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23 Commits
Author SHA1 Message Date
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
SMKRV 5e82b9669c Release v1.0.2 2024-11-19 13:10:18 +03:00
SMKRV 103f9d59e9 Release v1.0.1c 2024-11-19 12:46:25 +03:00
SMKRV 6ad67a5acf Release v1.0.1c 2024-11-19 12:45:26 +03:00
SMKRV 12e5778a1c Release v1.0.1b 2024-11-19 01:18:10 +03:00
SMKRV 5c85cba606 Release v1.0.1b 2024-11-19 00:59:35 +03:00
SMKRV 63d28e12d6 Release v1.0.1b 2024-11-19 00:59:15 +03:00
SMKRV 605c73c6c4 Release v1.0.1b 2024-11-19 00:56:56 +03:00
SMKRV 9d54f88520 Release v1.0.1b 2024-11-19 00:56:33 +03:00
SMKRV 34e93e0045 Release v1.0.1b 2024-11-19 00:53:21 +03:00
SMKRV 34bfd7dfe1 Release v1.0.1b 2024-11-19 00:51:57 +03:00
SMKRV e3487a48cb Release v1.0.1a 2024-11-19 00:37:43 +03:00
SMKRV 72a98d0076 bugfix 2024-11-19 00:34:14 +03:00
17 changed files with 1170 additions and 543 deletions
+32 -3
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@@ -2,13 +2,42 @@ name: Validate with hassfest
on:
push:
branches:
- main
- dev
paths:
- 'custom_components/**'
- '.github/workflows/**'
pull_request:
branches:
- main
paths:
- 'custom_components/**'
- '.github/workflows/**'
schedule:
- cron: "0 0 * * *"
- cron: "0 0 * * *" # Run daily at midnight UTC
workflow_dispatch: # Allow manual trigger
jobs:
validate:
name: Validate with hassfest
runs-on: ubuntu-latest
timeout-minutes: 10
steps:
- uses: actions/checkout@v3
- uses: home-assistant/actions/hassfest@master
- name: ⤵️ Check out code from GitHub
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: 🚀 Run hassfest validation
uses: home-assistant/actions/hassfest@master
- name: ️ Print hassfest version
if: always()
run: |
echo "Hassfest version: $(hassfest --version)"
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
-24
View File
@@ -1,24 +0,0 @@
name: Validate
on:
push:
pull_request:
schedule:
- cron: "0 0 * * *"
jobs:
validate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.x"
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: Run tests
run: |
pytest
+209 -91
View File
@@ -1,145 +1,263 @@
# 🤖 HA text AI Integration for Home Assistant
# 🤖 HA Text AI for Home Assistant
<div align="center">
![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg)
![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg?style=flat-square)
![GitHub downloads](https://img.shields.io/github/downloads/smkrv/ha-text-ai/total.svg?style=flat-square)
![GitHub stars](https://img.shields.io/github/stars/smkrv/ha-text-ai.svg?style=social)
![GitHub forks](https://img.shields.io/github/forks/smkrv/ha-text-ai.svg?style=social)
![GitHub issues](https://img.shields.io/github/issues/smkrv/ha-text-ai.svg)
[![hacs_badge](https://img.shields.io/badge/HACS-Default-orange.svg)](https://github.com/hacs/integration)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai.svg?style=flat-square)
[![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>
<p align="center">
Powerful OpenAI integration for Home Assistant enabling natural language interaction with your smart home
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>
---
## 📋 Table of Contents
- [Features](#-features)
- [Installation](#-installation)
- [Configuration](#-configuration)
- [Services](#-services)
- [Advanced Usage](#-advanced-usage)
- [Troubleshooting](#-troubleshooting)
- [Contributing](#-contributing)
## 🌟 Features
## ✨ Features
- 🧠 **Advanced AI Integration**:
- Support for latest GPT models
- Context-aware responses
- Multi-turn conversations
- 💬 **Natural Language Control**:
- Control devices using everyday language
- Get detailed explanations and recommendations
- 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
- 🔄 **Real-time AI Interaction**: Seamless communication with OpenAI's latest models
- 📝 **Conversation History**: Track and manage your AI interactions
- ⚙️ **Customizable Settings**: Fine-tune AI behavior with adjustable parameters
- 🔌 **Easy Integration**: Simple setup process through HACS or manual installation
- 🎯 **System Prompts**: Set context for more relevant AI responses
## 📋 Prerequisites
## 🚀 Installation
- Home Assistant 2023.8.0 or newer
- OpenAI API key ([Get one here](https://platform.openai.com/account/api-keys))
- Python 3.9 or newer
- Stable internet connection
## ⚡ Installation
### HACS Installation (Recommended)
1. Ensure [HACS](https://hacs.xyz/) is installed
2. Search for "HA text AI" in HACS
3. Click Install
4. Restart Home Assistant
1. Open HACS in Home Assistant
2. Click the "+" button
3. Search for "HA Text AI"
4. Click "Install"
5. Restart Home Assistant
<details>
<summary>Manual Installation Steps</summary>
```bash
# 1. Navigate to your Home Assistant configuration directory
cd ~/.homeassistant
# 2. Create custom_components directory if it doesn't exist
mkdir -p custom_components
# 3. Clone the repository
git clone https://github.com/smkrv/ha-text-ai.git custom_components/ha-text-ai
# 4. Restart Home Assistant
```
</details>
### Manual Installation
1. Download the latest release
2. Extract and copy `custom_components/ha_text_ai` to your `custom_components` directory
3. Restart Home Assistant
4. Add configuration via UI or YAML
## ⚙️ Configuration
### Basic 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
ha-text-ai:
api_key: your_openai_api_key
ha_text_ai:
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
```
### Advanced Configuration
```yaml
ha-text-ai:
api_key: your_openai_api_key
model: gpt-4
temperature: 0.8
max_tokens: 2000
api_endpoint: https://custom-endpoint.com/v1
request_interval: 2.0
```
## 🛠️ Available Services
## 🛠 Services
### Ask Question
### ask_question
```yaml
service: ha-text-ai.ask_question
service: ha_text_ai.ask_question
data:
question: "What's the weather like today?"
