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122 Commits
Author SHA1 Message Date
SMKRV 3097106e93 feat: Add configurable API timeout setting
- Add CONF_API_TIMEOUT configuration option (5-600 seconds, default 30)
- Update config_flow.py with api_timeout field in provider form and options flow
- Update api_client.py to use configurable timeout instead of hardcoded value
- Update coordinator.py to use api_timeout for async_process_message
- Update __init__.py to read and pass api_timeout from config
- Merge entry.data with entry.options for proper options flow support
- Add translations for api_timeout in all 8 language files (en, ru, de, es, it, hi, sr, zh)
- Bump version to 2.2.0

Closes #8
2025-12-22 00:07:17 +03:00
smkrvandGitHub 35073960b8 Delete ha-text-ai.code-workspace 2025-09-03 00:56:56 +03:00
SMKRV 8d0e0b5e44 docs: update README with context_messages parameter
- Added context_messages parameter to Platform Configuration table
- Fixed duplicate parameter entry in configuration docs
- Parameter allows 1-20 previous messages in context (default: 5)
2025-09-02 23:50:20 +03:00
SMKRV e91c3701c5 Fix: Resolve get_history service parameter handling issue
- Fixed async_get_history method to accept limit parameter and other filtering options
- Updated service schema to support all parameters from services.yaml
- Added support for start_date, include_metadata, and sort_order parameters
- Version bump to 2.1.9
2025-09-02 23:27:34 +03:00
smkrv 7f62101b3e Update HACS minimum HA version to align with README requirement (2024.12.0) 2025-09-02 23:15:01 +03:00
smkrvandGitHub 3729c3736f Update hassfest.yaml 2025-09-02 09:36:46 +03:00
smkrvandGitHub f5ce5e459a Update hassfest.yaml
fix: https://github.com/smkrv/ha-text-ai/security/code-scanning/2
2025-09-02 09:24:35 +03:00
smkrvGitHubCopilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
4064486b1e Potential fix for code scanning alert no. 1: Workflow does not contain permissions
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
2025-09-02 09:18:15 +03:00
SMKRV 185778dbd0 docs: Update AI models to latest versions
- Update OpenAI models to GPT-5 and GPT-5 mini
- Update Anthropic Claude models to 4.1, 4.0 series
- Update DeepSeek models to V3.1 and R1
- Update Google Gemini models to 2.5 and 2.0 series
- Modernize model descriptions and capabilities
2025-09-02 02:19:37 +03:00
SMKRV 83a255dee0 docs: Update README.md - actualize documentation
- Simplify HACS installation instructions
- Update recommended models section (remove year from title)
- Update Claude model names to current format (claude-3.5-sonnet, claude-3.5-haiku)
- Add missing parameters to get_history service documentation
- Remove non-configurable history_file_size parameter from table
- Add missing context_messages parameter to configuration table
- Update all model references in examples to use current naming
2025-09-02 02:11:34 +03:00
SMKRV 6b66dd6a4d docs: Update README with latest configuration defaults and Gemini models
- Update default model from gpt-4o to gpt-4o-mini
- Update default temperature from 0.7 to 0.1
- Update default max_history_size from 100 to 50
- Add gemini-2.0-flash as latest recommended Gemini model
- Fix logo image link to use main branch instead of specific commit
- Update configuration parameters table with current defaults
2025-09-02 02:06:58 +03:00
SMKRV bd82f23120 docs: Update HACS badge from Custom to Default 2025-09-02 01:56:24 +03:00
SMKRV eee9754033 fix: Fix JSON syntax errors in translation files
- Fixed missing closing brace in es.json selector.api_provider.options
- Fixed missing closing brace in de.json selector.api_provider.options
- All other translation files (hi.json, it.json, sr.json, zh.json) have correct syntax
- Ensures proper JSON validation and prevents parsing errors
2025-09-02 01:26:49 +03:00
SMKRV 517b1f11ae fix: Remove invalid response schema from services.yaml
Home Assistant's hassfest validation does not support 'response' section in services.yaml.
The response_variable functionality still works through supports_response=True flag in service registration.

Fixes hassfest validation error: extra keys not allowed @ data['ask_question']['response']
2025-09-02 01:22:20 +03:00
SMKRV ed8f19bfa9 fix: Add support for response_variable in ask_question service
- Added response schema definition in services.yaml for ask_question service
- Set supports_response=True flag when registering the service
- Fixed JSON syntax error in English translation file
- Added comprehensive documentation with examples for response_variable usage
- Users can now capture AI responses directly in variables without sensor delays

Resolves issue where scripts failed with 'Script does not support response_variable' error
2025-09-02 01:19:44 +03:00
SMKRV 7e3daf611b fix: Remove target requirements from services to fix mandatory device/area/entity selection issue
- Removed target blocks from all services in services.yaml
- Services now work as global services without requiring device/area/entity selection
- Users can call services directly with only required parameters
- Fixes issue #2 where services incorrectly required target selection after v2.1.8 update
2025-09-01 23:40:26 +03:00
SMKRV 37919be70f fix: Resolve hassfest validation errors in services.yaml
- Remove invalid response schema from ask_question service
- Add required target configuration for all services
- Ensure compliance with Home Assistant service schema requirements
2025-09-01 17:20:40 +03:00
SMKRV e427254584 feat: Implement response variables support and comprehensive production audit (v2.1.8)
🚀 Major Features:
- Add response variables support to ask_question service
- Eliminate 255-character limitation for AI responses
- Enable direct data access in automations without sensors
- Prevent race conditions in parallel automations

🔧 Production Code Audit & Fixes:
- Enhanced resource management with context managers in api_client.py
- Fixed critical race conditions with asyncio.Semaphore implementation
- Improved file operations with atomic writes and corruption handling
- Enhanced error handling and logging security (removed sensitive data)
- Fixed _check_memory_available method placement in coordinator.py

🌐 Translation Updates (8 languages):
- Updated all translation files with response variables information
- Enhanced service descriptions in: en, ru, de, es, it, hi, sr, zh
- Added information about direct response capability
- Maintained consistency across all language files

📚 Documentation Enhancements:
- Added comprehensive Response Variables section to README
- Created advanced automation examples with response_variable usage
- Added migration guide from sensors to response variables
- Enhanced service documentation with response data structure
- Added practical examples for multi-step AI workflows

🔄 Service Improvements:
- Enhanced ask_question service to return structured response data
- Added comprehensive response schema in services.yaml
- Improved error handling with success/failure indicators
- Added metadata support (tokens, model, timestamp)

�� Version & Manifest:
- Bumped version to 2.1.8
- Maintained compatibility with existing integrations
- Updated service documentation

This release addresses GitHub issue #2 and significantly improves the integration's
production readiness while adding powerful new response variable functionality.
2025-09-01 17:14:23 +03:00
SMKRV 76c5629fa0 refactor(google-gemini): rewrite integration using google-genai 1.16.0
Completely rewrote the Google Gemini integration logic based on google-genai 1.16.0 to fix issue #6.
Key changes:
- Updated to the latest google-genai library
- Made API endpoint abstract while retaining option for custom endpoint configuration
- Refactored logic and classes exclusively within Google Gemini implementation
- All changes are limited to Google Gemini integration refactoring with no impact on other functionality.
2025-05-21 01:27:47 +03:00
SMKRV 7958bd010b refactor(google-gemini): rewrite integration using google-genai 1.16.0
Completely rewrote the Google Gemini integration logic based on google-genai 1.16.0 to fix issue #6.
Key changes:
- Updated to the latest google-genai library
- Made API endpoint abstract while retaining option for custom endpoint configuration
- Refactored logic and classes exclusively within Google Gemini implementation
- All changes are limited to Google Gemini integration refactoring with no impact on other functionality.
2025-05-21 01:26:42 +03:00
SMKRV 8cd876195a Bump to version 2.1.6 2025-05-20 01:50:06 +03:00
SMKRV 376753e001 fix: correct field naming in Gemini API requests from camelCase to snake_case and improve message handling 2025-05-20 01:42:38 +03:00
SMKRV b6e73e847d fix(api_client): correct Google Gemini API integration
- Change JSON field names from camelCase to snake_case as required by Gemini API
  (generation_config, max_output_tokens, system_instruction)
- Improve message handling to ensure proper role alternation (user/model)
- Add safety checks for empty contents and ensure first message is always from user
- Implement robust error handling and response parsing
- Handle edge cases where candidatesTokenCount might be returned as a list

Fixes #6
2025-05-20 01:16:41 +03:00
SMKRV 440c734214 Bump release version to v2.1.4 2025-05-19 23:20:27 +03:00
SMKRV 73788373cd Release v2.1.3 2025-05-19 23:12:55 +03:00
SMKRV 4bfc96019b fix: DEFAULT_GEMINI_ENDPOINT 2025-05-19 15:53:43 +03:00
SMKRV 2138fc7654 fix: DEFAULT_GEMINI_ENDPOINT 2025-05-19 15:36:58 +03:00
SMKRV 95bd2ebb41 Add support for Google Gemini (thanks to @Azzedde) #5 2025-05-19 15:10:19 +03:00
smkrvandGitHub cad0fd7031 Merge pull request #5 from Azzedde/main
Add Gemini API provider support to HA Text AI integration by @Azzedde
2025-05-19 14:44:06 +03:00
Azzedde c003b258f6 Add Gemini API provider support to HA Text AI integration 2025-05-18 13:23:55 +02:00
SMKRV 65a10c77f4 ~ 2025-01-30 01:15:13 +03:00
SMKRV e1463828c9 ~ 2025-01-30 01:14:24 +03:00
SMKRV 5ebb9c9c66 fix: max_tokens value 2025-01-29 18:04:13 +03:00
SMKRV f17c631a79 fix: max_tokens value 2025-01-29 18:02:42 +03:00
SMKRV 0e06794384 refactor(docs): shields & community links updated 2025-01-29 03:05:47 +03:00
SMKRV d8a924909b refactor(docs): shields & community links updated 2025-01-29 03:05:11 +03:00
SMKRV 29f1659a02 refactor(docs): shields & community links updated 2025-01-29 03:04:39 +03:00
SMKRV 5b7905de80 refactor(docs): shields & community links updated 2025-01-29 03:03:48 +03:00
SMKRV cf9ac6dcea refactor(docs): shields & community links updated 2025-01-29 01:08:45 +03:00
SMKRV 568eb3e16c refactor(docs): shields updated 2025-01-29 00:58:27 +03:00
SMKRV 53fb150389 refactor(docs): shields updated 2025-01-29 00:58:09 +03:00
SMKRV acbb53d2af refactor(docs): shields updated 2025-01-29 00:57:27 +03:00
SMKRV e19db29441 refactor(docs): DeepSeek Integration 2025-01-28 16:25:59 +03:00
SMKRV bfd64d1122 Release v2.1.1: Token Handling Improvement and DeepSeek Support
- Completely reworked token handling mechanism
- Removed custom token calculation logic
- Direct max_tokens passing to LLM APIs
- Added support for DeepSeek provider
- Integrated deepseek-chat and deepseek-reasoner models

Thanks to @estiens for reporting token handling issues and providing valuable feedback (https://github.com/smkrv/ha-text-ai/issues/1).
2025-01-28 15:54:48 +03:00
SMKRV 82e1f0c4f9 Release v2.1.0 2024-12-13 00:06:08 +03:00
SMKRV 5c16eee6e4 fix: Read version from manifest.json 2024-12-12 16:03:15 +03:00
SMKRV e988d445a4 - Fixed version reading from manifest.json implementation 2024-12-11 22:01:01 +03:00
SMKRV f9bfb9ab7f fix: correct sw_version syntax in device_info
- Fixed version reading from manifest.json implementation
2024-12-11 21:57:27 +03:00
SMKRV 92dd1bc110 ~ 2024-12-11 00:00:12 +03:00
SMKRV 17d547325a refactor(docs): updated README services examples with more detailed configuration 2024-12-10 23:33:32 +03:00
SMKRV b8cb70217c refactor(docs): updated README shields 2024-12-10 23:27:49 +03:00
SMKRV 530d04f25d refactor(docs): updated README shields 2024-12-10 23:27:18 +03:00
SMKRV b71083b9bf bump to version 2.0.9 2024-12-10 17:25:47 +03:00
SMKRV f9f7d10f7f refactor(docs): updated README images 2024-12-10 17:21:41 +03:00
SMKRV 9f7cb20621 refactor(docs): updated README images 2024-12-10 17:19:52 +03:00
SMKRV 6fc3b23365 refactor(docs): updated README images 2024-12-10 17:18:55 +03:00
SMKRV 15c717fcb0 fix: Display only last Q&A in sensor state to prevent data truncation
- Show only the latest question and answer in sensor state
- Keep full conversation history in attributes
- Fix truncation issues in Home Assistant UI
- Maintain backwards compatibility
- No configuration changes required
2024-12-10 17:02:48 +03:00
SMKRV be06fddce1 fix: Display only last Q&A in sensor state to prevent data truncation
- Show only the latest question and answer in sensor state
- Keep full conversation history in attributes
- Fix truncation issues in Home Assistant UI
- Maintain backwards compatibility
- No configuration changes required
2024-12-10 16:19:17 +03:00
SMKRV 5f0bd861a7 docs(readme): Included note that the integration has been submitted to HACS store and is currently pending review in pull request: [pull request #2896](hacs/default#2896). 2024-12-10 00:00:18 +03:00
SMKRV 428aee46c8 docs(readme): Included note that the integration has been submitted to HACS store and is currently pending review in pull request: [pull request #2896](hacs/default#2896). 2024-12-09 23:59:51 +03:00
SMKRV 561bcf0b1d docs(Code of Conduct): Add Code of Conduct to promote community guidelines
- Implement Contributor Covenant Code of Conduct v1.4
- Establish clear expectations for community interactions
- Define standards of acceptable and unacceptable behavior
- Provide framework for reporting and addressing issues
- Emphasize inclusivity and respect for all contributors
2024-12-09 16:52:44 +03:00
SMKRV 2b1e42c665 docs(readme): Included note that the integration has been submitted to HACS store and is currently pending review in pull request: [pull request #2893](https://github.com/hacs/default/pull/2893). 2024-12-09 15:29:53 +03:00
SMKRV 2d68f29ab5 bump to version 2.0.8 2024-12-09 00:41:28 +03:00
SMKRV 19d4a93bca bump to version 2.0.8 2024-12-09 00:41:08 +03:00
SMKRV fb75c5f44e bump to version 2.0.9 2024-12-09 00:39:28 +03:00
SMKRV 52af987985 bump to version 2.0.9 2024-12-09 00:38:59 +03:00
SMKRV 162a30acdd bump to version 2.0.8-beta 2024-12-07 00:48:17 +03:00
SMKRV 898a6fc638 bump to version 2.0.8-beta 2024-12-07 00:43:53 +03:00
SMKRV 38e2362be4 bump to version 2.0.8-beta 2024-12-06 16:51:32 +03:00
SMKRV cea912d0b5 bump to version 2.0.8-beta 2024-12-06 16:51:09 +03:00
SMKRV 5ec00040c2 bump to version 2.0.8-beta 2024-12-06 16:50:26 +03:00
SMKRV 8d28fc4a0d bump to version 2.0.8-beta 2024-12-06 16:46:11 +03:00
SMKRV 7cc6587724 bump to version 2.0.8-beta 2024-12-06 16:35:26 +03:00
SMKRV bacf76e0a9 bump to version 2.0.8-beta 2024-12-06 16:33:46 +03:00
SMKRV f86c7bfd57 refactor(docs): relocate README images from misc/ to assets/ 2024-12-06 16:13:27 +03:00
SMKRV 2aaf340575 refactor(docs): relocate README images from misc/ to assets/ 2024-12-06 16:11:13 +03:00
SMKRV bae11ba85c refactor(docs): relocate README images from misc/ to assets/ 2024-12-06 16:10:04 +03:00
SMKRV 9eb7d8912c fix: sensor history attribute calculation 2024-12-06 12:26:56 +03:00
SMKRV d29535245f Release v2.0.7-beta 2024-12-06 12:00:23 +03:00
SMKRV ca3ae982b0 feat(performance): Optimize system resources and token estimation
- Improve JSON history file processing
- Add memory and disk space validation
- Enhance parallel request handling
- Refine token counting heuristics
2024-12-06 03:14:52 +03:00
SMKRV 0c4399b46c feat(performance): Optimize system resources and token estimation
- Improve JSON history file processing
- Add memory and disk space validation
- Enhance parallel request handling
- Refine token counting heuristics
2024-12-06 02:53:41 +03:00
SMKRV c13ef1921d feat(performance): Optimize system resources and token estimation
- Improve JSON history file processing
- Add memory and disk space validation
- Enhance parallel request handling
- Refine token counting heuristics
2024-12-06 02:51:06 +03:00
SMKRV 0fb9acfa8f docs:(README) 2024-12-05 02:00:24 +03:00
SMKRV 2ac4389e1a docs:(README) 2024-12-05 01:55:31 +03:00
SMKRV de194e425c docs:(README) 2024-12-05 01:54:09 +03:00
SMKRV 95f3d6506e docs:(README) 2024-12-05 01:49:26 +03:00
SMKRV 3e877243b9 docs:(README) 2024-12-05 01:46:28 +03:00
SMKRV fd795c9e90 docs:(readme) 2024-12-05 00:36:08 +03:00
SMKRV 5f5dc041b9 docs: structure 2024-12-04 23:32:05 +03:00
SMKRV 3d3885d43d Update README.md 2024-12-04 23:28:14 +03:00
smkrvandGitHub b059744716 Update README.md 2024-12-04 23:23:46 +03:00
SMKRV f2a41aaa2c docs: logo 2024-12-04 20:13:08 +03:00
SMKRV 1fcf751d0d docs: logo 2024-12-04 19:24:30 +03:00
SMKRV a45c9407fd docs: logo 2024-12-04 19:19:40 +03:00
SMKRV 21fdf108cf docs: logo 2024-12-04 19:17:09 +03:00
SMKRV c7ec2b3ea4 docs: logo 2024-12-04 19:13:57 +03:00
SMKRV 6c4da6cea5 docs: logo 2024-12-04 19:12:44 +03:00
SMKRV 3029c5dd26 docs: logo 2024-12-04 19:12:21 +03:00
SMKRV 3e97028094 docs: logo 2024-12-04 19:11:54 +03:00
SMKRV 1194c87134 docs: logo 2024-12-04 17:51:40 +03:00
SMKRV e03b5315c2 logo update 2024-12-04 17:51:02 +03:00
SMKRV fad887492f docs: logo 2024-12-04 17:48:04 +03:00
SMKRV f26df29937 docs: logo 2024-12-04 17:47:12 +03:00
SMKRV 69b54a08ba logo update 2024-12-04 17:42:32 +03:00
SMKRV 7ce77eb18e docs: logo 2024-12-04 17:36:18 +03:00
SMKRV 1480669dc8 icons update 2024-12-04 17:34:19 +03:00
SMKRV f397bbffe7 Release 2.0.5-beta 2024-12-03 18:29:24 +03:00
SMKRV 5709bce1ae docs(license): Switch to CC BY-NC-SA 4.0 2024-11-29 17:13:08 +03:00
SMKRV d549a36c3a docs(license): Switch to CC BY-NC-SA 4.0 2024-11-29 17:11:06 +03:00
SMKRV e9ba480e95 docs: Update to beta 2024-11-29 16:57:32 +03:00
SMKRV 8ac7154399 docs: Update to beta 2024-11-29 16:54:41 +03:00
SMKRV f25f2db885 Release v2.0.4-beta 2024-11-29 16:45:43 +03:00
SMKRV 621732ae0a feat(localization): Expand multilingual support
- Added translations for:
  * Chinese (zh)
  * Serbian (sr)
  * Italian (it)
  * Hindi (hi)
  * Spanish (es)

- Fixed minor bugs
- Improved language coverage
2024-11-29 16:44:21 +03:00
SMKRV ed85c659be docs(license): Switch to CC BY-NC-SA 4.0 2024-11-29 16:38:41 +03:00
SMKRV f6dcd1c382 docs(license): Switch to CC BY-NC-SA 4.0 2024-11-29 16:27:11 +03:00
SMKRV 37c572fd98 docs(license): Switch to CC BY-NC-SA 4.0 2024-11-29 16:27:04 +03:00
SMKRV 1ff709d05c docs: screenshots 2024-11-29 01:27:01 +03:00
SMKRV 83726feae1 Screenshots added 2024-11-29 01:24:57 +03:00
SMKRV f24c87cc51 Screenshots 2024-11-29 01:23:43 +03:00
SMKRV 1c40968a94 misc 2024-11-29 00:57:39 +03:00
SMKRV c37ec7c1dd Release v2.0.3-beta 2024-11-29 00:54:18 +03:00
SMKRV ff3e600302 Misc 2024-11-29 00:21:21 +03:00
38 changed files with 4494 additions and 720 deletions
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name: Validate with hassfest name: Validate with hassfest
permissions:
contents: read
on: on:
push: push:
branches: branches:
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name: Validate name: Validate
permissions:
contents: read
on: on:
push: push:
-40
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# 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
Thumbs.db
*.psd
*.zip
*.txt
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# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
issue tracker.
