llm.DEFAULT_INSTRUCTIONS_PROMPT
)
},
): TemplateSelector(),
vol.Optional(
CONF_LLM_HASS_API,
description={"suggested_value": options.get(CONF_LLM_HASS_API)},
default="none",
): SelectSelector(SelectSelectorConfig(options=hass_apis)),
vol.Required(
CONF_RECOMMENDED, default=options.get(CONF_RECOMMENDED, False)
): bool,
}
if options.get(CONF_RECOMMENDED):
return schema
schema.update(
{
vol.Optional(
CONF_CHAT_MODEL,
description={"suggested_value": options.get(CONF_CHAT_MODEL)},
default=RECOMMENDED_CHAT_MODEL,
): str,
vol.Optional(
CONF_MAX_TOKENS,
description={"suggested_value": options.get(CONF_MAX_TOKENS)},
default=RECOMMENDED_MAX_TOKENS,
): int,
vol.Optional(
CONF_TOP_P,
description={"suggested_value": options.get(CONF_TOP_P)},
default=RECOMMENDED_TOP_P,
): NumberSelector(NumberSelectorConfig(min=0, max=1, step=0.05)),
vol.Optional(
CONF_TEMPERATURE,
description={"suggested_value": options.get(CONF_TEMPERATURE)},
default=RECOMMENDED_TEMPERATURE,
): NumberSelector(NumberSelectorConfig(min=0, max=2, step=0.05)),
}
)
return schema
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"""Constants for the Groq Cloud API integration."""
import logging
DOMAIN = "groq_cloud_api"
LOGGER = logging.getLogger(__name__)
DEFAULT_NAME = "Groq Cloud API"
CONF_RECOMMENDED = "recommended"
CONF_PROMPT = "prompt"
CONF_CHAT_MODEL = "chat_model"
RECOMMENDED_CHAT_MODEL = "llama3-groq-70b-8192-tool-use-preview"
CONF_MAX_TOKENS = "max_tokens"
RECOMMENDED_MAX_TOKENS = 150
CONF_TOP_P = "top_p"
RECOMMENDED_TOP_P = 1.0
CONF_TEMPERATURE = "temperature"
RECOMMENDED_TEMPERATURE = 1.0
@@ -0,0 +1,332 @@
"""Conversation support for Groq Cloud."""
from collections.abc import Callable
import json
from typing import Any, Literal
import groq
from groq._types import NOT_GIVEN
from groq.types.chat import (
ChatCompletionAssistantMessageParam,
ChatCompletionMessage,
ChatCompletionMessageParam,
ChatCompletionMessageToolCallParam,
ChatCompletionSystemMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionToolParam,
ChatCompletionUserMessageParam,
)
from groq.types.chat.chat_completion_message_tool_call_param import Function
from groq.types.shared_params import FunctionDefinition
import voluptuous as vol
from voluptuous_openapi import convert
from homeassistant.components import assist_pipeline, 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.helpers.entity_platform import AddEntitiesCallback
from homeassistant.util import ulid
from . import GroqConfigEntry
from .const import (
CONF_CHAT_MODEL,
CONF_MAX_TOKENS,
CONF_PROMPT,
CONF_TEMPERATURE,
CONF_TOP_P,
DOMAIN,
LOGGER,
RECOMMENDED_CHAT_MODEL,
RECOMMENDED_MAX_TOKENS,
RECOMMENDED_TEMPERATURE,
RECOMMENDED_TOP_P,
)
# Max number of back and forth with the LLM to generate a response
MAX_TOOL_ITERATIONS = 10
async def async_setup_entry(
hass: HomeAssistant,
config_entry: GroqConfigEntry,
async_add_entities: AddEntitiesCallback,
) -> None:
"""Set up conversation entities."""
agent = GroqConversationEntity(config_entry)
async_add_entities([agent])
def _format_tool(
tool: llm.Tool, custom_serializer: Callable[[Any], Any] | None
) -> ChatCompletionToolParam:
"""Format tool specification."""
tool_spec = FunctionDefinition(
name=tool.name,
parameters=convert(tool.parameters, custom_serializer=custom_serializer),
)
if tool.description:
tool_spec["description"] = tool.description
return ChatCompletionToolParam(type="function", function=tool_spec)
class GroqConversationEntity(
conversation.ConversationEntity, conversation.AbstractConversationAgent
):
"""Groq conversation agent."""
_attr_has_entity_name = True
_attr_name = None
def __init__(self, entry: GroqConfigEntry) -> None:
"""Initialize the agent."""
self.entry = entry
self.history: dict[str, list[ChatCompletionMessageParam]] = {}
self._attr_unique_id = entry.entry_id
self._attr_device_info = dr.DeviceInfo(
identifiers={(DOMAIN, entry.entry_id)},
name=entry.title,
manufacturer="Groq",
model="Groq Cloud",
entry_type=dr.DeviceEntryType.SERVICE,
)
if self.entry.options.get(CONF_LLM_HASS_API):
self._attr_supported_features = (
conversation.ConversationEntityFeature.CONTROL
)
@property
def supported_languages(self) -> list[str] | Literal["*"]:
"""Return a list of supported languages."""
return MATCH_ALL
async def async_added_to_hass(self) -> None:
"""When entity is added to Home Assistant."""
await super().async_added_to_hass()
assist_pipeline.async_migrate_engine(
self.hass, "conversation", self.entry.entry_id, self.entity_id
)
conversation.async_set_agent(self.hass, self.entry, self)
self.entry.async_on_unload(
self.entry.add_update_listener(self._async_entry_update_listener)
)
async def async_will_remove_from_hass(self) -> None:
"""When entity will be removed from Home Assistant."""
