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First draft
This commit is contained in:
@@ -1 +1,58 @@
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# ha-groq-cloud-api
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# Groq Cloud API integration for Home Assistant 🏠
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This is a custom integration for using Groq Cloud API in the Assist pipeline, reducing the workload on the Home Assistant server.
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Groq Cloud provides multiple models like Llama 3.1, Gemma2, Groq for free! And no card required! (For now...)
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## Requirements 📖
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- An GroqCloud account 👤 --> You can create one [here](https://console.groq.com/login)
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- An `API Key` 🔑 --> You can generate one [here](https://console.groq.com/keys)
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## How to install ⚙️
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Before configuring the integration you must first install the `custom_integration`. You can do it through HACS or manually
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### HACS ✨
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1. **Add** ➕ [this repository](https://my.home-assistant.io/redirect/hacs_repository/?owner=HunorLaczko&repository=ha-groq-api&category=integration) to your HACS repositories:
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- **Click** on this link ⤵️
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[](https://my.home-assistant.io/redirect/hacs_repository/?owner=HunorLaczko&repository=ha-groq-api&category=integration)
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- Or **copy** this url ⤵️ and paste into your HACS custom repostories
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```url
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https://github.com/HunorLaczko/ha-groq-api
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```
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2. **Install** 💻 the `Groq Cloud API` integration
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3. **Restart** 🔁 Home Assistant
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### Manual Install ⌨️
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1. **Download** this repository
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2. **Copy** everything inside the `custom_components` folder into your Home Assistant's `custom_components` folder.
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3. **Restart** Home Assistant
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## Configuration 🔧
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For the options check out the OpenAI Conversation integration [here](https://www.home-assistant.io/integrations/openai_conversation).
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For the available models check out [Groq Cloud](https://console.groq.com/docs/models).
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### Home Assistant Dashboard 💻
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- Configure the integration by **clicking here** ⤵️
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[](https://my.home-assistant.io/redirect/config_flow_start/?domain=groq_cloud_api)
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- Or navigate to your `Devices & services` page and click `+ Add Integration`
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### Acknowledgements
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The code base is mostly identical [OpenAI Conversation integration](https://github.com/home-assistant/core/blob/dev/homeassistant/components/openai_conversation), just using the official Groq library instead of OpenAI.
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The Readme and HACS setup is based on [Fabio's excellent work](https://github.com/fabio-garavini/ha-groq-whisper-stt-api) with the Groq Whisper integration. Check out his other works as well!
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@@ -0,0 +1,52 @@
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"""Groq Cloud API integration."""
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import groq
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from homeassistant.config_entries import ConfigEntry
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from homeassistant.const import CONF_API_KEY, Platform
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from homeassistant.core import HomeAssistant
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from homeassistant.exceptions import ConfigEntryNotReady
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from .const import LOGGER
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PLATFORMS = (Platform.CONVERSATION,)
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type GroqConfigEntry = ConfigEntry[groq.AsyncClient]
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async def async_setup_entry(hass: HomeAssistant, entry: GroqConfigEntry) -> bool:
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"""Load entry."""
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LOGGER.info("Setting up %s", entry)
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client = groq.AsyncGroq(api_key=entry.data[CONF_API_KEY])
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try:
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await hass.async_add_executor_job(client.with_options(timeout=10.0).models.list)
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except groq.AuthenticationError as err:
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LOGGER.error("Invalid API key: %s", err)
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return False
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except groq.GroqError as err:
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raise ConfigEntryNotReady(err) from err
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entry.runtime_data = client
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await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
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entry.async_on_unload(entry.add_update_listener(async_update_listener))
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return True
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async def async_update_listener(hass: HomeAssistant, entry: ConfigEntry):
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"""Update entry."""
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await hass.config_entries.async_reload(entry.entry_id)
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return True
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async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
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"""Unload a config entry."""
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LOGGER.info("Unloading %s", entry)
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return await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
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@@ -0,0 +1,224 @@
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"""Config flow for GroqCloud Whisper integration."""
