mirror of
https://github.com/smkrv/ha-text-ai.git
synced 2026-07-22 15:14:01 +08:00
Compare commits
237
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
29f3ae5592 | ||
|
|
107d2a64fc | ||
|
|
e24bb884ef | ||
|
|
107a2ef962 | ||
|
|
9d58f2cf1e | ||
|
|
29f6860fe1 | ||
|
|
fa89026e05 | ||
|
|
9968452c46 | ||
|
|
9665634013 | ||
|
|
76d10ba8fb | ||
|
|
e9ea10203e | ||
|
|
92a4c2da02 | ||
|
|
b6d8eb98f6 | ||
|
|
b6b01bccd7 | ||
|
|
ace2339b4f | ||
|
|
166c1f9c9c | ||
|
|
e4039a08bc | ||
|
|
1da5b5941d | ||
|
|
6683f12c80 | ||
|
|
2277f48e46 | ||
|
|
d206bde15a | ||
|
|
af16d03915 | ||
|
|
bf26cd3cfb | ||
|
|
094062773a | ||
|
|
4cd95813bc | ||
|
|
c2064f0b64 | ||
|
|
fafd927610 | ||
|
|
7f46380054 | ||
|
|
351a8b18dd | ||
|
|
39833b333f | ||
|
|
888a41375b | ||
|
|
823abb22e4 | ||
|
|
a3c88309b4 | ||
|
|
beebc7e194 | ||
|
|
3f8f22ac61 | ||
|
|
12c95d0e92 | ||
|
|
b00f600cd9 | ||
|
|
a4925fc943 | ||
|
|
28248ac3c4 | ||
|
|
d2b5626977 | ||
|
|
b61429b52d | ||
|
|
d05b39d8ae | ||
|
|
6b3b0f1bd6 | ||
|
|
feb679ae77 | ||
|
|
9779e5552d | ||
|
|
fbd187dc29 | ||
|
|
e8b6116439 | ||
|
|
fcd3e79cb7 | ||
|
|
d03078cfd4 | ||
|
|
b94d859849 | ||
|
|
dc4fcdf578 | ||
|
|
da4c40017d | ||
|
|
ac420b6495 | ||
|
|
5791601c7e | ||
|
|
eb149184c3 | ||
|
|
d410073c64 | ||
|
|
b373f6c513 | ||
|
|
18395a2265 | ||
|
|
2e4c63ba7d | ||
|
|
9fdf7c4642 | ||
|
|
053a9050b6 | ||
|
|
7efabdfa70 | ||
|
|
e5077969e9 | ||
|
|
2688da5a82 | ||
|
|
4f46d077df | ||
|
|
bde856c576 | ||
|
|
083cb9f730 | ||
|
|
2644d720e7 | ||
|
|
2fe84ab801 | ||
|
|
ca1d79f848 | ||
|
|
e52572beaa | ||
|
|
0f77a98d76 | ||
|
|
ebede3d56b | ||
|
|
1692f5519f | ||
|
|
dad1aa1c45 | ||
|
|
5d2244db6e | ||
|
|
8a15cfe4b4 | ||
|
|
500c7fbe30 | ||
|
|
894b600b09 | ||
|
|
97f0b30cd6 | ||
|
|
9855e8a561 | ||
|
|
c2b259ade1 | ||
|
|
cfc185117c | ||
|
|
9e89920e79 | ||
|
|
af190da333 | ||
|
|
3e3ec45b19 | ||
|
|
f0fe593d78 | ||
|
|
8646118a27 | ||
|
|
31f21b3a6b | ||
|
|
12d87e30e1 | ||
|
|
6ecc3f72d1 | ||
|
|
e8c40dc6b8 | ||
|
|
0279517a42 | ||
|
|
072eab1703 | ||
|
|
3b38a6dd29 | ||
|
|
7f8d8be5fb | ||
|
|
3aa6b6a2ef | ||
|
|
d870cfbba6 | ||
|
|
13a9e1a5d7 | ||
|
|
06aba7e692 | ||
|
|
c73ff02bfb | ||
|
|
ed03170817 | ||
|
|
3079994a77 | ||
|
|
41b37f9edf | ||
|
|
8d65d3ef4e | ||
|
|
357c8b8be4 | ||
|
|
a47b343f93 | ||
|
|
4388e0f2e1 | ||
|
|
f2adff1d85 | ||
|
|
ad51da7950 | ||
|
|
7610a71829 | ||
|
|
8800f226d2 | ||
|
|
ba16932b44 | ||
|
|
81394345b4 | ||
|
|
72621d9d0e | ||
|
|
d35ded6502 | ||
|
|
b17e5c3db2 | ||
|
|
365c4df2a4 | ||
|
|
ab79d05e96 | ||
|
|
a208004fe0 | ||
|
|
51c714df25 | ||
|
|
87b45df180 | ||
|
|
accb15a92a | ||
|
|
a421825050 | ||
|
|
c55112c8f7 | ||
|
|
accbc5635e | ||
|
|
558ff7d141 | ||
|
|
fa70a0a4ab | ||
|
|
50b414a904 | ||
|
|
80c91039e1 | ||
|
|
966e01e7e2 | ||
|
|
82ffce1e25 | ||
|
|
c7257cc00a | ||
|
|
ab877c2e9a | ||
|
|
c6dcf307fd | ||
|
|
30d69e7ed1 | ||
|
|
bb8195c0d1 | ||
|
|
a813302e86 | ||
|
|
0f643664f7 | ||
|
|
665537cb6a | ||
|
|
766b9293cf | ||
|
|
6e014e30d9 | ||
|
|
30fc8ad1df | ||
|
|
bcad939a3d | ||
|
|
e153df85fb | ||
|
|
26908b5d81 | ||
|
|
0ddca8ff58 | ||
|
|
fd285d969e | ||
|
|
10bebe5eb5 | ||
|
|
fef5e81033 | ||
|
|
a325ae180a | ||
|
|
df1ae9cd55 | ||
|
|
d5380b4195 | ||
|
|
9e12ada4fa | ||
|
|
bb3240f1b3 | ||
|
|
7780ac89ef | ||
|
|
c58eae695e | ||
|
|
45244dcaa9 | ||
|
|
53b15fa74c | ||
|
|
9341b02f4b | ||
|
|
158db522a8 | ||
|
|
f3b76c0bc1 | ||
|
|
d11f961566 | ||
|
|
9d7f81d042 | ||
|
|
c95e1a829c | ||
|
|
7bd06e7b88 | ||
|
|
6e64b6feac | ||
|
|
f6c0e6265e | ||
|
|
662ce701ca | ||
|
|
72bbfb3f58 | ||
|
|
9306c12fcd | ||
|
|
9f1ea70c9f | ||
|
|
98913b359a | ||
|
|
a4905f0778 | ||
|
|
e603231633 | ||
|
|
345463322a | ||
|
|
c298866e3c | ||
|
|
75e97ac652 | ||
|
|
149ec16d57 | ||
|
|
31e30d94aa | ||
|
|
326f876410 | ||
|
|
58a7ae4229 | ||
|
|
8f796ad9dc | ||
|
|
8be860007a | ||
|
|
1985e201b4 | ||
|
|
4e4b41661b | ||
|
|
b24a99a11f | ||
|
|
69b151f990 | ||
|
|
2d4eb59d6c | ||
|
|
5037622fb6 | ||
|
|
962a089bf4 | ||
|
|
4c56565b66 | ||
|
|
8432038f09 | ||
|
|
929d916d41 | ||
|
|
675975d951 | ||
|
|
524ec87395 | ||
|
|
94f8193996 | ||
|
|
7c3fcf73c3 | ||
|
|
20bbf89679 | ||
|
|
86dca52d07 | ||
|
|
78d1561e74 | ||
|
|
054e4af258 | ||
|
|
dc03faa97e | ||
|
|
9a7635c2ae | ||
|
|
df3d79c20c | ||
|
|
d6144be7ed | ||
|
|
9afbb904b3 | ||
|
|
93558b2444 | ||
|
|
9f93f1ee18 | ||
|
|
30a9b53ba1 | ||
|
|
5175970d55 | ||
|
|
f6bfbd4a07 | ||
|
|
4ddb0dc977 | ||
|
|
24dc4ac4d4 | ||
|
|
976f4f16a3 | ||
|
|
2bdef2b494 | ||
|
|
42324a793b | ||
|
|
30aa894634 | ||
|
|
398b2550a9 | ||
|
|
f1deaa2014 | ||
|
|
f4b0ce902e | ||
|
|
d899144149 | ||
|
|
5d49b4a40b | ||
|
|
1a84727cf1 | ||
|
|
d3c7e25202 | ||
|
|
5e82b9669c | ||
|
|
103f9d59e9 | ||
|
|
6ad67a5acf | ||
|
|
12e5778a1c | ||
|
|
5c85cba606 | ||
|
|
63d28e12d6 | ||
|
|
605c73c6c4 | ||
|
|
9d54f88520 | ||
|
|
34e93e0045 | ||
|
|
34bfd7dfe1 | ||
|
|
e3487a48cb | ||
|
|
72a98d0076 |
@@ -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: ℹ️ Print hassfest version
|
||||
if: always()
|
||||
run: |
|
||||
echo "Hassfest version: $(hassfest --version)"
|
||||
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
@@ -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
|
||||
+35
-4
@@ -1,8 +1,39 @@
|
||||
# Python
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
*.so
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
|
||||
# Home Assistant
|
||||
.storage
|
||||
.cloud
|
||||
.google.token
|
||||
|
||||
# IDE
|
||||
.idea/
|
||||
.vscode/
|
||||
*.swp
|
||||
*.swo
|
||||
*~
|
||||
|
||||
# OS
|
||||
.DS_Store
|
||||
.env
|
||||
.venv
|
||||
venv/
|
||||
ENV/
|
||||
Thumbs.db
|
||||
*.psd
|
||||
*.zip
|
||||
|
||||
+110
@@ -0,0 +1,110 @@
|
||||
# 🤝 Contributing Guide
|
||||
|
||||
We welcome contributions to the HA Text AI project! This document will help you contribute to the project's development.
|
||||
|
||||
## 🌟 How to Contribute
|
||||
|
||||
### 1. Preparation
|
||||
|
||||
1. Fork the Repository
|
||||
- Go to the repository page on GitHub
|
||||
- Click the "Fork" button in the top right corner
|
||||
|
||||
2. Clone Your Fork
|
||||
```bash
|
||||
git clone https://github.com/YOUR_USERNAME/ha-text-ai.git
|
||||
cd ha-text-ai
|
||||
```
|
||||
|
||||
3. Set Up Remote Repositories
|
||||
```bash
|
||||
git remote add upstream https://github.com/smkrv/ha-text-ai.git
|
||||
```
|
||||
|
||||
### 2. Creating a Development Branch
|
||||
|
||||
```bash
|
||||
# Update the main branch
|
||||
git checkout main
|
||||
git pull upstream main
|
||||
|
||||
# Create a new branch for your feature
|
||||
git checkout -b feature/short-description-of-changes
|
||||
```
|
||||
|
||||
### 3. Development
|
||||
|
||||
- Follow the project's coding standards
|
||||
- Write clean and understandable code
|
||||
- Add comments when necessary
|
||||
- Create unit tests for new functionality
|
||||
|
||||
### 4. Committing Changes
|
||||
|
||||
```bash
|
||||
# Add modified files
|
||||
git add .
|
||||
|
||||
# Create a meaningful commit
|
||||
git commit -m "Feat: Add [short feature description]"
|
||||
```
|
||||
|
||||
### 5. Commit Message Style
|
||||
|
||||
Use the following prefixes:
|
||||
- `Feat:` - new feature
|
||||
- `Fix:` - bug fixes
|
||||
- `Docs:` - documentation updates
|
||||
- `Style:` - formatting changes
|
||||
- `Refactor:` - code refactoring
|
||||
- `Test:` - adding tests
|
||||
- `Chore:` - project maintenance
|
||||
|
||||
### 6. Pushing Changes
|
||||
|
||||
```bash
|
||||
# Push changes to your fork
|
||||
git push origin feature/short-description-of-changes
|
||||
```
|
||||
|
||||
### 7. Creating a Pull Request (PR)
|
||||
|
||||
1. Go to your fork on GitHub
|
||||
2. Click "New Pull Request"
|
||||
3. Select the base branch `main` of the original repository
|
||||
4. Fill out the PR description:
|
||||
- Brief description of changes
|
||||
- Motivation for changes
|
||||
- Screenshots (if applicable)
|
||||
|
||||
### 8. Review Process
|
||||
|
||||
- Project maintainers will review your PR
|
||||
- There may be comments and requests for changes
|
||||
- After approval, the PR will be merged
|
||||
|
||||
## 🛠 Code Requirements
|
||||
|
||||
- Follow PEP 8 for Python
|
||||
- Write clear and self-documenting code
|
||||
- Add type hints
|
||||
- Cover code with tests
|
||||
|
||||
## 🐛 Found a Bug?
|
||||
|
||||
1. Check existing Issues
|
||||
2. Create a new Issue with:
|
||||
- Bug description
|
||||
- Reproduction steps
|
||||
- Home Assistant version
|
||||
- Plugin version
|
||||
|
||||
## 📜 License
|
||||
|
||||
By contributing to the project, you agree to the [project's license](LICENSE).
|
||||
|
||||
## 🤔 Questions?
|
||||
|
||||
If you have any questions, create an Issue or contact the project maintainers.
|
||||
|
||||
**Thank you for your contribution!** 🎉
|
||||
@@ -19,3 +19,4 @@ AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
|
||||
|
||||
@@ -1,145 +1,243 @@
|
||||
# 🤖 HA text AI Integration for Home Assistant
|
||||
# 🤖 HA Text AI for Home Assistant
|
||||
|
||||
<div align="center">
|
||||
<div align="center">
|
||||
|
||||

|
||||

|
||||

|
||||

|
||||
[](https://github.com/hacs/integration)
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
    [](https://opensource.org/licenses/MIT) [](https://github.com/hacs/integration)
|
||||
|
||||
<img src="https://github.com/smkrv/ha-text-ai/blob/3e3ec45b195c92989434fde40ae110027f4ea124/misc/icons/icon.png" alt="HA Text AI" width="140"/>
|
||||
|
||||
### Advanced AI Integration for Home Assistant with multi-provider support
|
||||
</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 multiple AI providers including OpenAI GPT and Anthropic Claude models. Get intelligent responses, automate complex scenarios, and enhance your home automation with advanced natural language processing.
|
||||
</p>
|
||||
|
||||
---
|
||||
> [!NOTE]
|
||||
> 🚧 ALPHA VERSION 🚧
|
||||
> Expect: potential bugs, frequent changes, incomplete features.