model: "gpt-4" # optional
temperature: 0.7 # optional
question: "What's the optimal temperature for sleeping?"
model: "gpt-4o" # optional
temperature: 0.5 # optional
max_tokens: 500 # optional
```
### More Services
- `ha-text-ai.clear_history`: Reset conversation history
- `ha-text-ai.get_history`: Retrieve past interactions
- `ha-text-ai.set_system_prompt`: Configure AI behavior
### set_system_prompt
```yaml
service: ha_text_ai.set_system_prompt
data:
prompt: |
You are a home automation expert focused on:
1. Energy efficiency
2. Comfort optimization
3. Security considerations
Provide practical, actionable advice.
```
## 🔍 Advanced Usage
### clear_history
```yaml
service: ha_text_ai.clear_history
```
### Automation Example
### get_history
```yaml
service: ha_text_ai.get_history
data:
limit: 5 # optional
```
## 🔧 Advanced Examples
### Smart Energy Management
```yaml
automation:
alias: "AI Energy Optimization"
trigger:
platform: time_pattern
hours: "/2"
action:
- service: ha_text_ai.ask_question
data:
question: >
Current power usage: {{ states('sensor.total_power') }}W
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 }}"
```
### Contextual Lighting Control
```yaml
automation:
alias: "AI Lighting Assistant"
trigger:
platform: state
entity_id: binary_sensor.motion
to: 'on'
variables:
context: >
Time: {{ now().strftime('%H:%M') }}
Light Level: {{ states('sensor.illuminance') }}
Room: {{ trigger.to_state.attributes.room }}
Activity: {{ states('input_select.current_activity') }}
Weather: {{ states('weather.home') }}
action:
service: ha-text-ai.ask_question
data:
question: "What should I do when motion is detected?"
- service: ha_text_ai.ask_question
data:
question: >
Based on this context:
{{ 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 }}
```
## 🔧 Troubleshooting
## 📊 Performance Optimization
<details>
<summary>Common Issues and Solutions</summary>
### Token Usage
- Use focused system prompts
- Implement response caching
- Clear history periodically
- Monitor token usage
### API Key Issues
- Verify API key format
- Check API key permissions
- Ensure proper configuration in secrets.yaml
### Response Time
- Adjust request_interval
- Use faster models for simple queries
- Implement timeout handling
- Cache frequent responses
### Connection Problems
- Verify internet connection
- Check API endpoint accessibility
- Review Home Assistant logs
</details>
### Memory Management
- Set appropriate history limits
- Clear unused contexts
- Monitor memory usage
- Use efficient data structures
## 👥 Contributing
## ❗ Troubleshooting
We welcome contributions! Here's how you can help:
### API Issues
- Verify API key validity
- 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
Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Submit a pull request
2. Create feature branch (`git checkout -b feature/Enhancement`)
3. Commit changes (`git commit -m 'Add Enhancement'`)
4. Push branch (`git push origin feature/Enhancement`)
5. Open Pull Request
## 📝 License
MIT License - see [LICENSE](LICENSE) for details.
---
<div align="center">
**[Documentation](https://github.com/smkrv/ha-text-ai/wiki)** | **[Report Bug](https://github.com/smkrv/ha-text-ai/issues)** | **[Request Feature](https://github.com/smkrv/ha-text-ai/issues)**
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>
+62 -165
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@@ -1,207 +1,104 @@
"""The HA text AI integration."""
