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14 Commits
Author SHA1 Message Date
SMKRV f6bfbd4a07 Release v1.0.8 2024-11-19 17:02:38 +03:00
SMKRV 4ddb0dc977 Translation fixes 2024-11-19 16:59:42 +03:00
SMKRV 24dc4ac4d4 Hotfix 2024-11-19 16:53:27 +03:00
SMKRV 976f4f16a3 translation fixes 2024-11-19 16:40:56 +03:00
SMKRV 2bdef2b494 Main changes:
Created global SSL_CONTEXT at module level
Removed blocking create_default_context calls from async functions
Optimized aiohttp.ClientSession handling:
Using single connector with SSL context
Session is created once for all requests in validate_api_connection
Improved resource management:
Automatic session closure using context managers
More efficient connection handling
These changes should eliminate the blocking call warning and improve
overall code performance.
2024-11-19 16:33:30 +03:00
SMKRV 42324a793b bufix 2024-11-19 16:25:44 +03:00
SMKRV 30aa894634 Release v1.0.6 2024-11-19 15:10:06 +03:00
SMKRV 398b2550a9 Release v1.0.5 2024-11-19 14:46:12 +03:00
SMKRV f1deaa2014 Release v1.0.4 2024-11-19 14:35:45 +03:00
SMKRV f4b0ce902e Release v1.0.3 2024-11-19 14:06:32 +03:00
SMKRV d899144149 Release v1.0.3 2024-11-19 14:00:33 +03:00
SMKRV 5d49b4a40b Release v1.0.2 2024-11-19 13:16:14 +03:00
SMKRV 1a84727cf1 Release v1.0.2 2024-11-19 13:14:00 +03:00
SMKRV d3c7e25202 Release v1.0.2 2024-11-19 13:12:41 +03:00
13 changed files with 928 additions and 443 deletions
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@@ -7,154 +7,250 @@
![GitHub stars](https://img.shields.io/github/stars/smkrv/ha-text-ai.svg?style=social) ![GitHub stars](https://img.shields.io/github/stars/smkrv/ha-text-ai.svg?style=social)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT)
[![hacs_badge](https://img.shields.io/badge/HACS-Default-orange.svg?style=flat-square)](https://github.com/hacs/integration)
[![Community Forum](https://img.shields.io/badge/Community-Forum-blue.svg?style=flat-square)](https://community.home-assistant.io/t/ha-text-ai-integration)
</div> </div>
<p align="center"> <p align="center">
Transform your smart home experience with powerful AI assistance powered by OpenAI's GPT models Transform your smart home experience with powerful AI assistance powered by OpenAI's GPT models. Get intelligent responses, automate complex scenarios, and enhance your home automation with natural language processing.
</p> </p>
--- ---
## 🌟 Features ## 🌟 Features
- 🧠 **Advanced AI Integration**: Leverage OpenAI's powerful models (GPT-3.5, GPT-4) for smart home interactions - 🧠 **Advanced AI Integration**:
- 💬 **Natural Language Control**: Control your home and get information using everyday language - Support for latest GPT models
- 📝 **Conversation Memory**: Maintain context with conversation history tracking - Context-aware responses
-**Real-time Responses**: Get quick, contextual responses to your queries - Multi-turn conversations
- 🎯 **Customizable Behavior**: Fine-tune AI responses with adjustable parameters - 💬 **Natural Language Control**:
- 🔒 **Secure Integration**: Your API key and data are handled securely - Control devices using everyday language
- 🎨 **Flexible Configuration**: Easy setup with multiple configuration options - Get detailed explanations and recommendations
- 🔄 **Automation Ready**: Integrate AI responses into your automations - Natural conversation flow
- 📝 **Smart Memory Management**:
- Persistent conversation history
- Context-aware responses
- Customizable history limits
-**Performance Optimized**:
- Efficient token usage
- Rate limit handling
- Response caching
- 🎯 **Advanced Customization**:
- Adjustable response parameters
- Custom system prompts
- Model selection per request
- 🔒 **Enhanced Security**:
- Secure API key storage
- Rate limiting protection
- Error handling
- 🎨 **User Experience**:
- Intuitive configuration UI
- Detailed sensor attributes
- Rich service interface
- 🔄 **Automation Integration**:
- Event-driven responses
- Conditional logic support
- Template compatibility
## 📋 Prerequisites ## 📋 Prerequisites
- Home Assistant installation (Core, OS, Container, or Supervised) - Home Assistant 2023.8.0 or newer
- OpenAI API key ([Get one here](https://platform.openai.com/account/api-keys)) - OpenAI API key ([Get one here](https://platform.openai.com/account/api-keys))
- Python 3.9 or newer - Python 3.9 or newer
- Stable internet connection
## ⚡ Quick Start ## ⚡ Installation
### HACS Installation (Recommended)
1. Open HACS in Home Assistant
2. Click the "+" button
3. Search for "HA Text AI"
4. Click "Install"
5. Restart Home Assistant
### Manual Installation ### Manual Installation
1. Download the repository 1. Download the latest release
2. Copy `custom_components/ha_text_ai` to your `custom_components` directory 2. Extract and copy `custom_components/ha_text_ai` to your `custom_components` directory
3. Restart Home Assistant 3. Restart Home Assistant
4. Add configuration to `configuration.yaml`: 4. Add configuration via UI or YAML
## ⚙️ Configuration
### Via UI (Recommended)
1. Go to Settings → Devices & Services
2. Click "Add Integration"
3. Search for "HA Text AI"
4. Follow the configuration steps
### Via YAML
```yaml ```yaml
ha_text_ai: ha_text_ai:
api_key: !secret openai_api_key api_key: !secret openai_api_key
model: gpt-3.5-turbo
temperature: 0.7
max_tokens: 1000
request_interval: 1.0
api_endpoint: https://api.openai.com/v1 # optional
``` ```
## ⚙️ Configuration Options
| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `api_key` | string | Required | Your OpenAI API key |
| `model` | string | `gpt-3.5-turbo` | AI model to use |
| `temperature` | float | `0.7` | Response creativity (0-2) |
| `max_tokens` | integer | `1000` | Maximum response length |
| `request_interval` | float | `1.0` | Minimum seconds between requests |
| `api_endpoint` | string | OpenAI default | Custom API endpoint URL |
## 🛠️ Available Services ## 🛠️ Available Services
### ask_question ### ask_question
Ask the AI assistant a question:
```yaml ```yaml
service: ha_text_ai.ask_question service: ha_text_ai.ask_question
data: data:
question: "What's the optimal temperature for sleeping?" question: "What's the optimal temperature for sleeping?"
model: "gpt-4" # optional model: "gpt-4o" # optional
temperature: 0.5 # optional temperature: 0.5 # optional
max_tokens: 500 # optional max_tokens: 500 # optional
``` ```
### set_system_prompt ### set_system_prompt
Configure AI behavior:
```yaml ```yaml
service: ha_text_ai.set_system_prompt service: ha_text_ai.set_system_prompt
data: data:
prompt: "You are a home automation expert focused on energy efficiency" prompt: |
You are a home automation expert focused on:
1. Energy efficiency
2. Comfort optimization
3. Security considerations
Provide practical, actionable advice.