|
||||
> 🤝 Community Driven
|
||||
|
||||
## 📋 Table of Contents
|
||||
- [Features](#-features)
|
||||
- [Installation](#-installation)
|
||||
- [Configuration](#-configuration)
|
||||
- [Services](#-services)
|
||||
- [Advanced Usage](#-advanced-usage)
|
||||
- [Troubleshooting](#-troubleshooting)
|
||||
- [Contributing](#-contributing)
|
||||
## 🌟 Features
|
||||
|
||||
## ✨ Features
|
||||
- 🧠 **Multi-Provider AI Integration**:
|
||||
- Support for OpenAI GPT models
|
||||
- Anthropic Claude integration
|
||||
- Custom API endpoints
|
||||
- Flexible model selection
|
||||
|
||||
- 🔄 **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
|
||||
- 💬 **Advanced Language Processing**:
|
||||
- Context-aware responses
|
||||
- Multi-turn conversations
|
||||
- Custom system instructions
|
||||
- Natural conversation flow
|
||||
|
||||
## 🚀 Installation
|
||||
- 📝 **Enhanced Memory Management**:
|
||||
- Persistent conversation history
|
||||
- Context-aware responses
|
||||
- Customizable history limits
|
||||
- Model-specific filtering
|
||||
|
||||
- ⚡ **Performance Optimization**:
|
||||
- Efficient token usage
|
||||
- Smart rate limiting
|
||||
- Response caching
|
||||
- Request interval control
|
||||
|
||||
- 🎯 **Advanced Customization**:
|
||||
- Per-request model selection
|
||||
- Adjustable parameters
|
||||
- Custom system prompts
|
||||
- Temperature control
|
||||
|
||||
- 🔒 **Enhanced Security**:
|
||||
- Secure API key storage
|
||||
- Rate limiting protection
|
||||
- Error handling
|
||||
- Usage monitoring
|
||||
|
||||
- 🎨 **Improved User Experience**:
|
||||
- Intuitive configuration UI
|
||||
- Detailed sensor attributes
|
||||
- Rich service interface
|
||||
- Model selection UI
|
||||
|
||||
- 🔄 **Automation Integration**:
|
||||
- Event-driven responses
|
||||
- Conditional logic support
|
||||
- Template compatibility
|
||||
- Model-specific automation
|
||||
|
||||
## 📋 Prerequisites
|
||||
|
||||
- Home Assistant 2023.11 or later
|
||||
- Active API key from:
|
||||
- OpenAI ([Get key](https://platform.openai.com/account/api-keys))
|
||||
- Anthropic ([Get key](https://console.anthropic.com/))
|
||||
- OpenRouter ([Get key](https://openrouter.ai/keys))
|
||||
- Python 3.9 or newer
|
||||
- Stable internet connection
|
||||
|
||||
### Configuration Options
|
||||
- API Provider (OpenAI/Anthropic)
|
||||
- API Key (provider-specific)
|
||||
- Model Selection (flexible, provider-specific models)
|
||||
- Temperature (Creativity control, 0.0-2.0)
|
||||
- Max Tokens (Response length limit)
|
||||
- Request Interval (API call throttling)
|
||||
- Custom API Endpoint (optional)
|
||||
|
||||
#### ⓘ Potentially Compatible Providers
|
||||
The integration is designed to be flexible and may work with other providers offering OpenAI-compatible APIs:
|
||||
- Groq
|
||||
- Together AI
|
||||
- Perplexity AI
|
||||
- Mistral AI
|
||||
- Google AI
|
||||
- Local AI servers (like Ollama)
|
||||
- Custom OpenAI-compatible endpoints
|
||||
|
||||
#### Additional Notes
|
||||
- Not all providers guarantee full compatibility
|
||||
- Performance may vary between providers
|
||||
- Check individual provider's documentation
|
||||
- Ensure your API key has sufficient credits/quota
|
||||
|
||||
#### Provider Compatibility Requirements
|
||||
To be compatible, a provider should support:
|
||||
- OpenAI-like REST API structure
|
||||
- JSON request/response format
|
||||
- Standard authentication method
|
||||
- Similar model parameter handling
|
||||
|
||||
## ⚡ 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
|
||||
<a href="https://my.home-assistant.io/redirect/hacs_repository/?owner=smkrv&repository=ha-text-ai&category=Integration"><img src="https://my.home-assistant.io/badges/hacs_repository.svg" width="170" height="auto"></a>
|
||||
1. Open HACS in Home Assistant
|
||||
2. Click on "Integrations"
|
||||
3. Click "..." in top right corner
|
||||
4. Select "Custom repositories"
|
||||
5. Add repository URL: `https://github.com/smkrv/ha-text-ai`
|
||||
6. Choose "Integration" as category
|
||||
7. Click "Download"
|
||||
8. 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
|
||||
model: gpt-3.5-turbo
|
||||
ha_text_ai:
|
||||
api_provider: openai # or anthropic
|
||||
api_key: !secret ai_api_key
|
||||
model: gpt-4o-mini
|
||||
temperature: 0.7
|
||||
max_tokens: 1000
|
||||
request_interval: 1.0
|
||||
api_endpoint: https://api.openai.com/v1 # optional, for custom endpoints
|
||||
system_prompt: |
|
||||
You are a home automation expert assistant.
|
||||
Focus on practical and efficient solutions.
|
||||
```
|
||||
|
||||
### 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: "claude-3-sonnet" # optional
|
||||
temperature: 0.5 # optional
|
||||
max_tokens: 500 # optional
|
||||
context_messages: 10 #optional, number of previous messages to include in context, default: 5
|
||||
system_prompt: "You are a sleep optimization expert" # 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
|
||||
|
||||
## 🔍 Advanced Usage
|
||||
|
||||
### Automation Example
|
||||
### set_system_prompt
|
||||
```yaml
|
||||
automation:
|
||||
trigger:
|
||||
platform: state
|
||||
entity_id: binary_sensor.motion
|
||||
to: 'on'
|
||||
action:
|
||||
service: ha-text-ai.ask_question
|
||||
data:
|
||||
question: "What should I do when motion is detected?"
|
||||
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.
|
||||
```
|
||||
|
||||
## 🔧 Troubleshooting
|
||||
### clear_history
|
||||
```yaml
|
||||
service: ha_text_ai.clear_history
|
||||
```
|
||||
|
||||
<details>
|
||||
<summary>Common Issues and Solutions</summary>
|
||||
### get_history
|
||||
```yaml
|
||||
service: ha_text_ai.get_history
|
||||
data:
|
||||
limit: 5 # optional
|
||||
filter_model: "gpt-4o" # optional
|
||||
```
|
||||
|
||||
### API Key Issues
|
||||
- Verify API key format
|
||||
- Check API key permissions
|
||||
- Ensure proper configuration in secrets.yaml
|
||||
## 📘 FAQ
|
||||
|
||||
### Connection Problems
|
||||
- Verify internet connection
|
||||
- Check API endpoint accessibility
|
||||
- Review Home Assistant logs
|
||||
</details>
|
||||
**Q: Which AI providers are supported?**
|
||||
A: Currently OpenAI (GPT models) and Anthropic (Claude models) are supported, with more providers planned.
|
||||
|
||||
## 👥 Contributing
|
||||
**Q: How can I reduce API costs?**
|
||||
A: Use GPT-3.5-Turbo or Claude-3-Sonnet for most queries, implement caching, and optimize token usage.
|
||||
|
||||
We welcome contributions! Here's how you can help:
|
||||
**Q: Are there limitations on the number of requests?**
|
||||
A: Depends on your API provider's plan. We recommend monitoring usage and implementing request throttling via `request_interval` configuration.
|
||||
|
||||
**Q: Can I use custom models?**
|
||||
A: Yes, you can configure custom endpoints and use any compatible model by specifying it in the configuration.
|
||||
|
||||
**Q: How do I switch between different AI providers?**
|
||||
A: Simply change the model parameter in your configuration or service calls to use the desired provider's model.
|
||||
|
||||
**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, your data is secure. The system operates entirely on your local machine, keeping your data under your control. API keys are stored securely and all external communications use encrypted connections.
|
||||
|
||||
**Q: How do context messages work?**
|
||||
A: Context messages allow the AI to remember and reference previous conversation history. By default, 5 previous messages are included, but you can customize this from 1 to 20 messages to control the conversation depth and token usage.
|
||||
|
||||
## 🤝 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>
|
||||
|
||||
@@ -1,207 +1,295 @@
|
||||
"""The HA text AI integration."""
|
||||
"""The HA Text AI integration."""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Any
|
||||
import os
|
||||
import shutil
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Any, Dict
|
||||
|
||||
import voluptuous as vol
|
||||
from async_timeout import timeout
|
||||
|
||||
from homeassistant.config_entries import ConfigEntry
|
||||
from homeassistant.const import CONF_API_KEY, Platform
|
||||
from homeassistant.const import CONF_API_KEY, CONF_NAME, Platform
|
||||
from homeassistant.core import HomeAssistant, ServiceCall
|
||||
import homeassistant.helpers.config_validation as cv
|
||||
from homeassistant.exceptions import HomeAssistantError
|
||||
from homeassistant.exceptions import ConfigEntryNotReady, HomeAssistantError
|
||||
from homeassistant.helpers import config_validation as cv
|
||||
from homeassistant.helpers import aiohttp_client
|
||||
|
||||
from .coordinator import HATextAICoordinator
|
||||
from .api_client import APIClient
|
||||
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,
|
||||
CONF_API_PROVIDER,
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
API_PROVIDER_OPENAI,
|
||||
API_PROVIDER_ANTHROPIC,
|
||||
DEFAULT_MODEL,
|
||||
DEFAULT_TEMPERATURE,
|
||||
DEFAULT_MAX_TOKENS,
|
||||
DEFAULT_OPENAI_ENDPOINT,
|
||||
DEFAULT_ANTHROPIC_ENDPOINT,
|
||||
DEFAULT_REQUEST_INTERVAL,
|
||||
DEFAULT_CONTEXT_MESSAGES,
|
||||
API_TIMEOUT,
|
||||
SERVICE_ASK_QUESTION,
|
||||
SERVICE_CLEAR_HISTORY,
|
||||
SERVICE_GET_HISTORY,
|
||||
SERVICE_SET_SYSTEM_PROMPT,
|
||||
)
|
||||
from .coordinator import HATextAICoordinator
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
|
||||
async def async_setup(hass: HomeAssistant, config: dict[str, Any]) -> bool:
|
||||
"""Set up the HA text AI component from configuration.yaml."""
|
||||
CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
|
||||
|
||||
SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
|
||||
vol.Required("instance"): cv.string,
|
||||
vol.Required("question"): cv.string,
|
||||
vol.Optional("system_prompt"): cv.string,
|
||||
vol.Optional("model"): cv.string,
|
||||
vol.Optional("temperature"): cv.positive_float,
|
||||
vol.Optional("max_tokens"): cv.positive_int,
|
||||
vol.Optional("context_messages"): cv.positive_int,
|
||||
})
|
||||
|
||||
SERVICE_SCHEMA_SET_SYSTEM_PROMPT = vol.Schema({
|
||||
vol.Required("instance"): cv.string,
|
||||
vol.Required("prompt"): cv.string,
|
||||
})
|
||||
|
||||
SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
|
||||
vol.Required("instance"): cv.string,
|
||||
vol.Optional("limit"): cv.positive_int,
|
||||
vol.Optional("filter_model"): cv.string,
|
||||
})
|
||||
|
||||
def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAICoordinator:
|
||||
"""Get coordinator by instance name."""
|
||||
if instance.startswith("sensor."):
|
||||
instance = instance.replace("sensor.ha_text_ai_", "", 1)
|
||||
|
||||
for entry_id, coord in hass.data[DOMAIN].items():
|
||||
if isinstance(coord, HATextAICoordinator) and coord.instance_name.lower() == instance.lower():
|
||||
return coord
|
||||
|
||||
raise HomeAssistantError(f"Instance {instance} not found")
|
||||
|
||||
async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
|
||||
"""Set up the HA Text AI component."""
|
||||
hass.data.setdefault(DOMAIN, {})
|
||||
|
||||
try:
|
||||
source = os.path.join(os.path.dirname(__file__), 'icons', 'icon.svg')
|
||||
dest_dir = os.path.join(hass.config.path('www'), 'icons')
|
||||
os.makedirs(dest_dir, exist_ok=True)
|
||||
dest = os.path.join(dest_dir, 'icon.svg')
|
||||
if not os.path.exists(dest):
|
||||
shutil.copyfile(source, dest)
|
||||
except Exception as ex:
|
||||
_LOGGER.warning("Failed to copy custom icon: %s", str(ex))
|
||||
|
||||
async def async_ask_question(call: ServiceCall) -> None:
|
||||
"""Handle the ask_question service call.
|
||||
|
||||
Args:
|
||||
call: Service call containing question and optional parameters.
|
||||
"""
|
||||
"""Handle ask_question service."""
|
||||
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)}")
|
||||
coordinator = get_coordinator_by_instance(hass, call.data["instance"])
|
||||
await coordinator.async_ask_question(
|
||||
question=call.data["question"],
|
||||
model=call.data.get("model"),
|
||||
temperature=call.data.get("temperature"),
|
||||
max_tokens=call.data.get("max_tokens"),
|
||||
system_prompt=call.data.get("system_prompt"),
|
||||
context_messages=call.data.get("context_messages"),
|
||||
)
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error asking question: %s", str(err))
|
||||
raise HomeAssistantError(f"Failed to process question: {str(err)}")
|
||||
|
||||
async def async_clear_history(call: ServiceCall) -> None:
|
||||
"""Handle the clear_history service call."""
|
||||
"""Handle clear_history service."""
|
||||
try:
|
||||
if not hass.data[DOMAIN]:
|
||||
raise HomeAssistantError("No AI Text integration configured")
|
||||
coordinator = get_coordinator_by_instance(hass, call.data["instance"])
|
||||
await coordinator.async_clear_history()
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error clearing history: %s", str(err))
|
||||
raise HomeAssistantError(f"Failed to clear history: {str(err)}")
|
||||
|
||||
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.
|
||||
"""
|
||||
async def async_get_history(call: ServiceCall) -> list:
|
||||
"""Handle get_history service."""
|
||||
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)}")
|
||||
coordinator = get_coordinator_by_instance(hass, call.data["instance"])
|
||||
return await coordinator.async_get_history(
|
||||
limit=call.data.get("limit"),
|
||||
filter_model=call.data.get("filter_model")
|
||||
)
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error getting history: %s", str(err))
|
||||
raise HomeAssistantError(f"Failed to get history: {str(err)}")
|
||||
|
||||
async def async_set_system_prompt(call: ServiceCall) -> None:
|
||||
"""Handle the set_system_prompt service call."""
|
||||
"""Handle set_system_prompt service."""
|
||||
try:
|
||||
if not hass.data[DOMAIN]:
|
||||
raise HomeAssistantError("No AI Text integration configured")
|
||||
coordinator = get_coordinator_by_instance(hass, call.data["instance"])
|
||||
await coordinator.async_set_system_prompt(call.data["prompt"])
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error setting system prompt: %s", str(err))
|
||||
raise HomeAssistantError(f"Failed to set system prompt: {str(err)}")
|
||||
|
||||
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)
|
||||
),
|
||||
})
|
||||
schema=SERVICE_SCHEMA_ASK_QUESTION
|
||||
)
|
||||
|
||||
hass.services.async_register(
|
||||
DOMAIN,
|
||||
SERVICE_CLEAR_HISTORY,
|
||||
async_clear_history,
|
||||
schema=vol.Schema({})
|
||||
schema=vol.Schema({vol.Required("instance"): cv.string})
|
||||
)
|
||||
|
||||
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)
|
||||
),
|
||||
})
|
||||
schema=SERVICE_SCHEMA_GET_HISTORY
|
||||
)
|
||||
|
||||
hass.services.async_register(
|
||||
DOMAIN,
|
||||
SERVICE_SET_SYSTEM_PROMPT,
|
||||
async_set_system_prompt,
|
||||
schema=vol.Schema({
|
||||
vol.Required("prompt"): cv.string,
|
||||
})
|
||||
schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
|
||||
"""Set up HA text AI from a config entry."""
|
||||
async def async_check_api(session, endpoint: str, headers: dict, provider: str) -> bool:
|
||||
"""Check API availability for different providers."""