"""The HA Text AI integration."""
import logging
from typing import Any
import voluptuous as vol
from homeassistant.config_entries import ConfigEntry
from homeassistant.const import CONF_API_KEY, Platform
from homeassistant.core import HomeAssistant, ServiceCall
import homeassistant.helpers.config_validation as cv
from homeassistant.exceptions import HomeAssistantError
from homeassistant.const import CONF_API_KEY
from homeassistant.core import HomeAssistant
from homeassistant.exceptions import ConfigEntryNotReady
from homeassistant.helpers import aiohttp_client
from homeassistant.helpers import config_validation as cv
from .const import (
DOMAIN,
PLATFORMS,
SERVICE_ASK_QUESTION,
SERVICE_CLEAR_HISTORY,
SERVICE_GET_HISTORY,
SERVICE_SET_SYSTEM_PROMPT,
CONF_MODEL,
CONF_TEMPERATURE,
CONF_MAX_TOKENS,
CONF_API_ENDPOINT,
CONF_REQUEST_INTERVAL,
DEFAULT_MODEL,
DEFAULT_TEMPERATURE,
DEFAULT_MAX_TOKENS,
DEFAULT_API_ENDPOINT,
DEFAULT_REQUEST_INTERVAL,
)
from .coordinator import HATextAICoordinator
_LOGGER = logging.getLogger(__name__)
CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool:
"""Set up the HA text AI component from configuration.yaml."""
"""Set up the HA Text AI component."""
hass.data.setdefault(DOMAIN, {})
async def async_ask_question(call: ServiceCall) -> None:
"""Handle the ask_question service call.
Args:
call: Service call containing question and optional parameters.
"""
try:
# Get the coordinator from the first config entry
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
question = call.data["question"]
model = call.data.get("model", coordinator.model)
temperature = call.data.get("temperature", coordinator.temperature)
max_tokens = call.data.get("max_tokens", coordinator.max_tokens)
# Temporarily update parameters if they were overridden
original_model = coordinator.model
original_temperature = coordinator.temperature
original_max_tokens = coordinator.max_tokens
try:
coordinator.model = model
coordinator.temperature = temperature
coordinator.max_tokens = max_tokens
await coordinator.async_ask_question(question)
finally:
# Restore original parameters
coordinator.model = original_model
coordinator.temperature = original_temperature
coordinator.max_tokens = original_max_tokens
except Exception as ex:
_LOGGER.error("Error asking question: %s", str(ex))
raise HomeAssistantError(f"Failed to ask question: {str(ex)}")
async def async_clear_history(call: ServiceCall) -> None:
"""Handle the clear_history service call."""
try:
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()
except Exception as ex:
_LOGGER.error("Error clearing history: %s", str(ex))
raise HomeAssistantError(f"Failed to clear history: {str(ex)}")
async def async_get_history(call: ServiceCall) -> dict[str, list]:
"""Handle the get_history service call.
Returns:
Dictionary containing chat history.
"""
try:
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
limit = call.data.get("limit", 10)
history = list(coordinator._responses.items())[-limit:]
return {
"history": [
{"question": q, "response": r} for q, r in history
]
}
except Exception as ex:
_LOGGER.error("Error getting history: %s", str(ex))
raise HomeAssistantError(f"Failed to get history: {str(ex)}")
async def async_set_system_prompt(call: ServiceCall) -> None:
"""Handle the set_system_prompt service call."""
try:
if not hass.data[DOMAIN]:
raise HomeAssistantError("No AI Text integration configured")
coordinator = next(iter(hass.data[DOMAIN].values()))
prompt = call.data["prompt"]
coordinator.system_prompt = prompt
except Exception as ex:
_LOGGER.error("Error setting system prompt: %s", str(ex))
raise HomeAssistantError(f"Failed to set system prompt: {str(ex)}")
# Register services
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
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:
session = aiohttp_client.async_get_clientsession(hass)
coordinator = HATextAICoordinator(
hass,
api_key=entry.data[CONF_API_KEY],
endpoint=entry.data.get(CONF_API_ENDPOINT),
model=entry.data.get(CONF_MODEL),
temperature=entry.data.get(CONF_TEMPERATURE),
max_tokens=entry.data.get(CONF_MAX_TOKENS),
request_interval=entry.data.get(CONF_REQUEST_INTERVAL),
endpoint=entry.data.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT),
model=entry.data.get(CONF_MODEL, DEFAULT_MODEL),
temperature=entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
max_tokens=entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
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
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:
_LOGGER.error("Error setting up entry: %s", str(ex))
raise ConfigEntryNotReady from ex
_LOGGER.exception("Unexpected error setting up entry: %s", str(ex))
return False
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
"""Unload a config entry."""
try:
if entry.entry_id not in hass.data.get(DOMAIN, {}):
return True
unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
if unload_ok:
hass.data[DOMAIN].pop(entry.entry_id)
# Only remove services if this is the last entry
if not hass.data[DOMAIN]:
for service in [
SERVICE_ASK_QUESTION,
SERVICE_CLEAR_HISTORY,
SERVICE_GET_HISTORY,
SERVICE_SET_SYSTEM_PROMPT
]:
hass.services.async_remove(DOMAIN, service)
coordinator = hass.data[DOMAIN].pop(entry.entry_id)
await coordinator.async_shutdown()
return unload_ok
except Exception as ex:
_LOGGER.error("Error unloading entry: %s", str(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))
+231 -36
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@@ -1,8 +1,19 @@
"""Config flow for HA text AI integration."""