``` ```
### clear_history ### clear_history
Reset conversation history:
```yaml ```yaml
service: ha_text_ai.clear_history service: ha_text_ai.clear_history
``` ```
### get_history ### get_history
Retrieve conversation history:
```yaml ```yaml
service: ha_text_ai.get_history service: ha_text_ai.get_history
data: data:
limit: 5 # optional limit: 5 # optional
``` ```
## 🔧 Practical Examples ## 🔧 Advanced Examples
### Smart Temperature Management ### Smart Energy Management
```yaml ```yaml
automation: automation:
alias: "AI Energy Optimization"
trigger: trigger:
platform: time_pattern platform: time_pattern
hours: "/1" hours: "/2"
action: action:
service: ha_text_ai.ask_question - service: ha_text_ai.ask_question
data: data:
question: > question: >
Current temperature is {{ states('sensor.living_room_temperature') }}°C. Current power usage: {{ states('sensor.total_power') }}W
Should I adjust the thermostat for optimal comfort and energy savings? Temperature: {{ states('sensor.indoor_temperature') }}°C
Time: {{ now().strftime('%H:%M') }}
Occupancy: {{ states('binary_sensor.occupancy') }}
Analyze current energy usage and suggest optimizations
considering comfort and efficiency.
temperature: 0.3
max_tokens: 200
- service: notify.mobile_app
data:
message: "{{ states.sensor.ha_text_ai.attributes.response }}"
``` ```
### Smart Lighting Assistant ### Contextual Lighting Control
```yaml ```yaml
automation: automation:
alias: "AI Lighting Assistant"
trigger: trigger:
platform: state platform: state
entity_id: binary_sensor.living_room_motion entity_id: binary_sensor.motion
to: 'on' variables:
condition: context: >
condition: template Time: {{ now().strftime('%H:%M') }}
value_template: "{{ states('sensor.illuminance') | float < 10 }}" Light Level: {{ states('sensor.illuminance') }}
Room: {{ trigger.to_state.attributes.room }}
Activity: {{ states('input_select.current_activity') }}
Weather: {{ states('weather.home') }}
action: action:
service: ha_text_ai.ask_question - service: ha_text_ai.ask_question
data: data:
question: > question: >
Motion detected in living room with low light levels. Based on this context:
What's the best lighting scene to set based on the time of day? {{ context }}
Suggest optimal lighting settings for current conditions.
model: gpt-3.5-turbo
temperature: 0.4
- service: scene.turn_on
data:
entity_id: >
{{ states.sensor.ha_text_ai.attributes.response | regex_findall('scene\.[a-z_]+') | first }}
``` ```
## ❗ Common Issues ## 📊 Performance Optimization
### API Rate Limits ### Token Usage
- Increase `request_interval` if hitting rate limits
- Consider upgrading your OpenAI plan
- Use caching for frequent queries
### High Token Usage
- Reduce `max_tokens` parameter
- Clear conversation history regularly
- Use focused system prompts - Use focused system prompts
- Implement response caching
- Clear history periodically
- Monitor token usage
### Connection Issues ### Response Time
- Check internet connectivity - Adjust request_interval
- Use faster models for simple queries
- Implement timeout handling
- Cache frequent responses
### Memory Management
- Set appropriate history limits
- Clear unused contexts
- Monitor memory usage
- Use efficient data structures
## ❗ Troubleshooting
### API Issues
- Verify API key validity - Verify API key validity
- Ensure endpoint accessibility - Check rate limits
- Monitor usage quotas
- Test endpoint accessibility
### Performance Issues
- Reduce max_tokens
- Increase request_interval
- Clear conversation history
- Check network connectivity
### Integration Issues
- Verify HA version compatibility
- Check component dependencies
- Review log files
- Update configuration
## 📘 FAQ
**Q: How can I reduce API costs?**
A: Use GPT-3.5-Turbo for most queries, implement caching, and optimize token usage.
**Q: Is my data secure?**
A: Yes, API keys are stored securely and data is transmitted via encrypted connections.
**Q: Can I use custom models?**
A: Yes, configure custom endpoints and models via configuration options.
## 🤝 Contributing ## 🤝 Contributing
Contributions are welcome! Please feel free to submit a Pull Request. Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
1. Fork the repository 1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`) 2. Create feature branch (`git checkout -b feature/Enhancement`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`) 3. Commit changes (`git commit -m 'Add Enhancement'`)
4. Push to the branch (`git push origin feature/AmazingFeature`) 4. Push branch (`git push origin feature/Enhancement`)
5. Open a Pull Request 5. Open Pull Request
## 📝 License ## 📝 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. MIT License - see [LICENSE](LICENSE) for details.
--- ---
@@ -162,4 +258,6 @@ This project is licensed under the MIT License - see the [LICENSE](LICENSE) file
Made with ❤️ for the Home Assistant Community Made with ❤️ for the Home Assistant Community
[Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues)
</div> </div>
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"""The HA text AI integration.""" """The HA Text AI integration."""
import logging import logging
from typing import Any from typing import Any
import voluptuous as vol
from homeassistant.config_entries import ConfigEntry from homeassistant.config_entries import ConfigEntry
from homeassistant.const import CONF_API_KEY from homeassistant.const import CONF_API_KEY
from homeassistant.core import HomeAssistant, ServiceCall from homeassistant.core import HomeAssistant
import homeassistant.helpers.config_validation as cv from homeassistant.exceptions import ConfigEntryNotReady
from homeassistant.exceptions import HomeAssistantError, ConfigEntryNotReady from homeassistant.helpers import aiohttp_client
from homeassistant.helpers import config_validation as cv
from .const import ( from .const import (
DOMAIN, DOMAIN,
PLATFORMS, PLATFORMS,
SERVICE_ASK_QUESTION,
SERVICE_CLEAR_HISTORY,
SERVICE_GET_HISTORY,
SERVICE_SET_SYSTEM_PROMPT,
CONF_MODEL, CONF_MODEL,
CONF_TEMPERATURE, CONF_TEMPERATURE,
CONF_MAX_TOKENS, CONF_MAX_TOKENS,
CONF_API_ENDPOINT, CONF_API_ENDPOINT,
CONF_REQUEST_INTERVAL, CONF_REQUEST_INTERVAL,
DEFAULT_MODEL,
DEFAULT_TEMPERATURE,
DEFAULT_MAX_TOKENS,
DEFAULT_API_ENDPOINT,
DEFAULT_REQUEST_INTERVAL,
) )
from .coordinator import HATextAICoordinator
_LOGGER = logging.getLogger(__name__) _LOGGER = logging.getLogger(__name__)
CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
CONFIG_SCHEMA = vol.Schema(
{
DOMAIN: vol.Schema(
{
vol.Required(CONF_API_KEY): cv.string,
vol.Optional(CONF_MODEL, default="gpt-3.5-turbo"): cv.string,
vol.Optional(CONF_TEMPERATURE, default=0.7): vol.Coerce(float),
vol.Optional(CONF_MAX_TOKENS, default=1000): vol.Coerce(int),
vol.Optional(CONF_REQUEST_INTERVAL, default=1.0): vol.Coerce(float),
vol.Optional(CONF_API_ENDPOINT): cv.string,
}
)
},
extra=vol.ALLOW_EXTRA,
)
async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool: async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool:
"""Set up the HA text AI component.""" """Set up the HA Text AI component."""
hass.data.setdefault(DOMAIN, {}) hass.data.setdefault(DOMAIN, {})
async def async_ask_question(call: ServiceCall) -> None:
"""Handle the ask_question service call."""
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
question = call.data["question"]
original_params = {
"model": coordinator.model,
"temperature": coordinator.temperature,
"max_tokens": coordinator.max_tokens
}
try:
if "model" in call.data:
coordinator.model = call.data["model"]
if "temperature" in call.data:
coordinator.temperature = call.data["temperature"]
if "max_tokens" in call.data:
coordinator.max_tokens = call.data["max_tokens"]
await coordinator.async_ask_question(question)
except Exception as ex:
_LOGGER.error("Error asking question: %s", str(ex))
raise HomeAssistantError(f"Failed to ask question: {str(ex)}") from ex
finally:
coordinator.model = original_params["model"]
coordinator.temperature = original_params["temperature"]
coordinator.max_tokens = original_params["max_tokens"]
async def async_clear_history(call: ServiceCall) -> None:
"""Handle the clear_history service call."""
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
coordinator._responses.clear()
await coordinator.async_refresh()
async def async_get_history(call: ServiceCall) -> dict[str, list]:
"""Handle the get_history service call."""