All complaints will be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series
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**Consequence**: A warning with consequences for continued behavior. No
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### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
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with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see the FAQ at
https://www.contributor-covenant.org/faq. Translations are available at
https://www.contributor-covenant.org/translations.
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MIT License Attribution-NonCommercial-ShareAlike 4.0 International
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+390 -86
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<div align="center"> <div align="center">
![GitHub release](https://img.shields.io/github/release/smkrv/ha-text-ai.svg?style=flat-square) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai.svg?style=flat-square) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT) [![hacs_badge](https://img.shields.io/badge/HACS-Custom-41BDF5.svg?style=flat-square)](https://github.com/hacs/integration) ![/README.md](https://img.shields.io/badge/language-English-green?style=flat-square) ![/README_RU.md](https://img.shields.io/badge/language-Russian-green?style=flat-square) ![](https://img.shields.io/badge/language-Deutch-green?style=flat-square) ![GitHub release](https://img.shields.io/github/v/release/smkrv/ha-text-ai?style=flat-square) ![GitHub last commit](https://img.shields.io/github/last-commit/smkrv/ha-text-ai?style=flat-square) [![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg?style=flat-square)](https://creativecommons.org/licenses/by-nc-sa/4.0/) [![hacs_badge](https://img.shields.io/badge/HACS-Default-41BDF5.svg?style=flat-square)](https://github.com/hacs/integration)
![Deutsch](https://img.shields.io/badge/lang-DE-blue?style=flat-square) ![English](https://img.shields.io/badge/lang-EN-blue?style=flat-square) ![Español](https://img.shields.io/badge/lang-ES-blue?style=flat-square) ![हिन्दी](https://img.shields.io/badge/lang-HI-blue?style=flat-square) ![Italiano](https://img.shields.io/badge/lang-IT-blue?style=flat-square) ![Русский](https://img.shields.io/badge/lang-RU-blue?style=flat-square) ![Српски](https://img.shields.io/badge/lang-SR-blue?style=flat-square) ![中文](https://img.shields.io/badge/lang-ZH-blue?style=flat-square)
<img src="https://github.com/smkrv/ha-text-ai/blob/524849f6a945ec62c2cf6a6b7ecd9a28b37bf0fa/misc/icons/logo.jpg" alt="HA Text AI" height="160"/>
### Advanced AI Integration for Home Assistant with LLM multi-provider support <img src="https://github.com/smkrv/ha-text-ai/blob/main/custom_components/ha_text_ai/icons/logo%402x.png" alt="HA Text AI" style="width: 50%; max-width: 256px; max-height: 128px; aspect-ratio: 2/1; object-fit: contain;"/>
### Advanced AI Integration for [Home Assistant](https://www.home-assistant.io/) with LLM multi-provider support
</div> </div>
<p align="center"> <p align="center">
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. Transform your smart home experience with powerful AI assistance powered by multiple AI providers including OpenAI GPT, DeepSeek and Anthropic Claude models. Get intelligent responses, automate complex scenarios, and enhance your home automation with advanced natural language processing.
</p> </p>
--- ---
> [!IMPORTANT] > [!IMPORTANT]
> 🚧 ALPHA VERSION 🚧 > 🤝 Community Driven: for more details on the integration,
> Expect: potential bugs, frequent changes, incomplete features. > check out the discussion on the **[Home Assistant Community forum](https://community.home-assistant.io/t/ha-text-ai-transforming-home-automation-through-multi-llm-integration/799741)**
> 🤝 Community Driven
> >
> <a href="https://community.home-assistant.io/t/ha-text-ai-transforming-home-automation-with-multi-provider-language-models/799741"><img src="https://img.shields.io/badge/Community-blue?style=for-the-badge&logo=homeassistant&logoColor=white&color=03a9f4"/></a> > <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="210" height="auto"></a>
>
> [Screenshots](assets/images/screenshots/screenshot.jpg)
## 🌟 Features ## 🌟 Features
- 🧠 **Multi-Provider AI Integration**: - 🧠 **Multi-Provider AI Integration**: Support for OpenAI GPT, DeepSeek and Anthropic Claude models
- Support for OpenAI GPT models - 💬 **Advanced Language Processing**: Context-aware, multi-turn conversations
- Anthropic Claude integration - 📝 **Enhanced Memory Management**: Secure file-based history storage
- Custom API endpoints -**Performance Optimization**: Efficient token usage and smart rate limiting
- Flexible model selection - 🎯 **Advanced Customization**: Per-request model and parameter selection
- 🔒 **Enhanced Security**: Secure API key management and usage monitoring
- 🎨 **Improved User Experience**: Intuitive configuration and rich interfaces
- 🔄 **Automation Integration**: Event-driven responses and template compatibility
- 💬 **Advanced Language Processing**: <details>
- Context-aware responses <summary>📦 Detailed Feature Breakdown</summary>
- Multi-turn conversations
- Custom system instructions
- Natural conversation flow
- 📝 **Enhanced Memory Management**: ### 🧠 **Multi-Provider AI Integration**
- Persistent conversation history - Support for OpenAI GPT models
- Context-aware responses - Anthropic Claude integration
- Customizable history limits - DeepSeek integration
- Model-specific filtering - Custom API endpoints
- Flexible model selection
-**Performance Optimization**: ### 💬 **Advanced Language Processing**
- Efficient token usage - Context-aware responses
- Smart rate limiting - Multi-turn conversations
- Response caching - Custom system instructions
- Request interval control - Natural conversation flow
- 🎯 **Advanced Customization**: ### 📝 **Enhanced Memory Management**
- Per-request model selection - File-based conversation history storage
- Adjustable parameters - Automatic history rotation
- Custom system prompts - Configurable history size limits
- Temperature control - Secure storage in Home Assistant
- 🔒 **Enhanced Security**: ### ⚡ **Performance Optimization**
- Secure API key storage - Efficient token usage
- Rate limiting protection - Smart rate limiting
- Error handling - Response caching
- Usage monitoring - Request interval control
- 🎨 **Improved User Experience**: ### 🎯 **Advanced Customization**
- Intuitive configuration UI - Per-request model selection
- Detailed sensor attributes - Adjustable parameters
- Rich service interface - Custom system prompts
- Model selection UI - Temperature control
- 🔄 **Automation Integration**: ### 🔒 **Enhanced Security**
- Event-driven responses - Secure API key storage
- Conditional logic support - Rate limiting protection
- Template compatibility - Error handling
- Model-specific automation - 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
</details>
#### 🌐 Translations
| Code | Language | Status |
|------|----------|--------|
| 🇩🇪 de | Deutsch | Full |
| 🇬🇧 en | English | Primary |
| 🇪🇸 es | Español | Full |
| 🇮🇳 hi | हिन्दी | Full |
| 🇮🇹 it | Italiano | Full |
| 🇷🇺 ru | Русский | Full |
| 🇷🇸 sr | Српски | Full |
| 🇨🇳 zh | 中文 | Full |
## 📋 Prerequisites ## 📋 Prerequisites
- Home Assistant 2024.11 or later - Home Assistant 2024.12.0 or later (recommended for best compatibility)
- Active API key from: - Active API key from:
- OpenAI ([Get key](https://platform.openai.com/account/api-keys)) - OpenAI ([Get key](https://platform.openai.com/account/api-keys))
- Anthropic ([Get key](https://console.anthropic.com/)) - Anthropic ([Get key](https://console.anthropic.com/))
- DeepSeek ([Get key](https://platform.deepseek.com/api_keys))
- OpenRouter ([Get key](https://openrouter.ai/keys)) - OpenRouter ([Get key](https://openrouter.ai/keys))
- Google Gemini 🆕 ([Get key](https://ai.google.dev/gemini-api/docs/api-key)) thanks to ([@Azzedde](https://github.com/Azzedde))
- Any OpenAI-compatible API provider
- Python 3.9 or newer - Python 3.9 or newer
- Stable internet connection - Stable internet connection
### Configuration Options ## 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 ### 🔧 **Core Configuration Settings**
- 🌐 **API Provider**: OpenAI/Anthropic/DeepSeek/Gemini
- 🔑 **API Key**: Provider-specific authentication
- 🤖 **Model Selection**: Flexible, provider-specific models
- 🌡️ **Temperature**: Creativity control (0.0-2.0)
- 📏 **Max Tokens**: Response length limit (passed directly to the LLM API to control the maximum length of the response)
- ⏱️ **Request Interval**: API call throttling
- 💾 **History Size**: Number of messages to retain
- 🌍 **Custom API Endpoint**: Optional advanced configuration
### 🤖 **Recommended Models**
#### OpenAI Models
- **GPT-5** - The latest flagship model, best for complex reasoning
- **GPT-5 mini** - A cost-effective and fast model, suitable for most tasks
#### Anthropic Claude Models
- **Claude Opus 4.1** - The most capable model for handling complex tasks
- **Claude Sonnet 4** - Offers a balance between performance and cost
- **Claude Haiku 4** - The fastest and most economical option in the series
#### DeepSeek Models
- **DeepSeek-V3.1** - A general-purpose model for a wide range of tasks
- **DeepSeek-R1** - A specialized model focused on reasoning and coding
#### Google Gemini Models
- **Gemini 2.5 Pro & 2.5 Flash** - The newest and most advanced models available
- **Gemini 2.0 Pro & 2.0 Flash** - Previous generation models that are still powerful and efficient
<details>
<summary>🌐 Potentially Compatible Providers</summary>
#### Flexible Provider Ecosystem
The integration is designed to be flexible and may work with other providers offering OpenAI-compatible APIs: The integration is designed to be flexible and may work with other providers offering OpenAI-compatible APIs:
- Groq - Groq
- Together AI - Together AI
@@ -102,31 +161,41 @@ The integration is designed to be flexible and may work with other providers off
- Local AI servers (like Ollama) - Local AI servers (like Ollama)
- Custom OpenAI-compatible endpoints - Custom OpenAI-compatible endpoints
#### Additional Notes #### 🚨 Compatibility Notes
- Not all providers guarantee full compatibility - Not all providers guarantee full compatibility
- Performance may vary between providers - Performance may vary between providers
- Check individual provider's documentation - Check individual provider's documentation
- Ensure your API key has sufficient credits/quota - Ensure your API key has sufficient credits/quota
#### Provider Compatibility Requirements #### 🔍 Provider Compatibility Requirements
To be compatible, a provider should support: To be compatible, a provider should support:
- OpenAI-like REST API structure - OpenAI-like REST API structure
- JSON request/response format - JSON request/response format
- Standard authentication method - Standard authentication method
- Similar model parameter handling - Similar model parameter handling
</details>
## ⚡ Installation ## ⚡ Installation
### HACS Installation (Recommended) ### HACS Installation (Recommended)
>[!TIP]
>HA Text AI is available in the default HACS repository. You can install it directly through HACS or click the button below to open it there.