from typing import Any, Dict, Optional, Tuple
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.const import CONF_API_KEY
import homeassistant.helpers.config_validation as cv
from homeassistant.core import callback
from openai import AsyncOpenAI
from openai import OpenAIError, APIError, APIConnectionError, AuthenticationError, RateLimitError
from .const import (
DOMAIN,
@@ -18,70 +29,254 @@ from .const import (
DEFAULT_REQUEST_INTERVAL,
)
class HATextAIConfigFlow(config_entries.ConfigFlow):
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({
vol.Required(CONF_API_KEY): str,
vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): str,
vol.Optional(
CONF_TEMPERATURE,
default=DEFAULT_TEMPERATURE
): vol.All(
vol.Coerce(float),
vol.Range(min=0, max=2)
),
vol.Optional(
CONF_MAX_TOKENS,
default=DEFAULT_MAX_TOKENS
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=4096)
),
vol.Optional(CONF_API_ENDPOINT, default=DEFAULT_API_ENDPOINT): str,
vol.Optional(
CONF_REQUEST_INTERVAL,
default=DEFAULT_REQUEST_INTERVAL
): 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):
"""Handle a config flow for HA text AI."""
VERSION = 1
DOMAIN = DOMAIN # Define the domain as a class variable
async def async_step_user(self, user_input=None):
async def async_step_user(
self,
user_input: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""Handle the initial step."""
errors = {}
errors: Dict[str, str] = {}
if user_input is not None:
return self.async_create_entry(title="HA text AI", data=user_input)
try:
# Validate URL format
endpoint = user_input.get(CONF_API_ENDPOINT, DEFAULT_API_ENDPOINT)
try:
result = urlparse(endpoint)
if not all([result.scheme, result.netloc]):
errors["base"] = "invalid_url_format"
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()
return self.async_create_entry(
title="HA text AI",
data=user_input
)
errors["base"] = error_code
if error_code == "invalid_model":
_LOGGER.warning(
"Selected model %s not found in available models: %s",
user_input[CONF_MODEL],
", ".join(available_models)
)
except vol.Invalid as err:
_LOGGER.error("Validation error: %s", str(err))
errors["base"] = "invalid_input"
return self.async_show_form(
step_id="user",
data_schema=vol.Schema({
vol.Required("api_key"): str,
vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): str,
vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.Coerce(float),
vol.Optional(CONF_MAX_TOKENS, default=DEFAULT_MAX_TOKENS): vol.Coerce(int),
vol.Optional(CONF_API_ENDPOINT, default=DEFAULT_API_ENDPOINT): str,
vol.Optional(CONF_REQUEST_INTERVAL, default=DEFAULT_REQUEST_INTERVAL): vol.Coerce(float),
}),
data_schema=STEP_USER_DATA_SCHEMA,
errors=errors,
description_placeholders={
"default_model": DEFAULT_MODEL,
"default_endpoint": DEFAULT_API_ENDPOINT,
}
)
@staticmethod
@callback
def async_get_options_flow(config_entry):
def async_get_options_flow(
config_entry: config_entries.ConfigEntry,
) -> config_entries.OptionsFlow:
"""Get the options flow for this handler."""
return OptionsFlowHandler(config_entry)
class OptionsFlowHandler(config_entries.OptionsFlow):
"""Handle options flow for HA text AI."""
def __init__(self, config_entry):
def __init__(self, config_entry: config_entries.ConfigEntry) -> None:
"""Initialize options flow."""
self.config_entry = config_entry
async def async_step_init(self, user_input=None):
async def async_step_init(
self,
user_input: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""Handle options flow."""
if user_input is not None:
return self.async_create_entry(title="", data=user_input)
options_schema = vol.Schema({
vol.Optional(
CONF_TEMPERATURE,
default=self.config_entry.options.get(
CONF_TEMPERATURE, DEFAULT_TEMPERATURE
),
description={"suggested_value": DEFAULT_TEMPERATURE},
): vol.All(
vol.Coerce(float),
vol.Range(min=0, max=2)
),
vol.Optional(
CONF_MAX_TOKENS,
default=self.config_entry.options.get(
CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
),
description={"suggested_value": DEFAULT_MAX_TOKENS},
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=4096)
),
vol.Optional(
CONF_REQUEST_INTERVAL,
default=self.config_entry.options.get(
CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
),
description={"suggested_value": DEFAULT_REQUEST_INTERVAL},
): vol.All(
vol.Coerce(float),
vol.Range(min=0.1)
),
})
return self.async_show_form(
step_id="init",
data_schema=vol.Schema({
vol.Optional(
CONF_TEMPERATURE,
default=self.config_entry.options.get(
CONF_TEMPERATURE, DEFAULT_TEMPERATURE
),
): vol.Coerce(float),
vol.Optional(
CONF_MAX_TOKENS,
default=self.config_entry.options.get(
CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
),
): vol.Coerce(int),
vol.Optional(
CONF_REQUEST_INTERVAL,
default=self.config_entry.options.get(
CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
),
): vol.Coerce(float),
}),
data_schema=options_schema,
)
+134 -23
View File
@@ -1,30 +1,141 @@
"""Constants for the HA text AI integration."""