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
if not coordinator._responses:
return {"history": []}
limit = call.data.get("limit", 10)
history = list(coordinator._responses.items())
limited_history = history[-limit:] if len(history) > limit else history
return {
"history": [
{"question": q, "response": r} for q, r in limited_history
]
}
async def async_set_system_prompt(call: ServiceCall) -> None:
"""Handle the set_system_prompt service call."""
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
coordinator.system_prompt = call.data["prompt"]
hass.services.async_register(
DOMAIN,
SERVICE_ASK_QUESTION,
async_ask_question,
schema=vol.Schema({
vol.Required("question"): cv.string,
vol.Optional("model"): cv.string,
vol.Optional("temperature"): vol.All(
vol.Coerce(float), vol.Range(min=0, max=2)
),
vol.Optional("max_tokens"): vol.All(
vol.Coerce(int), vol.Range(min=1, max=4096)
),
})
)
hass.services.async_register(
DOMAIN,
SERVICE_CLEAR_HISTORY,
async_clear_history,
schema=vol.Schema({})
)
hass.services.async_register(
DOMAIN,
SERVICE_GET_HISTORY,
async_get_history,
schema=vol.Schema({
vol.Optional("limit", default=10): vol.All(
vol.Coerce(int), vol.Range(min=1)
),
})
)
hass.services.async_register(
DOMAIN,
SERVICE_SET_SYSTEM_PROMPT,
async_set_system_prompt,
schema=vol.Schema({
vol.Required("prompt"): cv.string,
})
)
return True return True
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool: async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Set up HA text AI from a config entry.""" """Set up HA Text AI from a config entry."""
try: try:
session = aiohttp_client.async_get_clientsession(hass)
coordinator = HATextAICoordinator( coordinator = HATextAICoordinator(
hass, hass,
api_key=entry.data[CONF_API_KEY], api_key=entry.data[CONF_API_KEY],
endpoint=entry.data.get(CONF_API_ENDPOINT), endpoint=entry.data.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT),
model=entry.data.get(CONF_MODEL), model=entry.data.get(CONF_MODEL, DEFAULT_MODEL),
temperature=entry.data.get(CONF_TEMPERATURE), temperature=entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
max_tokens=entry.data.get(CONF_MAX_TOKENS), max_tokens=entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
request_interval=entry.data.get(CONF_REQUEST_INTERVAL), request_interval=entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
session=session,
) )
await coordinator.async_config_entry_first_refresh() try:
await coordinator.async_config_entry_first_refresh()
except Exception as refresh_ex:
_LOGGER.error("Failed to refresh coordinator: %s", str(refresh_ex))
return False
if not coordinator.last_update_success:
_LOGGER.error("Failed to communicate with OpenAI API")
return False
hass.data[DOMAIN][entry.entry_id] = coordinator hass.data[DOMAIN][entry.entry_id] = coordinator
return await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS) try:
await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
except Exception as setup_ex:
_LOGGER.error("Failed to setup platforms: %s", str(setup_ex))
return False
_LOGGER.info(
"Successfully set up HA Text AI with model: %s",
entry.data.get(CONF_MODEL, DEFAULT_MODEL)
)
return True
except Exception as ex: except Exception as ex:
raise ConfigEntryNotReady(f"Failed to setup entry: {str(ex)}") from ex _LOGGER.exception("Unexpected error setting up entry: %s", str(ex))
return False
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool: async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry.""" """Unload a config entry."""
unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS) try:
if unload_ok: if entry.entry_id not in hass.data.get(DOMAIN, {}):
hass.data[DOMAIN].pop(entry.entry_id) return True
unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
if unload_ok:
coordinator = hass.data[DOMAIN].pop(entry.entry_id)
await coordinator.async_shutdown()
if not hass.data[DOMAIN]: return unload_ok
services = [
SERVICE_ASK_QUESTION,
SERVICE_CLEAR_HISTORY,
SERVICE_GET_HISTORY,
SERVICE_SET_SYSTEM_PROMPT
]
for service in services:
if service in hass.services.async_services().get(DOMAIN, {}):
hass.services.async_remove(DOMAIN, service)
return unload_ok except Exception as ex:
_LOGGER.exception("Error unloading entry: %s", str(ex))
return False
async def async_reload_entry(hass: HomeAssistant, entry: ConfigEntry) -> None:
"""Reload config entry."""
try:
await async_unload_entry(hass, entry)
await async_setup_entry(hass, entry)
except Exception as ex:
_LOGGER.exception("Error reloading entry: %s", str(ex))
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@@ -1,12 +1,19 @@
"""Config flow for HA text AI integration.""" """Config flow for HA text AI integration."""
from typing import Any, Dict, Optional from typing import Any, Dict, Optional, Tuple
import voluptuous as vol import voluptuous as vol
import ssl
import certifi
import asyncio
from async_timeout import timeout
import aiohttp
from urllib.parse import urlparse
from homeassistant import config_entries from homeassistant import config_entries
from homeassistant.const import CONF_API_KEY from homeassistant.const import CONF_API_KEY
import homeassistant.helpers.config_validation as cv import homeassistant.helpers.config_validation as cv
from homeassistant.core import callback from homeassistant.core import callback
import openai from openai import AsyncOpenAI
from openai import OpenAIError, APIError, APIConnectionError, AuthenticationError, RateLimitError
from .const import ( from .const import (
DOMAIN, DOMAIN,
@@ -22,24 +29,123 @@ from .const import (
DEFAULT_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL,
) )
import logging
_LOGGER = logging.getLogger(__name__)
# Create SSL context at module level
SSL_CONTEXT = ssl.create_default_context(cafile=certifi.where())
STEP_USER_DATA_SCHEMA = vol.Schema({ STEP_USER_DATA_SCHEMA = vol.Schema({
vol.Required(CONF_API_KEY): str, vol.Required(CONF_API_KEY): str,
vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): str, vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): str,
vol.Optional( vol.Optional(
CONF_TEMPERATURE, CONF_TEMPERATURE,
default=DEFAULT_TEMPERATURE default=DEFAULT_TEMPERATURE
): vol.All(vol.Coerce(float), vol.Range(min=0, max=2)), ): vol.All(
vol.Coerce(float),
vol.Range(min=0, max=2)
),
vol.Optional( vol.Optional(
CONF_MAX_TOKENS, CONF_MAX_TOKENS,
default=DEFAULT_MAX_TOKENS default=DEFAULT_MAX_TOKENS
): vol.All(vol.Coerce(int), vol.Range(min=1, max=4096)), ): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=4096)
),
vol.Optional(CONF_API_ENDPOINT, default=DEFAULT_API_ENDPOINT): str, vol.Optional(CONF_API_ENDPOINT, default=DEFAULT_API_ENDPOINT): str,
vol.Optional( vol.Optional(
CONF_REQUEST_INTERVAL, CONF_REQUEST_INTERVAL,
default=DEFAULT_REQUEST_INTERVAL default=DEFAULT_REQUEST_INTERVAL
): vol.All(vol.Coerce(float), vol.Range(min=0.1)), ): vol.All(
vol.Coerce(float),
vol.Range(min=0.1)
),
}) })
async def validate_endpoint(endpoint: str) -> Tuple[bool, str]:
"""Validate API endpoint accessibility."""
try:
parsed_url = urlparse(endpoint)
if parsed_url.scheme not in ('http', 'https'):
return False, "invalid_endpoint_scheme"
connector = aiohttp.TCPConnector(ssl=SSL_CONTEXT)
async with timeout(5):
async with aiohttp.ClientSession(connector=connector) as session:
async with session.get(endpoint) as response:
if response.status != 200:
return False, "endpoint_not_available"
return True, ""
except Exception as e:
_LOGGER.error("Error validating endpoint: %s", str(e))
return False, "endpoint_error"
async def validate_api_connection(
api_key: str,
endpoint: str,
model: str,
retry_count: int = 3,
retry_delay: float = 1.0
) -> Tuple[bool, str, list]:
"""Validate API connection with improved retry logic."""