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from __future__ import annotations
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from typing import Any
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from types import MappingProxyType
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import groq
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import voluptuous as vol
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from homeassistant.core import HomeAssistant
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from homeassistant.config_entries import (
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ConfigEntry,
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ConfigFlow,
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ConfigFlowResult,
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OptionsFlow,
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)
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from homeassistant.const import CONF_API_KEY, CONF_NAME, CONF_LLM_HASS_API
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from homeassistant.helpers import llm
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import homeassistant.helpers.config_validation as cv
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from homeassistant.helpers.selector import (
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NumberSelector,
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NumberSelectorConfig,
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SelectOptionDict,
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SelectSelector,
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SelectSelectorConfig,
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TemplateSelector,
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)
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from . import LOGGER
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from .const import (
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CONF_PROMPT,
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CONF_TEMPERATURE,
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DEFAULT_NAME,
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CONF_CHAT_MODEL,
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CONF_MAX_TOKENS,
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CONF_PROMPT,
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CONF_RECOMMENDED,
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CONF_TEMPERATURE,
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CONF_TOP_P,
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DOMAIN,
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RECOMMENDED_CHAT_MODEL,
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RECOMMENDED_MAX_TOKENS,
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RECOMMENDED_TEMPERATURE,
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RECOMMENDED_TOP_P,
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)
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STEP_USER_DATA_SCHEMA = vol.Schema(
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{
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vol.Required(CONF_NAME, default=DEFAULT_NAME): cv.string,
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vol.Required(CONF_API_KEY): cv.string,
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}
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)
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RECOMMENDED_OPTIONS = {
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CONF_RECOMMENDED: True,
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CONF_LLM_HASS_API: llm.LLM_API_ASSIST,
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CONF_PROMPT: llm.DEFAULT_INSTRUCTIONS_PROMPT,
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}
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async def validate_input(hass: HomeAssistant, data: dict[str, Any]):
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"""Validate the user input allows us to connect.
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Data has the keys from STEP_USER_DATA_SCHEMA with values provided by the user.
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"""
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client = groq.AsyncGroq(api_key=data[CONF_API_KEY])
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await hass.async_add_executor_job(client.with_options(timeout=10.0).models.list)
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class GroqConfigFlow(ConfigFlow, domain=DOMAIN):
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"""Handle UI config flow."""
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VERSION = 1
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MINOR_VERSION = 0
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async def async_step_user(
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self,
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user_input: dict[str, Any] | None = None,
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errors: dict[str, str] | None = None,
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) -> ConfigFlowResult:
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"""Handle initial step."""
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if user_input is None:
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return self.async_show_form(
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step_id="user", data_schema=STEP_USER_DATA_SCHEMA
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)
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errors = {}
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try:
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await validate_input(user_input)
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except groq.APIConnectionError:
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errors["base"] = "cannot_connect"
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except groq.AuthenticationError:
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errors["base"] = "invalid_auth"
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except Exception:
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LOGGER.exception("Unexpected exception")
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errors["base"] = "unknown"
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else:
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return self.async_create_entry(
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title="GroqCloud",
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data=user_input,
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options=RECOMMENDED_OPTIONS,
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)
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return self.async_show_form(
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step_id="user", data_schema=STEP_USER_DATA_SCHEMA, errors=errors
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)
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@staticmethod
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def async_get_options_flow(
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config_entry: ConfigEntry,
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) -> OptionsFlow:
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"""Create the options flow."""
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return GroqOptionsFlow(config_entry)
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class GroqOptionsFlow(OptionsFlow):
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"""Groq Cloud config flow options handler."""
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def __init__(self, config_entry: ConfigEntry) -> None:
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"""Initialize options flow."""
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self.config_entry = config_entry
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self.last_rendered_recommended = config_entry.options.get(
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CONF_RECOMMENDED, False
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)
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async def async_step_init(
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self, user_input: dict[str, Any] | None = None
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) -> ConfigFlowResult:
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"""Manage the options."""
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options: dict[str, Any] | MappingProxyType[str, Any] = self.config_entry.options
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if user_input is not None:
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if user_input[CONF_RECOMMENDED] == self.last_rendered_recommended:
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if user_input[CONF_LLM_HASS_API] == "none":
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user_input.pop(CONF_LLM_HASS_API)
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return self.async_create_entry(title="", data=user_input)
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# Re-render the options again, now with the recommended options shown/hidden
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self.last_rendered_recommended = user_input[CONF_RECOMMENDED]
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options = {
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CONF_RECOMMENDED: user_input[CONF_RECOMMENDED],
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CONF_PROMPT: user_input[CONF_PROMPT],
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CONF_LLM_HASS_API: user_input[CONF_LLM_HASS_API],
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}
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schema = groq_config_option_schema(self.hass, options)
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return self.async_show_form(
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step_id="init",
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data_schema=vol.Schema(schema),
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)
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def groq_config_option_schema(
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hass: HomeAssistant,
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options: dict[str, Any] | MappingProxyType[str, Any],
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) -> dict:
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"""Return a schema for Groq Cloud completion options."""