from typing import Final
from homeassistant.const import Platform
DOMAIN = "ha-text-ai"
PLATFORMS = [Platform.SENSOR]
# Domain and platforms
DOMAIN: Final = "ha_text_ai"
PLATFORMS: Final = [Platform.SENSOR]
# Configuration
CONF_MODEL = "model"
CONF_TEMPERATURE = "temperature"
CONF_MAX_TOKENS = "max_tokens"
CONF_API_ENDPOINT = "api_endpoint"
CONF_REQUEST_INTERVAL = "request_interval"
# Configuration constants
CONF_MODEL: Final = "model"
CONF_TEMPERATURE: Final = "temperature"
CONF_MAX_TOKENS: Final = "max_tokens"
CONF_API_ENDPOINT: Final = "api_endpoint"
CONF_REQUEST_INTERVAL: Final = "request_interval"
# Defaults
DEFAULT_MODEL = "gpt-3.5-turbo"
DEFAULT_TEMPERATURE = 0.7
DEFAULT_MAX_TOKENS = 1000
DEFAULT_API_ENDPOINT = "https://api.openai.com/v1"
DEFAULT_REQUEST_INTERVAL = 1.0
# Default values
DEFAULT_MODEL: Final = "gpt-3.5-turbo"
DEFAULT_TEMPERATURE: Final = 0.7
DEFAULT_MAX_TOKENS: Final = 1000
DEFAULT_API_ENDPOINT: Final = "https://api.openai.com/v1"
DEFAULT_REQUEST_INTERVAL: Final = 1.0
DEFAULT_TIMEOUT: Final = 30
DEFAULT_QUEUE_SIZE: Final = 100
DEFAULT_HISTORY_LIMIT: Final = 50
# Services
SERVICE_ASK_QUESTION = "ask_question"
SERVICE_CLEAR_HISTORY = "clear_history"
SERVICE_GET_HISTORY = "get_history"
SERVICE_SET_SYSTEM_PROMPT = "set_system_prompt"
# Parameter constraints
MIN_TEMPERATURE: Final = 0.0
MAX_TEMPERATURE: Final = 2.0
MIN_MAX_TOKENS: Final = 1
MAX_MAX_TOKENS: Final = 4096
MIN_REQUEST_INTERVAL: Final = 0.1
MIN_TIMEOUT: Final = 5
MAX_TIMEOUT: Final = 120
# Attributes
ATTR_QUESTION = "question"
ATTR_RESPONSE = "response"
ATTR_LAST_UPDATED = "last_updated"
# Service names
SERVICE_ASK_QUESTION: Final = "ask_question"
SERVICE_CLEAR_HISTORY: Final = "clear_history"
SERVICE_GET_HISTORY: Final = "get_history"
SERVICE_SET_SYSTEM_PROMPT: Final = "set_system_prompt"
# Service descriptions
SERVICE_ASK_QUESTION_DESCRIPTION: Final = "Ask a question to the AI model"
SERVICE_CLEAR_HISTORY_DESCRIPTION: Final = "Clear conversation history"
SERVICE_GET_HISTORY_DESCRIPTION: Final = "Get conversation history"
SERVICE_SET_SYSTEM_PROMPT_DESCRIPTION: Final = "Set system prompt for AI model"
# Attribute keys
ATTR_QUESTION: Final = "question"
ATTR_RESPONSE: Final = "response"
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_INVALID_API_KEY: Final = "invalid_api_key"
ERROR_CANNOT_CONNECT: Final = "cannot_connect"
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
CONF_MODEL_DESCRIPTION: Final = "AI model to use for responses"
CONF_TEMPERATURE_DESCRIPTION: Final = "Temperature for response generation (0-2)"
CONF_MAX_TOKENS_DESCRIPTION: Final = "Maximum tokens in response (1-4096)"
CONF_API_ENDPOINT_DESCRIPTION: Final = "API endpoint URL"
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_NAME: Final = "HA Text AI"
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"
+125 -45
View File
@@ -2,20 +2,14 @@
import asyncio
import logging
from datetime import timedelta
from typing import Any, Dict
from typing import Any, Dict, Optional
import openai
from openai import AsyncOpenAI, APIError, AuthenticationError, RateLimitError
from homeassistant.core import HomeAssistant
from homeassistant.helpers.update_coordinator import DataUpdateCoordinator
from homeassistant.exceptions import ConfigEntryAuthFailed
import async_timeout
from .const import (
DOMAIN,
DEFAULT_REQUEST_INTERVAL,
CONF_MODEL,
CONF_TEMPERATURE,
CONF_MAX_TOKENS,
)
from .const import DOMAIN
_LOGGER = logging.getLogger(__name__)
@@ -31,6 +25,7 @@ class HATextAICoordinator(DataUpdateCoordinator):
temperature: float,
max_tokens: int,
request_interval: float,
session: Optional[Any] = None,
) -> None:
"""Initialize."""
super().__init__(
@@ -40,18 +35,34 @@ class HATextAICoordinator(DataUpdateCoordinator):
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 = temperature
self.max_tokens = max_tokens
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
openai.api_key = self.api_key
if endpoint != "https://api.openai.com/v1":
openai.api_base = endpoint
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:
raise ValueError("API key is required")
if not isinstance(temperature, (int, float)) or not 0 <= temperature <= 2:
raise ValueError("Temperature must be between 0 and 2")
if not isinstance(max_tokens, int) or max_tokens < 1:
raise ValueError("Max tokens must be a positive integer")
async def _async_update_data(self) -> Dict[str, Any]:
"""Update data via OpenAI API."""