|
||||
try:
|
||||
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),
|
||||
if provider == API_PROVIDER_ANTHROPIC:
|
||||
check_url = f"{endpoint}/v1/models"
|
||||
else: # OpenAI
|
||||
check_url = f"{endpoint}/models"
|
||||
|
||||
async with timeout(API_TIMEOUT):
|
||||
async with session.get(check_url, headers=headers) as response:
|
||||
if response.status in [200, 404]:
|
||||
return True
|
||||
elif response.status == 401:
|
||||
raise ConfigEntryNotReady("Invalid API key")
|
||||
elif response.status == 429:
|
||||
_LOGGER.warning("Rate limit exceeded during API check")
|
||||
return False
|
||||
else:
|
||||
_LOGGER.error("API check failed with status: %d", response.status)
|
||||
return False
|
||||
except Exception as ex:
|
||||
_LOGGER.error("API check error: %s", str(ex))
|
||||
return False
|
||||
|
||||
async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
|
||||
"""Set up HA Text AI from a config entry."""
|
||||
try:
|
||||
if CONF_API_PROVIDER not in entry.data:
|
||||
_LOGGER.error("API provider not specified")
|
||||
raise ConfigEntryNotReady("API provider is required")
|
||||
|
||||
session = aiohttp_client.async_get_clientsession(hass)
|
||||
api_provider = entry.data.get(CONF_API_PROVIDER)
|
||||
model = entry.data.get(CONF_MODEL, DEFAULT_MODEL)
|
||||
endpoint = entry.data.get(
|
||||
CONF_API_ENDPOINT,
|
||||
DEFAULT_OPENAI_ENDPOINT if api_provider == API_PROVIDER_OPENAI
|
||||
else DEFAULT_ANTHROPIC_ENDPOINT
|
||||
).rstrip('/')
|
||||
api_key = entry.data[CONF_API_KEY]
|
||||
instance_name = entry.data.get(CONF_NAME, entry.entry_id)
|
||||
is_anthropic = api_provider == API_PROVIDER_ANTHROPIC
|
||||
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Accept": "application/json"
|
||||
}
|
||||
|
||||
if is_anthropic:
|
||||
headers["x-api-key"] = api_key
|
||||
headers["anthropic-version"] = "2023-06-01"
|
||||
else:
|
||||
headers["Authorization"] = f"Bearer {api_key}"
|
||||
|
||||
if not await async_check_api(session, endpoint, headers, api_provider):
|
||||
raise ConfigEntryNotReady("API connection failed")
|
||||
|
||||
_LOGGER.debug("Creating API client for %s with endpoint %s", api_provider, endpoint)
|
||||
|
||||
api_client = APIClient(
|
||||
session=session,
|
||||
endpoint=endpoint,
|
||||
headers=headers,
|
||||
api_provider=api_provider,
|
||||
model=model,
|
||||
)
|
||||
|
||||
coordinator = HATextAICoordinator(
|
||||
hass=hass,
|
||||
client=api_client,
|
||||
model=model,
|
||||
update_interval=entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
|
||||
instance_name=instance_name,
|
||||
max_tokens=entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
|
||||
temperature=entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
|
||||
is_anthropic=is_anthropic,
|
||||
context_messages=entry.data.get(
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
DEFAULT_CONTEXT_MESSAGES
|
||||
),
|
||||
)
|
||||
|
||||
coordinator.data = coordinator._initial_state.copy()
|
||||
_LOGGER.debug(f"Initial state set for coordinator {instance_name}")
|
||||
|
||||
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)
|
||||
await hass.config_entries.async_forward_entry_setups(entry, PLATFORMS)
|
||||
|
||||
_LOGGER.info(
|
||||
"Successfully set up %s instance '%s' with model %s",
|
||||
api_provider,
|
||||
instance_name,
|
||||
model
|
||||
)
|
||||
|
||||
return True
|
||||
|
||||
except Exception as ex:
|
||||
_LOGGER.error("Error setting up entry: %s", str(ex))
|
||||
raise ConfigEntryNotReady from ex
|
||||
_LOGGER.exception("Setup error: %s", str(ex))
|
||||
raise ConfigEntryNotReady(f"Setup error: {str(ex)}") from ex
|
||||
|
||||
async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
|
||||
"""Unload a config entry."""
|
||||
try:
|
||||
unload_ok = await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
|
||||
if unload_ok:
|
||||
if entry.entry_id in hass.data[DOMAIN]:
|
||||
coordinator = hass.data[DOMAIN][entry.entry_id]
|
||||
|
||||
if hasattr(coordinator.client, 'shutdown'):
|
||||
await coordinator.client.shutdown()
|
||||
|
||||
await coordinator.async_shutdown()
|
||||
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)
|
||||
return await hass.config_entries.async_unload_platforms(entry, PLATFORMS)
|
||||
|
||||
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
|
||||
|
||||
@@ -0,0 +1,180 @@
|
||||
"""API Client for HA Text AI."""
|
||||
import logging
|
||||
import asyncio
|
||||
from typing import Any, Dict, List, Optional
|
||||
from aiohttp import ClientSession, ClientTimeout
|
||||
from async_timeout import timeout
|
||||
|
||||
from homeassistant.core import HomeAssistant
|
||||
from homeassistant.exceptions import HomeAssistantError
|
||||
from .const import (
|
||||
API_TIMEOUT,
|
||||
API_RETRY_COUNT,
|
||||
API_PROVIDER_ANTHROPIC,
|
||||
MIN_TEMPERATURE,
|
||||
MAX_TEMPERATURE,
|
||||
MIN_MAX_TOKENS,
|
||||
MAX_MAX_TOKENS,
|
||||
)
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
|
||||
class APIClient:
|
||||
"""API Client for OpenAI and Anthropic."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
session: ClientSession,
|
||||
endpoint: str,
|
||||
headers: Dict[str, str],
|
||||
api_provider: str,
|
||||
model: str,
|
||||
) -> None:
|
||||
"""Initialize API client."""
|
||||
self.session = session
|
||||
self.endpoint = endpoint
|
||||
self.headers = headers
|
||||
self.api_provider = api_provider
|
||||
self.model = model
|
||||
self.timeout = ClientTimeout(total=API_TIMEOUT)
|
||||
|
||||
def _validate_parameters(
|
||||
self,
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
) -> None:
|
||||
"""Validate API parameters."""
|
||||
if not MIN_TEMPERATURE <= temperature <= MAX_TEMPERATURE:
|
||||
raise ValueError(
|
||||
f"Temperature must be between {MIN_TEMPERATURE} and {MAX_TEMPERATURE}"
|
||||
)
|
||||
if not MIN_MAX_TOKENS <= max_tokens <= MAX_MAX_TOKENS:
|
||||
raise ValueError(
|
||||
f"Max tokens must be between {MIN_MAX_TOKENS} and {MAX_MAX_TOKENS}"
|
||||
)
|
||||
|
||||
async def _make_request(
|
||||
self,
|
||||
url: str,
|
||||
payload: Dict[str, Any],
|
||||
) -> Dict[str, Any]:
|
||||
"""Make API request with retry logic."""
|
||||
for attempt in range(API_RETRY_COUNT):
|
||||
try:
|
||||
async with timeout(API_TIMEOUT):
|
||||
async with self.session.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers=self.headers,
|
||||
timeout=self.timeout
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
error_data = await response.json()
|
||||
raise HomeAssistantError(f"API error: {error_data}")
|
||||
return await response.json()
|
||||
except asyncio.TimeoutError:
|
||||
if attempt == API_RETRY_COUNT - 1:
|
||||
raise HomeAssistantError("API request timed out")
|
||||
await asyncio.sleep(1 * (attempt + 1))
|
||||
except Exception as e:
|
||||
if attempt == API_RETRY_COUNT - 1:
|
||||
raise
|
||||
_LOGGER.warning("API request failed, retrying: %s", str(e))
|
||||
await asyncio.sleep(1 * (attempt + 1))
|
||||
|
||||
async def create(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Dict[str, str]],
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
) -> Dict[str, Any]:
|
||||
"""Create completion using appropriate API."""
|
||||
try:
|
||||
self._validate_parameters(temperature, max_tokens)
|
||||
|
||||
if self.api_provider == API_PROVIDER_ANTHROPIC:
|
||||
return await self._create_anthropic_completion(
|
||||
model, messages, temperature, max_tokens
|
||||
)
|
||||
else:
|
||||
return await self._create_openai_completion(
|
||||
model, messages, temperature, max_tokens
|
||||
)
|
||||
except Exception as e:
|
||||
_LOGGER.error("API request failed: %s", str(e))
|
||||
raise HomeAssistantError(f"API request failed: {str(e)}")
|
||||
|
||||
async def _create_openai_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Dict[str, str]],
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
) -> Dict[str, Any]:
|
||||
"""Create completion using OpenAI API."""
|
||||
url = f"{self.endpoint}/chat/completions"
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": messages,
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
}
|
||||
|
||||
data = await self._make_request(url, payload)
|
||||
return {
|
||||
"choices": [
|
||||
{
|
||||
"message": {
|
||||
"content": data["choices"][0]["message"]["content"]
|
||||
}
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": data["usage"]["prompt_tokens"],
|
||||
"completion_tokens": data["usage"]["completion_tokens"],
|
||||
"total_tokens": data["usage"]["total_tokens"]
|
||||
}
|
||||
}
|
||||
|
||||
async def _create_anthropic_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Dict[str, str]],
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
) -> Dict[str, Any]:
|
||||
"""Create completion using Anthropic API."""
|
||||
url = f"{self.endpoint}/v1/messages"
|
||||
|
||||
# Convert messages to Anthropic format
|
||||
system_prompt = next(
|
||||
(msg["content"] for msg in messages if msg["role"] == "system"),
|
||||
None
|
||||
)
|
||||
conversation = [msg for msg in messages if msg["role"] != "system"]
|
||||
|
||||
payload = {
|
||||
"model": model,
|
||||
"messages": conversation,
|
||||
"max_tokens": max_tokens,
|
||||
"temperature": temperature,
|
||||
}
|
||||
if system_prompt:
|
||||
payload["system"] = system_prompt
|
||||
|
||||
data = await self._make_request(url, payload)
|
||||
return {
|
||||
"choices": [
|
||||
{
|
||||
"message": {
|
||||
"content": data["content"][0]["text"]
|
||||
}
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": data["usage"]["input_tokens"],
|
||||
"completion_tokens": data["usage"]["output_tokens"],
|
||||
"total_tokens": data["usage"]["input_tokens"] + data["usage"]["output_tokens"]
|
||||
}
|
||||
}
|
||||
@@ -1,8 +1,14 @@
|
||||
"""Config flow for HA text AI integration."""
|
||||
import logging
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
import voluptuous as vol
|
||||
from homeassistant import config_entries
|
||||
import homeassistant.helpers.config_validation as cv
|
||||
from homeassistant.const import CONF_API_KEY, CONF_NAME
|
||||
from homeassistant.core import callback
|
||||
from homeassistant.data_entry_flow import FlowResult
|
||||
from homeassistant.helpers.aiohttp_client import async_get_clientsession
|
||||
from homeassistant.helpers import selector
|
||||
|
||||
from .const import (
|
||||
DOMAIN,
|
||||
@@ -11,77 +17,231 @@ from .const import (
|
||||
CONF_MAX_TOKENS,
|
||||
CONF_API_ENDPOINT,
|
||||
CONF_REQUEST_INTERVAL,
|
||||
CONF_API_PROVIDER,
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
API_PROVIDER_OPENAI,
|
||||
API_PROVIDER_ANTHROPIC,
|
||||
API_PROVIDERS,
|
||||
DEFAULT_MODEL,
|
||||
DEFAULT_TEMPERATURE,
|
||||
DEFAULT_MAX_TOKENS,
|
||||
DEFAULT_API_ENDPOINT,
|
||||
DEFAULT_REQUEST_INTERVAL,
|
||||
DEFAULT_OPENAI_ENDPOINT,
|
||||
DEFAULT_ANTHROPIC_ENDPOINT,
|
||||
DEFAULT_CONTEXT_MESSAGES,
|
||||
MIN_TEMPERATURE,
|
||||
MAX_TEMPERATURE,
|
||||
MIN_MAX_TOKENS,
|
||||
MAX_MAX_TOKENS,
|
||||
MIN_REQUEST_INTERVAL,
|
||||
)
|
||||
|
||||
class HATextAIConfigFlow(config_entries.ConfigFlow):
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
|
||||
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):
|
||||
def __init__(self) -> None:
|
||||
"""Initialize flow."""
|
||||
self._errors = {}
|
||||
self._data = {}
|
||||
self._provider = None
|
||||
|
||||
async def async_step_user(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
|
||||
"""Handle the initial step."""
|
||||
errors = {}
|
||||
if user_input is None:
|
||||
return self.async_show_form(
|
||||
step_id="user",
|
||||
data_schema=vol.Schema({
|
||||
vol.Required(CONF_API_PROVIDER): selector.SelectSelector(
|
||||
selector.SelectSelectorConfig(
|
||||
options=API_PROVIDERS,
|
||||
translation_key="api_provider"
|
||||
)
|
||||
),
|
||||
})
|
||||
)
|
||||
|
||||
if user_input is not None:
|
||||
return self.async_create_entry(title="HA text AI", data=user_input)
|
||||
self._provider = user_input[CONF_API_PROVIDER]
|
||||
return await self.async_step_provider()
|
||||
|
||||
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),
|
||||
}),
|
||||
errors=errors,
|
||||
async def async_step_provider(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
|
||||
"""Handle provider configuration step."""
|
||||
if user_input is None:
|
||||
default_endpoint = (
|
||||
DEFAULT_OPENAI_ENDPOINT if self._provider == API_PROVIDER_OPENAI
|
||||
else DEFAULT_ANTHROPIC_ENDPOINT
|
||||
)
|
||||
|
||||
suggested_name = f"HA Text AI {len(self._async_current_entries()) + 1}"
|
||||
|
||||
return self.async_show_form(
|
||||
step_id="provider",
|
||||
data_schema=vol.Schema({
|
||||
vol.Required(CONF_NAME, default=suggested_name): str,
|
||||
vol.Required(CONF_API_KEY): str,
|
||||
vol.Required(CONF_MODEL, default=DEFAULT_MODEL): str,
|
||||
vol.Required(CONF_API_ENDPOINT, default=default_endpoint): str,
|
||||
vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
|
||||
),
|
||||
vol.Optional(CONF_MAX_TOKENS, default=DEFAULT_MAX_TOKENS): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
|
||||
),
|
||||
vol.Optional(CONF_REQUEST_INTERVAL, default=DEFAULT_REQUEST_INTERVAL): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_REQUEST_INTERVAL)
|
||||
),
|
||||
vol.Optional(
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
default=DEFAULT_CONTEXT_MESSAGES
|
||||
): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=20)
|
||||
),
|
||||
}),
|
||||
errors=self._errors
|
||||
)
|
||||
|
||||
instance_name = user_input[CONF_NAME]
|
||||
await self._async_validate_name(instance_name)
|
||||
if self._errors:
|
||||
return await self.async_step_provider()
|
||||
|
||||
if not await self._async_validate_api(user_input):
|
||||
return await self.async_step_provider()
|
||||
|
||||
return await self._create_entry(user_input)
|
||||
|
||||
async def _async_validate_name(self, name: str) -> bool:
|
||||
"""Validate that the name is unique."""
|
||||
for entry in self._async_current_entries():
|
||||
if entry.data.get(CONF_NAME) == name:
|
||||
self._errors["name"] = "name_exists"
|
||||
return False
|
||||
return True
|
||||
|
||||
async def _async_validate_api(self, user_input: Dict[str, Any]) -> bool:
|
||||
"""Validate API connection."""