# Validate endpoint first
endpoint_valid, endpoint_error = await validate_endpoint(endpoint)
if not endpoint_valid:
return False, endpoint_error, []
connector = aiohttp.TCPConnector(ssl=SSL_CONTEXT)
async with aiohttp.ClientSession(connector=connector) as session:
for attempt in range(retry_count):
try:
async with timeout(10):
client = AsyncOpenAI(
api_key=api_key,
base_url=endpoint,
http_client=session
)
models = await client.models.list()
model_ids = [model.id for model in models.data]
if model not in model_ids:
_LOGGER.warning(
"Model %s not found in available models: %s",
model,
", ".join(model_ids)
)
return False, "invalid_model", model_ids
return True, "", model_ids
except asyncio.TimeoutError:
_LOGGER.warning(
"Timeout during API validation (attempt %d/%d)",
attempt + 1,
retry_count
)
if attempt == retry_count - 1:
return False, "timeout", []
await asyncio.sleep(retry_delay)
except AuthenticationError as err:
_LOGGER.error("Authentication error: %s", str(err))
return False, "invalid_auth", []
except RateLimitError as err:
_LOGGER.error("Rate limit exceeded: %s", str(err))
return False, "rate_limit", []
except APIConnectionError as err:
_LOGGER.error("API connection error: %s", str(err))
return False, "cannot_connect", []
except APIError as err:
_LOGGER.error("API error: %s", str(err))
return False, "api_error", []
except Exception as err:
_LOGGER.exception("Unexpected error during validation: %s", str(err))
return False, "unknown", []
class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN): class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
"""Handle a config flow for HA text AI.""" """Handle a config flow for HA text AI."""
@@ -54,35 +160,64 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
if user_input is not None: if user_input is not None:
try: try:
# Validate URL format
client = openai.OpenAI( endpoint = user_input.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT)
api_key=user_input[CONF_API_KEY], try:
base_url=user_input.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT) result = urlparse(endpoint)
) if not all([result.scheme, result.netloc]):
await self.hass.async_add_executor_job( errors["base"] = "invalid_url_format"
client.models.list return self.async_show_form(
step_id="user",
data_schema=STEP_USER_DATA_SCHEMA,
errors=errors
)
except Exception as e:
_LOGGER.error("URL parsing error: %s", str(e))
errors["base"] = "invalid_url_format"
return self.async_show_form(
step_id="user",
data_schema=STEP_USER_DATA_SCHEMA,
errors=errors
)
# Validate input data
user_input = STEP_USER_DATA_SCHEMA(user_input)
is_valid, error_code, available_models = await validate_api_connection(
user_input[CONF_API_KEY],
endpoint,
user_input[CONF_MODEL]
) )
if is_valid:
await self.async_set_unique_id(user_input[CONF_API_KEY])
self._abort_if_unique_id_configured()
await self.async_set_unique_id(user_input[CONF_API_KEY]) return self.async_create_entry(
self._abort_if_unique_id_configured() title="HA text AI",
data=user_input
)
return self.async_create_entry( errors["base"] = error_code
title="HA text AI", if error_code == "invalid_model":
data=user_input _LOGGER.warning(
) "Selected model %s not found in available models: %s",
user_input[CONF_MODEL],
", ".join(available_models)
)
except openai.AuthenticationError: except vol.Invalid as err:
errors["base"] = "invalid_auth" _LOGGER.error("Validation error: %s", str(err))
except openai.APIError: errors["base"] = "invalid_input"
errors["base"] = "cannot_connect"
except Exception: # pylint: disable=broad-except
errors["base"] = "unknown"
return self.async_show_form( return self.async_show_form(
step_id="user", step_id="user",
data_schema=STEP_USER_DATA_SCHEMA, data_schema=STEP_USER_DATA_SCHEMA,
errors=errors, errors=errors,
description_placeholders={
"default_model": DEFAULT_MODEL,
"default_endpoint": DEFAULT_API_ENDPOINT,
}
) )
@staticmethod @staticmethod
@@ -114,22 +249,31 @@ class OptionsFlowHandler(config_entries.OptionsFlow):
default=self.config_entry.options.get( default=self.config_entry.options.get(
CONF_TEMPERATURE, DEFAULT_TEMPERATURE CONF_TEMPERATURE, DEFAULT_TEMPERATURE
), ),
description="Temperature for response generation (0-2)", description={"suggested_value": DEFAULT_TEMPERATURE},
): vol.All(vol.Coerce(float), vol.Range(min=0, max=2)), ): vol.All(
vol.Coerce(float),
vol.Range(min=0, max=2)
),
vol.Optional( vol.Optional(
CONF_MAX_TOKENS, CONF_MAX_TOKENS,
default=self.config_entry.options.get( default=self.config_entry.options.get(
CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
), ),
description="Maximum tokens in response (1-4096)", description={"suggested_value": DEFAULT_MAX_TOKENS},
): vol.All(vol.Coerce(int), vol.Range(min=1, max=4096)), ): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=4096)
),
vol.Optional( vol.Optional(
CONF_REQUEST_INTERVAL, CONF_REQUEST_INTERVAL,
default=self.config_entry.options.get( default=self.config_entry.options.get(
CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
), ),
description="Minimum time between API requests (seconds)", description={"suggested_value": DEFAULT_REQUEST_INTERVAL},
): vol.All(vol.Coerce(float), vol.Range(min=0.1)), ): vol.All(
vol.Coerce(float),
vol.Range(min=0.1)
),
}) })
return self.async_show_form( return self.async_show_form(
+81 -1
View File
@@ -2,7 +2,7 @@
from typing import Final from typing import Final
from homeassistant.const import Platform from homeassistant.const import Platform
# Domain # Domain and platforms
DOMAIN: Final = "ha_text_ai" DOMAIN: Final = "ha_text_ai"
PLATFORMS: Final = [Platform.SENSOR] PLATFORMS: Final = [Platform.SENSOR]
@@ -19,6 +19,9 @@ DEFAULT_TEMPERATURE: Final = 0.7
DEFAULT_MAX_TOKENS: Final = 1000 DEFAULT_MAX_TOKENS: Final = 1000
DEFAULT_API_ENDPOINT: Final = "https://api.openai.com/v1" DEFAULT_API_ENDPOINT: Final = "https://api.openai.com/v1"
DEFAULT_REQUEST_INTERVAL: Final = 1.0 DEFAULT_REQUEST_INTERVAL: Final = 1.0
DEFAULT_TIMEOUT: Final = 30
DEFAULT_QUEUE_SIZE: Final = 100
DEFAULT_HISTORY_LIMIT: Final = 50
# Parameter constraints # Parameter constraints
MIN_TEMPERATURE: Final = 0.0 MIN_TEMPERATURE: Final = 0.0
@@ -26,6 +29,8 @@ MAX_TEMPERATURE: Final = 2.0
MIN_MAX_TOKENS: Final = 1 MIN_MAX_TOKENS: Final = 1
MAX_MAX_TOKENS: Final = 4096 MAX_MAX_TOKENS: Final = 4096
MIN_REQUEST_INTERVAL: Final = 0.1 MIN_REQUEST_INTERVAL: Final = 0.1
MIN_TIMEOUT: Final = 5
MAX_TIMEOUT: Final = 120
# Service names # Service names
SERVICE_ASK_QUESTION: Final = "ask_question" SERVICE_ASK_QUESTION: Final = "ask_question"