<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> <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 1. Open HACS in Home Assistant
2. Click on "Integrations" 2. Click on "Integrations"
3. Click "..." in top right corner 3. Search for "HA Text AI"
4. Select "Custom repositories" 4. Click "Download"
5. Add repository URL: `https://github.com/smkrv/ha-text-ai` 5. Restart Home Assistant
6. Choose "Integration" as category
7. Click "Download" **Alternative Method (Custom Repository):**
8. Restart Home Assistant If the integration is not found in the default repository:
1. Click "..." in top right corner of HACS
2. Select "Custom repositories"
3. Add repository URL: `https://github.com/smkrv/ha-text-ai`
4. Choose "Integration" as category
5. Click "Download"
### Manual Installation ### Manual Installation
1. Download the latest release 1. Download the latest release
@@ -142,7 +211,8 @@ To be compatible, a provider should support:
3. Search for "HA Text AI" 3. Search for "HA Text AI"
4. Follow the configuration steps 4. Follow the configuration steps
### Via YAML <details>
<summary>📦 Via YAML (Advanced)</summary>
### Platform Configuration (Global Settings) ### Platform Configuration (Global Settings)
@@ -150,7 +220,7 @@ To be compatible, a provider should support:
ha_text_ai: ha_text_ai:
api_provider: openai # Required api_provider: openai # Required
api_key: !secret ai_api_key # Required api_key: !secret ai_api_key # Required
model: gpt-4o-mini # Strongly recommended model: gpt-4o # Strongly recommended
temperature: 0.7 # Optional temperature: 0.7 # Optional
max_tokens: 1000 # Optional max_tokens: 1000 # Optional
request_interval: 1.0 # Optional request_interval: 1.0 # Optional
@@ -167,7 +237,7 @@ sensor:
- platform: ha_text_ai - platform: ha_text_ai
name: "My AI Assistant" # Required, unique identifier name: "My AI Assistant" # Required, unique identifier
api_provider: openai # Optional (inherits from platform) api_provider: openai # Optional (inherits from platform)
model: "gpt-4o-mini" # Optional model: "gpt-4o" # Optional
temperature: 0.7 # Optional temperature: 0.7 # Optional
max_tokens: 1000 # Optional max_tokens: 1000 # Optional
``` ```
@@ -178,14 +248,16 @@ sensor:
| Parameter | Type | Required | Default | Description | | Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------| |-----------|------|----------|---------|-------------|
| `api_provider` | String | ✅ | - | AI service provider (openai, anthropic) | | `api_provider` | String | ✅ | - | AI service provider (openai, anthropic, deepseek, gemini) |
| `api_key` | String | ✅ | - | Authentication key for AI service | | `api_key` | String | ✅ | - | Authentication key for AI service |
| `model` | String | ⚠️ | Provider default | Strongly recommended: Specific AI model to use. If not specified, the provider's default model will be used | | `model` | String | ⚠️ | gpt-4o-mini | Strongly recommended: Specific AI model to use. Default varies by provider |
| `temperature` | Float | ❌ | 0.7 | Response creativity level (0.0-2.0) | | `temperature` | Float | ❌ | 0.1 | Response creativity level (0.0-2.0) |
| `max_tokens` | Integer | ❌ | 1000 | Maximum response length | | `max_tokens` | Integer | ❌ | 1000 | Maximum response length |
| `request_interval` | Float | ❌ | 1.0 | Delay between API requests | | `request_interval` | Float | ❌ | 1.0 | Delay between API requests |
| `api_endpoint` | URL | ⚠️ | Provider default | Custom API endpoint | | `api_endpoint` | URL | ⚠️ | Provider default | Custom API endpoint |
| `system_prompt` | String | ❌ | - | Default context for AI interactions | | `system_prompt` | String | ❌ | - | Default context for AI interactions |
| `max_history_size` | Integer | ❌ | 50 | Maximum number of conversation entries to store |
| `context_messages` | Integer | ❌ | 5 | Number of previous messages to include in context (1-20) |
#### Sensor Configuration #### Sensor Configuration
@@ -194,28 +266,58 @@ sensor:
| `platform` | String | ✅ | - | Must be `ha_text_ai` | | `platform` | String | ✅ | - | Must be `ha_text_ai` |
| `name` | String | ✅ | - | Unique sensor identifier | | `name` | String | ✅ | - | Unique sensor identifier |
| `api_provider` | String | ❌ | Platform setting | Override global provider | | `api_provider` | String | ❌ | Platform setting | Override global provider |
| `model` | String | ⚠️ | Platform setting | Recommended: Override global model. If not specified, uses platform or provider default | | `model` | String | ⚠️ | Provider default | Recommended: Override global model (gpt-4o-mini, deepseek-chat, gemini-2.0-flash) |
| `temperature` | Float | ❌ | Platform setting | Override global temperature | | `temperature` | Float | ❌ | 0.1 | Override global temperature |
| `max_tokens` | Integer | ❌ | Platform setting | Override global max tokens | | `max_tokens` | Integer | ❌ | 1000 | Override global max tokens |
</details>
## 🛠️ Available Services ## 🛠️ Available Services
### 🔄 Response Variables (New!)
**HA Text AI now supports response variables** - a powerful feature that returns AI responses directly from service calls, eliminating the need for separate text sensors and the 255-character limitation!
#### ✨ Key Benefits:
- **Unlimited response length** - No more 255-character truncation
- **Direct data access** - Get responses immediately in automations
- **Race condition prevention** - Eliminates conflicts in parallel automations
- **Simplified workflows** - No need to read from sensors
### ask_question ### ask_question
```yaml ```yaml
service: ha_text_ai.ask_question service: ha_text_ai.ask_question
data: data:
question: "What's the optimal temperature for sleeping?" question: "What's the optimal temperature for sleeping?"
model: "claude-3-sonnet" # optional model: "claude-3.5-sonnet" # optional
temperature: 0.5 # optional temperature: 0.5 # optional
max_tokens: 500 # optional max_tokens: 500 # optional
context_messages: 10 #optional, number of previous messages to include in context, default: 5 context_messages: 10 #optional, number of previous messages to include in context, default: 5
system_prompt: "You are a sleep optimization expert" # optional system_prompt: "You are a sleep optimization expert" # optional
instance: sensor.ha_text_ai_gpt
response_variable: ai_response # NEW! Store response data directly
```
#### 📊 Response Data Structure:
```yaml
# The service returns structured data:
response_text: "The optimal sleeping temperature is 65-68°F (18-20°C)..."
tokens_used: 150
prompt_tokens: 50
completion_tokens: 100
model_used: "claude-3.5-sonnet"
instance: "sensor.ha_text_ai_gpt"
question: "What's the optimal temperature for sleeping?"
timestamp: "2025-02-09T16:57:00.000Z"
success: true
# error: "Error message" (only present if success: false)
``` ```
### set_system_prompt ### set_system_prompt
```yaml ```yaml
service: ha_text_ai.set_system_prompt service: ha_text_ai.set_system_prompt
data: data:
instance: sensor.ha_text_ai_gpt
prompt: | prompt: |
You are a home automation expert focused on: You are a home automation expert focused on:
1. Energy efficiency 1. Energy efficiency
@@ -227,14 +329,163 @@ data:
### clear_history ### clear_history
```yaml ```yaml
service: ha_text_ai.clear_history service: ha_text_ai.clear_history
data:
instance: sensor.ha_text_ai_gpt
``` ```
### get_history ### get_history
```yaml ```yaml
service: ha_text_ai.get_history service: ha_text_ai.get_history
data: data:
limit: 5 # optional limit: 5 # optional, number of conversations to return (1-100)
filter_model: "gpt-4o" # optional filter_model: "gpt-4o" # optional, filter by specific AI model
start_date: "2025-02-01" # optional, filter conversations from this date
include_metadata: false # optional, include tokens, response time, etc.
sort_order: "newest" # optional, sort order: "newest" or "oldest"
instance: sensor.ha_text_ai_gpt
```
## 🚀 Advanced Automation Examples with Response Variables
### Example 1: Smart Home Advice with Direct Response
```yaml
automation:
- alias: "Get AI Home Advice"
trigger:
- platform: state
entity_id: input_button.ask_ai_advice
action:
- service: ha_text_ai.ask_question
data:
question: "What's the best way to optimize energy usage in my home?"
instance: sensor.ha_text_ai_gpt
response_variable: ai_advice
- service: notify.mobile_app
data:
title: "🏠 Smart Home Tip"
message: |
{{ ai_advice.response_text }}
📊 Tokens used: {{ ai_advice.tokens_used }}
🤖 Model: {{ ai_advice.model_used }}
```
### Example 2: Weather-Based AI Recommendations
```yaml
automation:
- alias: "Weather-Based AI Suggestions"
trigger:
- platform: numeric_state
entity_id: sensor.outdoor_temperature
below: 0
action:
- service: ha_text_ai.ask_question
data:
question: |
The outdoor temperature is {{ states('sensor.outdoor_temperature') }}°C.
What should I do to prepare my home for freezing weather?
system_prompt: "You are a home maintenance expert. Provide practical, actionable advice."
instance: sensor.ha_text_ai_gpt
response_variable: winter_advice
- if:
- condition: template
value_template: "{{ winter_advice.success }}"
then:
- service: persistent_notification.create
data:
title: "❄️ Winter Preparation Advice"
message: |
{{ winter_advice.response_text }}
Generated at: {{ winter_advice.timestamp }}
else:
- service: persistent_notification.create
data:
title: "⚠️ AI Service Error"
message: "Failed to get winter advice: {{ winter_advice.error }}"
```
### Example 3: Multi-Step AI Workflow
```yaml
automation:
- alias: "Multi-Step AI Analysis"
trigger:
- platform: state
entity_id: input_button.analyze_home_status
action:
# Step 1: Get current status analysis
- service: ha_text_ai.ask_question
data:
question: |
Current home status:
- Temperature: {{ states('sensor.indoor_temperature') }}°C
- Humidity: {{ states('sensor.indoor_humidity') }}%
- Energy usage: {{ states('sensor.power_consumption') }}W
Analyze this data and provide insights.
instance: sensor.ha_text_ai_gpt
response_variable: status_analysis
# Step 2: Get recommendations based on analysis
- service: ha_text_ai.ask_question
data:
question: |
Based on this analysis: "{{ status_analysis.response_text[:500] }}"
Provide 3 specific actionable recommendations for improvement.
context_messages: 2 # Include previous conversation
instance: sensor.ha_text_ai_gpt
response_variable: recommendations
# Step 3: Send comprehensive report
- service: notify.telegram
data:
title: "🏠 Home Analysis Report"
message: |
**Analysis:**
{{ status_analysis.response_text }}
**Recommendations:**
{{ recommendations.response_text }}
**Report Details:**
- Total tokens used: {{ status_analysis.tokens_used + recommendations.tokens_used }}
- Analysis model: {{ status_analysis.model_used }}
- Generated: {{ recommendations.timestamp }}
```
### 💡 Migration from Sensors to Response Variables
#### Old Method (Limited):
```yaml
# ❌ Old way - limited to 255 characters, race conditions
automation:
- alias: "Old AI Response Method"
action:
- service: ha_text_ai.ask_question
data:
question: "Long question here..."
instance: sensor.ha_text_ai_gpt
- delay: "00:00:05" # Wait for sensor update
- service: notify.mobile
data:
message: "{{ state_attr('sensor.ha_text_ai_gpt', 'response')[:255] }}..." # Truncated!
```
#### New Method (Unlimited):
```yaml
# ✅ New way - unlimited length, immediate access, no race conditions
automation:
- alias: "New AI Response Method"
action:
- service: ha_text_ai.ask_question
data:
question: "Long question here..."
instance: sensor.ha_text_ai_gpt
response_variable: ai_response # Direct access!
- service: notify.mobile
data:
message: "{{ ai_response.response_text }}" # Full response, no truncation!
``` ```
### 🏷️ HA Text AI Sensor Naming Convention ### 🏷️ HA Text AI Sensor Naming Convention
@@ -243,7 +494,7 @@ data:
- Only lowercase letters (a-z) - Only lowercase letters (a-z)
- Numbers (0-9) - Numbers (0-9)
- Underscore (_) - Underscore (_)
- Maximum length: 50 characters (including `ha_text_ai_` prefix (14 characters) - Maximum length: 50 characters (including `ha_text_ai_`)
#### Sensor Name Structure #### Sensor Name Structure
```yaml ```yaml
@@ -254,7 +505,7 @@ sensor.ha_text_ai_YOUR_UNIQUE_SUFFIX
# Examples: # Examples:
sensor.ha_text_ai_gpt # GPT-based sensor sensor.ha_text_ai_gpt # GPT-based sensor
sensor.ha_text_ai_claude # Claude-based sensor sensor.ha_text_ai_claude # Claude-based sensor
sensor.ha_text_ai_gpt # Custom suffix sensor.ha_text_ai_abc # Custom suffix
``` ```
#### Response Retrieval #### Response Retrieval
@@ -271,6 +522,7 @@ automation:
- service: ha_text_ai.ask_question - service: ha_text_ai.ask_question
data: data:
question: "Home automation advice" question: "Home automation advice"
instance: sensor.ha_text_ai_gpt
- service: notify.mobile - service: notify.mobile
data: data:
message: > message: >
@@ -287,6 +539,16 @@ automation:
### 🔍 HA Text AI Sensor Attributes ### 🔍 HA Text AI Sensor Attributes
- 🤖 **Model and Provider Information**: Tracking current AI model and service provider
- 🚦 **System Status**: Real-time API and processing readiness
- 📊 **Performance Metrics**: Request success rates and response times
- 💬 **Conversation Tracking**: Token usage and interaction history are estimated using a heuristic method based on word count and specific word characteristics, which may differ from actual token usage.
- 🕒 **Last Interaction Details**: Recent query and response tracking
- ❤️ **System Health**: Error monitoring and service uptime
<details>
<summary>📦 Detailed Sensor Attributes</summary>
#### Model and Provider Information #### Model and Provider Information
```yaml ```yaml
# Name of the AI model currently in use (e.g., latest version of GPT) # Name of the AI model currently in use (e.g., latest version of GPT)
@@ -342,6 +604,12 @@ automation:
# Tokens used in the AI's generated responses # Tokens used in the AI's generated responses
{{ state_attr('sensor.ha_text_ai_gpt', 'Completion tokens') }} # 0 {{ state_attr('sensor.ha_text_ai_gpt', 'Completion tokens') }} # 0
# Number of entries in current history file
{{ state_attr('sensor.ha_text_ai_gpt', 'History size') }} # 0
# Last few conversation entries (limited to 1 for performance)
{{ state_attr('sensor.ha_text_ai_gpt', 'conversation_history') }} # [...]
``` ```
#### Last Interaction Details #### Last Interaction Details
@@ -368,19 +636,27 @@ automation:
{{ state_attr('sensor.ha_text_ai_gpt', 'Uptime') }} # 547,58 {{ state_attr('sensor.ha_text_ai_gpt', 'Uptime') }} # 547,58
``` ```
### History Storage
Conversation history stored in `.storage/ha_text_ai_history/` directory:
- Each instance has its own history file (JSON)
- Files are automatically rotated when size limit is reached
- Archived history files are timestamped
- Default maximum file size: 1MB
### 💡 Pro Tips ### 💡 Pro Tips
- Always check attribute existence - Always check attribute existence
- Use these attributes for monitoring and automation - Use these attributes for monitoring and automation
- Some values might be 0 or empty initially - Some values might be 0 or empty initially
</details>
## 📘 FAQ ## 📘 FAQ
**Q: Which AI providers are supported?** **Q: Which AI providers are supported?**
A: Currently OpenAI (GPT models) and Anthropic (Claude models) are supported, with more providers planned. A: OpenAI (GPT models), Anthropic (Claude models), DeepSeek, Google Gemini, and OpenRouter are officially supported, with many other OpenAI-compatible providers working as well.
**Q: How can I reduce API costs?** **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. A: Use gpt-4o-mini or claude-3.5-haiku for most queries, implement caching, and optimize token usage.
**Q: Are there limitations on the number of requests?** **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. A: Depends on your API provider's plan. We recommend monitoring usage and implementing request throttling via `request_interval` configuration.
@@ -391,8 +667,11 @@ A: Yes, you can configure custom endpoints and use any compatible model by speci
**Q: How do I switch between different AI providers?** **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. 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?** **Q: What are the token limits for different models?**
A: Use GPT-3.5-Turbo for most queries, implement caching, and optimize token usage. A: Token limits vary by provider and model. OpenAI's gpt-4o supports up to 128K tokens, Claude 3.5 Sonnet supports up to 200K tokens, while smaller models typically have 8K-32K limits. Check your provider's documentation for specific limits.
**Q: How do I monitor token usage?**
A: Use the sensor attributes like `Total tokens`, `Prompt tokens`, and `Completion tokens` to track usage. You can also create automations to alert you when usage exceeds certain thresholds.
**Q: Is my data secure?** **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. 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.
@@ -400,6 +679,15 @@ A: Yes, your data is secure. The system operates entirely on your local machine,
**Q: How do context messages work?** **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. 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.
**Q: Where is conversation history stored?**
A: History is stored in files under the `.storage/ha_text_ai_history/` directory, with automatic rotation and size management.
**Q: Can I access old conversation history?**
A: Yes, archived history files are stored with timestamps and can be accessed manually if needed.
**Q: How much history is kept?**
A: By default, up to 100 conversations are stored, but this can be configured. Files are automatically rotated when they reach 1MB.
## 🤝 Contributing ## 🤝 Contributing
Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md). Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
@@ -410,9 +698,23 @@ Contributions welcome! Please read our [Contributing Guide](CONTRIBUTING.md).
4. Push branch (`git push origin feature/Enhancement`) 4. Push branch (`git push origin feature/Enhancement`)
5. Open Pull Request 5. Open Pull Request
## Legal Disclaimer and Limitation of Liability
### Software Disclaimer
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE 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.
## 📝 License ## 📝 License
MIT License - see [LICENSE](LICENSE) for details. Author: SMKRV
[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) - see [LICENSE](LICENSE) for details.