|
||||
try:
|
||||
session = async_get_clientsession(self.hass)
|
||||
headers = self._get_api_headers(user_input)
|
||||
endpoint = user_input[CONF_API_ENDPOINT].rstrip('/')
|
||||
|
||||
check_url = (
|
||||
f"{endpoint}/v1/models" if self._provider == API_PROVIDER_ANTHROPIC
|
||||
else f"{endpoint}/models"
|
||||
)
|
||||
|
||||
async with session.get(check_url, headers=headers) as response:
|
||||
if response.status == 401:
|
||||
self._errors["base"] = "invalid_auth"
|
||||
return False
|
||||
elif response.status not in [200, 404]:
|
||||
self._errors["base"] = "cannot_connect"
|
||||
return False
|
||||
return True
|
||||
|
||||
except Exception as err:
|
||||
_LOGGER.error("API validation error: %s", str(err))
|
||||
self._errors["base"] = "cannot_connect"
|
||||
return False
|
||||
|
||||
def _get_api_headers(self, user_input: Dict[str, Any]) -> Dict[str, str]:
|
||||
"""Get API headers based on provider."""
|
||||
api_key = user_input[CONF_API_KEY]
|
||||
|
||||
if self._provider == API_PROVIDER_ANTHROPIC:
|
||||
return {
|
||||
"x-api-key": api_key,
|
||||
"anthropic-version": "2023-06-01",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
return {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
|
||||
async def _create_entry(self, user_input: Dict[str, Any]) -> FlowResult:
|
||||
"""Create the config entry."""
|
||||
instance_name = user_input[CONF_NAME]
|
||||
unique_id = f"{DOMAIN}_{instance_name}_{self._provider}".lower().replace(" ", "_")
|
||||
|
||||
return self.async_create_entry(
|
||||
title=instance_name,
|
||||
data={
|
||||
CONF_API_PROVIDER: self._provider,
|
||||
CONF_NAME: instance_name,
|
||||
**user_input,
|
||||
"unique_id": unique_id,
|
||||
CONF_CONTEXT_MESSAGES: user_input.get(
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
DEFAULT_CONTEXT_MESSAGES)
|
||||
}
|
||||
)
|
||||
|
||||
@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):
|
||||
class OptionsFlowHandler(config_entries.OptionsFlow):
|
||||
"""Handle options flow."""
|
||||
|
||||
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):
|
||||
"""Handle options flow."""
|
||||
async def async_step_init(self, user_input: Optional[Dict[str, Any]] = None) -> FlowResult:
|
||||
"""Manage the options."""
|
||||
if user_input is not None:
|
||||
return self.async_create_entry(title="", data=user_input)
|
||||
|
||||
current_data = {**self.config_entry.data, **self.config_entry.options}
|
||||
|
||||
return self.async_show_form(
|
||||
step_id="init",
|
||||
data_schema=vol.Schema({
|
||||
vol.Optional(
|
||||
CONF_MODEL,
|
||||
default=current_data.get(CONF_MODEL, DEFAULT_MODEL)
|
||||
): str,
|
||||
vol.Optional(
|
||||
CONF_TEMPERATURE,
|
||||
default=self.config_entry.options.get(
|
||||
CONF_TEMPERATURE, DEFAULT_TEMPERATURE
|
||||
),
|
||||
): vol.Coerce(float),
|
||||
default=current_data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)
|
||||
): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
|
||||
),
|
||||
vol.Optional(
|
||||
CONF_MAX_TOKENS,
|
||||
default=self.config_entry.options.get(
|
||||
CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS
|
||||
),
|
||||
): vol.Coerce(int),
|
||||
default=current_data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS)
|
||||
): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
|
||||
),
|
||||
vol.Optional(
|
||||
CONF_REQUEST_INTERVAL,
|
||||
default=self.config_entry.options.get(
|
||||
CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL
|
||||
),
|
||||
): vol.Coerce(float),
|
||||
}),
|
||||
default=current_data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)
|
||||
): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_REQUEST_INTERVAL)
|
||||
),
|
||||
vol.Optional(
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
default=current_data.get(
|
||||
CONF_CONTEXT_MESSAGES,
|
||||
DEFAULT_CONTEXT_MESSAGES
|
||||
)
|
||||
): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=20)
|
||||
),
|
||||
})
|
||||
)
|
||||
|
||||
@@ -1,30 +1,201 @@
|
||||
"""Constants for the HA text AI integration."""
|
||||
from homeassistant.const import Platform
|
||||
from typing import Final
|
||||
import voluptuous as vol
|
||||
from homeassistant.const import Platform, CONF_API_KEY, CONF_NAME
|
||||
from homeassistant.helpers import config_validation as cv
|
||||
|
||||
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"
|
||||
# Provider configuration
|
||||
CONF_API_PROVIDER: Final = "api_provider"
|
||||
API_PROVIDER_OPENAI: Final = "openai"
|
||||
API_PROVIDER_ANTHROPIC: Final = "anthropic"
|
||||
|
||||
# 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
|
||||
API_PROVIDERS: Final = [
|
||||
API_PROVIDER_OPENAI,
|
||||
API_PROVIDER_ANTHROPIC
|
||||
]
|
||||
|
||||
# Services
|
||||
SERVICE_ASK_QUESTION = "ask_question"
|
||||
SERVICE_CLEAR_HISTORY = "clear_history"
|
||||
SERVICE_GET_HISTORY = "get_history"
|
||||
SERVICE_SET_SYSTEM_PROMPT = "set_system_prompt"
|
||||
# Default endpoints
|
||||
DEFAULT_OPENAI_ENDPOINT: Final = "https://api.openai.com/v1"
|
||||
DEFAULT_ANTHROPIC_ENDPOINT: Final = "https://api.anthropic.com"
|
||||
|
||||
# Attributes
|
||||
ATTR_QUESTION = "question"
|
||||
ATTR_RESPONSE = "response"
|
||||
ATTR_LAST_UPDATED = "last_updated"
|
||||
# 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"
|
||||
CONF_INSTANCE: Final = "instance"
|
||||
CONF_MAX_HISTORY_SIZE: Final = "max_history_size"
|
||||
CONF_IS_ANTHROPIC: Final = "is_anthropic"
|
||||
CONF_CONTEXT_MESSAGES: Final = "context_messages"
|
||||
|
||||
# Default values
|
||||
DEFAULT_MODEL: Final = "gpt-4o-mini"
|
||||
DEFAULT_TEMPERATURE: Final = 0.1
|
||||
DEFAULT_MAX_TOKENS: Final = 1000
|
||||
DEFAULT_REQUEST_INTERVAL: Final = 1.0
|
||||
DEFAULT_TIMEOUT: Final = 30
|
||||
DEFAULT_MAX_HISTORY: Final = 50
|
||||
DEFAULT_NAME: Final = "HA Text AI"
|
||||
DEFAULT_CONTEXT_MESSAGES: Final = 5
|
||||
|
||||
# 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
|
||||
MAX_REQUEST_INTERVAL: Final = 60.0
|
||||
|
||||
# API constants
|
||||
API_TIMEOUT: Final = 30
|
||||
API_RETRY_COUNT: Final = 3
|
||||
|
||||
# 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"
|
||||
|
||||
# Attribute keys
|
||||
ATTR_QUESTION: Final = "question"
|
||||
ATTR_RESPONSE: Final = "response"
|
||||
ATTR_INSTANCE: Final = "instance"
|
||||
ATTR_MODEL: Final = "model"
|
||||
ATTR_TEMPERATURE: Final = "temperature"
|
||||
ATTR_MAX_TOKENS: Final = "max_tokens"
|
||||
ATTR_SYSTEM_PROMPT: Final = "system_prompt"
|
||||
ATTR_API_STATUS: Final = "api_status"
|
||||
ATTR_ERROR_COUNT: Final = "error_count"
|
||||
ATTR_CONVERSATION_HISTORY: Final = "conversation_history"
|
||||
|
||||
# Sensor attributes
|
||||
ATTR_TOTAL_RESPONSES: Final = "total_responses"
|
||||
ATTR_TOTAL_ERRORS: Final = "total_errors"
|
||||
ATTR_AVG_RESPONSE_TIME: Final = "average_response_time"
|
||||
ATTR_LAST_REQUEST_TIME: Final = "last_request_time"
|
||||
ATTR_LAST_ERROR: Final = "last_error"
|
||||
ATTR_IS_PROCESSING: Final = "is_processing"
|
||||
ATTR_IS_RATE_LIMITED: Final = "is_rate_limited"
|
||||
ATTR_IS_MAINTENANCE: Final = "is_maintenance"
|
||||
ATTR_API_VERSION: Final = "api_version"
|
||||
ATTR_ENDPOINT_STATUS: Final = "endpoint_status"
|
||||
ATTR_PERFORMANCE_METRICS: Final = "performance_metrics"
|
||||
ATTR_HISTORY_SIZE: Final = "history_size"
|
||||
ATTR_UPTIME: Final = "uptime"
|
||||
ATTR_API_PROVIDER: Final = "api_provider"
|
||||
ATTR_METRICS: Final = "metrics"
|
||||
ATTR_STATE: Final = "state"
|
||||
ATTR_LAST_RESPONSE: Final = "last_response"
|
||||
ATTR_ERROR: Final = "error"
|
||||
ATTR_TIMESTAMP: Final = "timestamp"
|
||||
|
||||
# Sensor metrics
|
||||
METRIC_TOTAL_TOKENS: Final = "total_tokens"
|
||||
METRIC_PROMPT_TOKENS: Final = "prompt_tokens"
|
||||
METRIC_COMPLETION_TOKENS: Final = "completion_tokens"
|
||||
METRIC_SUCCESSFUL_REQUESTS: Final = "successful_requests"
|
||||
METRIC_FAILED_REQUESTS: Final = "failed_requests"
|
||||
METRIC_AVERAGE_LATENCY: Final = "average_latency"
|
||||
METRIC_MAX_LATENCY: Final = "max_latency"
|
||||
METRIC_MIN_LATENCY: Final = "min_latency"
|
||||
|
||||
# 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_INVALID_INSTANCE: Final = "invalid_instance"
|
||||
ERROR_NAME_EXISTS: Final = "name_exists"
|
||||
|
||||
# Entity attributes
|
||||
ENTITY_ICON: Final = "mdi:robot"
|
||||
ENTITY_ICON_ERROR: Final = "mdi:robot-dead"
|
||||
ENTITY_ICON_PROCESSING: Final = "mdi:robot-excited"
|
||||
|
||||
# State attributes
|
||||
STATE_READY: Final = "ready"
|
||||
STATE_PROCESSING: Final = "processing"
|
||||
STATE_ERROR: Final = "error"
|
||||
STATE_INITIALIZING: Final = "initializing"
|
||||
STATE_MAINTENANCE: Final = "maintenance"
|
||||
STATE_RATE_LIMITED: Final = "rate_limited"
|
||||
STATE_DISCONNECTED: Final = "disconnected"
|
||||
|
||||
# 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"
|
||||
|
||||
# Service schema constants
|
||||
SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
|
||||
vol.Required(CONF_INSTANCE): cv.string,
|
||||
vol.Required("question"): cv.string,
|
||||
vol.Optional("system_prompt"): cv.string,
|
||||
vol.Optional("model"): cv.string,
|
||||
vol.Optional("temperature"): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
|
||||
),
|
||||
vol.Optional("max_tokens"): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
|
||||
),
|
||||
vol.Optional("context_messages"): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=20)
|
||||
)
|
||||
})
|
||||
|
||||
SERVICE_SCHEMA_SET_SYSTEM_PROMPT = vol.Schema({
|
||||
vol.Required(CONF_INSTANCE): cv.string,
|
||||
vol.Required("prompt"): cv.string
|
||||
})
|
||||
|
||||
SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
|
||||
vol.Required(CONF_INSTANCE): cv.string,
|
||||
vol.Optional("limit", default=10): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=100)
|
||||
),
|
||||
vol.Optional("filter_model"): cv.string
|
||||
})
|
||||
|
||||
# Configuration schema
|
||||
CONFIG_SCHEMA = vol.Schema({
|
||||
DOMAIN: vol.Schema({
|
||||
vol.Required(CONF_NAME): cv.string,
|
||||
vol.Required(CONF_API_KEY): cv.string,
|
||||
vol.Required(CONF_API_PROVIDER): vol.In(API_PROVIDERS),
|
||||
vol.Optional(CONF_MODEL, default=DEFAULT_MODEL): cv.string,
|
||||
vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
|
||||
),
|
||||
vol.Optional(CONF_MAX_TOKENS, default=DEFAULT_MAX_TOKENS): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=MIN_MAX_TOKENS, max=MAX_MAX_TOKENS)
|
||||
),
|
||||
vol.Optional(CONF_API_ENDPOINT): cv.string,
|
||||
vol.Optional(CONF_REQUEST_INTERVAL, default=DEFAULT_REQUEST_INTERVAL): vol.All(
|
||||
vol.Coerce(float),
|
||||
vol.Range(min=MIN_REQUEST_INTERVAL, max=MAX_REQUEST_INTERVAL)
|
||||
),
|
||||
vol.Optional(CONF_MAX_HISTORY_SIZE, default=DEFAULT_MAX_HISTORY): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=100),
|
||||
),
|
||||
vol.Optional(CONF_CONTEXT_MESSAGES, default=DEFAULT_CONTEXT_MESSAGES): vol.All(
|
||||
vol.Coerce(int),
|
||||
vol.Range(min=1, max=20)
|
||||
)
|
||||
})
|
||||
}, extra=vol.ALLOW_EXTRA)
|
||||
|
||||
@@ -1,114 +1,377 @@
|
||||
"""Data coordinator for HA text AI."""
|
||||
import asyncio
|
||||
"""The HA Text AI coordinator."""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from datetime import timedelta
|
||||
from typing import Any, Dict
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
import openai
|
||||
from homeassistant.core import HomeAssistant
|
||||
from homeassistant.helpers.update_coordinator import DataUpdateCoordinator
|
||||
from homeassistant.exceptions import ConfigEntryAuthFailed
|
||||
from homeassistant.util import dt as dt_util
|
||||
from homeassistant.exceptions import HomeAssistantError
|
||||
|
||||
from .const import (
|
||||
DOMAIN,
|
||||
DEFAULT_REQUEST_INTERVAL,
|
||||
CONF_MODEL,
|
||||
CONF_TEMPERATURE,
|
||||
CONF_MAX_TOKENS,
|
||||
STATE_READY,
|
||||
STATE_PROCESSING,
|
||||
STATE_ERROR,
|
||||
STATE_RATE_LIMITED,
|
||||
STATE_MAINTENANCE,
|
||||
DEFAULT_MAX_TOKENS,
|
||||
DEFAULT_TEMPERATURE,
|
||||
DEFAULT_MAX_HISTORY,
|
||||
DEFAULT_CONTEXT_MESSAGES,
|
||||
)
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
|
||||
class HATextAICoordinator(DataUpdateCoordinator):
|
||||
"""Class to manage fetching data from the API."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
hass: HomeAssistant,
|
||||
api_key: str,
|
||||
endpoint: str,
|
||||
client: Any,
|
||||
model: str,
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
request_interval: float,
|
||||
update_interval: int,
|
||||
instance_name: str,
|
||||
max_tokens: int = DEFAULT_MAX_TOKENS,
|
||||
temperature: float = DEFAULT_TEMPERATURE,
|
||||
max_history_size: int = DEFAULT_MAX_HISTORY,
|
||||
context_messages: int = DEFAULT_CONTEXT_MESSAGES,
|
||||
is_anthropic: bool = False,
|
||||
) -> None:
|
||||
"""Initialize."""
|
||||
super().__init__(
|
||||
hass,
|
||||
_LOGGER,
|
||||
name=DOMAIN,
|
||||
update_interval=timedelta(seconds=request_interval),
|
||||
)
|
||||
|
||||
self.api_key = api_key
|
||||
self.endpoint = endpoint
|
||||
"""Initialize coordinator."""