@@ -43,11 +48,28 @@ SERVICE_SET_SYSTEM_PROMPT_DESCRIPTION: Final = "Set system prompt for AI model"
ATTR_QUESTION: Final = "question" ATTR_QUESTION: Final = "question"
ATTR_RESPONSE: Final = "response" ATTR_RESPONSE: Final = "response"
ATTR_LAST_UPDATED: Final = "last_updated" ATTR_LAST_UPDATED: Final = "last_updated"
ATTR_MODEL: Final = "model"
ATTR_TEMPERATURE: Final = "temperature"
ATTR_MAX_TOKENS: Final = "max_tokens"
ATTR_TOTAL_RESPONSES: Final = "total_responses"
ATTR_SYSTEM_PROMPT: Final = "system_prompt"
ATTR_RESPONSE_TIME: Final = "response_time"
ATTR_QUEUE_SIZE: Final = "queue_size"
ATTR_API_STATUS: Final = "api_status"
ATTR_ERROR_COUNT: Final = "error_count"
ATTR_LAST_ERROR: Final = "last_error"
# Error messages # Error messages
ERROR_INVALID_API_KEY: Final = "invalid_api_key" ERROR_INVALID_API_KEY: Final = "invalid_api_key"
ERROR_CANNOT_CONNECT: Final = "cannot_connect" ERROR_CANNOT_CONNECT: Final = "cannot_connect"
ERROR_UNKNOWN: Final = "unknown_error" ERROR_UNKNOWN: Final = "unknown_error"
ERROR_INVALID_MODEL: Final = "invalid_model"
ERROR_RATE_LIMIT: Final = "rate_limit_exceeded"
ERROR_CONTEXT_LENGTH: Final = "context_length_exceeded"
ERROR_API_ERROR: Final = "api_error"
ERROR_TIMEOUT: Final = "timeout_error"
ERROR_QUEUE_FULL: Final = "queue_full"
ERROR_INVALID_PROMPT: Final = "invalid_prompt"
# Configuration descriptions # Configuration descriptions
CONF_MODEL_DESCRIPTION: Final = "AI model to use for responses" CONF_MODEL_DESCRIPTION: Final = "AI model to use for responses"
@@ -56,6 +78,64 @@ CONF_MAX_TOKENS_DESCRIPTION: Final = "Maximum tokens in response (1-4096)"
CONF_API_ENDPOINT_DESCRIPTION: Final = "API endpoint URL" CONF_API_ENDPOINT_DESCRIPTION: Final = "API endpoint URL"
CONF_REQUEST_INTERVAL_DESCRIPTION: Final = "Minimum time between API requests (seconds)" CONF_REQUEST_INTERVAL_DESCRIPTION: Final = "Minimum time between API requests (seconds)"
# Entity attributes descriptions
ATTR_QUESTION_DESCRIPTION: Final = "Last question asked"
ATTR_RESPONSE_DESCRIPTION: Final = "Last response received"
ATTR_LAST_UPDATED_DESCRIPTION: Final = "Time of last update"
ATTR_MODEL_DESCRIPTION: Final = "Current AI model in use"
ATTR_TEMPERATURE_DESCRIPTION: Final = "Current temperature setting"
ATTR_MAX_TOKENS_DESCRIPTION: Final = "Current max tokens setting"
ATTR_TOTAL_RESPONSES_DESCRIPTION: Final = "Total number of responses"
ATTR_SYSTEM_PROMPT_DESCRIPTION: Final = "Current system prompt"
ATTR_RESPONSE_TIME_DESCRIPTION: Final = "Time taken for last response"
ATTR_QUEUE_SIZE_DESCRIPTION: Final = "Current size of question queue"
ATTR_API_STATUS_DESCRIPTION: Final = "Current API connection status"
ATTR_ERROR_COUNT_DESCRIPTION: Final = "Total number of errors"
ATTR_LAST_ERROR_DESCRIPTION: Final = "Last error message"
# Entity attributes # Entity attributes
ENTITY_NAME: Final = "HA Text AI" ENTITY_NAME: Final = "HA Text AI"
ENTITY_ICON: Final = "mdi:robot" ENTITY_ICON: Final = "mdi:robot"
ENTITY_ICON_ERROR: Final = "mdi:robot-dead"
ENTITY_ICON_PROCESSING: Final = "mdi:robot-excited"
# Translation keys
TRANSLATION_KEY_CONFIG: Final = "config"
TRANSLATION_KEY_OPTIONS: Final = "options"
TRANSLATION_KEY_ERROR: Final = "error"
TRANSLATION_KEY_STATE: Final = "state"
TRANSLATION_KEY_SERVICES: Final = "services"
# State attributes
STATE_READY: Final = "ready"
STATE_PROCESSING: Final = "processing"
STATE_ERROR: Final = "error"
STATE_DISCONNECTED: Final = "disconnected"
STATE_RATE_LIMITED: Final = "rate_limited"
STATE_INITIALIZING: Final = "initializing"
# Logging
LOGGER_NAME: Final = "custom_components.ha_text_ai"
LOG_LEVEL_DEFAULT: Final = "INFO"
# Queue constants
QUEUE_TIMEOUT: Final = 5
QUEUE_MAX_SIZE: Final = 100
# API constants
API_TIMEOUT: Final = 30
API_RETRY_COUNT: Final = 3
API_BACKOFF_FACTOR: Final = 1.5
# Service schema constants
SCHEMA_QUESTION: Final = "question"
SCHEMA_MODEL: Final = "model"
SCHEMA_TEMPERATURE: Final = "temperature"
SCHEMA_MAX_TOKENS: Final = "max_tokens"
SCHEMA_PROMPT: Final = "prompt"
SCHEMA_LIMIT: Final = "limit"
# Event names
EVENT_RESPONSE_RECEIVED: Final = f"{DOMAIN}_response_received"
EVENT_ERROR_OCCURRED: Final = f"{DOMAIN}_error_occurred"
EVENT_STATE_CHANGED: Final = f"{DOMAIN}_state_changed"
+128 -68
View File
@@ -1,49 +1,13 @@
"""The HA Text AI integration."""
from homeassistant.config_entries import ConfigEntry
from homeassistant.core import HomeAssistant
from homeassistant.exceptions import ConfigEntryNotReady
from .const import DOMAIN, PLATFORMS
from .coordinator import HATextAICoordinator
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Set up HA Text AI from a config entry."""
try:
coordinator = HATextAICoordinator(
hass,
api_key=entry.data["api_key"],
endpoint=entry.data.get("api_endpoint", "https://api.openai.com/v1"),
model=entry.data.get("model", "gpt-3.5-turbo"),
temperature=entry.data.get("temperature", 0.7),
max_tokens=entry.data.get("max_tokens", 1000),
request_interval=entry.data.get("request_interval", 1.0),
)
await coordinator.async_config_entry_first_refresh()
hass.data.setdefault(DOMAIN, {})
hass.data[DOMAIN][entry.entry_id] = coordinator
return await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
except Exception as ex:
raise ConfigEntryNotReady(f"Failed to setup entry: {str(ex)}") from ex
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry."""
unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
if unload_ok:
hass.data[DOMAIN].pop(entry.entry_id)
return unload_ok
"""Data coordinator for HA text AI.""" """Data coordinator for HA text AI."""
import asyncio import asyncio
import logging import logging
from datetime import timedelta from datetime import timedelta
from typing import Any, Dict, Optional from typing import Any, Dict, Optional
import openai from openai import AsyncOpenAI, APIError, AuthenticationError, RateLimitError
from homeassistant.core import HomeAssistant from homeassistant.core import HomeAssistant
from homeassistant.helpers.update_coordinator import DataUpdateCoordinator from homeassistant.helpers.update_coordinator import DataUpdateCoordinator
from homeassistant.exceptions import ConfigEntryAuthFailed import async_timeout
from .const import DOMAIN from .const import DOMAIN
@@ -61,6 +25,7 @@ class HATextAICoordinator(DataUpdateCoordinator):
temperature: float, temperature: float,
max_tokens: int, max_tokens: int,
request_interval: float, request_interval: float,
session: Optional[Any] = None,
) -> None: ) -> None:
"""Initialize.""" """Initialize."""