@@ -59,56 +70,125 @@ class HATextAICoordinator(DataUpdateCoordinator):
return self._responses
try:
question = await self._question_queue.get()
response_content = await self.hass.async_add_executor_job(
self._make_api_call, question
async with async_timeout.timeout(30):
question = await self._question_queue.get()
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
)
response = {
"question": question,
"response": response_content
}
self._responses[question] = response
_LOGGER.debug(f"Response from API: {response}")
return self._responses
except openai.error.AuthenticationError as err:
raise ConfigEntryAuthFailed from err
except Exception as err:
_LOGGER.error("Error communicating with API: %s", err)
return self._responses
async def _handle_timeout_error(self) -> None:
"""Handle timeout errors."""
self._error_count += 1
if not self._question_queue.empty():
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."""
try:
messages = [{"role": "system", "content": self.system_prompt}] if self.system_prompt else []
messages = []
if self.system_prompt:
messages.append({"role": "system", "content": self.system_prompt})
messages.append({"role": "user", "content": question})
completion = openai.chat.completions.create(
completion = await self.client.chat.completions.create(
model=self.model,
messages=messages,
temperature=self.temperature,
max_tokens=self.max_tokens,
)
return completion.choices[0].message.content
except Exception as err:
_LOGGER.error("Error in API call: %s", err)
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)
_LOGGER.debug(f"Question added to queue: {question}")
await self.async_refresh()
def clear_history(self) -> None:
"""Clear the stored question and response history."""
self._responses.clear()
_LOGGER.info("History cleared.")
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()
def get_history(self, limit: int = 10) -> Dict[str, Any]:
"""Get the history of questions and responses."""
return {"history": list(self._responses.values())[-limit:]}
await self.client.close()
self._is_ready = False
def set_system_prompt(self, prompt: str) -> None:
"""Set a system prompt that will be used for all future questions."""
self.system_prompt = prompt
_LOGGER.info(f"System prompt set: {prompt}")
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
+8 -9
View File
@@ -1,15 +1,14 @@
{
"domain": "ha-text-ai",
"name": "HA text AI",
"domain": "ha_text_ai",
"name": "HA Text AI",
"codeowners": ["@smkrv"],
"config_flow": true,
"documentation": "https://github.com/smkrv/ha-text-ai",
"dependencies": [],
"documentation": "https://github.com/smkrv/ha-text-ai/wiki",
"iot_class": "cloud_polling",
"issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
"requirements": ["openai>=1.0.0"],
"ssdp": [],
"zeroconf": [],
"homekit": {},
"dependencies": [],
"codeowners": ["@smkrv"],
"version": "1.0.0",
"iot_class": "cloud_polling"
"version": "1.0.7",
"zeroconf": []
}
+142 -19
View File
@@ -1,16 +1,49 @@
"""Sensor platform for HA text AI."""
from typing import Any, Callable, Dict, Optional
from datetime import datetime
import logging
from typing import Any, Dict, Optional
from homeassistant.components.sensor import SensorEntity, SensorStateClass
from homeassistant.components.sensor import (
SensorEntity,
SensorStateClass,
SensorDeviceClass,
)
from homeassistant.config_entries import ConfigEntry
from homeassistant.core import HomeAssistant
from homeassistant.helpers.entity_platform import AddEntitiesCallback
from homeassistant.helpers.typing import StateType
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
_LOGGER = logging.getLogger(__name__)
async def async_setup_entry(
hass: HomeAssistant,
entry: ConfigEntry,
@@ -23,6 +56,10 @@ async def async_setup_entry(
class HATextAISensor(CoordinatorEntity, SensorEntity):
"""HA text AI Sensor."""
_attr_has_entity_name = True
_attr_state_class = SensorStateClass.MEASUREMENT
_attr_device_class = SensorDeviceClass.TIMESTAMP
def __init__(
self,
coordinator: HATextAICoordinator,
@@ -32,27 +69,113 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
super().__init__(coordinator)
self._config_entry = config_entry
self._attr_unique_id = f"{config_entry.entry_id}"
self._attr_name = "HA text AI"
self._attr_state_class = SensorStateClass.MEASUREMENT
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
def state(self) -> StateType:
"""Return the state of the sensor."""
if self.coordinator.data:
return "Ready" # Assuming "Ready" is a valid state, you might want to return something meaningful, like the last response time.