|
||||
self.instance_name = instance_name
|
||||
self.hass = hass
|
||||
self.client = client
|
||||
self.model = model
|
||||
self.temperature = temperature
|
||||
self.max_tokens = max_tokens
|
||||
self._question_queue = asyncio.Queue()
|
||||
self._responses: Dict[str, Any] = {}
|
||||
self.system_prompt: Optional[str] = None
|
||||
self.max_history_size = max_history_size
|
||||
self.is_anthropic = is_anthropic
|
||||
|
||||
openai.api_key = self.api_key
|
||||
if endpoint != "https://api.openai.com/v1":
|
||||
openai.api_base = endpoint
|
||||
# Initialize with default state
|
||||
self._initial_state = {
|
||||
"state": STATE_READY,
|
||||
"metrics": {
|
||||
"total_tokens": 0,
|
||||
"prompt_tokens": 0,
|
||||
"completion_tokens": 0,
|
||||
"successful_requests": 0,
|
||||
"failed_requests": 0,
|
||||
"total_errors": 0,
|
||||
"average_latency": 0,
|
||||
"max_latency": 0,
|
||||
"min_latency": float('inf'),
|
||||
},
|
||||
"last_response": {
|
||||
"timestamp": dt_util.utcnow().isoformat(),
|
||||
"question": "",
|
||||
"response": "",
|
||||
"model": model,
|
||||
"instance": instance_name,
|
||||
"error": None
|
||||
},
|
||||
"is_processing": False,
|
||||
"is_rate_limited": False,
|
||||
"is_maintenance": False,
|
||||
"endpoint_status": "ready",
|
||||
"uptime": 0,
|
||||
"system_prompt": None,
|
||||
"history_size": 0,
|
||||
"conversation_history": [],
|
||||
}
|
||||
|
||||
update_interval_td = timedelta(seconds=update_interval)
|
||||
|
||||
super().__init__(
|
||||
hass,
|
||||
_LOGGER,
|
||||
name=instance_name,
|
||||
update_interval=update_interval_td,
|
||||
)
|
||||
|
||||
# Register instance
|
||||
self.hass.data.setdefault(DOMAIN, {})
|
||||
self.hass.data[DOMAIN][instance_name] = self
|
||||
self.context_messages = context_messages
|
||||
|
||||
self._system_prompt = None
|
||||
self._conversation_history = []
|
||||
self._performance_metrics = self._initial_state["metrics"].copy()
|
||||
self._is_processing = False
|
||||
self._is_rate_limited = False
|
||||
self._is_maintenance = False
|
||||
self.endpoint_status = "ready"
|
||||
self.last_response = self._initial_state["last_response"].copy()
|
||||
self._start_time = dt_util.utcnow()
|
||||
|
||||
_LOGGER.info(f"Initialized HA Text AI coordinator with instance: {instance_name}")
|
||||
|
||||
async def _async_update_data(self) -> Dict[str, Any]:
|
||||
"""Update data via OpenAI API."""
|
||||
if self._question_queue.empty():
|
||||
return self._responses
|
||||
|
||||
"""Update data via library."""
|
||||
try:
|
||||
question = await self._question_queue.get()
|
||||
response_content = await self.hass.async_add_executor_job(
|
||||
self._make_api_call, question
|
||||
)
|
||||
response = {
|
||||
"question": question,
|
||||
"response": response_content
|
||||
current_state = self._get_current_state()
|
||||
_LOGGER.debug(f"Updating data for {self.instance_name}, current state: {current_state}")
|
||||
|
||||
data = {
|
||||
"state": current_state,
|
||||
"metrics": self._performance_metrics,
|
||||
"last_response": self.last_response,
|
||||
"is_processing": self._is_processing,
|
||||
"is_rate_limited": self._is_rate_limited,
|
||||
"is_maintenance": self._is_maintenance,
|
||||
"endpoint_status": self.endpoint_status,
|
||||
"uptime": (dt_util.utcnow() - self._start_time).total_seconds(),
|
||||
"system_prompt": self._system_prompt,
|
||||
"history_size": len(self._conversation_history),
|
||||
"conversation_history": self._conversation_history,
|
||||
}
|
||||
self._responses[question] = response
|
||||
_LOGGER.debug(f"Response from API: {response}")
|
||||
return self._responses
|
||||
|
||||
except openai.error.AuthenticationError as err:
|
||||
raise ConfigEntryAuthFailed from err
|
||||
# Validate data
|
||||
if not isinstance(data, dict):
|
||||
raise ValueError("Invalid data format")
|
||||
|
||||
_LOGGER.debug(f"Updated data for {self.instance_name}: {data}")
|
||||
return data
|
||||
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error communicating with API: %s", err)
|
||||
return self._responses
|
||||
_LOGGER.error(f"Error updating data for {self.instance_name}: {err}")
|
||||
return self._initial_state
|
||||
|
||||
def _make_api_call(self, question: str) -> str:
|
||||
"""Make API call to OpenAI."""
|
||||
async def async_update_ha_state(self) -> None:
|
||||
"""Update Home Assistant state."""
|
||||
try:
|
||||
messages = [{"role": "system", "content": self.system_prompt}] if self.system_prompt else []
|
||||
messages.append({"role": "user", "content": question})
|
||||
completion = openai.chat.completions.create(
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
temperature=self.temperature,
|
||||
max_tokens=self.max_tokens,
|
||||
)
|
||||
return completion.choices[0].message.content
|
||||
_LOGGER.debug(f"Requesting state update for {self.instance_name}")
|
||||
await self.async_request_refresh()
|
||||
|
||||
# Force update of all entities
|
||||
for entity_id in self.hass.states.async_entity_ids():
|
||||
if entity_id.startswith(f"sensor.ha_text_ai_{self.instance_name}"):
|
||||
self.hass.states.async_set(entity_id, self._get_current_state())
|
||||
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error in API call: %s", err)
|
||||
_LOGGER.error(f"Error updating HA state for {self.instance_name}: {err}")
|
||||
|
||||
def _get_current_state(self) -> str:
|
||||
"""Get current state based on internal flags."""
|
||||
if self._is_processing:
|
||||
return STATE_PROCESSING
|
||||
elif self._is_rate_limited:
|
||||
return STATE_RATE_LIMITED
|
||||
elif self._is_maintenance:
|
||||
return STATE_MAINTENANCE
|
||||
elif self.last_response.get("error"):
|
||||
return STATE_ERROR
|
||||
return STATE_READY
|
||||
|
||||
def _calculate_context_tokens(self, messages: List[Dict[str, str]]) -> int:
|
||||
try:
|
||||
if self.is_anthropic and hasattr(self.client, 'count_tokens'):
|
||||
return sum(self.client.count_tokens(msg['content']) for msg in messages)
|
||||
|
||||
return sum(len(msg['content']) // 4 for msg in messages)
|
||||
except Exception as e:
|
||||
_LOGGER.warning(f"Error calculating context tokens: {e}")
|
||||
return 0
|
||||
|
||||
async def async_ask_question(
|
||||
self,
|
||||
question: str,
|
||||
model: Optional[str] = None,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
system_prompt: Optional[str] = None,
|
||||
context_messages: Optional[int] = None,
|
||||
) -> dict:
|
||||
"""Process a question with optional parameters."""
|
||||
return await self.async_process_question(
|
||||
question, model, temperature, max_tokens, system_prompt, context_messages
|
||||
)
|
||||
|
||||
async def async_process_question(
|
||||
self,
|
||||
question: str,
|
||||
model: Optional[str] = None,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
system_prompt: Optional[str] = None,
|
||||
context_messages: Optional[int] = None,
|
||||
) -> dict:
|
||||
temp_context_messages = context_messages or self.context_messages
|
||||
|
||||
if not question:
|
||||
raise ValueError("Question cannot be empty")
|
||||
|
||||
_LOGGER.debug(f"Processing question for instance {self.instance_name}")
|
||||
|
||||
try:
|
||||
self._is_processing = True
|
||||
await self.async_update_ha_state()
|
||||
|
||||
temp_model = model or self.model
|
||||
temp_temperature = temperature or self.temperature
|
||||
temp_max_tokens = max_tokens or self.max_tokens
|
||||
temp_system_prompt = system_prompt or self._system_prompt
|
||||
|
||||
start_time = dt_util.utcnow()
|
||||
|
||||
messages = []
|
||||
if temp_system_prompt:
|
||||
if self.is_anthropic:
|
||||
system_content = f"\n\nHuman: {temp_system_prompt}\n\nAssistant: I understand and will follow these instructions."
|
||||
messages.append({"role": "user", "content": system_content})
|
||||
else:
|
||||
messages.append({"role": "system", "content": temp_system_prompt})
|
||||
|
||||
# Add conversation history
|
||||
context_history = self._conversation_history[-temp_context_messages:]
|
||||
for entry in context_history:
|
||||
messages.append({"role": "user", "content": entry["question"]})
|
||||
messages.append({"role": "assistant", "content": entry["response"]})
|
||||
|
||||
messages.append({"role": "user", "content": question})
|
||||
|
||||
kwargs = {
|
||||
"model": temp_model,
|
||||
"temperature": temp_temperature,
|
||||
"max_tokens": temp_max_tokens,
|
||||
"messages": messages,
|
||||
}
|
||||
|
||||
response = await self.async_process_message(question, **kwargs)
|
||||
|
||||
# Update metrics
|
||||
end_time = dt_util.utcnow()
|
||||
latency = (end_time - start_time).total_seconds()
|
||||
self._update_metrics(latency, response)
|
||||
|
||||
# Update history
|
||||
self._update_history(question, response)
|
||||
|
||||
return response
|
||||
|
||||
except Exception as err:
|
||||
self._handle_error(err)
|
||||
raise HomeAssistantError(f"Failed to process question: {err}")
|
||||
|
||||
finally:
|
||||
self._is_processing = False
|
||||
await self.async_update_ha_state()
|
||||
|
||||
async def async_process_message(self, question: str, **kwargs) -> dict:
|
||||
"""Process message using the AI client."""
|
||||
try:
|
||||
if self.is_anthropic:
|
||||
response = await self._process_anthropic_message(question, **kwargs)
|
||||
else:
|
||||
response = await self._process_openai_message(question, **kwargs)
|
||||
|
||||
self.last_response = {
|
||||
"timestamp": dt_util.utcnow().isoformat(),
|
||||
"question": question,
|
||||
"response": response["content"],
|
||||
"model": kwargs.get("model", self.model),
|
||||
"instance": self.instance_name,
|
||||
"error": None
|
||||
}
|
||||
|
||||
return response
|
||||
|
||||
except Exception as err:
|
||||
self._handle_error(err)
|
||||
raise
|
||||
|
||||
async def async_ask_question(self, question: str) -> None:
|
||||
"""Add question to queue."""
|
||||
await self._question_queue.put(question)
|
||||
_LOGGER.debug(f"Question added to queue: {question}")
|
||||
await self.async_refresh()
|
||||
async def _process_anthropic_message(self, question: str, **kwargs) -> dict:
|
||||
"""Process message using Anthropic API."""
|
||||
response = await self.client.messages.create(
|
||||
model=kwargs["model"],
|
||||
max_tokens=kwargs["max_tokens"],
|
||||
messages=kwargs["messages"],
|
||||
temperature=kwargs["temperature"],
|
||||
)
|
||||
return {
|
||||
"content": response.content[0].text,
|
||||
"tokens": {
|
||||
"prompt": response.usage.input_tokens,
|
||||
"completion": response.usage.output_tokens,
|
||||
"total": response.usage.input_tokens + response.usage.output_tokens
|
||||
}
|
||||
}
|
||||
|
||||
def clear_history(self) -> None:
|
||||
"""Clear the stored question and response history."""
|
||||
self._responses.clear()
|
||||
_LOGGER.info("History cleared.")
|
||||
async def _process_openai_message(self, question: str, **kwargs) -> dict:
|
||||
"""Process message using OpenAI API."""
|
||||
try:
|
||||
response = await self.client.create(
|
||||
model=kwargs["model"],
|
||||
messages=kwargs["messages"],
|
||||
temperature=kwargs["temperature"],
|
||||
max_tokens=kwargs["max_tokens"],
|
||||
)
|
||||
|
||||
def get_history(self, limit: int = 10) -> Dict[str, Any]:
|
||||
"""Get the history of questions and responses."""
|
||||
return {"history": list(self._responses.values())[-limit:]}
|
||||
return {
|
||||
"content": response["choices"][0]["message"]["content"],
|
||||
"tokens": {
|
||||
"prompt": response["usage"]["prompt_tokens"],
|
||||
"completion": response["usage"]["completion_tokens"],
|
||||
"total": response["usage"]["total_tokens"]
|
||||
}
|
||||
}
|
||||
except Exception as e:
|
||||
_LOGGER.error(f"Error in OpenAI API call: {str(e)}")
|
||||
raise
|
||||
|
||||
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}")
|
||||
def _update_metrics(self, latency: float, response: dict) -> None:
|
||||
"""Update performance metrics."""
|
||||
metrics = self._performance_metrics
|
||||
tokens = response.get("tokens", {})
|
||||
|
||||
metrics["total_tokens"] += tokens.get("total", 0)
|
||||
metrics["prompt_tokens"] += tokens.get("prompt", 0)
|
||||
metrics["completion_tokens"] += tokens.get("completion", 0)
|
||||
metrics["successful_requests"] += 1
|
||||
|
||||
metrics["average_latency"] = (
|
||||
(metrics["average_latency"] * (metrics["successful_requests"] - 1) + latency)
|
||||
/ metrics["successful_requests"]
|
||||
)
|
||||
metrics["max_latency"] = max(metrics["max_latency"], latency)
|
||||
metrics["min_latency"] = min(metrics["min_latency"], latency)
|
||||
|
||||
def _update_history(self, question: str, response: dict) -> None:
|
||||
"""Update conversation history."""
|
||||
self._conversation_history.append({
|
||||
"timestamp": dt_util.utcnow().isoformat(),
|
||||
"question": question,
|
||||
"response": response["content"]
|
||||
})
|
||||
|
||||
while len(self._conversation_history) > self.max_history_size:
|
||||
self._conversation_history.pop(0)
|
||||
|
||||
def _handle_error(self, error: Exception) -> None:
|
||||
"""Handle error and update metrics."""
|
||||
self._performance_metrics["total_errors"] += 1
|
||||
self._performance_metrics["failed_requests"] += 1
|
||||
|
||||
self.last_response = {
|
||||
"timestamp": dt_util.utcnow().isoformat(),
|
||||
"question": "",
|
||||
"response": "",
|
||||
"model": self.model,
|
||||
"instance": self.instance_name,
|
||||
"error": str(error)
|
||||
}
|
||||
|
||||
async def async_clear_history(self) -> None:
|
||||
"""Clear conversation history."""
|
||||
self._conversation_history = []
|
||||
await self.async_update_ha_state()
|
||||
|
||||
async def async_get_history(self) -> List[Dict[str, str]]:
|
||||
"""Get conversation history."""
|
||||
return self._conversation_history
|
||||
|
||||
async def async_set_system_prompt(self, prompt: str) -> None:
|
||||
"""Set system prompt."""