## 💡 Support the Project ## 💡 Support the Project
@@ -432,10 +734,12 @@ If you want to say thanks financially, you can send a small token of appreciatio
--- ---
<div align="center"><img src="https://github.com/smkrv/ha-text-ai/blob/2aaf3405759eb2d97624834594e24ace896131df/assets/images/icons/footer_icon.png" alt="HA Text AI" style="width: 128px; height: auto;"/></div>
<div align="center"> <div align="center">
Made with ❤️ and Claude 3.5 Sonnet for the Home Assistant Community Made with ❤️ for the Home Assistant Community
[Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues) [Report Bug](https://github.com/smkrv/ha-text-ai/issues) · [Request Feature](https://github.com/smkrv/ha-text-ai/issues)
</div> </div>
+148
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@@ -0,0 +1,148 @@
# Using response_variable with HA Text AI
After updating the HA Text AI integration, it now supports using the `response_variable` parameter in Home Assistant scripts and automations.
## What Changed
- Added response schema support in the `ha_text_ai.ask_question` service
- Service is now correctly registered with `supports_response=True` flag
- You can now use `response_variable` to capture AI response in a variable
## Example Usage in Script
```yaml
action: ha_text_ai.ask_question
data:
context_messages: 0
temperature: 0.7
max_tokens: 1000
instance: sensor.ha_text_ai_gemini
question: "What time is it?"
response_variable: ai_response
```
## Example Usage in Automation
```yaml
alias: "Get AI Response"
trigger:
- platform: state
entity_id: input_boolean.ask_ai
to: "on"
action:
- action: ha_text_ai.ask_question
data:
instance: sensor.ha_text_ai_gemini
question: "What's the current weather?"
temperature: 0.7
max_tokens: 500
response_variable: weather_response
- action: notify.persistent_notification
data:
title: "AI Response"
message: "{{ weather_response.response_text }}"
```
## Available Fields in response_variable
When you use `response_variable`, you will receive an object with the following fields:
- `response_text` (string) - The AI response text
- `tokens_used` (integer) - Total number of tokens used
- `prompt_tokens` (integer) - Number of tokens in the prompt
- `completion_tokens` (integer) - Number of tokens in the completion
- `model_used` (string) - The AI model that was used for the response
- `instance` (string) - The instance name that was used
- `question` (string) - The original question that was asked
- `timestamp` (string) - ISO timestamp when the response was generated
- `success` (boolean) - Whether the request was successful
- `error` (string) - Error message if the request failed
## Example Using Response Fields
```yaml
action:
- action: ha_text_ai.ask_question
data:
instance: sensor.ha_text_ai_gemini
question: "Tell me a joke"
response_variable: joke_response
- condition: template
value_template: "{{ joke_response.success }}"
- action: input_text.set_value
target:
entity_id: input_text.last_ai_response
data:
value: "{{ joke_response.response_text }}"
- action: input_number.set_value
target:
entity_id: input_number.tokens_used
data:
value: "{{ joke_response.tokens_used }}"
```
## Error Handling
```yaml
action:
- action: ha_text_ai.ask_question
data:
instance: sensor.ha_text_ai_gemini
question: "Test question"
response_variable: ai_result
- choose:
- conditions:
- condition: template
value_template: "{{ ai_result.success }}"
sequence:
- action: notify.mobile_app_phone
data:
title: "AI Response"
message: "{{ ai_result.response_text }}"
- conditions:
- condition: template
value_template: "{{ not ai_result.success }}"
sequence:
- action: notify.mobile_app_phone
data:
title: "AI Error"
message: "Error: {{ ai_result.error }}"
```
## Migration from Old Approach
**Old method (without response_variable):**
```yaml
# Ask question
- action: ha_text_ai.ask_question
data:
instance: sensor.ha_text_ai_gemini
question: "Hello!"
# Wait and read response from sensor
- delay: 00:00:05
- action: notify.mobile_app_phone
data:
message: "{{ states('sensor.ha_text_ai_gemini') }}"
```
**New method (with response_variable):**
```yaml
# Ask question and get response immediately
- action: ha_text_ai.ask_question
data:
instance: sensor.ha_text_ai_gemini
question: "Hello!"
response_variable: greeting_response
- action: notify.mobile_app_phone
data:
message: "{{ greeting_response.response_text }}"
```
The new approach is more reliable as it doesn't require waiting and reading from the sensor.
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@@ -1,11 +1,19 @@
"""The HA Text AI integration.""" """
The HA Text AI integration.
@license: CC BY-NC-SA 4.0 International
@author: SMKRV
@github: https://github.com/smkrv/ha-text-ai
@source: https://github.com/smkrv/ha-text-ai
"""
from __future__ import annotations from __future__ import annotations
import logging import logging
import os import os
import shutil import shutil
import hashlib
from datetime import datetime, timedelta from datetime import datetime, timedelta
from typing import Any, Dict from typing import Any, Dict, TypeVar
import voluptuous as vol import voluptuous as vol
from async_timeout import timeout from async_timeout import timeout
@@ -27,29 +35,38 @@ from .const import (
CONF_MAX_TOKENS, CONF_MAX_TOKENS,
CONF_API_ENDPOINT, CONF_API_ENDPOINT,
CONF_REQUEST_INTERVAL, CONF_REQUEST_INTERVAL,
CONF_API_TIMEOUT,
CONF_API_PROVIDER, CONF_API_PROVIDER,
CONF_CONTEXT_MESSAGES, CONF_CONTEXT_MESSAGES,
API_PROVIDER_OPENAI, API_PROVIDER_OPENAI,
API_PROVIDER_ANTHROPIC, API_PROVIDER_ANTHROPIC,
API_PROVIDER_DEEPSEEK,
API_PROVIDER_GEMINI,
DEFAULT_MODEL, DEFAULT_MODEL,
DEFAULT_DEEPSEEK_MODEL,
DEFAULT_GEMINI_MODEL,
DEFAULT_TEMPERATURE, DEFAULT_TEMPERATURE,
DEFAULT_MAX_TOKENS, DEFAULT_MAX_TOKENS,
DEFAULT_OPENAI_ENDPOINT, DEFAULT_OPENAI_ENDPOINT,
DEFAULT_ANTHROPIC_ENDPOINT, DEFAULT_ANTHROPIC_ENDPOINT,
DEFAULT_DEEPSEEK_ENDPOINT,
DEFAULT_GEMINI_ENDPOINT,
DEFAULT_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL,
DEFAULT_API_TIMEOUT,
DEFAULT_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES,
API_TIMEOUT,
SERVICE_ASK_QUESTION, SERVICE_ASK_QUESTION,
SERVICE_CLEAR_HISTORY, SERVICE_CLEAR_HISTORY,
SERVICE_GET_HISTORY, SERVICE_GET_HISTORY,
SERVICE_SET_SYSTEM_PROMPT, SERVICE_SET_SYSTEM_PROMPT,
DEFAULT_MAX_HISTORY, DEFAULT_MAX_HISTORY,
CONF_MAX_HISTORY_SIZE, CONF_MAX_HISTORY_SIZE,
ICONS_SUBDOMAIN,
) )
_LOGGER = logging.getLogger(__name__) _LOGGER = logging.getLogger(__name__)
CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN) CONFIG_SCHEMA = cv.config_entry_only_config_schema(DOMAIN)
ConfigType = TypeVar("ConfigType", bound=Dict[str, Any])
SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({ SERVICE_SCHEMA_ASK_QUESTION = vol.Schema({
vol.Required("instance"): cv.string, vol.Required("instance"): cv.string,
@@ -70,6 +87,9 @@ SERVICE_SCHEMA_GET_HISTORY = vol.Schema({
vol.Required("instance"): cv.string, vol.Required("instance"): cv.string,
vol.Optional("limit"): cv.positive_int, vol.Optional("limit"): cv.positive_int,
vol.Optional("filter_model"): cv.string, vol.Optional("filter_model"): cv.string,
vol.Optional("start_date"): cv.string,
vol.Optional("include_metadata"): cv.boolean,
vol.Optional("sort_order"): vol.In(["newest", "oldest"]),
}) })
def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAICoordinator: def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAICoordinator:
@@ -83,25 +103,24 @@ def get_coordinator_by_instance(hass: HomeAssistant, instance: str) -> HATextAIC
raise HomeAssistantError(f"Instance {instance} not found") raise HomeAssistantError(f"Instance {instance} not found")
async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool: def get_file_hash(file_path: str) -> str:
"""Set up the HA Text AI component.""" """Calculate SHA256 hash of file."""
sha256_hash = hashlib.sha256()
with open(file_path, "rb") as f:
for byte_block in iter(lambda: f.read(4096), b""):
sha256_hash.update(byte_block)
return sha256_hash.hexdigest()
async def async_setup(hass: HomeAssistant, config: ConfigType) -> bool:
"""Set up the Home Assistant Text AI component."""
# Initialize domain data storage
hass.data.setdefault(DOMAIN, {}) hass.data.setdefault(DOMAIN, {})
try: async def async_ask_question(call: ServiceCall) -> dict:
source = os.path.join(os.path.dirname(__file__), 'icons', 'icon.svg') """Handle ask_question service with response data."""
dest_dir = os.path.join(hass.config.path('www'), 'icons')
os.makedirs(dest_dir, exist_ok=True)
dest = os.path.join(dest_dir, 'icon.png')
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 ask_question service."""
try: try:
coordinator = get_coordinator_by_instance(hass, call.data["instance"]) coordinator = get_coordinator_by_instance(hass, call.data["instance"])
await coordinator.async_ask_question( response = await coordinator.async_ask_question(
question=call.data["question"], question=call.data["question"],
model=call.data.get("model"), model=call.data.get("model"),
temperature=call.data.get("temperature"), temperature=call.data.get("temperature"),
@@ -109,9 +128,34 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
system_prompt=call.data.get("system_prompt"), system_prompt=call.data.get("system_prompt"),
context_messages=call.data.get("context_messages"), context_messages=call.data.get("context_messages"),
) )
# Return structured response data
return {
"response_text": response.get("content", ""),
"tokens_used": response.get("tokens", {}).get("total", 0),
"prompt_tokens": response.get("tokens", {}).get("prompt", 0),
"completion_tokens": response.get("tokens", {}).get("completion", 0),
"model_used": response.get("model", call.data.get("model", coordinator.model)),
"instance": call.data["instance"],
"question": call.data["question"],
"timestamp": response.get("timestamp"),
"success": True
}
except Exception as err: except Exception as err:
_LOGGER.error("Error asking question: %s", str(err)) _LOGGER.error("Error asking question: %s", str(err))
raise HomeAssistantError(f"Failed to process question: {str(err)}") # Return error response
return {
"response_text": "",
"tokens_used": 0,
"prompt_tokens": 0,
"completion_tokens": 0,
"model_used": call.data.get("model", ""),
"instance": call.data["instance"],
"question": call.data["question"],
"timestamp": datetime.now().isoformat(),
"success": False,
"error": str(err)
}
async def async_clear_history(call: ServiceCall) -> None: async def async_clear_history(call: ServiceCall) -> None:
"""Handle clear_history service.""" """Handle clear_history service."""
@@ -128,7 +172,10 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
coordinator = get_coordinator_by_instance(hass, call.data["instance"]) coordinator = get_coordinator_by_instance(hass, call.data["instance"])
return await coordinator.async_get_history( return await coordinator.async_get_history(
limit=call.data.get("limit"), limit=call.data.get("limit"),
filter_model=call.data.get("filter_model") filter_model=call.data.get("filter_model"),
start_date=call.data.get("start_date"),
include_metadata=call.data.get("include_metadata", False),
sort_order=call.data.get("sort_order", "newest")
) )
except Exception as err: except Exception as err:
_LOGGER.error("Error getting history: %s", str(err)) _LOGGER.error("Error getting history: %s", str(err))
@@ -143,11 +190,13 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
_LOGGER.error("Error setting system prompt: %s", str(err)) _LOGGER.error("Error setting system prompt: %s", str(err))
raise HomeAssistantError(f"Failed to set system prompt: {str(err)}") raise HomeAssistantError(f"Failed to set system prompt: {str(err)}")
# Register services
hass.services.async_register( hass.services.async_register(
DOMAIN, DOMAIN,
SERVICE_ASK_QUESTION, SERVICE_ASK_QUESTION,
async_ask_question, async_ask_question,
schema=SERVICE_SCHEMA_ASK_QUESTION schema=SERVICE_SCHEMA_ASK_QUESTION,
supports_response=True
) )
hass.services.async_register( hass.services.async_register(
@@ -171,22 +220,79 @@ async def async_setup(hass: HomeAssistant, config: Dict[str, Any]) -> bool:
schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT schema=SERVICE_SCHEMA_SET_SYSTEM_PROMPT
) )
# Handle icons
try:
source_icon_path = os.path.join(
os.path.dirname(__file__),
ICONS_SUBDOMAIN,
'icon@2x.png'
)
destination_directory = os.path.join(
hass.config.path('www'),
DOMAIN,
ICONS_SUBDOMAIN
)
destination_icon_path = os.path.join(
destination_directory,
'icon.png'
)
if not os.path.exists(source_icon_path):
_LOGGER.error("Source icon not found: %s", source_icon_path)
return True
def create_directory():
os.makedirs(destination_directory, exist_ok=True)
await hass.async_add_executor_job(create_directory)
should_copy = True
if os.path.exists(destination_icon_path):
source_hash = await hass.async_add_executor_job(get_file_hash, source_icon_path)
dest_hash = await hass.async_add_executor_job(get_file_hash, destination_icon_path)
should_copy = source_hash != dest_hash
if should_copy:
def copy_file():
shutil.copyfile(source_icon_path, destination_icon_path)
await hass.async_add_executor_job(copy_file)
_LOGGER.debug("Icon updated: %s", destination_icon_path)
except PermissionError as e:
_LOGGER.error("Permission denied when managing icons: %s", str(e))
except Exception as e:
_LOGGER.error("Failed to manage icons: %s", str(e))
return True return True
async def async_check_api(session, endpoint: str, headers: dict, provider: str) -> bool: async def async_check_api(session, endpoint: str, headers: dict, provider: str, api_timeout: int = DEFAULT_API_TIMEOUT) -> bool:
"""Check API availability for different providers.""" """Check API availability for different providers."""
try: try:
if provider == API_PROVIDER_ANTHROPIC: if provider == API_PROVIDER_GEMINI:
# Gemini API does not support GET /models for validation, just check key presence
if headers.get("Authorization", "").replace("Bearer ", ""):
return True
else:
_LOGGER.error("Gemini API key is missing or empty")
return False
elif provider == API_PROVIDER_ANTHROPIC:
check_url = f"{endpoint}/v1/models" check_url = f"{endpoint}/v1/models"
elif provider == API_PROVIDER_DEEPSEEK:
check_url = f"{endpoint}/models"
else: # OpenAI else: # OpenAI
check_url = f"{endpoint}/models" check_url = f"{endpoint}/models"
async with timeout(API_TIMEOUT): async with timeout(api_timeout):
async with session.get(check_url, headers=headers) as response: async with session.get(check_url, headers=headers) as response:
if response.status in [200, 404]: if response.status in [200, 404]:
return True return True
elif response.status == 401: elif response.status == 401:
raise ConfigEntryNotReady("Invalid API key") _LOGGER.error("Invalid API key")
return False
elif response.status == 429: elif response.status == 429:
_LOGGER.warning("Rate limit exceeded during API check") _LOGGER.warning("Rate limit exceeded during API check")
return False return False
@@ -206,22 +312,24 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
_LOGGER.error("API provider not specified") _LOGGER.error("API provider not specified")
raise ConfigEntryNotReady("API provider is required") raise ConfigEntryNotReady("API provider is required")
# Get configuration # Get configuration (merge data with options to apply any runtime changes)
config = {**entry.data, **entry.options}
session = aiohttp_client.async_get_clientsession(hass) session = aiohttp_client.async_get_clientsession(hass)
api_provider = entry.data.get(CONF_API_PROVIDER) api_provider = config.get(CONF_API_PROVIDER)
model = entry.data.get(CONF_MODEL, DEFAULT_MODEL) model = config.get(CONF_MODEL, DEFAULT_MODEL)
endpoint = entry.data.get( endpoint = config.get(
CONF_API_ENDPOINT, CONF_API_ENDPOINT,
DEFAULT_OPENAI_ENDPOINT if api_provider == API_PROVIDER_OPENAI DEFAULT_OPENAI_ENDPOINT if api_provider == API_PROVIDER_OPENAI
else DEFAULT_ANTHROPIC_ENDPOINT else DEFAULT_ANTHROPIC_ENDPOINT
).rstrip('/') ).rstrip('/')
api_key = entry.data[CONF_API_KEY] api_key = entry.data[CONF_API_KEY] # API key stays in data, not in options
instance_name = entry.data.get(CONF_NAME, entry.entry_id) instance_name = entry.data.get(CONF_NAME, entry.entry_id)
request_interval = entry.data.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL) request_interval = config.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)
max_tokens = entry.data.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS) api_timeout = config.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT)
temperature = entry.data.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE) max_tokens = config.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS)
max_history_size = entry.data.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY) temperature = config.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)
context_messages = entry.data.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES) max_history_size = config.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
context_messages = config.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
is_anthropic = api_provider == API_PROVIDER_ANTHROPIC is_anthropic = api_provider == API_PROVIDER_ANTHROPIC
headers = { headers = {
@@ -235,7 +343,7 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
else: else:
headers["Authorization"] = f"Bearer {api_key}" headers["Authorization"] = f"Bearer {api_key}"
if not await async_check_api(session, endpoint, headers, api_provider): if not await async_check_api(session, endpoint, headers, api_provider, api_timeout):
raise ConfigEntryNotReady("API connection failed") raise ConfigEntryNotReady("API connection failed")
_LOGGER.debug("Creating API client for %s with endpoint %s", api_provider, endpoint) _LOGGER.debug("Creating API client for %s with endpoint %s", api_provider, endpoint)
@@ -246,6 +354,7 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
headers=headers, headers=headers,
api_provider=api_provider, api_provider=api_provider,
model=model, model=model,
api_timeout=api_timeout,
) )
coordinator = HATextAICoordinator( coordinator = HATextAICoordinator(
@@ -259,6 +368,7 @@ async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:
max_history_size=max_history_size, max_history_size=max_history_size,
context_messages=context_messages, context_messages=context_messages,
is_anthropic=is_anthropic, is_anthropic=is_anthropic,
api_timeout=api_timeout,
) )
_LOGGER.debug(f"Created coordinator for {instance_name}") _LOGGER.debug(f"Created coordinator for {instance_name}")
+222 -17
View File
@@ -1,16 +1,27 @@
"""API Client for HA Text AI.""" """
API Client for HA Text AI.