return "Not Ready"
if not self.coordinator.data or not self.coordinator.last_update_success_time:
return None
try:
if isinstance(self.coordinator.last_update_success_time, datetime):
return dt_util.as_local(self.coordinator.last_update_success_time)
return self.coordinator.last_update_success_time
except Exception as err:
_LOGGER.error("Error getting state: %s", err, exc_info=True)
return None
@property
def extra_state_attributes(self) -> Optional[Dict[str, Any]]:
def extra_state_attributes(self) -> Dict[str, Any]:
"""Return entity specific state attributes."""
if not self.coordinator.data:
return None
keys = list(self.coordinator.data.keys())
values = list(self.coordinator.data.values())
last_question = keys[-1]
last_response = values[-1]
return {
ATTR_QUESTION: last_question,
ATTR_RESPONSE: last_response,
ATTR_LAST_UPDATED: self.coordinator.last_update_success_time,
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
def available(self) -> bool:
"""Return if entity is available."""
return self.coordinator.last_update_success
async def async_added_to_hass(self) -> None:
"""When entity is added to hass."""
await super().async_added_to_hass()
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()
+108 -22
View File
@@ -1,66 +1,109 @@
# Service to ask a question
ask_question:
name: Ask Question
description: Send a question to the AI and get a 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:
question:
name: Question
description: The question or prompt to send to the AI
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
example: "What is the weather like today?"
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:
text:
multiline: true
type: text
model:
name: Model
description: Override the default model for this question (optional)
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
example: "gpt-4"
example: "gpt-3.5-turbo"
default: "gpt-3.5-turbo"
selector:
select:
options:
- "gpt-3.5-turbo"
- "gpt-4"
- "gpt-4-32k"
- label: "GPT-3.5 Turbo (Fast & Efficient)"
value: "gpt-3.5-turbo"
- label: "GPT-3.5 Turbo 16K (Extended)"
value: "gpt-3.5-turbo-16k"
- label: "GPT-4 (Most Capable)"
value: "gpt-4"
- label: "GPT-4 32K (Extended Context)"
value: "gpt-4-32k"
- label: "GPT-4 Turbo (Latest)"
value: "gpt-4-1106-preview"
mode: dropdown
temperature:
name: Temperature
description: Control randomness in the response (0.0-1.0, lower is more focused)
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
default: 0.7
selector:
number:
min: 0.0
max: 1.0
max: 2.0
step: 0.1
mode: slider
unit_of_measurement: ""
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
default: 1000
selector:
number:
min: 1
max: 4000
max: 4096
step: 1
mode: box
# Service to clear response history
clear_history:
name: Clear History
description: Clear the stored question and response history
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: {}
# Service to get response history
get_history:
name: Get History
description: Get the history of questions and responses
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:
limit:
name: Limit
description: Maximum number of history items 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
default: 10
selector:
@@ -68,17 +111,60 @@ get_history:
min: 1
max: 100
step: 1
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
# Service to set system prompt
set_system_prompt:
name: Set System Prompt
description: Set a system prompt that will be used for all future questions
description: >-
Configure the AI's behavior by setting a system prompt.
This affects how the AI interprets and responds to all future questions.
The prompt will persist until changed or cleared.
fields:
prompt:
name: System Prompt
description: The system prompt to set
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
example: "You are a helpful assistant specializing in home automation"
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:
text:
multiline: true
type: text
max_length: 1000
clear_prompt:
name: Clear Existing Prompt
description: >-
Set to true to remove the current system prompt before applying the new one.
This ensures no conflicting instructions remain.
required: false
default: false
selector:
boolean: {}
@@ -1,38 +1,61 @@
{
"config": {
"step": {
"user": {
"title": "Set up HA text AI",
"description": "Set up your OpenAI integration",
"data": {
"api_key": "API Key",
"model": "Model",
"temperature": "Temperature",
"max_tokens": "Max Tokens",
"api_endpoint": "API Endpoint",
"request_interval": "Request Interval (seconds)"
"config": {
"option": {
"api_key": {
"name": "API Key",
"description": "Your OpenAI API key"
},
"model": {
"name": "Model",
"description": "AI model to use for responses"
},
"temperature": {
"name": "Temperature",
"description": "Temperature for response generation (0-2)"
},
"max_tokens": {
"name": "Max Tokens",
"description": "Maximum tokens in response (1-4096)"
},
"api_endpoint": {
"name": "API Endpoint",
"description": "API endpoint URL"
},
"request_interval": {
"name": "Request Interval",
"description": "Minimum time between API requests (seconds)"
}
}
}
},
"options": {
"temperature": "Temperature",
"max_tokens": "Max Tokens",
"request_interval": "Request Interval"
},
"error": {
"auth": "API key is invalid.",
"cannot_connect": "Failed to connect to API.",
"unknown": "Unexpected error occurred."