|
||||
self._system_prompt = prompt
|
||||
await self.async_update_ha_state()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
|
After Width: | Height: | Size: 678 KiB |
@@ -1,15 +1,28 @@
|
||||
{
|
||||
"domain": "ha-text-ai",
|
||||
"name": "HA text AI",
|
||||
"config_flow": true,
|
||||
"documentation": "https://github.com/smkrv/ha-text-ai",
|
||||
"issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
|
||||
"requirements": ["openai>=1.0.0"],
|
||||
"ssdp": [],
|
||||
"zeroconf": [],
|
||||
"homekit": {},
|
||||
"dependencies": [],
|
||||
"domain": "ha_text_ai",
|
||||
"name": "HA Text AI",
|
||||
"after_dependencies": ["http"],
|
||||
"bluetooth": [],
|
||||
"codeowners": ["@smkrv"],
|
||||
"version": "1.0.0",
|
||||
"iot_class": "cloud_polling"
|
||||
"config_flow": true,
|
||||
"dependencies": [],
|
||||
"documentation": "https://github.com/smkrv/ha-text-ai",
|
||||
"integration_type": "service",
|
||||
"iot_class": "cloud_polling",
|
||||
"issue_tracker": "https://github.com/smkrv/ha-text-ai/issues",
|
||||
"loggers": ["custom_components.ha_text_ai"],
|
||||
"mqtt": [],
|
||||
"quality_scale": "silver",
|
||||
"requirements": [
|
||||
"openai>=1.12.0",
|
||||
"anthropic>=0.8.0",
|
||||
"aiohttp>=3.8.0",
|
||||
"async-timeout>=4.0.0",
|
||||
"certifi>=2024.2.2"
|
||||
],
|
||||
"single_config_entry": false,
|
||||
"ssdp": [],
|
||||
"usb": [],
|
||||
"version": "2.0.0",
|
||||
"zeroconf": []
|
||||
}
|
||||
|
||||
@@ -1,27 +1,87 @@
|
||||
"""Sensor platform for HA text AI."""
|
||||
from typing import Any, Callable, Dict, Optional
|
||||
"""Sensor platform for HA Text AI."""
|
||||
import logging
|
||||
import math
|
||||
from typing import Any, Dict
|
||||
|
||||
from homeassistant.components.sensor import SensorEntity, SensorStateClass
|
||||
from homeassistant.components.sensor import (
|
||||
SensorEntity,
|
||||
SensorEntityDescription,
|
||||
)
|
||||
from homeassistant.config_entries import ConfigEntry
|
||||
from homeassistant.core import HomeAssistant
|
||||
from homeassistant.helpers.device_registry import DeviceInfo
|
||||
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 homeassistant.util import slugify
|
||||
|
||||
from .const import (
|
||||
DOMAIN,
|
||||
CONF_MODEL,
|
||||
CONF_API_PROVIDER,
|
||||
ATTR_TOTAL_RESPONSES,
|
||||
ATTR_TOTAL_ERRORS,
|
||||
ATTR_AVG_RESPONSE_TIME,
|
||||
ATTR_LAST_REQUEST_TIME,
|
||||
ATTR_LAST_ERROR,
|
||||
ATTR_IS_PROCESSING,
|
||||
ATTR_IS_RATE_LIMITED,
|
||||
ATTR_IS_MAINTENANCE,
|
||||
ATTR_API_VERSION,
|
||||
ATTR_ENDPOINT_STATUS,
|
||||
ATTR_PERFORMANCE_METRICS,
|
||||
ATTR_HISTORY_SIZE,
|
||||
ATTR_UPTIME,
|
||||
ATTR_API_PROVIDER,
|
||||
ATTR_MODEL,
|
||||
ATTR_SYSTEM_PROMPT,
|
||||
ATTR_API_STATUS,
|
||||
ATTR_RESPONSE,
|
||||
ATTR_QUESTION,
|
||||
ATTR_CONVERSATION_HISTORY,
|
||||
METRIC_TOTAL_TOKENS,
|
||||
METRIC_PROMPT_TOKENS,
|
||||
METRIC_COMPLETION_TOKENS,
|
||||
METRIC_SUCCESSFUL_REQUESTS,
|
||||
METRIC_FAILED_REQUESTS,
|
||||
METRIC_AVERAGE_LATENCY,
|
||||
METRIC_MAX_LATENCY,
|
||||
METRIC_MIN_LATENCY,
|
||||
STATE_READY,
|
||||
STATE_PROCESSING,
|
||||
STATE_ERROR,
|
||||
STATE_INITIALIZING,
|
||||
STATE_MAINTENANCE,
|
||||
STATE_RATE_LIMITED,
|
||||
STATE_DISCONNECTED,
|
||||
ENTITY_ICON,
|
||||
ENTITY_ICON_ERROR,
|
||||
ENTITY_ICON_PROCESSING,
|
||||
)
|
||||
|
||||
from .const import DOMAIN, ATTR_QUESTION, ATTR_RESPONSE, ATTR_LAST_UPDATED
|
||||
from .coordinator import HATextAICoordinator
|
||||
|
||||
_LOGGER = logging.getLogger(__name__)
|
||||
|
||||
async def async_setup_entry(
|
||||
hass: HomeAssistant,
|
||||
entry: ConfigEntry,
|
||||
async_add_entities: AddEntitiesCallback,
|
||||
) -> None:
|
||||
"""Set up the HA text AI sensor."""
|
||||
"""Set up the HA Text AI sensor."""
|
||||
coordinator = hass.data[DOMAIN][entry.entry_id]
|
||||
async_add_entities([HATextAISensor(coordinator, entry)], True)
|
||||
instance_name = coordinator.instance_name
|
||||
|
||||
_LOGGER.debug(f"Setting up sensor with instance: {instance_name}")
|
||||
|
||||
sensor = HATextAISensor(coordinator, entry)
|
||||
async_add_entities([sensor], True)
|
||||
|
||||
class HATextAISensor(CoordinatorEntity, SensorEntity):
|
||||
"""HA text AI Sensor."""
|
||||
"""HA Text AI Sensor."""
|
||||
|
||||
coordinator: HATextAICoordinator
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
@@ -30,29 +90,205 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
|
||||
) -> None:
|
||||
"""Initialize the sensor."""
|
||||
super().__init__(coordinator)
|
||||
|
||||
self._config_entry = config_entry
|
||||
self._instance_name = coordinator.instance_name
|
||||
self._conversation_history = []
|
||||
self._system_prompt = None
|
||||
|
||||
self._attr_name = f"HA Text AI {self._instance_name}"
|
||||
self.entity_id = f"sensor.ha_text_ai_{slugify(self._instance_name)}"
|
||||
self._attr_unique_id = f"{config_entry.entry_id}"
|
||||
self._attr_name = "HA text AI"
|
||||
self._attr_state_class = SensorStateClass.MEASUREMENT
|
||||
|
||||
self.entity_description = SensorEntityDescription(
|
||||
key=f"ha_text_ai_{self._instance_name}",
|
||||
entity_registry_enabled_default=True,
|
||||
)
|
||||
|
||||
self._current_state = STATE_INITIALIZING
|
||||
self._error_count = 0
|
||||
self._last_error = None
|
||||
self._last_update = None
|
||||
self._is_processing = False
|
||||
self._last_response = {}
|
||||
self._metrics = {}
|
||||
|
||||
model = config_entry.data.get(CONF_MODEL, "Unknown")
|
||||
api_provider = config_entry.data.get(CONF_API_PROVIDER, "Unknown")
|
||||
|
||||
self._attr_device_info = DeviceInfo(
|
||||
identifiers={(DOMAIN, self._attr_unique_id)},
|
||||
name=self._attr_name, # Используем имя сенсора
|
||||
manufacturer="Community",
|
||||
model=f"{model} ({api_provider} provider)",
|
||||
sw_version="1.0.0",
|
||||
)
|
||||
|
||||
_LOGGER.debug(f"Initialized sensor: {self.entity_id} for instance: {self._instance_name}")
|
||||
|
||||
@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"
|
||||
def available(self) -> bool:
|
||||
"""Return if entity is available."""
|
||||
return (
|
||||
self.coordinator.last_update_success
|
||||
and self.coordinator.data is not None
|
||||
and self._current_state != STATE_DISCONNECTED
|
||||
)
|
||||
|
||||
def _sanitize_value(self, value: Any) -> Any:
|
||||
"""Sanitize values for JSON serialization."""
|
||||
if isinstance(value, float):
|
||||
if math.isinf(value) or math.isnan(value):
|
||||
return None
|
||||
return value
|
||||
|
||||
def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Sanitize all attributes for JSON serialization."""
|
||||
return {
|
||||
key: self._sanitize_value(value)
|
||||
for key, value in attributes.items()
|
||||
if value is not None
|
||||
}
|
||||
|
||||
@property
|
||||
def extra_state_attributes(self) -> Optional[Dict[str, Any]]:
|
||||
def native_value(self) -> StateType:
|
||||
"""Return the native value of the sensor."""
|
||||
if not self.coordinator.last_update_success or not self.coordinator.data:
|
||||
self._current_state = STATE_DISCONNECTED
|
||||
return self._current_state
|
||||
|
||||
status = self.coordinator.data.get("state", STATE_READY)
|
||||
self._current_state = status
|
||||
return status
|
||||
|
||||
@property
|
||||
def icon(self) -> str:
|
||||
"""Return the icon based on the current state."""
|
||||
if self._current_state == STATE_ERROR:
|
||||
return ENTITY_ICON_ERROR
|
||||
elif self._current_state == STATE_PROCESSING:
|
||||
return ENTITY_ICON_PROCESSING
|
||||
return ENTITY_ICON
|
||||
|
||||
@property
|
||||
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,
|
||||
}
|
||||
return {}
|
||||
|
||||
try:
|
||||
data = self.coordinator.data
|
||||
attributes = {
|
||||
ATTR_MODEL: self._config_entry.data.get(CONF_MODEL, "Unknown"),
|
||||
ATTR_API_PROVIDER: self._config_entry.data.get(CONF_API_PROVIDER, "Unknown"),
|
||||
ATTR_API_STATUS: self._current_state,
|
||||
ATTR_TOTAL_ERRORS: self._error_count,
|
||||
ATTR_LAST_ERROR: self._last_error,
|
||||
"instance_name": self._instance_name,
|
||||
ATTR_SYSTEM_PROMPT: data.get("system_prompt"),
|
||||
ATTR_IS_PROCESSING: data.get("is_processing", False),
|
||||
ATTR_IS_RATE_LIMITED: data.get("is_rate_limited", False),
|
||||
ATTR_IS_MAINTENANCE: data.get("is_maintenance", False),
|
||||
ATTR_ENDPOINT_STATUS: data.get("endpoint_status", "unknown"),
|
||||
ATTR_UPTIME: data.get("uptime", 0),
|
||||
ATTR_HISTORY_SIZE: data.get("history_size", 0),
|
||||
ATTR_CONVERSATION_HISTORY: data.get("conversation_history", []),
|
||||
}
|
||||
|
||||
# Add metrics
|
||||
metrics = data.get("metrics", {})
|
||||
if isinstance(metrics, dict):
|
||||
self._metrics = metrics
|
||||
attributes.update({
|
||||
METRIC_TOTAL_TOKENS: metrics.get("total_tokens", 0),
|
||||
METRIC_PROMPT_TOKENS: metrics.get("prompt_tokens", 0),
|
||||
METRIC_COMPLETION_TOKENS: metrics.get("completion_tokens", 0),
|
||||
METRIC_SUCCESSFUL_REQUESTS: metrics.get("successful_requests", 0),
|
||||
METRIC_FAILED_REQUESTS: metrics.get("failed_requests", 0),
|
||||
METRIC_AVERAGE_LATENCY: metrics.get("average_latency", 0),
|
||||
METRIC_MAX_LATENCY: metrics.get("max_latency", 0),
|
||||
METRIC_MIN_LATENCY: metrics.get("min_latency", float("inf")),
|
||||
})
|
||||
|
||||
# Add last response
|
||||
last_response = data.get("last_response", {})
|
||||
if isinstance(last_response, dict):
|
||||
self._last_response = last_response
|
||||
attributes.update({
|
||||
ATTR_RESPONSE: last_response.get("response", ""),
|
||||
ATTR_QUESTION: last_response.get("question", ""),
|
||||
"last_model": last_response.get("model", ""),
|
||||
"last_timestamp": last_response.get("timestamp", ""),
|
||||
"last_error": last_response.get("error"),
|
||||
})
|
||||
|
||||
# Add performance metrics if available
|
||||
if ATTR_PERFORMANCE_METRICS in data:
|
||||
attributes[ATTR_PERFORMANCE_METRICS] = data[ATTR_PERFORMANCE_METRICS]
|
||||
|
||||
# Add API version if available
|
||||
if ATTR_API_VERSION in data:
|
||||
attributes[ATTR_API_VERSION] = data[ATTR_API_VERSION]
|
||||
|
||||
return self._sanitize_attributes(attributes)
|
||||
|
||||
except Exception as err:
|
||||
_LOGGER.error("Error preparing attributes: %s", err, exc_info=True)
|
||||
return {}
|
||||
|
||||
async def async_added_to_hass(self) -> None:
|
||||
"""When entity is added to hass."""
|
||||
await super().async_added_to_hass()
|
||||
self._handle_coordinator_update()
|
||||
_LOGGER.debug(f"Entity {self.entity_id} added to Home Assistant")
|
||||
|
||||
def _handle_coordinator_update(self) -> None:
|
||||
"""Handle updated data from the coordinator."""
|
||||
try:
|
||||
data = self.coordinator.data
|
||||
if not self.coordinator.last_update_success or not data:
|
||||
self._current_state = STATE_DISCONNECTED
|
||||
_LOGGER.warning(f"No data available for {self.entity_id}")
|
||||
self.async_write_ha_state()
|
||||
return
|
||||
|
||||
self._is_processing = data.get("is_processing", False)
|
||||
|
||||
# Update conversation history and system prompt
|
||||
self._conversation_history = data.get("conversation_history", [])
|
||||
self._system_prompt = data.get("system_prompt")
|
||||
|
||||
# Update state based on conditions
|
||||
if self._is_processing:
|
||||
self._current_state = STATE_PROCESSING
|
||||
elif data.get("is_rate_limited"):
|
||||
self._current_state = STATE_RATE_LIMITED
|
||||
elif data.get("is_maintenance"):
|
||||
self._current_state = STATE_MAINTENANCE
|
||||
elif data.get("error"):
|
||||
self._current_state = STATE_ERROR
|
||||
self._last_error = data["error"]
|
||||
self._error_count += 1
|
||||
else:
|
||||
self._current_state = data.get("state", STATE_READY)
|
||||
|
||||
# Update last update timestamp
|
||||
self._last_update = dt_util.utcnow()
|
||||
|
||||
_LOGGER.debug(
|
||||
f"Updated {self.entity_id} state to: {self._current_state} "
|
||||
f"(available: {self.available})"
|
||||
)
|
||||
|
||||
except Exception as err:
|
||||
self._current_state = STATE_ERROR
|
||||
self._last_error = str(err)
|
||||
self._error_count += 1
|
||||
_LOGGER.error(
|
||||
"Error handling update for %s: %s",
|
||||
self.entity_id,
|
||||
err,
|
||||
exc_info=True
|
||||
)
|
||||
|
||||
self.async_write_ha_state()
|
||||
|
||||
@@ -1,84 +1,75 @@
|
||||
# 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.
|
||||
fields:
|
||||
instance:
|
||||
name: Instance
|
||||
description: Name of the HA Text AI instance to use
|
||||
required: true
|
||||
selector:
|
||||
entity:
|
||||
integration: ha_text_ai
|
||||
domain: sensor
|
||||
|
||||
question:
|
||||
name: Question
|
||||
description: The question or prompt to send to the AI
|
||||
description: Your question or prompt for the AI assistant
|
||||
required: true
|
||||
example: "What is the weather like today?"