@license: CC BY-NC-SA 4.0 International
@author: SMKRV
@github: https://github.com/smkrv/ha-text-ai
@source: https://github.com/smkrv/ha-text-ai
"""
import logging import logging
import asyncio import asyncio
from typing import Any, Dict, List, Optional from typing import Any, Dict, List, Optional
from aiohttp import ClientSession, ClientTimeout from aiohttp import ClientSession, ClientTimeout
from async_timeout import timeout from async_timeout import timeout
from datetime import datetime, timedelta
from homeassistant.core import HomeAssistant from homeassistant.core import HomeAssistant
from homeassistant.exceptions import HomeAssistantError from homeassistant.exceptions import HomeAssistantError
from .const import ( from .const import (
API_TIMEOUT, DEFAULT_API_TIMEOUT,
API_RETRY_COUNT, API_RETRY_COUNT,
API_PROVIDER_ANTHROPIC, API_PROVIDER_ANTHROPIC,
API_PROVIDER_DEEPSEEK,
API_PROVIDER_OPENAI,
API_PROVIDER_GEMINI,
MIN_TEMPERATURE, MIN_TEMPERATURE,
MAX_TEMPERATURE, MAX_TEMPERATURE,
MIN_MAX_TOKENS, MIN_MAX_TOKENS,
@@ -30,6 +41,7 @@ class APIClient:
headers: Dict[str, str], headers: Dict[str, str],
api_provider: str, api_provider: str,
model: str, model: str,
api_timeout: int = DEFAULT_API_TIMEOUT,
) -> None: ) -> None:
"""Initialize API client.""" """Initialize API client."""
self.session = session self.session = session
@@ -37,21 +49,38 @@ class APIClient:
self.headers = headers self.headers = headers
self.api_provider = api_provider self.api_provider = api_provider
self.model = model self.model = model
self.timeout = ClientTimeout(total=API_TIMEOUT) self.api_timeout = api_timeout
self.timeout = ClientTimeout(total=api_timeout)
self._closed = False
async def __aenter__(self):
"""Async context manager entry."""
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
"""Async context manager exit."""
await self.shutdown()
def _validate_parameters( def _validate_parameters(
self, self,
temperature: float, temperature: float,
max_tokens: int, max_tokens: int,
) -> None: ) -> None:
"""Validate API parameters.""" """Validate API parameters with enhanced type checking."""
# Type validation
if not isinstance(temperature, (int, float)):
raise TypeError(f"Temperature must be a number, got {type(temperature)}")
if not isinstance(max_tokens, int):
raise TypeError(f"Max tokens must be an integer, got {type(max_tokens)}")
# Range validation
if not MIN_TEMPERATURE <= temperature <= MAX_TEMPERATURE: if not MIN_TEMPERATURE <= temperature <= MAX_TEMPERATURE:
raise ValueError( raise ValueError(
f"Temperature must be between {MIN_TEMPERATURE} and {MAX_TEMPERATURE}" f"Temperature must be between {MIN_TEMPERATURE} and {MAX_TEMPERATURE}, got {temperature}"
) )
if not MIN_MAX_TOKENS <= max_tokens <= MAX_MAX_TOKENS: if not MIN_MAX_TOKENS <= max_tokens <= MAX_MAX_TOKENS:
raise ValueError( raise ValueError(
f"Max tokens must be between {MIN_MAX_TOKENS} and {MAX_MAX_TOKENS}" f"Max tokens must be between {MIN_MAX_TOKENS} and {MAX_MAX_TOKENS}, got {max_tokens}"
) )
async def _make_request( async def _make_request(
@@ -60,10 +89,13 @@ class APIClient:
payload: Dict[str, Any], payload: Dict[str, Any],
) -> Dict[str, Any]: ) -> Dict[str, Any]:
"""Make API request with retry logic.""" """Make API request with retry logic."""
_LOGGER.debug(f"API Request: URL={url}, Payload={payload}") # Log request without sensitive data
safe_payload = {k: v for k, v in payload.items() if k not in ['messages', 'system']}
_LOGGER.debug(f"API Request: URL={url}, Safe payload: {safe_payload}")
for attempt in range(API_RETRY_COUNT): for attempt in range(API_RETRY_COUNT):
try: try:
async with timeout(API_TIMEOUT): async with timeout(self.api_timeout):
async with self.session.post( async with self.session.post(
url, url,
json=payload, json=payload,
@@ -73,16 +105,18 @@ class APIClient:
_LOGGER.debug(f"Response status: {response.status}") _LOGGER.debug(f"Response status: {response.status}")
if response.status != 200: if response.status != 200:
error_data = await response.json() error_data = await response.json()
_LOGGER.error(f"API error: {error_data}") # Log error without sensitive data
raise HomeAssistantError(f"API error: {error_data}") safe_error = {k: v for k, v in error_data.items() if k not in ['message', 'details']}
_LOGGER.error(f"API error (status {response.status}): {safe_error}")
raise HomeAssistantError(f"API error: status {response.status}")
return await response.json() return await response.json()
except asyncio.TimeoutError: except asyncio.TimeoutError:
_LOGGER.warning(f"Timeout on attempt {attempt + 1}") _LOGGER.warning(f"Timeout on attempt {attempt + 1}/{API_RETRY_COUNT}")
if attempt == API_RETRY_COUNT - 1: if attempt == API_RETRY_COUNT - 1:
raise HomeAssistantError("API request timed out") raise HomeAssistantError("API request timed out")
await asyncio.sleep(1 * (attempt + 1)) await asyncio.sleep(1 * (attempt + 1))
except Exception as e: except Exception as e:
_LOGGER.warning(f"API request failed on attempt {attempt + 1}: {str(e)}") _LOGGER.warning(f"API request failed on attempt {attempt + 1}/{API_RETRY_COUNT}: {type(e).__name__}")
if attempt == API_RETRY_COUNT - 1: if attempt == API_RETRY_COUNT - 1:
raise raise
await asyncio.sleep(1 * (attempt + 1)) await asyncio.sleep(1 * (attempt + 1))
@@ -102,19 +136,53 @@ class APIClient:
return await self._create_anthropic_completion( return await self._create_anthropic_completion(
model, messages, temperature, max_tokens model, messages, temperature, max_tokens
) )
elif self.api_provider == API_PROVIDER_DEEPSEEK:
return await self._create_deepseek_completion(
model, messages, temperature, max_tokens
)
elif self.api_provider == API_PROVIDER_GEMINI:
return await self._create_gemini_completion(
model, messages, temperature, max_tokens
)
else: else:
return await self._create_openai_completion( return await self._create_openai_completion(
model, messages, temperature, max_tokens model, messages, temperature, max_tokens
) )
except (KeyError, IndexError) as e:
if "'choices'" in str(e) or "'message'" in str(e):
raise HomeAssistantError("Failed to get a response from the AI model. Please check your internet connection and try again later.")
else:
raise
except Exception as e: except Exception as e:
_LOGGER.error("API request failed: %s", str(e)) _LOGGER.error("API request failed: %s", str(e))
raise HomeAssistantError(f"API request failed: {str(e)}") raise HomeAssistantError(f"API request failed: {str(e)}")
async def _create_deepseek_completion(
self,
model: str,
messages: List[Dict[str, str]],
temperature: float,
max_tokens: int,
) -> Dict[str, Any]:
"""Create completion using DeepSeek API."""
url = f"{self.endpoint}/chat/completions"
payload = {
"model": model,
"messages": messages,
"temperature": temperature,
"max_tokens": max_tokens,
"stream": False
}
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_openai_completion( async def _create_openai_completion(
self, self,
model: str, model: str,
@@ -199,6 +267,143 @@ class APIClient:
_LOGGER.error(f"Connection check failed: {str(e)}") _LOGGER.error(f"Connection check failed: {str(e)}")
return False return False
async def _create_gemini_completion(
self,
model: str,
messages: List[Dict[str, str]],
temperature: float,
max_tokens: int,
) -> Dict[str, Any]:
"""Create completion using Gemini API with google-genai library.
Args:
model: The model name to use
messages: List of message dictionaries with role and content
temperature: Sampling temperature between 0.0 and 2.0
max_tokens: Maximum number of tokens to generate
Returns:
Dictionary with response content and token usage
"""
try:
def import_genai():
from google import genai
return genai
genai = await asyncio.to_thread(import_genai)
# Extract API key from headers (Bearer token)
api_key = self.headers.get("Authorization", "").replace("Bearer ", "")
def create_client():
if self.endpoint and self.endpoint != "https://generativelanguage.googleapis.com/v1beta":
return genai.Client(api_key=api_key, transport="rest",
client_options={"api_endpoint": self.endpoint})
else:
return genai.Client(api_key=api_key)
client = await asyncio.to_thread(create_client)
# Process messages to extract system instruction and chat history
system_instruction = ""
contents = []
for msg in messages:
if msg['role'] == 'system':
system_instruction += msg['content'] + "\n"
else:
# For chat history, we need to convert to the format Gemini expects
role = "user" if msg['role'] == 'user' else "model"
contents.append({
"role": role,
"parts": [{"text": msg['content']}]
})
# Create configuration
def create_config():
from google.genai import types
config = types.GenerateContentConfig(
temperature=temperature,
max_output_tokens=max_tokens,
)
# Add system instruction if present
if system_instruction:
config.system_instruction = system_instruction.strip()
return config
config = await asyncio.to_thread(create_config)
def generate_content():
# For single message without history, use generate_content
if len(contents) <= 1:
# If we have no content yet, create a simple prompt
if not contents:
prompt = "I need your assistance."
else:
prompt = contents[0]["parts"][0]["text"]
return client.models.generate_content(
model=model,
contents=prompt,
config=config
)
else:
# For multi-turn conversations, use chat
chat = client.chats.create(model=model, config=config)
# Send all messages in sequence
for content in contents:
if content["role"] == "user":
response = chat.send_message(content["parts"][0]["text"])
# We don't send assistant messages as they're already part of the history
return response
response = await asyncio.to_thread(generate_content)
# Extract response text
def extract_response():
response_text = response.text if hasattr(response, 'text') else ""
# Try to get token usage if available
usage = {}
if hasattr(response, 'usage_metadata'):
usage = {
"prompt_tokens": getattr(response.usage_metadata, 'prompt_token_count', 0),
"completion_tokens": getattr(response.usage_metadata, 'candidates_token_count', 0),
"total_tokens": getattr(response.usage_metadata, 'total_token_count', 0)
}
else:
# Estimate token count as fallback
usage = {
"prompt_tokens": len(" ".join([m["content"] for m in messages]).split()) // 3,
"completion_tokens": len(response_text.split()) // 3,
"total_tokens": 0 # Will be calculated below
}
usage["total_tokens"] = usage["prompt_tokens"] + usage["completion_tokens"]
return response_text, usage
response_text, usage = await asyncio.to_thread(extract_response)
return {
"choices": [{
"message": {
"content": response_text
}
}],
"usage": usage
}
except ImportError as e:
_LOGGER.error(f"Google Gemini library not installed: {str(e)}")
raise HomeAssistantError(f"Missing dependency: {str(e)}. Please install google-genai.")
except Exception as e:
_LOGGER.error(f"Gemini API error: {str(e)}")
raise HomeAssistantError(f"Gemini API error: {str(e)}")
async def shutdown(self) -> None: async def shutdown(self) -> None:
"""Shutdown API client.""" """Shutdown API client."""
_LOGGER.debug("Shutting down API client") _LOGGER.debug("Shutting down API client")
+242 -28
View File
@@ -1,6 +1,14 @@
"""Config flow for HA text AI integration.""" """
Config flow for HA text AI integration.