conversation.async_unset_agent(self.hass, self.entry)
await super().async_will_remove_from_hass()
async def async_process(
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[ChatCompletionToolParam] | 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.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.ulid_to_bytes(user_input.conversation_id)
conversation_id = ulid.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)
)
):
user_name = user.name
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,
)
]
except TemplateError as err:
LOGGER.error("Error rendering prompt: %s", err)
intent_response = intent.IntentResponse(language=user_input.language)
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 = [
ChatCompletionSystemMessageParam(role="system", content=prompt),
*messages[1:],
ChatCompletionUserMessageParam(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,
{"messages": messages, "tools": llm_api.tools if llm_api else None},
)
client = self.entry.runtime_data
# To prevent infinite loops, we limit the number of iterations
for _iteration in range(MAX_TOOL_ITERATIONS):
try:
result = await client.chat.completions.create(
model=options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL),
messages=messages,
tools=tools or NOT_GIVEN,
max_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=conversation_id,
)
except groq.GroqError as err:
intent_response = intent.IntentResponse(language=user_input.language)
intent_response.async_set_error(
intent.IntentResponseErrorCode.UNKNOWN,
f"Sorry, I had a problem talking to Groq: {err}",
)
return conversation.ConversationResult(
response=intent_response, conversation_id=conversation_id
)
LOGGER.debug("Response %s", result)
response = result.choices[0].message
def message_convert(
message: ChatCompletionMessage,
) -> ChatCompletionMessageParam:
"""Convert from class to TypedDict."""
tool_calls: list[ChatCompletionMessageToolCallParam] = []
if message.tool_calls:
tool_calls = [
ChatCompletionMessageToolCallParam(
id=tool_call.id,
function=Function(
arguments=tool_call.function.arguments,
name=tool_call.function.name,
),
type=tool_call.type,
)
for tool_call in message.tool_calls
]
param = ChatCompletionAssistantMessageParam(
role=message.role,
content=message.content,
)
if tool_calls:
param["tool_calls"] = tool_calls
return param
messages.append(message_convert(response))
tool_calls = response.tool_calls
if not tool_calls or not llm_api:
break
for tool_call in tool_calls:
tool_input = llm.ToolInput(
tool_name=tool_call.function.name,
tool_args=json.loads(tool_call.function.arguments),
)
LOGGER.debug(
"Tool call: %s(%s)", tool_input.tool_name, tool_input.tool_args
)
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)
messages.append(
ChatCompletionToolMessageParam(
role="tool",
tool_call_id=tool_call.id,
content=json.dumps(tool_response),
)
)
self.history[conversation_id] = messages
intent_response = intent.IntentResponse(language=user_input.language)
intent_response.async_set_speech(response.content or "")
return conversation.ConversationResult(
response=intent_response, conversation_id=conversation_id
)
async def _async_entry_update_listener(
self, hass: HomeAssistant, entry: ConfigEntry
) -> None:
"""Handle options update."""
# Reload as we update device info + entity name + supported features
await hass.config_entries.async_reload(entry.entry_id)
@@ -0,0 +1,17 @@
{
"domain": "groq_cloud_api",
"name": "Groq Cloud API",
"version": "0.0.1",
"codeowners": [
"@HunorLaczko"
],
"config_flow": true,
"dependencies": [],
"documentation": "https://github.com/HunorLaczko/ha-groq-cloud-api",
"issue_tracker": "https://github.com/HunorLaczko/ha-groq-cloud-api/issues",
"homekit": {},
"iot_class": "cloud_push",
"requirements": [],
"ssdp": [],
"zeroconf": []
}
@@ -0,0 +1,39 @@
{
"config": {
"step": {
"user": {
"data": {
"api_key": "[%key:common::config_flow::data::api_key%]"
}
}
},
"error": {
"cannot_connect": "[%key:common::config_flow::error::cannot_connect%]",
"invalid_auth": "[%key:common::config_flow::error::invalid_auth%]",
"unknown": "[%key:common::config_flow::error::unknown%]"
}
},
"options": {
"step": {
"init": {
"data": {
"prompt": "Instructions",
"chat_model": "[%key:common::generic::model%]",
"max_tokens": "Maximum tokens to return in response",
"temperature": "Temperature",
"top_p": "Top P",
"llm_hass_api": "[%key:common::config_flow::data::llm_hass_api%]",
"recommended": "Recommended model settings"
},
"data_description": {
"prompt": "Instruct how the LLM should respond. This can be a template."
}
}
}
},
"exceptions": {
"invalid_config_entry": {
"message": "Invalid config entry provided. Got {config_entry}"
}
}
}
@@ -0,0 +1,39 @@
{
"config": {
"step": {
"user": {
"data": {
"api_key": "[%key:common::config_flow::data::api_key%]"
}
}
},
"error": {
"cannot_connect": "[%key:common::config_flow::error::cannot_connect%]",
"invalid_auth": "[%key:common::config_flow::error::invalid_auth%]",
"unknown": "[%key:common::config_flow::error::unknown%]"
}
},
"options": {
"step": {
"init": {
"data": {
"prompt": "Utasítások",
"chat_model": "[%key:common::generic::model%]",
"max_tokens": "Válaszban visszatérítendő maximális tokenek száma",
"temperature": "Hőmérséklet",
"top_p": "Top P",
"llm_hass_api": "[%key:common::config_flow::data::llm_hass_api%]",
"recommended": "Ajánlott modellbeállítások"
},
"data_description": {
"prompt": "Add meg, hogy LLM hogyan reagáljon. Ez egy sablon is lehet."
}
}
}
},
"exceptions": {
"invalid_config_entry": {
"message": "Érvénytelen beállítás megadva. Ezt kaptam: {config_entry}"
}
}
}