|
||||
selector:
|
||||
text:
|
||||
multiline: true
|
||||
type: text
|
||||
|
||||
system_prompt:
|
||||
name: System Prompt
|
||||
description: Optional system prompt to set context for this specific question
|
||||
required: false
|
||||
selector:
|
||||
text:
|
||||
multiline: true
|
||||
|
||||
context_messages:
|
||||
name: Context Messages
|
||||
description: Number of previous messages to include in context (1-20)
|
||||
required: false
|
||||
default: 5
|
||||
selector:
|
||||
number:
|
||||
min: 1
|
||||
max: 20
|
||||
step: 1
|
||||
mode: box
|
||||
|
||||
model:
|
||||
name: Model
|
||||
description: Override the default model for this question (optional)
|
||||
description: "Select AI model to use (optional, overrides default setting)"
|
||||
required: false
|
||||
example: "gpt-4"
|
||||
default: "gpt-3.5-turbo"
|
||||
selector:
|
||||
select:
|
||||
options:
|
||||
- "gpt-3.5-turbo"
|
||||
- "gpt-4"
|
||||
- "gpt-4-32k"
|
||||
selector:
|
||||
text:
|
||||
multiline: false
|
||||
|
||||
temperature:
|
||||
name: Temperature
|
||||
description: Control randomness in the response (0.0-1.0, lower is more focused)
|
||||
description: Controls response creativity (0.0-2.0)
|
||||
required: false
|
||||
default: 0.7
|
||||
selector:
|
||||
number:
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
max: 2.0
|
||||
step: 0.1
|
||||
mode: slider
|
||||
|
||||
max_tokens:
|
||||
name: Max Tokens
|
||||
description: Maximum length of the response
|
||||
description: Maximum length of the response (1-4096 tokens)
|
||||
required: false
|
||||
default: 1000
|
||||
selector:
|
||||
number:
|
||||
min: 1
|
||||
max: 4000
|
||||
max: 4096
|
||||
step: 1
|
||||
|
||||
# Service to clear response history
|
||||
clear_history:
|
||||
name: Clear History
|
||||
description: Clear the stored question and response history
|
||||
fields: {}
|
||||
|
||||
# Service to get response history
|
||||
get_history:
|
||||
name: Get History
|
||||
description: Get the history of questions and responses
|
||||
fields:
|
||||
limit:
|
||||
name: Limit
|
||||
description: Maximum number of history items to return
|
||||
required: false
|
||||
default: 10
|
||||
selector:
|
||||
number:
|
||||
min: 1
|
||||
max: 100
|
||||
step: 1
|
||||
|
||||
# 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
|
||||
fields:
|
||||
prompt:
|
||||
name: System Prompt
|
||||
description: The system prompt to set
|
||||
required: true
|
||||
example: "You are a helpful assistant specializing in home automation"
|
||||
selector:
|
||||
text:
|
||||
multiline: true
|
||||
mode: box
|
||||
|
||||
@@ -0,0 +1,261 @@
|
||||
{
|
||||
"config": {
|
||||
"step": {
|
||||
"provider": {
|
||||
"title": "KI-Anbieter auswählen",
|
||||
"description": "Wählen Sie den KI-Dienst-Anbieter für diese Instanz",
|
||||
"data": {
|
||||
"api_provider": "API-Anbieter",
|
||||
"context_messages": "Anzahl der zu speichernden Kontextnachrichten (1-20)"
|
||||
}
|
||||
},
|
||||
"user": {
|
||||
"title": "HA Text AI Instanz konfigurieren",
|
||||
"description": "Richten Sie eine neue KI-Assistenten-Instanz mit Ihrem ausgewählten Anbieter ein",
|
||||
"data": {
|
||||
"name": "Instanzname (z.B. 'GPT Assistent', 'Claude Helfer')",
|
||||
"api_key": "API-Schlüssel für Authentifizierung",
|
||||
"model": "Zu verwendendes KI-Modell",
|
||||
"temperature": "Antwort-Kreativität (0-2, niedriger = fokussierter)",
|
||||
"max_tokens": "Maximale Antwortlänge (1-4096 Token)",
|
||||
"api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
|
||||
"request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
|
||||
"context_messages": "Anzahl der zu speichernden Kontextnachrichten (1-20)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"name_exists": "Eine Instanz mit diesem Namen existiert bereits",
|
||||
"invalid_name": "Ungültiger Instanzname",
|
||||
"invalid_auth": "Authentifizierung fehlgeschlagen - überprüfen Sie Ihren API-Schlüssel",
|
||||
"invalid_api_key": "Ungültiger API-Schlüssel - bitte überprüfen Sie Ihre Anmeldedaten",
|
||||
"cannot_connect": "Verbindung zum API-Dienst fehlgeschlagen",
|
||||
"invalid_model": "Ausgewähltes Modell ist nicht verfügbar",
|
||||
"rate_limit": "Anfragelimit überschritten",
|
||||
"context_length": "Kontextlänge überschritten",
|
||||
"rate_limit_exceeded": "API-Anfragelimit überschritten",
|
||||
"maintenance": "Dienst ist in Wartung",
|
||||
"invalid_response": "Ungültige API-Antwort erhalten",
|
||||
"api_error": "API-Dienst-Fehler aufgetreten",
|
||||
"timeout": "Anfrage-Zeitüberschreitung",
|
||||
"invalid_instance": "Ungültige Instanz angegeben",
|
||||
"unknown": "Unerwarteter Fehler aufgetreten"
|
||||
}
|
||||
},
|
||||
"options": {
|
||||
"step": {
|
||||
"init": {
|
||||
"title": "Instanzeinstellungen aktualisieren",
|
||||
"description": "Einstellungen für diese KI-Assistenten-Instanz ändern",
|
||||
"data": {
|
||||
"model": "KI-Modell",
|
||||
"temperature": "Antwort-Kreativität (0-2)",
|
||||
"max_tokens": "Maximale Antwortlänge (1-4096)",
|
||||
"request_interval": "Minimales Anfragen-Intervall (0,1-60 Sekunden)",
|
||||
"context_messages": "Anzahl der vorherigen Nachrichten, die in den Kontext einbezogen werden sollen (1-20)"
|
||||
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"services": {
|
||||
"ask_question": {
|
||||
"name": "Frage stellen (HA Text AI)",
|
||||
"description": "Senden Sie eine Frage an das KI-Modell und erhalten Sie eine detaillierte Antwort. Die Antwort wird in der Gesprächshistorie gespeichert und kann später abgerufen werden.",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instanz",
|
||||
"description": "Name der zu verwendenden HA Text AI Instanz"
|
||||
},
|
||||
"question": {
|
||||
"name": "Frage",
|
||||
"description": "Ihre Frage oder Eingabeaufforderung für den KI-Assistenten"
|
||||
},
|
||||
"context_messages": {
|
||||
"name": "Kontextnachrichten",
|
||||
"description": "Anzahl der vorherigen Nachrichten, die in den Kontext einbezogen werden sollen (1-20)"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "Systemaufforderung",
|
||||
"description": "Optionale Systemaufforderung zur Kontexteinstellung für diese spezifische Frage"
|
||||
},
|
||||
"model": {
|
||||
"name": "Modell",
|
||||
"description": "Wählen Sie das zu verwendende KI-Modell (optional, überschreibt Standardeinstellung)"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Temperatur",
|
||||
"description": "Steuert die Antwort-Kreativität (0,0-2,0)"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Max. Token",
|
||||
"description": "Maximale Länge der Antwort (1-4096 Token)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"clear_history": {
|
||||
"name": "Verlauf löschen",
|
||||
"description": "Alle gespeicherten Fragen und Antworten aus dem Gesprächsverlauf löschen",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instanz",
|
||||
"description": "Name der HA Text AI Instanz, für die der Verlauf gelöscht werden soll"
|
||||
}
|
||||
}
|
||||
},
|
||||
"get_history": {
|
||||
"name": "Verlauf abrufen",
|
||||
"description": "Gesprächsverlauf mit optionaler Filterung und Sortierung abrufen",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instanz",
|
||||
"description": "Name der HA Text AI Instanz, aus der der Verlauf abgerufen werden soll"
|
||||
},
|
||||
"limit": {
|
||||
"name": "Limit",
|
||||
"description": "Anzahl der zurückzugebenden Gespräche (1-100)"
|
||||
},
|
||||
"filter_model": {
|
||||
"name": "Modell filtern",
|
||||
"description": "Gespräche nach bestimmtem KI-Modell filtern"
|
||||
},
|
||||
"start_date": {
|
||||
"name": "Startdatum",
|
||||
"description": "Gespräche ab diesem Datum/Zeitpunkt filtern"
|
||||
},
|
||||
"include_metadata": {
|
||||
"name": "Metadaten einbeziehen",
|
||||
"description": "Zusätzliche Informationen wie verwendete Token, Antwortzeit usw. einbeziehen"
|
||||
},
|
||||
"sort_order": {
|
||||
"name": "Sortierreihenfolge",
|
||||
"description": "Sortierreihenfolge der Ergebnisse (neueste oder älteste zuerst)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"set_system_prompt": {
|
||||
"name": "Systemaufforderung festlegen",
|
||||
"description": "Standardmäßige Systemverhaltensinstruktionen für alle zukünftigen Gespräche festlegen",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instanz",
|
||||
"description": "Name der HA Text AI Instanz, für die die Systemaufforderung festgelegt werden soll"
|
||||
},
|
||||
"prompt": {
|
||||
"name": "Systemaufforderung",
|
||||
"description": "Anweisungen, die definieren, wie sich die KI verhalten und antworten soll"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"entity": {
|
||||
"sensor": {
|
||||
"ha_text_ai": {
|
||||
"name": "{name}",
|
||||
"state": {
|
||||
"ready": "Bereit",
|
||||
"processing": "Verarbeitung",
|
||||
"error": "Fehler",
|
||||
"disconnected": "Getrennt",
|
||||
"rate_limited": "Anfragelimit",
|
||||
"maintenance": "Wartung",
|
||||
"initializing": "Initialisierung",
|
||||
"retrying": "Wiederholung",
|
||||
"queued": "In Warteschlange"
|
||||
},
|
||||
"state_attributes": {
|
||||
"question": {
|
||||
"name": "Letzte Frage"
|
||||
},
|
||||
"response": {
|
||||
"name": "Letzte Antwort"
|
||||
},
|
||||
"model": {
|
||||
"name": "Aktuelles Modell"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Temperatur"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Max. Token"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "Systemaufforderung"
|
||||
},
|
||||
"response_time": {
|
||||
"name": "Letzte Antwortzeit"
|
||||
},
|
||||
"total_responses": {
|
||||
"name": "Gesamte Antworten"
|
||||
},
|
||||
"error_count": {
|
||||
"name": "Fehleranzahl"
|
||||
},
|
||||
"last_error": {
|
||||
"name": "Letzter Fehler"
|
||||
},
|
||||
"api_status": {
|
||||
"name": "API-Status"
|
||||
},
|
||||
"tokens_used": {
|
||||
"name": "Insgesamt verwendete Token"
|
||||
},
|
||||
"average_response_time": {
|
||||
"name": "Durchschnittliche Antwortzeit"
|
||||
},
|
||||
"last_request_time": {
|
||||
"name": "Letzte Anforderungszeit"
|
||||
},
|
||||
"is_processing": {
|
||||
"name": "Verarbeitungsstatus"
|
||||
},
|
||||
"is_rate_limited": {
|
||||
"name": "Status Anfragelimit"
|
||||
},
|
||||
"is_maintenance": {
|
||||
"name": "Wartungsstatus"
|
||||
},
|
||||
"api_version": {
|
||||
"name": "API-Version"
|
||||
},
|
||||
"endpoint_status": {
|
||||
"name": "Endpunktstatus"
|
||||
},
|
||||
"performance_metrics": {
|
||||
"name": "Leistungsmetriken"
|
||||
},
|
||||
"history_size": {
|
||||
"name": "Verlaufsgröße"
|
||||
},
|
||||
"uptime": {
|
||||
"name": "Betriebszeit"
|
||||
},
|
||||
"total_tokens": {
|
||||
"name": "Gesamte Token"
|
||||
},
|
||||
"prompt_tokens": {
|
||||
"name": "Prompt-Token"
|
||||
},
|
||||
"completion_tokens": {
|
||||
"name": "Abschluss-Token"
|
||||
},
|
||||
"successful_requests": {
|
||||
"name": "Erfolgreiche Anfragen"
|
||||
},
|
||||
"failed_requests": {
|
||||
"name": "Fehlgeschlagene Anfragen"
|
||||
},
|
||||
"average_latency": {
|
||||
"name": "Durchschnittliche Latenz"
|
||||
},
|
||||
"max_latency": {
|
||||
"name": "Maximale Latenz"
|
||||
},
|
||||
"min_latency": {
|
||||
"name": "Minimale Latenz"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,38 +1,260 @@
|
||||
{
|
||||
"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": {
|
||||
"step": {
|
||||
"provider": {
|
||||
"title": "Select AI Provider",
|
||||
"description": "Choose which AI service provider to use for this instance",
|
||||
"data": {
|
||||
"api_provider": "API Provider",
|
||||
"context_messages": "Number of context messages to retain (1-20)"
|
||||
}
|
||||
},
|
||||
"user": {
|
||||
"title": "Configure HA Text AI Instance",
|
||||
"description": "Set up a new AI assistant instance with your selected provider",
|
||||
"data": {
|
||||
"name": "Instance name (e.g., 'GPT Assistant', 'Claude Helper')",
|
||||
"api_key": "API key for authentication",
|
||||
"model": "AI model to use",
|
||||
"temperature": "Response creativity (0-2, lower = more focused)",
|
||||
"max_tokens": "Maximum response length (1-4096 tokens)",
|
||||
"api_endpoint": "Custom API endpoint URL (optional)",
|
||||
"request_interval": "Minimum time between requests (0.1-60 seconds)",
|
||||
"context_messages": "Number of context messages to retain (1-20)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"name_exists": "An instance with this name already exists",
|
||||
"invalid_name": "Invalid instance name",
|
||||
"invalid_auth": "Authentication failed - check your API key",
|
||||
"invalid_api_key": "Invalid API key - please verify your credentials",
|
||||
"cannot_connect": "Failed to connect to API service",
|
||||
"invalid_model": "Selected model is not available",
|
||||
"rate_limit": "Rate limit exceeded",
|
||||
"context_length": "Context length exceeded",
|
||||
"rate_limit_exceeded": "API rate limit exceeded",
|
||||
"maintenance": "Service is under maintenance",
|
||||
"invalid_response": "Invalid API response received",
|
||||
"api_error": "API service error occurred",
|
||||
"timeout": "Request timed out",
|
||||
"invalid_instance": "Invalid instance specified",
|
||||
"unknown": "Unexpected error occurred"
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"auth": "API key is invalid.",
|
||||
"cannot_connect": "Failed to connect to API.",
|
||||
"unknown": "Unexpected error occurred."