@license: CC BY-NC-SA 4.0 International
@author: SMKRV
@github: https://github.com/smkrv/ha-text-ai
@source: https://github.com/smkrv/ha-text-ai
"""
import logging import logging
from typing import Any, Dict, Optional from typing import Any, Dict, Optional
from datetime import datetime, timedelta
import voluptuous as vol import voluptuous as vol
from homeassistant import config_entries from homeassistant import config_entries
@@ -17,23 +25,33 @@ from .const import (
CONF_MAX_TOKENS, CONF_MAX_TOKENS,
CONF_API_ENDPOINT, CONF_API_ENDPOINT,
CONF_REQUEST_INTERVAL, CONF_REQUEST_INTERVAL,
CONF_API_TIMEOUT,
CONF_API_PROVIDER, CONF_API_PROVIDER,
CONF_CONTEXT_MESSAGES, CONF_CONTEXT_MESSAGES,
API_PROVIDER_OPENAI, API_PROVIDER_OPENAI,
API_PROVIDER_ANTHROPIC, API_PROVIDER_ANTHROPIC,
API_PROVIDER_DEEPSEEK,
API_PROVIDER_GEMINI,
API_PROVIDERS, API_PROVIDERS,
DEFAULT_MODEL, DEFAULT_MODEL,
DEFAULT_DEEPSEEK_MODEL,
DEFAULT_GEMINI_MODEL,
DEFAULT_TEMPERATURE, DEFAULT_TEMPERATURE,
DEFAULT_MAX_TOKENS, DEFAULT_MAX_TOKENS,
DEFAULT_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL,
DEFAULT_API_TIMEOUT,
DEFAULT_OPENAI_ENDPOINT, DEFAULT_OPENAI_ENDPOINT,
DEFAULT_ANTHROPIC_ENDPOINT, DEFAULT_ANTHROPIC_ENDPOINT,
DEFAULT_DEEPSEEK_ENDPOINT,
DEFAULT_GEMINI_ENDPOINT,
DEFAULT_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES,
MIN_TEMPERATURE, MIN_TEMPERATURE,
MAX_TEMPERATURE, MAX_TEMPERATURE,
MIN_MAX_TOKENS, MIN_MAX_TOKENS,
MAX_MAX_TOKENS, MAX_MAX_TOKENS,
MIN_REQUEST_INTERVAL, MIN_REQUEST_INTERVAL,
MIN_API_TIMEOUT,
MAX_API_TIMEOUT,
DEFAULT_NAME_PREFIX, DEFAULT_NAME_PREFIX,
DEFAULT_MAX_HISTORY, DEFAULT_MAX_HISTORY,
CONF_MAX_HISTORY_SIZE, CONF_MAX_HISTORY_SIZE,
@@ -83,9 +101,19 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
self._errors = {} self._errors = {}
if user_input is None: if user_input is None:
default_endpoint = ( # Selecting an endpoint by provider
DEFAULT_OPENAI_ENDPOINT if self._provider == API_PROVIDER_OPENAI default_endpoint = {
else DEFAULT_ANTHROPIC_ENDPOINT API_PROVIDER_OPENAI: DEFAULT_OPENAI_ENDPOINT,
API_PROVIDER_ANTHROPIC: DEFAULT_ANTHROPIC_ENDPOINT,
API_PROVIDER_DEEPSEEK: DEFAULT_DEEPSEEK_ENDPOINT,
API_PROVIDER_GEMINI: DEFAULT_GEMINI_ENDPOINT,
}.get(self._provider, DEFAULT_OPENAI_ENDPOINT)
# Selecting the default model by provider
default_model = (
DEFAULT_DEEPSEEK_MODEL if self._provider == API_PROVIDER_DEEPSEEK else
DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else
DEFAULT_MODEL
) )
return self.async_show_form( return self.async_show_form(
@@ -93,7 +121,7 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
data_schema=vol.Schema({ data_schema=vol.Schema({
vol.Required(CONF_NAME, default="my_assistant"): str, vol.Required(CONF_NAME, default="my_assistant"): str,
vol.Required(CONF_API_KEY): str, vol.Required(CONF_API_KEY): str,
vol.Required(CONF_MODEL, default=DEFAULT_MODEL): str, vol.Required(CONF_MODEL, default=default_model): str,
vol.Required(CONF_API_ENDPOINT, default=default_endpoint): str, vol.Required(CONF_API_ENDPOINT, default=default_endpoint): str,
vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All( vol.Optional(CONF_TEMPERATURE, default=DEFAULT_TEMPERATURE): vol.All(
vol.Coerce(float), vol.Coerce(float),
@@ -107,6 +135,10 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
vol.Coerce(float), vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL) vol.Range(min=MIN_REQUEST_INTERVAL)
), ),
vol.Optional(CONF_API_TIMEOUT, default=DEFAULT_API_TIMEOUT): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional( vol.Optional(
CONF_CONTEXT_MESSAGES, CONF_CONTEXT_MESSAGES,
default=DEFAULT_CONTEXT_MESSAGES default=DEFAULT_CONTEXT_MESSAGES
@@ -124,43 +156,185 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
}) })
) )
# Debug log to identify what's in the input
_LOGGER.debug(f"Provider step input data: {user_input}")
input_copy = user_input.copy() input_copy = user_input.copy()
# Check if CONF_NAME exists in input_copy and ensure it's not empty
if CONF_NAME not in input_copy or not input_copy[CONF_NAME]:
_LOGGER.warning(f"Missing name in configuration input: {input_copy}")
input_copy[CONF_NAME] = f"gemini_assistant_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
_LOGGER.info(f"Auto-generated name: {input_copy[CONF_NAME]}")
# Ensure API key is present
if CONF_API_KEY not in input_copy or not input_copy[CONF_API_KEY]:
self._errors["base"] = "invalid_auth"
_LOGGER.error("API validation error: 'api_key'")
return self.async_show_form(
step_id="provider",
data_schema=vol.Schema({
vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
vol.Required(CONF_API_KEY): str,
vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
vol.Coerce(float),
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
),
vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL)
),
vol.Optional(CONF_API_TIMEOUT, default=input_copy.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT)): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional(
CONF_CONTEXT_MESSAGES,
default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=20)
),
vol.Optional(
CONF_MAX_HISTORY_SIZE,
default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=100)
),
}),
errors=self._errors
)
try: try:
# Validate and normalize the name
normalized_name = self._validate_and_normalize_name(input_copy[CONF_NAME]) normalized_name = self._validate_and_normalize_name(input_copy[CONF_NAME])
input_copy[CONF_NAME] = normalized_name input_copy[CONF_NAME] = normalized_name
except ValueError as e: except ValueError as e:
return self.async_show_form( return self.async_show_form(
step_id="provider", step_id="provider",
data_schema=vol.Schema({ data_schema=vol.Schema({
vol.Required(CONF_NAME, default=input_copy[CONF_NAME]): str, vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
vol.Required(CONF_API_KEY, default=input_copy[CONF_API_KEY]): str, vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
vol.Required(CONF_MODEL, default=input_copy[CONF_MODEL]): str, vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
vol.Required(CONF_API_ENDPOINT, default=input_copy[CONF_API_ENDPOINT]): str, vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All( vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
vol.Coerce(float), vol.Coerce(float),
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE) vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
), ),
vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL)
),
vol.Optional(CONF_API_TIMEOUT, default=input_copy.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT)): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional(
CONF_CONTEXT_MESSAGES,
default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=20)
),
vol.Optional(
CONF_MAX_HISTORY_SIZE,
default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=100)
),
}), }),
errors={"name": str(e)} errors={"name": str(e)}
) )
try: try:
if not await self._async_validate_api(input_copy): # Special handling for Gemini API validation
return self.async_show_form( if self._provider == API_PROVIDER_GEMINI:
step_id="provider", # For Gemini, we just check if API key is present as there's no simple endpoint to validate
data_schema=vol.Schema({ if not input_copy.get(CONF_API_KEY):
}), self._errors["base"] = "invalid_auth"
errors=self._errors _LOGGER.error("API validation error: 'api_key'")
) return self.async_show_form(
step_id="provider",
data_schema=vol.Schema({
vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
vol.Required(CONF_API_KEY): str,
vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL)): str,
vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT)): str,
# Other fields remain the same
}),
errors=self._errors
)
else:
# For other providers, validate API connection
if not await self._async_validate_api(input_copy):
return self.async_show_form(
step_id="provider",
data_schema=vol.Schema({
vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_MODEL)): str,
vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_OPENAI_ENDPOINT)): str,
vol.Optional(CONF_TEMPERATURE, default=input_copy.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE)): vol.All(
vol.Coerce(float),
vol.Range(min=MIN_TEMPERATURE, max=MAX_TEMPERATURE)
),
vol.Optional(CONF_MAX_TOKENS, default=input_copy.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=input_copy.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL)): vol.All(
vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL)
),
vol.Optional(CONF_API_TIMEOUT, default=input_copy.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT)): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional(
CONF_CONTEXT_MESSAGES,
default=input_copy.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=20)
),
vol.Optional(
CONF_MAX_HISTORY_SIZE,
default=input_copy.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY)
): vol.All(
vol.Coerce(int),
vol.Range(min=1, max=100)
),
}),
errors=self._errors
)
except Exception as e: except Exception as e:
# Handle any unexpected exceptions during validation
_LOGGER.exception("Unexpected error during API validation")
return self.async_show_form( return self.async_show_form(
step_id="provider", step_id="provider",
data_schema=vol.Schema({ data_schema=vol.Schema({
vol.Required(CONF_NAME, default=input_copy.get(CONF_NAME, "my_assistant")): str,
vol.Required(CONF_API_KEY, default=input_copy.get(CONF_API_KEY, "")): str,
vol.Required(CONF_MODEL, default=input_copy.get(CONF_MODEL, DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else DEFAULT_MODEL)): str,
vol.Required(CONF_API_ENDPOINT, default=input_copy.get(CONF_API_ENDPOINT, DEFAULT_GEMINI_ENDPOINT if self._provider == API_PROVIDER_GEMINI else DEFAULT_OPENAI_ENDPOINT)): str,
# Other fields remain the same
}), }),
errors={"base": str(e)} errors={"base": str(e)}
) )
# All validation passed, create the entry
return await self._create_entry(input_copy) return await self._create_entry(input_copy)
def _validate_and_normalize_name(self, name: str) -> str: def _validate_and_normalize_name(self, name: str) -> str:
@@ -198,23 +372,34 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
async def _async_validate_api(self, user_input: Dict[str, Any]) -> bool: async def _async_validate_api(self, user_input: Dict[str, Any]) -> bool:
"""Validate API connection.""" """Validate API connection."""
try: try:
if CONF_API_KEY not in user_input:
_LOGGER.error("API validation error: 'api_key'")
self._errors["base"] = "invalid_auth"
return False
session = async_get_clientsession(self.hass) session = async_get_clientsession(self.hass)
headers = self._get_api_headers(user_input) headers = self._get_api_headers(user_input)
endpoint = user_input[CONF_API_ENDPOINT].rstrip('/') endpoint = user_input[CONF_API_ENDPOINT].rstrip('/')
check_url = ( if self._provider == API_PROVIDER_GEMINI:
f"{endpoint}/v1/models" if self._provider == API_PROVIDER_ANTHROPIC if not user_input[CONF_API_KEY]:
else f"{endpoint}/models"
)
async with session.get(check_url, headers=headers) as response:
if response.status == 401:
self._errors["base"] = "invalid_auth" self._errors["base"] = "invalid_auth"
return False return False
elif response.status not in [200, 404]:
self._errors["base"] = "cannot_connect"
return False
return True return True
else:
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: except Exception as err:
_LOGGER.error("API validation error: %s", str(err)) _LOGGER.error("API validation error: %s", str(err))
@@ -223,6 +408,9 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
def _get_api_headers(self, user_input: Dict[str, Any]) -> Dict[str, str]: def _get_api_headers(self, user_input: Dict[str, Any]) -> Dict[str, str]:
"""Get API headers based on provider.""" """Get API headers based on provider."""
if CONF_API_KEY not in user_input:
return {"Content-Type": "application/json"}
api_key = user_input[CONF_API_KEY] api_key = user_input[CONF_API_KEY]
if self._provider == API_PROVIDER_ANTHROPIC: if self._provider == API_PROVIDER_ANTHROPIC:
@@ -231,6 +419,11 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
"anthropic-version": "2023-06-01", "anthropic-version": "2023-06-01",
"Content-Type": "application/json" "Content-Type": "application/json"
} }
elif self._provider == API_PROVIDER_GEMINI:
return {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
return { return {
"Authorization": f"Bearer {api_key}", "Authorization": f"Bearer {api_key}",
"Content-Type": "application/json" "Content-Type": "application/json"
@@ -243,6 +436,12 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
unique_id = f"{DOMAIN}_{normalized_name}_{self._provider}".lower() unique_id = f"{DOMAIN}_{normalized_name}_{self._provider}".lower()
default_model = (
DEFAULT_DEEPSEEK_MODEL if self._provider == API_PROVIDER_DEEPSEEK else
DEFAULT_GEMINI_MODEL if self._provider == API_PROVIDER_GEMINI else
DEFAULT_MODEL
)
entry_data = { entry_data = {
CONF_API_PROVIDER: self._provider, CONF_API_PROVIDER: self._provider,
CONF_NAME: instance_name, CONF_NAME: instance_name,
@@ -250,10 +449,11 @@ class HATextAIConfigFlow(config_entries.ConfigFlow, domain=DOMAIN):
CONF_API_KEY: user_input.get(CONF_API_KEY), CONF_API_KEY: user_input.get(CONF_API_KEY),
CONF_API_ENDPOINT: user_input.get(CONF_API_ENDPOINT), CONF_API_ENDPOINT: user_input.get(CONF_API_ENDPOINT),
"unique_id": unique_id, "unique_id": unique_id,
CONF_MODEL: user_input.get(CONF_MODEL, DEFAULT_MODEL), CONF_MODEL: user_input.get(CONF_MODEL, default_model),
CONF_TEMPERATURE: user_input.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE), CONF_TEMPERATURE: user_input.get(CONF_TEMPERATURE, DEFAULT_TEMPERATURE),
CONF_MAX_TOKENS: user_input.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS), CONF_MAX_TOKENS: user_input.get(CONF_MAX_TOKENS, DEFAULT_MAX_TOKENS),
CONF_REQUEST_INTERVAL: user_input.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL), CONF_REQUEST_INTERVAL: user_input.get(CONF_REQUEST_INTERVAL, DEFAULT_REQUEST_INTERVAL),
CONF_API_TIMEOUT: user_input.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT),
CONF_CONTEXT_MESSAGES: user_input.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES), CONF_CONTEXT_MESSAGES: user_input.get(CONF_CONTEXT_MESSAGES, DEFAULT_CONTEXT_MESSAGES),
CONF_MAX_HISTORY_SIZE: user_input.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY), CONF_MAX_HISTORY_SIZE: user_input.get(CONF_MAX_HISTORY_SIZE, DEFAULT_MAX_HISTORY),
} }
@@ -289,13 +489,20 @@ class OptionsFlowHandler(config_entries.OptionsFlow):
return self.async_create_entry(title="", data=user_input) return self.async_create_entry(title="", data=user_input)
current_data = {**self.config_entry.data, **self.config_entry.options} current_data = {**self.config_entry.data, **self.config_entry.options}
provider = current_data.get(CONF_API_PROVIDER)
default_model = (
DEFAULT_DEEPSEEK_MODEL if provider == API_PROVIDER_DEEPSEEK else
DEFAULT_GEMINI_MODEL if provider == API_PROVIDER_GEMINI else
DEFAULT_MODEL
)
return self.async_show_form( return self.async_show_form(
step_id="init", step_id="init",
data_schema=vol.Schema({ data_schema=vol.Schema({
vol.Optional( vol.Optional(
CONF_MODEL, CONF_MODEL,
default=current_data.get(CONF_MODEL, DEFAULT_MODEL) default=current_data.get(CONF_MODEL, default_model)
): str, ): str,
vol.Optional( vol.Optional(
CONF_TEMPERATURE, CONF_TEMPERATURE,
@@ -318,6 +525,13 @@ class OptionsFlowHandler(config_entries.OptionsFlow):
vol.Coerce(float), vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL) vol.Range(min=MIN_REQUEST_INTERVAL)
), ),
vol.Optional(
CONF_API_TIMEOUT,
default=current_data.get(CONF_API_TIMEOUT, DEFAULT_API_TIMEOUT)
): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional( vol.Optional(
CONF_CONTEXT_MESSAGES, CONF_CONTEXT_MESSAGES,
default=current_data.get( default=current_data.get(
+54 -4
View File
@@ -1,8 +1,19 @@
"""Constants for the HA text AI integration.""" """
Constants for the HA text AI integration.