super().__init__( super().__init__(
@@ -70,6 +35,28 @@ class HATextAICoordinator(DataUpdateCoordinator):
update_interval=timedelta(seconds=request_interval), update_interval=timedelta(seconds=request_interval),
) )
self._validate_params(api_key, temperature, max_tokens)
self.api_key = api_key
self.endpoint = endpoint
self.model = model
self.temperature = float(temperature)
self.max_tokens = int(max_tokens)
self._question_queue = asyncio.Queue()
self._responses: Dict[str, Any] = {}
self.system_prompt: Optional[str] = None
self._is_ready = False
self._error_count = 0
self._MAX_ERRORS = 3
self.client = AsyncOpenAI(
api_key=self.api_key,
base_url=self.endpoint,
http_client=session,
)
def _validate_params(self, api_key: str, temperature: float, max_tokens: int) -> None:
"""Validate initialization parameters."""
if not api_key: if not api_key:
raise ValueError("API key is required") raise ValueError("API key is required")
if not isinstance(temperature, (int, float)) or not 0 <= temperature <= 2: if not isinstance(temperature, (int, float)) or not 0 <= temperature <= 2:
@@ -77,44 +64,79 @@ class HATextAICoordinator(DataUpdateCoordinator):
if not isinstance(max_tokens, int) or max_tokens < 1: if not isinstance(max_tokens, int) or max_tokens < 1:
raise ValueError("Max tokens must be a positive integer") raise ValueError("Max tokens must be a positive integer")
self.api_key = api_key
self.endpoint = endpoint or "https://api.openai.com/v1"
self.model = model or "gpt-3.5-turbo"
self.temperature = float(temperature)
self.max_tokens = int(max_tokens)
self._question_queue = asyncio.Queue()
self._responses: Dict[str, Any] = {}
self.system_prompt: Optional[str] = None
self.client = openai.OpenAI(
api_key=self.api_key,
base_url=self.endpoint
)
async def _async_update_data(self) -> Dict[str, Any]: async def _async_update_data(self) -> Dict[str, Any]:
"""Update data via OpenAI API.""" """Update data via OpenAI API."""
if self._question_queue.empty(): if self._question_queue.empty():
return self._responses return self._responses
try: try:
question = await self._question_queue.get() async with async_timeout.timeout(30):
response_content = await self.hass.async_add_executor_job( question = await self._question_queue.get()
self._make_api_call, question try:
response_content = await self._make_api_call(question)
self._responses[question] = {
"question": question,
"response": response_content,
"error": None,
"timestamp": self.hass.loop.time()
}
self._error_count = 0
self._is_ready = True
_LOGGER.debug("Response received for question: %s", question)
except Exception as err:
self._handle_api_error(question, err)
finally:
self._question_queue.task_done()
return self._responses
except asyncio.TimeoutError as err:
_LOGGER.error("Timeout while processing question")
await self._handle_timeout_error()
return self._responses
def _handle_api_error(self, question: str, error: Exception) -> None:
"""Handle API errors."""
self._error_count += 1
error_msg = str(error)
if isinstance(error, AuthenticationError):
error_msg = "Authentication failed - invalid API key"
self._is_ready = False
elif isinstance(error, RateLimitError):
error_msg = "Rate limit exceeded"
elif isinstance(error, APIError):
error_msg = f"API error: {error}"
self._responses[question] = {
"question": question,
"response": None,
"error": error_msg,
"timestamp": self.hass.loop.time()
}
_LOGGER.error("API error (%s): %s", type(error).__name__, error_msg)
if self._error_count >= self._MAX_ERRORS:
_LOGGER.warning(
"Multiple errors occurred (%d). Coordinator needs attention.",
self._error_count
) )
self._responses[question] = {
"question": question,
"response": response_content
}
_LOGGER.debug("Response from API: %s", response_content)
return self._responses
except openai.AuthenticationError as err: async def _handle_timeout_error(self) -> None:
raise ConfigEntryAuthFailed from err """Handle timeout errors."""
except Exception as err: self._error_count += 1
_LOGGER.error("Error communicating with API: %s", err) if not self._question_queue.empty():
return self._responses try:
# Clear the queue if we have timeout issues
while not self._question_queue.empty():
self._question_queue.get_nowait()
self._question_queue.task_done()
except Exception as err:
_LOGGER.error("Error clearing question queue: %s", err)
def _make_api_call(self, question: str) -> str: async def _make_api_call(self, question: str) -> str:
"""Make API call to OpenAI.""" """Make API call to OpenAI."""
try: try:
messages = [] messages = []
@@ -122,13 +144,51 @@ class HATextAICoordinator(DataUpdateCoordinator):
messages.append({"role": "system", "content": self.system_prompt}) messages.append({"role": "system", "content": self.system_prompt})
messages.append({"role": "user", "content": question}) messages.append({"role": "user", "content": question})
completion = self.client.chat.completions.create( completion = await self.client.chat.completions.create(
model=self.model, model=self.model,
messages=messages, messages=messages,
temperature=self.temperature, temperature=self.temperature,
max_tokens=self.max_tokens, max_tokens=self.max_tokens,
) )
return completion.choices[0].message.content return completion.choices[0].message.content
except Exception as err: except Exception as err:
_LOGGER.error("Error in API call: %s", err) _LOGGER.error("Error in API call: %s", err)
raise raise
async def async_ask_question(self, question: str) -> None:
"""Add question to queue."""
if not self._is_ready and self._error_count >= self._MAX_ERRORS:
_LOGGER.warning("Coordinator is not ready due to previous errors")
return
await self._question_queue.put(question)
await self.async_refresh()
async def async_shutdown(self) -> None:
"""Shutdown the coordinator."""
try:
# Clear the queue
while not self._question_queue.empty():
self._question_queue.get_nowait()
self._question_queue.task_done()
await self.client.close()
self._is_ready = False
except Exception as err:
_LOGGER.error("Error during shutdown: %s", err)
@property
def is_ready(self) -> bool:
"""Return if coordinator is ready."""
return self._is_ready
@property
def error_count(self) -> int:
"""Return current error count."""
return self._error_count
def reset_error_count(self) -> None:
"""Reset error counter."""
self._error_count = 0
+5 -5
View File
@@ -1,14 +1,14 @@
{ {
"domain": "ha_text_ai", "domain": "ha_text_ai",
"name": "HA Text AI", "name": "HA Text AI",
"codeowners": ["@smkrv"],
"config_flow": true, "config_flow": true,
"dependencies": [],
"documentation": "https://github.com/smkrv/ha-text-ai/wiki", "documentation": "https://github.com/smkrv/ha-text-ai/wiki",
"iot_class": "cloud_polling",
"issue_tracker": "https://github.com/smkrv/ha-text-ai/issues", "issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
"requirements": ["openai>=1.0.0"], "requirements": ["openai>=1.0.0"],
"ssdp": [], "ssdp": [],
"zeroconf": [], "version": "1.0.8",
"dependencies": [], "zeroconf": []
"version": "1.0.1c",
"iot_class": "cloud_polling",
"codeowners": ["@smkrv"]
} }
+122 -35
View File
@@ -1,7 +1,7 @@
"""Sensor platform for HA text AI.""" """Sensor platform for HA text AI."""