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hass_apis: list[SelectOptionDict] = [
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SelectOptionDict(
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label="No control",
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value="none",
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)
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]
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hass_apis.extend(
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SelectOptionDict(
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label=api.name,
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value=api.id,
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)
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for api in llm.async_get_apis(hass)
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)
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schema = {
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vol.Optional(
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CONF_PROMPT,
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description={
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"suggested_value": options.get(
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CONF_PROMPT, llm.DEFAULT_INSTRUCTIONS_PROMPT
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)
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},
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): TemplateSelector(),
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vol.Optional(
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CONF_LLM_HASS_API,
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description={"suggested_value": options.get(CONF_LLM_HASS_API)},
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default="none",
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): SelectSelector(SelectSelectorConfig(options=hass_apis)),
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vol.Required(
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CONF_RECOMMENDED, default=options.get(CONF_RECOMMENDED, False)
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): bool,
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}
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if options.get(CONF_RECOMMENDED):
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return schema
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schema.update(
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{
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vol.Optional(
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CONF_CHAT_MODEL,
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description={"suggested_value": options.get(CONF_CHAT_MODEL)},
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default=RECOMMENDED_CHAT_MODEL,
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): str,
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vol.Optional(
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CONF_MAX_TOKENS,
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description={"suggested_value": options.get(CONF_MAX_TOKENS)},
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default=RECOMMENDED_MAX_TOKENS,
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): int,
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vol.Optional(
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CONF_TOP_P,
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description={"suggested_value": options.get(CONF_TOP_P)},
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default=RECOMMENDED_TOP_P,
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): NumberSelector(NumberSelectorConfig(min=0, max=1, step=0.05)),
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vol.Optional(
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CONF_TEMPERATURE,
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description={"suggested_value": options.get(CONF_TEMPERATURE)},
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default=RECOMMENDED_TEMPERATURE,
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): NumberSelector(NumberSelectorConfig(min=0, max=2, step=0.05)),
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}
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)
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return schema
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@@ -0,0 +1,19 @@
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"""Constants for the Groq Cloud API integration."""
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import logging
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DOMAIN = "groq_cloud_api"
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LOGGER = logging.getLogger(__name__)
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DEFAULT_NAME = "Groq Cloud API"
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CONF_RECOMMENDED = "recommended"
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CONF_PROMPT = "prompt"
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CONF_CHAT_MODEL = "chat_model"
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RECOMMENDED_CHAT_MODEL = "llama3-groq-70b-8192-tool-use-preview"
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CONF_MAX_TOKENS = "max_tokens"
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RECOMMENDED_MAX_TOKENS = 150
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CONF_TOP_P = "top_p"
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RECOMMENDED_TOP_P = 1.0
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CONF_TEMPERATURE = "temperature"
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RECOMMENDED_TEMPERATURE = 1.0
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@@ -0,0 +1,332 @@
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"""Conversation support for Groq Cloud."""
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from collections.abc import Callable
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import json
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from typing import Any, Literal
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import groq
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from groq._types import NOT_GIVEN
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from groq.types.chat import (
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ChatCompletionAssistantMessageParam,
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ChatCompletionMessage,
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ChatCompletionMessageParam,
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ChatCompletionMessageToolCallParam,
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ChatCompletionSystemMessageParam,
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ChatCompletionToolMessageParam,
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ChatCompletionToolParam,
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ChatCompletionUserMessageParam,
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)
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from groq.types.chat.chat_completion_message_tool_call_param import Function
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from groq.types.shared_params import FunctionDefinition
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import voluptuous as vol
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from voluptuous_openapi import convert
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from homeassistant.components import assist_pipeline, conversation
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from homeassistant.components.conversation import trace
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from homeassistant.config_entries import ConfigEntry
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from homeassistant.const import CONF_LLM_HASS_API, MATCH_ALL
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from homeassistant.core import HomeAssistant
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from homeassistant.exceptions import HomeAssistantError, TemplateError
|
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from homeassistant.helpers import device_registry as dr, intent, llm, template
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||||
from homeassistant.helpers.entity_platform import AddEntitiesCallback
|
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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
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||||
|
||||
|
||||
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}"
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user