|
||||
"options": {
|
||||
"step": {
|
||||
"init": {
|
||||
"title": "Update Instance Settings",
|
||||
"description": "Modify settings for this AI assistant instance",
|
||||
"data": {
|
||||
"model": "AI model",
|
||||
"temperature": "Response creativity (0-2)",
|
||||
"max_tokens": "Maximum response length (1-4096)",
|
||||
"request_interval": "Minimum request interval (0.1-60 seconds)",
|
||||
"context_messages": "Number of previous messages to include in context (1-20)"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"abort": {
|
||||
"already_configured": "Device is already configured"
|
||||
}
|
||||
},
|
||||
"options": {
|
||||
"step": {
|
||||
"init": {
|
||||
"title": "HA text AI Options",
|
||||
"data": {
|
||||
"temperature": "Temperature",
|
||||
"max_tokens": "Max Tokens",
|
||||
"request_interval": "Request Interval (seconds)"
|
||||
"services": {
|
||||
"ask_question": {
|
||||
"name": "Ask Question (HA Text AI)",
|
||||
"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.",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instance",
|
||||
"description": "Name of the HA Text AI instance to use"
|
||||
},
|
||||
"question": {
|
||||
"name": "Question",
|
||||
"description": "Your question or prompt for the AI assistant"
|
||||
},
|
||||
"context_messages": {
|
||||
"name": "Context Messages",
|
||||
"description": "Number of previous messages to include in context (1-20)"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "System Prompt",
|
||||
"description": "Optional system prompt to set context for this specific question"
|
||||
},
|
||||
"model": {
|
||||
"name": "Model",
|
||||
"description": "Select AI model to use (optional, overrides default setting)"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Temperature",
|
||||
"description": "Controls response creativity (0.0-2.0)"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Max Tokens",
|
||||
"description": "Maximum length of the response (1-4096 tokens)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"clear_history": {
|
||||
"name": "Clear History",
|
||||
"description": "Delete all stored questions and responses from the conversation history",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instance",
|
||||
"description": "Name of the HA Text AI instance to clear history for"
|
||||
}
|
||||
}
|
||||
},
|
||||
"get_history": {
|
||||
"name": "Get History",
|
||||
"description": "Retrieve conversation history with optional filtering and sorting",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instance",
|
||||
"description": "Name of the HA Text AI instance to get history from"
|
||||
},
|
||||
"limit": {
|
||||
"name": "Limit",
|
||||
"description": "Number of conversations to return (1-100)"
|
||||
},
|
||||
"filter_model": {
|
||||
"name": "Filter Model",
|
||||
"description": "Filter conversations by specific AI model"
|
||||
},
|
||||
"start_date": {
|
||||
"name": "Start Date",
|
||||
"description": "Filter conversations starting from this date/time"
|
||||
},
|
||||
"include_metadata": {
|
||||
"name": "Include Metadata",
|
||||
"description": "Include additional information like tokens used, response time, etc."
|
||||
},
|
||||
"sort_order": {
|
||||
"name": "Sort Order",
|
||||
"description": "Sort order for results (newest or oldest first)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"set_system_prompt": {
|
||||
"name": "Set System Prompt",
|
||||
"description": "Set default system behavior instructions for all future conversations",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Instance",
|
||||
"description": "Name of the HA Text AI instance to set system prompt for"
|
||||
},
|
||||
"prompt": {
|
||||
"name": "System Prompt",
|
||||
"description": "Instructions that define how the AI should behave and respond"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"entity": {
|
||||
"sensor": {
|
||||
"ha_text_ai": {
|
||||
"name": "{name}",
|
||||
"state": {
|
||||
"ready": "Ready",
|
||||
"processing": "Processing",
|
||||
"error": "Error",
|
||||
"disconnected": "Disconnected",
|
||||
"rate_limited": "Rate Limited",
|
||||
"maintenance": "Maintenance",
|
||||
"initializing": "Initializing",
|
||||
"retrying": "Retrying",
|
||||
"queued": "Queued"
|
||||
},
|
||||
"state_attributes": {
|
||||
"question": {
|
||||
"name": "Last Question"
|
||||
},
|
||||
"response": {
|
||||
"name": "Last Response"
|
||||
},
|
||||
"model": {
|
||||
"name": "Current Model"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Temperature"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Max Tokens"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "System Prompt"
|
||||
},
|
||||
"response_time": {
|
||||
"name": "Last Response Time"
|
||||
},
|
||||
"total_responses": {
|
||||
"name": "Total Responses"
|
||||
},
|
||||
"error_count": {
|
||||
"name": "Error Count"
|
||||
},
|
||||
"last_error": {
|
||||
"name": "Last Error"
|
||||
},
|
||||
"api_status": {
|
||||
"name": "API Status"
|
||||
},
|
||||
"tokens_used": {
|
||||
"name": "Total Tokens Used"
|
||||
},
|
||||
"average_response_time": {
|
||||
"name": "Average Response Time"
|
||||
},
|
||||
"last_request_time": {
|
||||
"name": "Last Request Time"
|
||||
},
|
||||
"is_processing": {
|
||||
"name": "Processing Status"
|
||||
},
|
||||
"is_rate_limited": {
|
||||
"name": "Rate Limited Status"
|
||||
},
|
||||
"is_maintenance": {
|
||||
"name": "Maintenance Status"
|
||||
},
|
||||
"api_version": {
|
||||
"name": "API Version"
|
||||
},
|
||||
"endpoint_status": {
|
||||
"name": "Endpoint Status"
|
||||
},
|
||||
"performance_metrics": {
|
||||
"name": "Performance Metrics"
|
||||
},
|
||||
"history_size": {
|
||||
"name": "History Size"
|
||||
},
|
||||
"uptime": {
|
||||
"name": "Uptime"
|
||||
},
|
||||
"total_tokens": {
|
||||
"name": "Total Tokens"
|
||||
},
|
||||
"prompt_tokens": {
|
||||
"name": "Prompt Tokens"
|
||||
},
|
||||
"completion_tokens": {
|
||||
"name": "Completion Tokens"
|
||||
},
|
||||
"successful_requests": {
|
||||
"name": "Successful Requests"
|
||||
},
|
||||
"failed_requests": {
|
||||
"name": "Failed Requests"
|
||||
},
|
||||
"average_latency": {
|
||||
"name": "Average Latency"
|
||||
},
|
||||
"max_latency": {
|
||||
"name": "Maximum Latency"
|
||||
},
|
||||
"min_latency": {
|
||||
"name": "Minimum Latency"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,260 @@
|
||||
{
|
||||
"config": {
|
||||
"step": {
|
||||
"provider": {
|
||||
"title": "Выбор провайдера ИИ",
|
||||
"description": "Выберите сервис ИИ для этого экземпляра",
|
||||
"data": {
|
||||
"api_provider": "Провайдер API",
|
||||
"context_messages": "Количество сообщений в контексте (1-20)"
|
||||
}
|
||||
},
|
||||
"user": {
|
||||
"title": "Настройка экземпляра HA Text AI",
|
||||
"description": "Настройте нового помощника ИИ с выбранным провайдером",
|
||||
"data": {
|
||||
"name": "Название экземпляра (например, 'GPT Помощник', 'Claude Ассистент')",
|
||||
"api_key": "API-ключ для аутентификации",
|
||||
"model": "Модель ИИ для использования",
|
||||
"temperature": "Креативность ответов (0-2, меньше = более сфокусированно)",
|
||||
"max_tokens": "Максимальная длина ответа (1-4096 токенов)",
|
||||
"api_endpoint": "Пользовательский URL-адрес API (необязательно)",
|
||||
"request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
|
||||
"context_messages": "Количество сохраняемых контекстных сообщений (1-20)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"error": {
|
||||
"name_exists": "Экземпляр с таким именем уже существует",
|
||||
"invalid_name": "Некорректное имя экземпляра",
|
||||
"invalid_auth": "Ошибка аутентификации - проверьте API-ключ",
|
||||
"invalid_api_key": "Неверный API-ключ - проверьте учетные данные",
|
||||
"cannot_connect": "Не удалось подключиться к сервису API",
|
||||
"invalid_model": "Выбранная модель недоступна",
|
||||
"rate_limit": "Превышен лимит запросов",
|
||||
"context_length": "Превышена длина контекста",
|
||||
"rate_limit_exceeded": "Превышен лимит API",
|
||||
"maintenance": "Сервис на техническом обслуживании",
|
||||
"invalid_response": "Получен некорректный ответ API",
|
||||
"api_error": "Произошла ошибка сервиса API",
|
||||
"timeout": "Время ожидания истекло",
|
||||
"invalid_instance": "Указан неверный экземпляр",
|
||||
"unknown": "Произошла непредвиденная ошибка"
|
||||
}
|
||||
},
|
||||
"options": {
|
||||
"step": {
|
||||
"init": {
|
||||
"title": "Обновление настроек экземпляра",
|
||||
"description": "Измените настройки для этого помощника ИИ",
|
||||
"data": {
|
||||
"model": "Модель ИИ",
|
||||
"temperature": "Креативность ответов (0-2)",
|
||||
"max_tokens": "Максимальная длина ответа (1-4096)",
|
||||
"request_interval": "Минимальный интервал запросов (0.1-60 секунд)",
|
||||
"context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"services": {
|
||||
"ask_question": {
|
||||
"name": "Задать вопрос (HA Text AI)",
|
||||
"description": "Отправьте вопрос модели ИИ и получите подробный ответ. Ответ будет сохранен в истории беседы и может быть извлечен позже.",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Экземпляр",
|
||||
"description": "Название экземпляра HA Text AI для использования"
|
||||
},
|
||||
"question": {
|
||||
"name": "Вопрос",
|
||||
"description": "Ваш вопрос или запрос помощнику ИИ"
|
||||
},
|
||||
"context_messages": {
|
||||
"name": "Контекстные сообщения",
|
||||
"description": "Количество предыдущих сообщений для включения в контекст (1-20)"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "Системный промпт",
|
||||
"description": "Необязательный системный промпт для установки контекста для этого конкретного вопроса"
|
||||
},
|
||||
"model": {
|
||||
"name": "Модель",
|
||||
"description": "Выберите модель ИИ (необязательно, переопределяет настройки по умолчанию)"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Температура",
|
||||
"description": "Управляет креативностью ответа (0.0-2.0)"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Максимальное количество токенов",
|
||||
"description": "Максимальная длина ответа (1-4096 токенов)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"clear_history": {
|
||||
"name": "Очистить историю",
|
||||
"description": "Удалить все сохраненные вопросы и ответы из истории беседы",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Экземпляр",
|
||||
"description": "Название экземпляра HA Text AI для очистки истории"
|
||||
}
|
||||
}
|
||||
},
|
||||
"get_history": {
|
||||
"name": "Получить историю",
|
||||
"description": "Получить историю беседы с дополнительной фильтрацией и сортировкой",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Экземпляр",
|
||||
"description": "Название экземпляра HA Text AI для получения истории"
|
||||
},
|
||||
"limit": {
|
||||
"name": "Лимит",
|
||||
"description": "Количество возвращаемых бесед (1-100)"
|
||||
},
|
||||
"filter_model": {
|
||||
"name": "Фильтр модели",
|
||||
"description": "Фильтрация бесед по конкретной модели ИИ"
|
||||
},
|
||||
"start_date": {
|
||||
"name": "Начальная дата",
|
||||
"description": "Фильтрация бесед, начиная с указанной даты/времени"
|
||||
},
|
||||
"include_metadata": {
|
||||
"name": "Включить метаданные",
|
||||
"description": "Включить дополнительную информацию, например, использованные токены, время ответа и т.д."
|
||||
},
|
||||
"sort_order": {
|
||||
"name": "Порядок сортировки",
|
||||
"description": "Порядок результатов (сначала новые или старые)"
|
||||
}
|
||||
}
|
||||
},
|
||||
"set_system_prompt": {
|
||||
"name": "Установить системный промпт",
|
||||
"description": "Установить инструкции по умолчанию для поведения ИИ во всех будущих разговорах",
|
||||
"fields": {
|
||||
"instance": {
|
||||
"name": "Экземпляр",
|
||||
"description": "Название экземпляра HA Text AI для установки системного промпта"
|
||||
},
|
||||
"prompt": {
|
||||
"name": "Системный промпт",
|
||||
"description": "Инструкции, определяющие, как ИИ должен вести себя и отвечать"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
"entity": {
|
||||
"sensor": {
|
||||
"ha_text_ai": {
|
||||
"name": "{name}",
|
||||
"state": {
|
||||
"ready": "Готов",
|
||||
"processing": "Обработка",
|
||||
"error": "Ошибка",
|
||||
"disconnected": "Отключен",
|
||||
"rate_limited": "Лимит запросов",
|
||||
"maintenance": "Техническое обслуживание",
|
||||
"initializing": "Инициализация",
|
||||
"retrying": "Повторная попытка",
|
||||
"queued": "В очереди"
|
||||
},
|
||||
"state_attributes": {
|
||||
"question": {
|
||||
"name": "Последний вопрос"
|
||||
},
|
||||
"response": {
|
||||
"name": "Последний ответ"
|
||||
},
|
||||
"model": {
|
||||
"name": "Текущая модель"
|
||||
},
|
||||
"temperature": {
|
||||
"name": "Температура"
|
||||
},
|
||||
"max_tokens": {
|
||||
"name": "Максимальное количество токенов"
|
||||
},
|
||||
"system_prompt": {
|
||||
"name": "Системный промпт"
|
||||
},
|
||||
"response_time": {
|
||||
"name": "Время последнего ответа"
|
||||
},
|
||||
"total_responses": {
|
||||
"name": "Всего ответов"
|
||||
},
|
||||
"error_count": {
|
||||
"name": "Количество ошибок"
|
||||
},
|
||||
"last_error": {
|
||||
"name": "Последняя ошибка"
|
||||
},
|
||||
"api_status": {
|
||||
"name": "Статус API"
|
||||
},
|
||||
"tokens_used": {
|
||||
"name": "Всего использовано токенов"
|
||||
},
|
||||
"average_response_time": {
|
||||
"name": "Среднее время ответа"
|
||||
},
|
||||
"last_request_time": {
|
||||
"name": "Время последнего запроса"
|
||||
},
|
||||
"is_processing": {
|
||||
"name": "Статус обработки"
|
||||
},
|
||||
"is_rate_limited": {
|
||||
"name": "Статус лимита запросов"
|
||||
},
|
||||
"is_maintenance": {
|
||||
"name": "Статус обслуживания"
|
||||
},
|
||||
"api_version": {
|
||||
"name": "Версия API"
|
||||
},
|
||||
"endpoint_status": {
|
||||
"name": "Статус эндпоинта"
|
||||
},
|
||||
"performance_metrics": {
|
||||
"name": "Показатели производительности"
|
||||
},
|
||||
"history_size": {
|
||||
"name": "Размер истории"
|
||||
},
|
||||
"uptime": {
|
||||
"name": "Время работы"
|
||||
},
|
||||
"total_tokens": {
|
||||
"name": "Всего токенов"
|
||||
},
|
||||
"prompt_tokens": {
|
||||
"name": "Токены промпта"
|
||||
},
|
||||
"completion_tokens": {
|
||||
"name": "Токены завершения"
|
||||
},
|
||||
"successful_requests": {
|
||||
"name": "Успешные запросы"
|
||||
},
|
||||
"failed_requests": {
|
||||
"name": "Неудачные запросы"
|
||||
},
|
||||
"average_latency": {
|
||||
"name": "Средняя задержка"
|
||||
},
|
||||
"max_latency": {
|
||||
"name": "Максимальная задержка"
|
||||
},
|
||||
"min_latency": {
|
||||
"name": "Минимальная задержка"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Binary file not shown.
@@ -1,7 +1,9 @@
|
||||
{
|
||||
"name": "HA text AI",
|
||||
"render_readme": true,
|
||||
"icon": "mdi:robot",
|
||||
"domains": ["sensor"],
|
||||
"homeassistant": "2023.8.0",
|
||||
"icon": "mdi:brain"
|
||||
"homeassistant": "2024.11.0",
|
||||
"version": "2.0.0",
|
||||
"documentation": "https://github.com/smkrv/ha-text-ai"
|
||||
}
|
||||
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 618 KiB |
@@ -1,3 +0,0 @@
|
||||
pytest
|
||||
pytest-asyncio
|
||||
homeassistant
|
||||
@@ -0,0 +1,19 @@
|
||||
```
|
||||
ha-text-ai/
|
||||
│
|
||||
├── custom_components/
|
||||
│ └── ha_text_ai/
|
||||
│ ├── __init__.py
|
||||
│ ├── config_flow.py
|
||||
│ ├── coordinator.py
|
||||
│ ├── manifest.json
|
||||
│ ├── sensor.py
|
||||
│ ├── services.yaml
|
||||
│ ├── const.py
|
||||
│ └── api_client.py
|
||||
│
|
||||
└── strings/
|
||||
├── en.json
|
||||
├── de.json
|
||||
└── ru.json
|
||||
```
|
||||
@@ -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()
|
||||
@@ -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]
|
||||
Reference in New Issue
Block a user