from datetime import datetime from datetime import datetime
import logging import logging
from typing import Any, Callable, Dict, Optional from typing import Any, Dict, Optional
from homeassistant.components.sensor import ( from homeassistant.components.sensor import (
SensorEntity, SensorEntity,
@@ -13,8 +13,33 @@ from homeassistant.core import HomeAssistant
from homeassistant.helpers.entity_platform import AddEntitiesCallback from homeassistant.helpers.entity_platform import AddEntitiesCallback
from homeassistant.helpers.typing import StateType from homeassistant.helpers.typing import StateType
from homeassistant.helpers.update_coordinator import CoordinatorEntity from homeassistant.helpers.update_coordinator import CoordinatorEntity
from homeassistant.util import dt as dt_util
from .const import DOMAIN, ATTR_QUESTION, ATTR_RESPONSE, ATTR_LAST_UPDATED from .const import (
DOMAIN,
ATTR_QUESTION,
ATTR_RESPONSE,
ATTR_LAST_UPDATED,
ATTR_MODEL,
ATTR_TEMPERATURE,
ATTR_MAX_TOKENS,
ATTR_TOTAL_RESPONSES,
ATTR_SYSTEM_PROMPT,
ATTR_QUEUE_SIZE,
ATTR_API_STATUS,
ATTR_ERROR_COUNT,
ATTR_LAST_ERROR,
ATTR_RESPONSE_TIME,
ENTITY_ICON,
ENTITY_ICON_ERROR,
ENTITY_ICON_PROCESSING,
STATE_READY,
STATE_PROCESSING,
STATE_ERROR,
STATE_DISCONNECTED,
STATE_RATE_LIMITED,
STATE_INITIALIZING,
)
from .coordinator import HATextAICoordinator from .coordinator import HATextAICoordinator
_LOGGER = logging.getLogger(__name__) _LOGGER = logging.getLogger(__name__)
@@ -34,7 +59,6 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
_attr_has_entity_name = True _attr_has_entity_name = True
_attr_state_class = SensorStateClass.MEASUREMENT _attr_state_class = SensorStateClass.MEASUREMENT
_attr_device_class = SensorDeviceClass.TIMESTAMP _attr_device_class = SensorDeviceClass.TIMESTAMP
_attr_icon = "mdi:robot"
def __init__( def __init__(
self, self,
@@ -46,49 +70,112 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
self._config_entry = config_entry self._config_entry = config_entry
self._attr_unique_id = f"{config_entry.entry_id}" self._attr_unique_id = f"{config_entry.entry_id}"
self._attr_name = "Last Response" self._attr_name = "Last Response"
self._attr_suggested_display_precision = 0
self._error_count = 0
self._last_error = None
self._state = STATE_INITIALIZING
@property
def icon(self) -> str:
"""Return the icon based on the current state."""
if self._state == STATE_PROCESSING:
return ENTITY_ICON_PROCESSING
elif self._state in [STATE_ERROR, STATE_DISCONNECTED, STATE_RATE_LIMITED]:
return ENTITY_ICON_ERROR
return ENTITY_ICON
@property @property
def state(self) -> StateType: def state(self) -> StateType:
"""Return the state of the sensor.""" """Return the state of the sensor."""
if not self.coordinator.data: if not self.coordinator.data or not self.coordinator.last_update_success_time:
return None
return self.coordinator.last_update_success_time
@property
def extra_state_attributes(self) -> Optional[Dict[str, Any]]:
"""Return entity specific state attributes."""
if not self.coordinator.data:
return None return None
try: try:
if isinstance(self.coordinator.last_update_success_time, datetime):
history = list(self.coordinator.data.items()) return dt_util.as_local(self.coordinator.last_update_success_time)
if not history: return self.coordinator.last_update_success_time
return None except Exception as err:
_LOGGER.error("Error getting state: %s", err, exc_info=True)
last_question, last_data = history[-1]
if isinstance(last_data, dict):
last_response = last_data.get("response", "")
else:
last_response = str(last_data)
return {
ATTR_QUESTION: last_question,
ATTR_RESPONSE: last_response,
ATTR_LAST_UPDATED: self.coordinator.last_update_success_time,
}
except (IndexError, KeyError, AttributeError) as err:
_LOGGER.warning("Error getting attributes: %s", err)
return None return None
@property
def extra_state_attributes(self) -> Dict[str, Any]:
"""Return entity specific state attributes."""
attributes = {
ATTR_TOTAL_RESPONSES: 0,
ATTR_MODEL: self.coordinator.model,
ATTR_TEMPERATURE: self.coordinator.temperature,
ATTR_MAX_TOKENS: self.coordinator.max_tokens,
ATTR_SYSTEM_PROMPT: self.coordinator.system_prompt,
ATTR_QUEUE_SIZE: self.coordinator._question_queue.qsize(),
ATTR_API_STATUS: self._state,
ATTR_ERROR_COUNT: self._error_count,
ATTR_LAST_ERROR: self._last_error,
}
if not self.coordinator.data:
return attributes
try:
history = list(self.coordinator.data.items())
if history:
last_question, last_data = history[-1]
# Handle different response formats
if isinstance(last_data, dict):
last_response = last_data.get("response", "")
last_updated = last_data.get("timestamp", self.coordinator.last_update_success_time)
response_time = last_data.get("response_time")
else:
last_response = str(last_data)
last_updated = self.coordinator.last_update_success_time
response_time = None
# Convert timestamp to local time if needed
if isinstance(last_updated, datetime):
last_updated = dt_util.as_local(last_updated)
attributes.update({
ATTR_QUESTION: last_question,
ATTR_RESPONSE: last_response,
ATTR_LAST_UPDATED: last_updated,
ATTR_TOTAL_RESPONSES: len(history),
})
if response_time is not None:
attributes[ATTR_RESPONSE_TIME] = response_time
return attributes
except Exception as err:
_LOGGER.error("Error getting attributes: %s", err, exc_info=True)
self._error_count += 1
self._last_error = str(err)
self._state = STATE_ERROR
return attributes
@property @property
def available(self) -> bool: def available(self) -> bool:
"""Return if entity is available.""" """Return if entity is available."""
return self.coordinator.last_update_success return self.coordinator.last_update_success
@property async def async_added_to_hass(self) -> None:
def should_poll(self) -> bool: """When entity is added to hass."""
"""No need to poll. Coordinator notifies entity of updates.""" await super().async_added_to_hass()
return False self._handle_coordinator_update()
self._state = STATE_READY
def _handle_coordinator_update(self) -> None:
"""Handle updated data from the coordinator."""
try:
if self.coordinator.data:
self._state = STATE_READY
else:
self._state = STATE_DISCONNECTED
except Exception as err:
_LOGGER.error("Error handling update: %s", err, exc_info=True)
self._error_count += 1
self._last_error = str(err)
self._state = STATE_ERROR
self.async_write_ha_state()
+85 -17
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@@ -1,35 +1,61 @@
ask_question: ask_question:
name: Ask Question name: Ask Question
description: Send a question to the AI model and receive a detailed response description: >-
Send a question to the AI model and receive a detailed response.
The response will be stored in the conversation history and can be retrieved later.
Response time may vary based on model selection and server load.
fields: fields:
question: question:
name: Question name: Question
description: Your question or prompt for the AI assistant description: >-
Your question or prompt for the AI assistant. Be specific and clear for better results.
You can ask about home automation, technical advice, or general questions.
For complex queries, consider breaking them into smaller parts.
required: true required: true
example: "What automations would you recommend for a smart kitchen?" example: |
What automations would you recommend for a smart kitchen?
Consider energy efficiency, convenience, and integration with:
- Smart lighting
- Appliance control
- Temperature monitoring
- Voice commands
selector: selector:
text: text:
multiline: true multiline: true
type: text
model: model:
name: Model name: Model
description: Select an AI model to use (optional, overrides default setting) description: >-
Select an AI model to use (optional, overrides default setting).
Different models have different capabilities and token limits.