@license: CC BY-NC-SA 4.0 International
@author: SMKRV
@github: https://github.com/smkrv/ha-text-ai
@source: https://github.com/smkrv/ha-text-ai
"""
import os
import json
from typing import Final from typing import Final
import voluptuous as vol import voluptuous as vol
from homeassistant.const import Platform, CONF_API_KEY, CONF_NAME from homeassistant.const import Platform, CONF_API_KEY, CONF_NAME
from homeassistant.helpers import config_validation as cv from homeassistant.helpers import config_validation as cv
import logging
_LOGGER = logging.getLogger(__name__)
# Domain and platforms # Domain and platforms
DOMAIN: Final = "ha_text_ai" DOMAIN: Final = "ha_text_ai"
@@ -12,15 +23,37 @@ PLATFORMS: list[str] = ["sensor"]
CONF_API_PROVIDER: Final = "api_provider" CONF_API_PROVIDER: Final = "api_provider"
API_PROVIDER_OPENAI: Final = "openai" API_PROVIDER_OPENAI: Final = "openai"
API_PROVIDER_ANTHROPIC: Final = "anthropic" API_PROVIDER_ANTHROPIC: Final = "anthropic"
API_PROVIDER_DEEPSEEK: Final = "deepseek"
API_PROVIDER_GEMINI: Final = "gemini"
API_PROVIDERS: Final = [ API_PROVIDERS: Final = [
API_PROVIDER_OPENAI, API_PROVIDER_OPENAI,
API_PROVIDER_ANTHROPIC API_PROVIDER_ANTHROPIC,
API_PROVIDER_DEEPSEEK,
API_PROVIDER_GEMINI
] ]
# Read version from manifest.json
MANIFEST_PATH = os.path.join(os.path.dirname(__file__), "manifest.json")
try:
with open(MANIFEST_PATH) as manifest_file:
manifest = json.load(manifest_file)
VERSION = manifest.get("version", "unknown")
except FileNotFoundError:
VERSION = "unknown"
_LOGGER.warning("manifest.json not found at %s", MANIFEST_PATH)
except json.JSONDecodeError as err:
VERSION = "unknown"
_LOGGER.error("Error decoding JSON from manifest.json: %s", err)
except Exception as err:
VERSION = "unknown"
_LOGGER.error("Error reading manifest.json: %s", err)
# Default endpoints # Default endpoints
DEFAULT_OPENAI_ENDPOINT: Final = "https://api.openai.com/v1" DEFAULT_OPENAI_ENDPOINT: Final = "https://api.openai.com/v1"
DEFAULT_ANTHROPIC_ENDPOINT: Final = "https://api.anthropic.com" DEFAULT_ANTHROPIC_ENDPOINT: Final = "https://api.anthropic.com"
DEFAULT_DEEPSEEK_ENDPOINT: Final = "https://api.deepseek.com"
DEFAULT_GEMINI_ENDPOINT: Final = "https://generativelanguage.googleapis.com/v1beta"
# Configuration constants # Configuration constants
CONF_MODEL: Final = "model" CONF_MODEL: Final = "model"
@@ -28,32 +61,45 @@ CONF_TEMPERATURE: Final = "temperature"
CONF_MAX_TOKENS: Final = "max_tokens" CONF_MAX_TOKENS: Final = "max_tokens"
CONF_API_ENDPOINT: Final = "api_endpoint" CONF_API_ENDPOINT: Final = "api_endpoint"
CONF_REQUEST_INTERVAL: Final = "request_interval" CONF_REQUEST_INTERVAL: Final = "request_interval"
CONF_API_TIMEOUT: Final = "api_timeout"
CONF_INSTANCE: Final = "instance" CONF_INSTANCE: Final = "instance"
CONF_MAX_HISTORY_SIZE: Final = "max_history_size" # Correct constant name CONF_MAX_HISTORY_SIZE: Final = "max_history_size" # Correct constant name
CONF_IS_ANTHROPIC: Final = "is_anthropic" CONF_IS_ANTHROPIC: Final = "is_anthropic"
CONF_CONTEXT_MESSAGES: Final = "context_messages" CONF_CONTEXT_MESSAGES: Final = "context_messages"
ABSOLUTE_MAX_HISTORY_SIZE = 500
MAX_ATTRIBUTE_SIZE = 4 * 1024
MAX_HISTORY_FILE_SIZE = 1 * 1024 * 1024
ICONS_SUBDOMAIN = "icons"
# Default values # Default values
DEFAULT_MODEL: Final = "gpt-4o-mini" DEFAULT_MODEL: Final = "gpt-4o-mini"
DEFAULT_DEEPSEEK_MODEL: Final = "deepseek-chat"
DEFAULT_GEMINI_MODEL: Final = "gemini-2.0-flash"
DEFAULT_TEMPERATURE: Final = 0.1 DEFAULT_TEMPERATURE: Final = 0.1
DEFAULT_MAX_TOKENS: Final = 1000 DEFAULT_MAX_TOKENS: Final = 1000
DEFAULT_REQUEST_INTERVAL: Final = 1.0 DEFAULT_REQUEST_INTERVAL: Final = 1.0
DEFAULT_TIMEOUT: Final = 30 DEFAULT_TIMEOUT: Final = 30
DEFAULT_API_TIMEOUT: Final = 30
DEFAULT_MAX_HISTORY: Final = 50 DEFAULT_MAX_HISTORY: Final = 50
DEFAULT_NAME: Final = "HA Text AI" DEFAULT_NAME: Final = "HA Text AI"
DEFAULT_NAME_PREFIX = "ha_text_ai" DEFAULT_NAME_PREFIX = "ha_text_ai"
DEFAULT_CONTEXT_MESSAGES: Final = 5 DEFAULT_CONTEXT_MESSAGES: Final = 5
TRUNCATION_INDICATOR = " ... "
# Parameter constraints # Parameter constraints
MIN_TEMPERATURE: Final = 0.0 MIN_TEMPERATURE: Final = 0.0
MAX_TEMPERATURE: Final = 2.0 MAX_TEMPERATURE: Final = 2.0
MIN_MAX_TOKENS: Final = 1 MIN_MAX_TOKENS: Final = 1
MAX_MAX_TOKENS: Final = 4096 MAX_MAX_TOKENS: Final = 100000
MIN_REQUEST_INTERVAL: Final = 0.1 MIN_REQUEST_INTERVAL: Final = 0.1
MAX_REQUEST_INTERVAL: Final = 60.0 MAX_REQUEST_INTERVAL: Final = 60.0
MIN_API_TIMEOUT: Final = 5
MAX_API_TIMEOUT: Final = 600
# API constants # API constants
API_TIMEOUT: Final = 30 API_TIMEOUT: Final = 30 # Legacy constant, use CONF_API_TIMEOUT from config
API_RETRY_COUNT: Final = 3 API_RETRY_COUNT: Final = 3
# Service names # Service names
@@ -190,6 +236,10 @@ CONFIG_SCHEMA = vol.Schema({
vol.Coerce(float), vol.Coerce(float),
vol.Range(min=MIN_REQUEST_INTERVAL, max=MAX_REQUEST_INTERVAL) vol.Range(min=MIN_REQUEST_INTERVAL, max=MAX_REQUEST_INTERVAL)
), ),
vol.Optional(CONF_API_TIMEOUT, default=DEFAULT_API_TIMEOUT): vol.All(
vol.Coerce(int),
vol.Range(min=MIN_API_TIMEOUT, max=MAX_API_TIMEOUT)
),
vol.Optional(CONF_MAX_HISTORY_SIZE, default=DEFAULT_MAX_HISTORY): vol.All( # Correct usage vol.Optional(CONF_MAX_HISTORY_SIZE, default=DEFAULT_MAX_HISTORY): vol.All( # Correct usage
vol.Coerce(int), vol.Coerce(int),
vol.Range(min=1, max=100), vol.Range(min=1, max=100),
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+2 -1
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@@ -16,6 +16,7 @@
"requirements": [ "requirements": [
"openai>=1.12.0", "openai>=1.12.0",
"anthropic>=0.8.0", "anthropic>=0.8.0",
"google-genai>=1.16.0",
"aiohttp>=3.8.0", "aiohttp>=3.8.0",
"async-timeout>=4.0.0", "async-timeout>=4.0.0",
"certifi>=2024.2.2" "certifi>=2024.2.2"
@@ -23,6 +24,6 @@
"single_config_entry": false, "single_config_entry": false,
"ssdp": [], "ssdp": [],
"usb": [], "usb": [],
"version": "2.0.3-beta", "version": "2.2.0",
"zeroconf": [] "zeroconf": []
} }
+79 -49
View File
@@ -1,7 +1,15 @@
"""Sensor platform for HA Text AI.""" """
Sensor platform for HA Text AI.
@license: CC BY-NC-SA 4.0 International
@author: SMKRV
@github: https://github.com/smkrv/ha-text-ai
@source: https://github.com/smkrv/ha-text-ai
"""
import logging import logging
import math import math
from typing import Any, Dict from typing import Any, Dict
from datetime import datetime, timedelta
from homeassistant.components.sensor import ( from homeassistant.components.sensor import (
SensorEntity, SensorEntity,
@@ -60,6 +68,8 @@ from .const import (
ENTITY_ICON_PROCESSING, ENTITY_ICON_PROCESSING,
DEFAULT_NAME_PREFIX, DEFAULT_NAME_PREFIX,
CONF_MAX_HISTORY_SIZE, CONF_MAX_HISTORY_SIZE,
MAX_ATTRIBUTE_SIZE,
VERSION,
) )
from .coordinator import HATextAICoordinator from .coordinator import HATextAICoordinator
@@ -146,7 +156,7 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
name=self._attr_name, name=self._attr_name,
manufacturer="Community", manufacturer="Community",
model=f"{model} ({api_provider} provider)", model=f"{model} ({api_provider} provider)",
sw_version="1.0.0", sw_version=VERSION,
) )
_LOGGER.debug( _LOGGER.debug(
@@ -171,12 +181,29 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]: def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]:
"""Sanitize all attributes for JSON serialization.""" """Sanitize all attributes for JSON serialization."""
return { sanitized = {
key: self._sanitize_value(value) key: self._sanitize_value(value)
for key, value in attributes.items() for key, value in attributes.items()
if value is not None if value is not None
} }
# Log metrics for debugging
metrics_keys = [
METRIC_TOTAL_TOKENS,
METRIC_PROMPT_TOKENS,
METRIC_COMPLETION_TOKENS,
METRIC_SUCCESSFUL_REQUESTS,
METRIC_FAILED_REQUESTS,
METRIC_AVERAGE_LATENCY,
METRIC_MAX_LATENCY,
METRIC_MIN_LATENCY,
]
metrics_values = {k: sanitized.get(k) for k in metrics_keys if k in sanitized}
_LOGGER.debug(f"Metrics for {self.entity_id}: {metrics_values}")
return sanitized
@property @property
def native_value(self) -> StateType: def native_value(self) -> StateType:
"""Return the native value of the sensor.""" """Return the native value of the sensor."""
@@ -205,68 +232,65 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
try: try:
data = self.coordinator.data data = self.coordinator.data
metrics = data.get("metrics", {})
# Base attributes
attributes = { attributes = {
ATTR_MODEL: self._config_entry.data.get(CONF_MODEL, "Unknown"), ATTR_MODEL: self._config_entry.data.get(CONF_MODEL, "Unknown"),
ATTR_API_PROVIDER: self._config_entry.data.get( ATTR_API_PROVIDER: self._config_entry.data.get(CONF_API_PROVIDER, "Unknown"),
CONF_API_PROVIDER, "Unknown"
),
ATTR_API_STATUS: self._current_state, ATTR_API_STATUS: self._current_state,
ATTR_TOTAL_ERRORS: self._error_count, ATTR_TOTAL_ERRORS: metrics.get("total_errors", 0),
ATTR_LAST_ERROR: self._last_error,
"instance_name": self._instance_name, "instance_name": self._instance_name,
"normalized_name": self._normalized_name, "normalized_name": self._normalized_name,
ATTR_SYSTEM_PROMPT: data.get("system_prompt"), ATTR_SYSTEM_PROMPT: (data.get("system_prompt", "")[:MAX_ATTRIBUTE_SIZE]
if data.get("system_prompt") else None),
ATTR_IS_PROCESSING: data.get("is_processing", False), ATTR_IS_PROCESSING: data.get("is_processing", False),
ATTR_IS_RATE_LIMITED: data.get("is_rate_limited", False), ATTR_IS_RATE_LIMITED: data.get("is_rate_limited", False),
ATTR_IS_MAINTENANCE: data.get("is_maintenance", False), ATTR_IS_MAINTENANCE: data.get("is_maintenance", False),
ATTR_ENDPOINT_STATUS: data.get("endpoint_status", "unknown"), ATTR_ENDPOINT_STATUS: data.get("endpoint_status", "unknown"),
ATTR_UPTIME: data.get("uptime", 0), ATTR_UPTIME: round(data.get("uptime", 0), 2),
ATTR_HISTORY_SIZE: data.get("history_size", 0), ATTR_HISTORY_SIZE: data.get("history_size", 0),
ATTR_CONVERSATION_HISTORY: data.get("conversation_history", []),
} }
# Add metrics # History limit
metrics = data.get("metrics", {}) conversation_history = data.get("conversation_history", [])
if isinstance(metrics, dict): if conversation_history:
self._metrics = metrics limited_history = []
attributes.update( for entry in conversation_history:
{ limited_entry = {
METRIC_TOTAL_TOKENS: metrics.get("total_tokens", 0), "timestamp": entry["timestamp"],
METRIC_PROMPT_TOKENS: metrics.get("prompt_tokens", 0), "question": entry["question"][:MAX_ATTRIBUTE_SIZE],
METRIC_COMPLETION_TOKENS: metrics.get("completion_tokens", 0), "response": entry["response"][:MAX_ATTRIBUTE_SIZE]
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")),
} }
) limited_history.append(limited_entry)
attributes[ATTR_CONVERSATION_HISTORY] = limited_history
# Add last response # Metrics
if isinstance(metrics, dict):
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: round(metrics.get("average_latency", 0), 2),
METRIC_MAX_LATENCY: round(metrics.get("max_latency", 0), 2),
METRIC_MIN_LATENCY: (metrics.get("min_latency")
if metrics.get("min_latency") != float("inf")
else None),
})
# Last response handling
last_response = data.get("last_response", {}) last_response = data.get("last_response", {})
if isinstance(last_response, dict): if isinstance(last_response, dict):
self._last_response = last_response attributes.update({
attributes.update( ATTR_RESPONSE: last_response.get("response", "")[:MAX_ATTRIBUTE_SIZE],
{ ATTR_QUESTION: last_response.get("question", "")[:MAX_ATTRIBUTE_SIZE],
ATTR_RESPONSE: last_response.get("response", ""), "last_model": last_response.get("model", ""),
ATTR_QUESTION: last_response.get("question", ""), "last_timestamp": last_response.get("timestamp", ""),
"last_model": last_response.get("model", ""), "last_error": (last_response.get("error", "")[:MAX_ATTRIBUTE_SIZE]
"last_timestamp": last_response.get("timestamp", ""), if last_response.get("error") else None),
"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) return self._sanitize_attributes(attributes)
@@ -292,6 +316,12 @@ class HATextAISensor(CoordinatorEntity, SensorEntity):
self._is_processing = data.get("is_processing", False) self._is_processing = data.get("is_processing", False)
# Update metrics
metrics = data.get("metrics", {})
if isinstance(metrics, dict):
self._metrics.update(metrics)
_LOGGER.debug(f"Updated metrics for {self.entity_id}: {self._metrics}")
# Update conversation history and system prompt # Update conversation history and system prompt
self._conversation_history = data.get("conversation_history", []) self._conversation_history = data.get("conversation_history", [])
self._system_prompt = data.get("system_prompt") self._system_prompt = data.get("system_prompt")
+3 -2
View File
@@ -3,6 +3,7 @@ ask_question:
description: >- description: >-
Send a question to the AI model and receive a detailed response. 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. The response will be stored in the conversation history and can be retrieved later.
This service now returns response data directly, eliminating the need to read from sensors.