"invalid_api_key": "Invalid API key",
"cannot_connect": "Cannot connect to the API",
"unknown_error": "Unknown error",
"invalid_model": "Invalid model",
"rate_limit_exceeded": "Rate limit exceeded",
"context_length_exceeded": "Context length exceeded",
"api_error": "API error",
"timeout_error": "Timeout error",
"queue_full": "Queue full",
"invalid_prompt": "Invalid prompt"
},
"abort": {
"already_configured": "Device is already configured"
"state": {
"ready": "Ready",
"processing": "Processing",
"error": "Error",
"disconnected": "Disconnected",
"rate_limited": "Rate limited",
"initializing": "Initializing"
},
"services": {
"ask_question": "Ask Question",
"clear_history": "Clear History",
"get_history": "Get History",
"set_system_prompt": "Set System Prompt"
}
},
"options": {
"step": {
"init": {
"title": "HA text AI Options",
"data": {
"temperature": "Temperature",
"max_tokens": "Max Tokens",
"request_interval": "Request Interval (seconds)"
}
}
}
}
}
@@ -0,0 +1,61 @@
{
"config": {
"option": {
"api_key": {
"name": "API ключ",
"description": "Ваш API ключ OpenAI"
},
"model": {
"name": "Модель",
"description": "Модель AI для генерации ответов"
},
"temperature": {
"name": "Температура",
"description": "Температура для генерации ответов (0-2)"
},
"max_tokens": {
"name": "Максимальное количество токенов",
"description": "Максимальное количество токенов в ответе (1-4096)"
},
"api_endpoint": {
"name": "Конечная точка API",
"description": "URL конечной точки API"
},
"request_interval": {
"name": "Интервал запросов",
"description": "Минимальное время между запросами к API в секундах"
}
}
},
"options": {
"temperature": "Температура",
"max_tokens": "Максимальное количество токенов",
"request_interval": "Интервал запросов"
},
"error": {
"invalid_api_key": "Неверный API ключ",
"cannot_connect": "Не удается подключиться к API",
"unknown_error": "Неизвестная ошибка",
"invalid_model": "Неверная модель",
"rate_limit_exceeded": "Превышен лимит запросов",
"context_length_exceeded": "Превышена длина контекста",
"api_error": "Ошибка API",
"timeout_error": "Время ожидания истекло",
"queue_full": "Очередь полна",
"invalid_prompt": "Неверный запрос"
},
"state": {
"ready": "Готово",
"processing": "Обработка",
"error": "Ошибка",
"disconnected": "Отключено",
"rate_limited": "Ограниченный по скорости",
"initializing": "Инициализация"
},
"services": {
"ask_question": "Задать вопрос",
"clear_history": "Очистить историю",
"get_history": "Получить историю",
"set_system_prompt": "Установить системный запрос"
}
}
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+4 -2
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@@ -2,6 +2,8 @@
"name": "HA text AI",
"render_readme": true,
"domains": ["sensor"],
"homeassistant": "2023.8.0",
"icon": "mdi:brain"
"homeassistant": "2024.11.0",
"icon": "mdi:brain",
"version": "1.0.7",
"documentation": "https://github.com/smkrv/ha-text-ai"
}
-8
View File
@@ -1,8 +0,0 @@
"""Common fixtures for tests."""
import pytest
from homeassistant.core import HomeAssistant
@pytest.fixture
def hass() -> HomeAssistant:
"""Return a Home Assistant instance for testing."""
return HomeAssistant()
-65
View File
@@ -1,65 +0,0 @@
"""Tests for the HA text AI integration."""
from unittest.mock import AsyncMock, patch
import pytest
from custom_components.ha_text_ai.const import DOMAIN
from homeassistant.core import HomeAssistant
from homeassistant.setup import async_setup_component
@pytest.fixture
def mock_setup_entry() -> AsyncMock:
"""Override async_setup_entry."""
with patch(
"custom_components.ha_text_ai.async_setup_entry",
return_value=True,
) as mock_setup_entry:
yield mock_setup_entry
@pytest.fixture
def mock_coordinator() -> AsyncMock:
"""Override coordinator."""
with patch(
"custom_components.ha_text_ai.coordinator.HATextAICoordinator",
return_value=AsyncMock(),
) as mock_coordinator:
yield mock_coordinator
async def test_async_setup(hass: HomeAssistant, mock_setup_entry: AsyncMock) -> None:
"""Test the initial setup."""
assert await async_setup_component(hass, DOMAIN, {
DOMAIN: {
"api_key": "test_key",
"model": "gpt-3.5-turbo",
"temperature": 0.7,
"max_tokens": 1000,
"api_endpoint": "https://api.openai.com/v1",
"request_interval": 1.0
}
})
await hass.async_block_till_done()
assert DOMAIN in hass.data
async def test_async_setup_entry(
hass: HomeAssistant,
mock_coordinator: AsyncMock
) -> None:
"""Test setup entry."""
entry = MockConfigEntry(
domain=DOMAIN,
data={
"api_key": "test_key",
"model": "gpt-3.5-turbo",
"temperature": 0.7,
"max_tokens": 1000,
"api_endpoint": "https://api.openai.com/v1",
"request_interval": 1.0
},
)
entry.add_to_hass(hass)
assert await hass.config_entries.async_setup(entry.entry_id)
await hass.async_block_till_done()
assert len(mock_coordinator.mock_calls) == 1
assert DOMAIN in hass.data
assert entry.entry_id in hass.data[DOMAIN]