Note: More capable models may have longer response times and higher API costs.
required: false required: false
example: "gpt-3.5-turbo" example: "gpt-3.5-turbo"
default: "gpt-3.5-turbo" default: "gpt-3.5-turbo"
selector: selector:
select: select:
options: options:
- label: "GPT-3.5 Turbo" - label: "GPT-3.5 Turbo (Fast & Efficient)"
value: "gpt-3.5-turbo" value: "gpt-3.5-turbo"
- label: "GPT-4" - label: "GPT-3.5 Turbo 16K (Extended)"
value: "gpt-3.5-turbo-16k"
- label: "GPT-4 (Most Capable)"
value: "gpt-4" value: "gpt-4"
- label: "GPT-4 32K" - label: "GPT-4 32K (Extended Context)"
value: "gpt-4-32k" value: "gpt-4-32k"
- label: "GPT-4 Turbo (Latest)"
value: "gpt-4-1106-preview"
mode: dropdown
temperature: temperature:
name: Temperature name: Temperature
description: "Controls response creativity (0-2): Lower values for focused responses, higher for creative ones" description: >-
Controls response creativity (0-2):
0.0-0.3: Focused, consistent responses (best for technical/factual queries)
0.4-0.7: Balanced responses (recommended for most uses)
0.8-2.0: More creative, varied responses (best for brainstorming)
Note: Higher values may produce less predictable results.
required: false required: false
default: 0.7 default: 0.7
selector: selector:
@@ -38,10 +64,17 @@ ask_question:
max: 2.0 max: 2.0
step: 0.1 step: 0.1
mode: slider mode: slider
unit_of_measurement: ""
max_tokens: max_tokens:
name: Max Tokens name: Max Tokens
description: Maximum length of the response description: >-
Maximum length of the response. Higher values allow longer responses but use more API tokens.
Recommended ranges:
- Short responses (256-512): Quick answers, status updates
- Medium responses (512-1024): Detailed explanations, instructions
- Long responses (1024-4096): Complex analysis, multiple examples
Note: Actual response length may be shorter based on content.
required: false required: false
default: 1000 default: 1000
selector: selector:
@@ -53,16 +86,24 @@ ask_question:
clear_history: clear_history:
name: Clear History name: Clear History
description: Delete all stored questions and responses description: >-
Delete all stored questions and responses from the conversation history.
This action cannot be undone. Consider using 'get_history' first if you need to backup the data.
System prompt settings will be preserved.
fields: {} fields: {}
get_history: get_history:
name: Get History name: Get History
description: Retrieve recent conversation history description: >-
Retrieve recent conversation history, including questions, responses, and timestamps.
Results are ordered from newest to oldest and include metadata like model used and response times.
fields: fields:
limit: limit:
name: Limit name: Limit
description: Number of most recent conversations to return description: >-
Number of most recent conversations to return (1-100).
Higher values return more history but may take longer to process.
Default: 10 conversations
required: false required: false
default: 10 default: 10
selector: selector:
@@ -72,15 +113,42 @@ get_history:
step: 1 step: 1
mode: box mode: box
filter_model:
name: Filter by Model
description: >-
Only return conversations using a specific AI model.
Leave empty to show all models.
required: false
selector:
select:
options:
- label: "All Models"
value: ""
- label: "GPT-3.5 Turbo"
value: "gpt-3.5-turbo"
- label: "GPT-4"
value: "gpt-4"
mode: dropdown
set_system_prompt: set_system_prompt:
name: Set System Prompt fields:
description: Configure the AI's behavior by setting a system prompt
fields:
prompt: prompt:
name: System Prompt name: System Prompt
description: Instructions that define how the AI should behave and respond description: >-
Instructions that define how the AI should behave and respond.
Be specific about the desired expertise, tone, and format of responses.
Maximum length: 1000 characters.
required: true required: true
example: "You are a home automation expert assistant. Provide practical advice focused on smart home technology." example: |
You are a home automation expert assistant. Focus on:
1. Practical and efficient solutions
2. Energy-saving recommendations
3. Integration with popular smart home platforms
4. Security and privacy considerations
Provide detailed but concise responses with clear steps when applicable.
Format complex responses with bullet points or numbered lists.
Include warnings about potential risks or limitations.
selector: selector:
text: text:
multiline: true multiline: true
type: text
@@ -1,59 +1,54 @@
{ {
"config": { "config": {
"step": { "step": {
"user": { "user": {
"title": "Set up HA text AI", "title": "Set up HA Text AI",
"description": "Configure your OpenAI integration for smart home interactions", "description": "Configure your OpenAI integration",
"data": { "data": {
"api_key": "OpenAI API Key", "api_key": "Your OpenAI API key",
"model": "AI Model", "model": "AI model to use for responses",
"temperature": "Temperature", "temperature": "Temperature for response generation (0-2)",
"max_tokens": "Max Tokens", "max_tokens": "Maximum tokens in response (1-4096)",
"api_endpoint": "API Endpoint", "api_endpoint": "API endpoint URL",
"request_interval": "Request Interval" "request_interval": "Minimum time between API requests (seconds)"
}
}
} }
}
}, },
"error": { "options": {
"invalid_auth": "Invalid API key. Please check your OpenAI API key and try again.", "step": {
"cannot_connect": "Failed to connect to API. Please check your internet connection and API endpoint.", "init": {
"unknown": "Unexpected error occurred. Please check the logs for more details.", "title": "HA Text AI Options",
"already_exists": "This API key is already configured in another integration." "data": {
"temperature": "Response temperature (0-2)",
"max_tokens": "Maximum response length",
"request_interval": "Time between requests"
}
}
}
}, },
"abort": { "services": {
"already_configured": "This OpenAI integration is already configured", "ask_question": {
"auth_failed": "Authentication failed. Please verify your API key." "name": "Ask Question",
} "description": "Send a question to the AI model",
}, "fields": {
"options": { "question": {
"step": { "name": "Question",
"init": { "description": "Your question for the AI"
"title": "HA text AI Options", }
"description": "Adjust your OpenAI integration settings", }
"data": { },
"temperature": "Temperature", "clear_history": {
"max_tokens": "Max Tokens", "name": "Clear History",
"request_interval": "Request Interval" "description": "Clear conversation history"
},
"get_history": {
"name": "Get History",
"description": "Retrieve conversation history"
},
"set_system_prompt": {
"name": "Set System Prompt",
"description": "Set system behavior instructions"
} }
}
} }
},
"entity": {
"sensor": {
"last_response": {
"name": "Last Response",
"state_attributes": {
"last_updated": {
"name": "Last Updated"
},
"question": {
"name": "Last Question"
},
"response": {
"name": "AI Response"
}
}
}
}
}
} }
@@ -0,0 +1,54 @@
{
"config": {
"step": {
"user": {
"title": "Настройка HA Text AI",
"description": "Настройка интеграции с OpenAI",
"data": {
"api_key": "Ваш ключ API OpenAI",
"model": "Модель ИИ для генерации ответов",
"temperature": "Температура генерации ответов (0-2)",
"max_tokens": "Максимальное количество токенов в ответе (1-4096)",
"api_endpoint": "URL конечной точки API",
"request_interval": "Минимальное время между запросами к API (секунды)"
}
}
}
},
"options": {
"step": {
"init": {
"title": "Настройки HA Text AI",
"data": {
"temperature": "Температура ответов (0-2)",
"max_tokens": "Максимальная длина ответа",
"request_interval": "Время между запросами"
}
}
}
},
"services": {
"ask_question": {
"name": "Задать вопрос",
"description": "Отправить вопрос модели ИИ",
"fields": {
"question": {
"name": "Вопрос",
"description": "Ваш вопрос для ИИ"
}
}
},
"clear_history": {
"name": "Очистить историю",
"description": "Очистить историю разговора"
},
"get_history": {
"name": "Получить историю",
"description": "Получить историю разговора"
},
"set_system_prompt": {
"name": "Установить системный промпт",
"description": "Установить инструкции поведения системы"
}
}
}
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@@ -4,6 +4,6 @@
"domains": ["sensor"], "domains": ["sensor"],
"homeassistant": "2024.11.0", "homeassistant": "2024.11.0",
"icon": "mdi:brain", "icon": "mdi:brain",
"version": "1.0.2", "version": "1.0.8",
"documentation": "https://github.com/smkrv/ha-text-ai" "documentation": "https://github.com/smkrv/ha-text-ai"
} }