fields: fields:
instance: instance:
name: Instance name: Instance
@@ -63,13 +64,13 @@ ask_question:
max_tokens: max_tokens:
name: Max Tokens name: Max Tokens
description: Maximum length of the response (1-4096 tokens) description: Maximum length of the response (tokens)
required: false required: false
default: 1000 default: 1000
selector: selector:
number: number:
min: 1 min: 1
max: 4096 max: 100000
step: 1 step: 1
mode: box mode: box
@@ -2,71 +2,106 @@
"config": { "config": {
"step": { "step": {
"provider": { "provider": {
"title": "KI-Anbieter auswählen", "title": "Wählen Sie AI-Anbieter",
"description": "Wählen Sie den KI-Dienstanbieter für diese Instanz aus.", "description": "Wählen Sie, welchen AI-Dienstanbieter Sie für diese Instanz verwenden möchten.",
"data": { "data": {
"api_provider": "API-Anbieter", "api_provider": "API-Anbieter",
"context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)" "context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)",
"max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
}
},
"provider": {
"title": "Anbieter-Einstellungen",
"description": "Geben Sie die Verbindungsdetails für Ihren gewählten AI-Anbieter an.",
"data": {
"name": "Instanzname (z. B. 'GPT Assistant', 'Claude Helper')",
"api_key": "API-Schlüssel zur Authentifizierung",
"model": "Zu verwendendes AI-Modell",
"api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
"temperature": "Kreativität der Antwort (0-2, niedriger = fokussierter)",
"max_tokens": "Maximale Länge der Antwort (1-100000 Token)",
"request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
"api_timeout": "API-Anfrage Timeout in Sekunden (5-600)",
"context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)",
"max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
} }
}, },
"user": { "user": {
"title": "HA Text AI-Instanz konfigurieren", "title": "HA Text AI Instanz konfigurieren",
"description": "Richten Sie eine neue KI-Assistenteninstanz mit Ihrem ausgewählten Anbieter ein.", "description": "Richten Sie eine neue AI-Assistenteninstanz mit Ihrem ausgewählten Anbieter ein.",
"data": { "data": {
"name": "Instanzname (z. B. 'GPT-Assistent', 'Claude-Helfer')", "name": "Instanzname (z. B. 'GPT Assistant', 'Claude Helper')",
"api_key": "API-Schlüssel zur Authentifizierung", "api_key": "API-Schlüssel zur Authentifizierung",
"model": "Zu verwendendes KI-Modell", "model": "Zu verwendendes AI-Modell",
"temperature": "Antwortkreativität (0-2, niedriger = fokussierter)", "temperature": "Kreativität der Antwort (0-2, niedriger = fokussierter)",
"max_tokens": "Maximale Antwortlänge (1-4096 Token)", "max_tokens": "Maximale Länge der Antwort (1-100000 Token)",
"api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)", "api_endpoint": "Benutzerdefinierte API-Endpunkt-URL (optional)",
"api_provider": "API-Anbieter", "api_provider": "API-Anbieter",
"request_interval": "Mindestzeit zwischen Anfragen (0,1-60 Sekunden)", "request_interval": "Minimale Zeit zwischen Anfragen (0,1-60 Sekunden)",
"api_timeout": "API-Anfrage Timeout in Sekunden (5-600)",
"context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)", "context_messages": "Anzahl der zu behaltenden Kontextnachrichten (1-20)",
"max_history_size": "Maximale Größe des Konversationsverlaufs (1-100)" "max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
} }
} }
}, },
"error": { "error": {
"history_storage_error": "Fehler beim Initialisieren des Verlaufspeichers. Überprüfen Sie die Berechtigungen.",
"history_rotation_error": "Fehler beim Drehen der Verlaufsdatei.",
"history_file_access_error": "Zugriff auf das Verzeichnis für den Verlaufsspeicher nicht möglich.",
"name_exists": "Eine Instanz mit diesem Namen existiert bereits", "name_exists": "Eine Instanz mit diesem Namen existiert bereits",
"invalid_name": "Ungültiger Instanzname", "invalid_name": "Ungültiger Instanzname",
"invalid_auth": "Authentifizierung fehlgeschlagen - überprüfen Sie Ihren API-Schlüssel", "invalid_auth": "Authentifizierung fehlgeschlagen - überprüfen Sie Ihren API-Schlüssel",
"invalid_api_key": "Ungültiger API-Schlüssel - überprüfen Sie Ihre Anmeldedaten", "invalid_api_key": "Ungültiger API-Schlüssel - bitte überprüfen Sie Ihre Anmeldeinformationen",
"cannot_connect": "Verbindung zum API-Dienst fehlgeschlagen", "cannot_connect": "Verbindung zum API-Dienst fehlgeschlagen",
"invalid_model": "Das ausgewählte Modell ist nicht verfügbar", "invalid_model": "Ausgewähltes Modell ist nicht verfügbar",
"rate_limit": "Ratenlimit überschritten", "rate_limit": "Rate-Limit überschritten",
"context_length": "Kontextlänge überschritten", "context_length": "Kontextlänge überschritten",
"rate_limit_exceeded": "API-Ratenlimit überschritten", "rate_limit_exceeded": "API-Rate-Limit überschritten",
"maintenance": "Dienst befindet sich in der Wartung", "maintenance": "Dienst ist in Wartung",
"invalid_response": "Ungültige API-Antwort empfangen", "invalid_response": "Ungültige API-Antwort erhalten",
"api_error": "Fehler im API-Dienst aufgetreten", "api_error": "Ein Fehler im API-Dienst ist aufgetreten",
"timeout": "Anfrage ist abgelaufen", "timeout": "Zeitüberschreitung bei der Anfrage",
"invalid_instance": "Ungültige Instanz angegeben", "invalid_instance": "Ungültige Instanz angegeben",
"unknown": "Es ist ein unerwarteter Fehler aufgetreten", "unknown": "Unerwarteter Fehler aufgetreten",
"empty": "Name darf nicht leer sein", "empty": "Name darf nicht leer sein",
"invalid_characters": "Name darf nur Buchstaben, Zahlen, Leerzeichen, Unterstriche und Bindestriche enthalten", "invalid_characters": "Name darf nur Buchstaben, Zahlen, Leerzeichen, Unterstriche und Bindestriche enthalten",
"name_too_long": "Name darf maximal 50 Zeichen lang sein" "name_too_long": "Name darf höchstens 50 Zeichen lang sein"
},
"abort": {
"already_configured": "Instanz bereits konfiguriert"
} }
}, },
"options": { "options": {
"step": { "step": {
"init": { "init": {
"title": "Instanzeinstellungen aktualisieren", "title": "Instanzeinstellungen aktualisieren",
"description": "Ändern Sie die Einstellungen für diese KI-Assistenteninstanz.", "description": "Ändern Sie die Einstellungen für diese AI-Assistenteninstanz.",
"data": { "data": {
"model": "KI-Modell", "model": "AI-Modell",
"temperature": "Antwortkreativität (0-2)", "temperature": "Kreativität der Antwort (0-2)",
"max_tokens": "Maximale Antwortlänge (1-4096)", "max_tokens": "Maximale Länge der Antwort (1-100000)",
"request_interval": "Mindestzeitraum zwischen Anfragen (0,1-60 Sekunden)", "request_interval": "Minimale Anfrageintervall (0,1-60 Sekunden)",
"api_timeout": "API-Anfrage Timeout in Sekunden (5-600)",
"context_messages": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)", "context_messages": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)",
"max_history_size": "Maximale Größe des Konversationsverlaufs (1-100)" "max_history_size": "Maximale Größe des Gesprächsverlaufs (1-100)"
} }
} }
} }
}, },
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (compatible)",
"anthropic": "Anthropic (compatible)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": { "services": {
"ask_question": { "ask_question": {
"name": "Frage stellen (HA Text AI)", "name": "Frage stellen (HA Text AI)",
"description": "Senden Sie eine Frage an das KI-Modell und erhalten Sie eine detaillierte Antwort. Die Antwort wird im Konversationsverlauf gespeichert und kann später abgerufen werden.", "description": "Stellen Sie eine Frage an das AI-Modell und erhalten Sie eine detaillierte Antwort. Dieser Service gibt jetzt Antwortdaten direkt zurück, wodurch separate Textsensoren und die 255-Zeichen-Begrenzung überflüssig werden. Die Antwort wird auch im Gesprächsverlauf gespeichert.",
"fields": { "fields": {
"instance": { "instance": {
"name": "Instanz", "name": "Instanz",
@@ -74,43 +109,43 @@
}, },
"question": { "question": {
"name": "Frage", "name": "Frage",
"description": "Ihre Frage oder Aufforderung an den KI-Assistenten" "description": "Ihre Frage oder Aufforderung für den AI-Assistenten"
}, },
"context_messages": { "context_messages": {
"name": "Kontextnachrichten", "name": "Kontextnachrichten",
"description": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)" "description": "Anzahl der vorherigen Nachrichten, die im Kontext enthalten sein sollen (1-20)"
}, },
"system_prompt": { "system_prompt": {
"name": "Systemprompt", "name": "Systemaufforderung",
"description": "Optionaler Systemprompt, um den Kontext für diese spezielle Frage festzulegen" "description": "Optionale Systemaufforderung zur Festlegung des Kontexts für diese spezifische Frage"
}, },
"model": { "model": {
"name": "Modell", "name": "Modell",
"description": "Wählen Sie das zu verwendende KI-Modell aus (optional, überschreibt die Standardeinstellung)" "description": "Wählen Sie das zu verwendende AI-Modell (optional, überschreibt die Standardeinstellung)"
}, },
"temperature": { "temperature": {
"name": "Temperatur", "name": "Temperatur",
"description": "Steuert die Antwortkreativität (0.0-2.0)" "description": "Steuert die Kreativität der Antwort (0,0-2,0)"
}, },
"max_tokens": { "max_tokens": {
"name": "Max. Token", "name": "Max Tokens",
"description": "Maximale Länge der Antwort (1-4096 Token)" "description": "Maximale Länge der Antwort (1-100000 Token)"
} }
} }
}, },
"clear_history": { "clear_history": {
"name": "Verlauf löschen", "name": "Verlauf löschen",
"description": "Alle gespeicherten Fragen und Antworten aus dem Konversationsverlauf löschen", "description": "Löschen Sie alle gespeicherten Fragen und Antworten aus dem Gesprächsverlauf",
"fields": { "fields": {
"instance": { "instance": {
"name": "Instanz", "name": "Instanz",
"description": "Name der HA Text AI-Instanz, deren Verlauf gelöscht werden soll" "description": "Name der HA Text AI-Instanz, für die der Verlauf gelöscht werden soll"
} }
} }
}, },
"get_history": { "get_history": {
"name": "Verlauf abrufen", "name": "Verlauf abrufen",
"description": "Konversationsverlauf mit optionalem Filtern und Sortieren abrufen", "description": "Rufen Sie den Gesprächsverlauf mit optionaler Filterung und Sortierung ab",
"fields": { "fields": {
"instance": { "instance": {
"name": "Instanz", "name": "Instanz",
@@ -118,19 +153,19 @@
}, },
"limit": { "limit": {
"name": "Limit", "name": "Limit",
"description": "Anzahl der zurückzugebenden Konversationen (1-100)" "description": "Anzahl der zurückzugebenden Gespräche (1-100)"
}, },
"filter_model": { "filter_model": {
"name": "Modell filtern", "name": "Modell filtern",
"description": "Konversationen nach einem bestimmten KI-Modell filtern" "description": "Gespräche nach spezifischem AI-Modell filtern"
}, },
"start_date": { "start_date": {
"name": "Startdatum", "name": "Startdatum",
"description": "Konversationen ab diesem Datum/Uhrzeit filtern" "description": "Gespräche ab diesem Datum/Zeit filtern"
}, },
"include_metadata": { "include_metadata": {
"name": "Metadaten einschließen", "name": "Metadaten einbeziehen",
"description": "Zusätzliche Informationen wie verwendete Token, Antwortzeit usw. einschließen" "description": "Zusätzliche Informationen wie verwendete Tokens, Antwortzeit usw. einbeziehen"
}, },
"sort_order": { "sort_order": {
"name": "Sortierreihenfolge", "name": "Sortierreihenfolge",
@@ -139,16 +174,16 @@
} }
}, },
"set_system_prompt": { "set_system_prompt": {
"name": "Systemprompt festlegen", "name": "Systemaufforderung festlegen",
"description": "Legen Sie Standardanweisungen für das Systemverhalten für alle zukünftigen Konversationen fest", "description": "Standardverhaltensanweisungen für alle zukünftigen Gespräche festlegen",
"fields": { "fields": {
"instance": { "instance": {
"name": "Instanz", "name": "Instanz",
"description": "Name der HA Text AI-Instanz, für die der Systemprompt festgelegt werden soll" "description": "Name der HA Text AI-Instanz, für die die Systemaufforderung festgelegt werden soll"
}, },
"prompt": { "prompt": {
"name": "Systemprompt", "name": "Systemaufforderung",
"description": "Anweisungen, die definieren, wie sich die KI verhalten und antworten soll" "description": "Anweisungen, die definieren, wie die AI sich verhalten und antworten soll"
} }
} }
} }
@@ -162,11 +197,11 @@
"processing": "Verarbeitung", "processing": "Verarbeitung",
"error": "Fehler", "error": "Fehler",
"disconnected": "Getrennt", "disconnected": "Getrennt",
"rate_limited": "Ratenlimit", "rate_limited": "Rate limitiert",
"maintenance": "Wartung", "maintenance": "Wartung",
"initializing": "Initialisierung", "initializing": "Initialisierung",
"retrying": "Wiederholen", "retrying": "Wiederholen",
"queued": "Warteschlange" "queued": "In der Warteschlange"
}, },
"state_attributes": { "state_attributes": {
"question": { "question": {
@@ -182,16 +217,16 @@
"name": "Temperatur" "name": "Temperatur"
}, },
"max_tokens": { "max_tokens": {
"name": "Max. Token" "name": "Max Tokens"
}, },
"system_prompt": { "system_prompt": {
"name": "Systemprompt" "name": "Systemaufforderung"
}, },
"response_time": { "response_time": {
"name": "Letzte Antwortzeit" "name": "Letzte Antwortzeit"
}, },
"total_responses": { "total_responses": {
"name": "Gesamtzahl der Antworten" "name": "Gesamtantworten"
}, },
"error_count": { "error_count": {
"name": "Fehleranzahl" "name": "Fehleranzahl"
@@ -203,19 +238,19 @@
"name": "API-Status" "name": "API-Status"
}, },
"tokens_used": { "tokens_used": {
"name": "Verwendete Token insgesamt" "name": "Gesamte verwendete Tokens"
}, },
"average_response_time": { "average_response_time": {
"name": "Durchschnittliche Antwortzeit" "name": "Durchschnittliche Antwortzeit"
}, },
"last_request_time": { "last_request_time": {
"name": "Zeitpunkt der letzten Anfrage" "name": "Letzte Anfragezeit"
}, },
"is_processing": { "is_processing": {
"name": "Verarbeitungsstatus" "name": "Verarbeitungsstatus"
}, },
"is_rate_limited": { "is_rate_limited": {
"name": "Ratenlimit-Status" "name": "Rate-limitiert Status"
}, },
"is_maintenance": { "is_maintenance": {
"name": "Wartungsstatus" "name": "Wartungsstatus"
@@ -224,25 +259,25 @@
"name": "API-Version" "name": "API-Version"
}, },
"endpoint_status": { "endpoint_status": {
"name": "Endpunkt-Status" "name": "Endpunktstatus"
}, },
"performance_metrics": { "performance_metrics": {
"name": "Leistungsmetriken" "name": "Leistungskennzahlen"
}, },
"history_size": { "history_size": {
"name": "Verlaufsgröße" "name": "Größe des Verlaufs"
}, },
"uptime": { "uptime": {
"name": "Betriebszeit" "name": "Betriebszeit"
}, },
"total_tokens": { "total_tokens": {
"name": "Gesamtzahl der Token" "name": "Gesamte Tokens"
}, },
"prompt_tokens": { "prompt_tokens": {
"name": "Prompt-Token" "name": "Eingabe Tokens"
}, },
"completion_tokens": { "completion_tokens": {
"name": "Completion-Token" "name": "Vervollständigungs Tokens"
}, },
"successful_requests": { "successful_requests": {
"name": "Erfolgreiche Anfragen" "name": "Erfolgreiche Anfragen"
@@ -6,7 +6,24 @@
"description": "Choose which AI service provider to use for this instance.", "description": "Choose which AI service provider to use for this instance.",
"data": { "data": {
"api_provider": "API Provider", "api_provider": "API Provider",
"context_messages": "Number of context messages to retain (1-20)" "context_messages": "Number of context messages to retain (1-20)",
"max_history_size": "Maximum conversation history size (1-100)"
}
},
"provider": {
"title": "Provider Settings",
"description": "Provide connection details for your chosen AI provider.",
"data": {
"name": "Instance name (e.g., 'GPT Assistant', 'Claude Helper')",
"api_key": "API key for authentication",
"model": "AI model to use",
"api_endpoint": "Custom API endpoint URL (optional)",
"temperature": "Response creativity (0-2, lower = more focused)",
"max_tokens": "Maximum response length (1-100000 tokens)",
"request_interval": "Minimum time between requests (0.1-60 seconds)",
"api_timeout": "API request timeout in seconds (5-600)",
"context_messages": "Number of context messages to retain (1-20)",
"max_history_size": "Maximum conversation history size (1-100)"
} }
}, },
"user": { "user": {
@@ -17,16 +34,20 @@
"api_key": "API key for authentication", "api_key": "API key for authentication",
"model": "AI model to use", "model": "AI model to use",
"temperature": "Response creativity (0-2, lower = more focused)", "temperature": "Response creativity (0-2, lower = more focused)",
"max_tokens": "Maximum response length (1-4096 tokens)", "max_tokens": "Maximum response length (1-100000 tokens)",
"api_endpoint": "Custom API endpoint URL (optional)", "api_endpoint": "Custom API endpoint URL (optional)",
"api_provider": "API Provider", "api_provider": "API Provider",
"request_interval": "Minimum time between requests (0.1-60 seconds)", "request_interval": "Minimum time between requests (0.1-60 seconds)",
"api_timeout": "API request timeout in seconds (5-600)",
"context_messages": "Number of context messages to retain (1-20)", "context_messages": "Number of context messages to retain (1-20)",
"max_history_size": "Maximum conversation history size (1-100)" "max_history_size": "Maximum conversation history size (1-100)"
} }
} }
}, },
"error": { "error": {
"history_storage_error": "Failed to initialize history storage. Check permissions.",
"history_rotation_error": "Error during history file rotation.",
"history_file_access_error": "Cannot access history storage directory.",
"name_exists": "An instance with this name already exists", "name_exists": "An instance with this name already exists",
"invalid_name": "Invalid instance name", "invalid_name": "Invalid instance name",
"invalid_auth": "Authentication failed - check your API key", "invalid_auth": "Authentication failed - check your API key",
@@ -45,6 +66,9 @@
"empty": "Name cannot be empty", "empty": "Name cannot be empty",
"invalid_characters": "Name can only contain letters, numbers, spaces, underscores and hyphens", "invalid_characters": "Name can only contain letters, numbers, spaces, underscores and hyphens",
"name_too_long": "Name must be 50 characters or less" "name_too_long": "Name must be 50 characters or less"
},
"abort": {
"already_configured": "Instance already configured"
} }
}, },
"options": { "options": {
@@ -55,18 +79,29 @@
"data": { "data": {
"model": "AI model", "model": "AI model",
"temperature": "Response creativity (0-2)", "temperature": "Response creativity (0-2)",
"max_tokens": "Maximum response length (1-4096)", "max_tokens": "Maximum response length (1-100000)",
"request_interval": "Minimum request interval (0.1-60 seconds)", "request_interval": "Minimum request interval (0.1-60 seconds)",
"api_timeout": "API request timeout in seconds (5-600)",
"context_messages": "Number of previous messages to include in context (1-20)", "context_messages": "Number of previous messages to include in context (1-20)",
"max_history_size": "Maximum conversation history size (1-100)" "max_history_size": "Maximum conversation history size (1-100)"
} }
} }
} }
}, },
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (compatible)",
"anthropic": "Anthropic (compatible)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": { "services": {
"ask_question": { "ask_question": {
"name": "Ask Question (HA Text AI)", "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.", "description": "Send a question to the AI model and receive a detailed response. This service now returns response data directly, eliminating the need for separate text sensors and the 255-character limitation. The response will also be stored in the conversation history.",
"fields": { "fields": {
"instance": { "instance": {
"name": "Instance", "name": "Instance",
@@ -94,7 +129,7 @@
}, },
"max_tokens": { "max_tokens": {
"name": "Max Tokens", "name": "Max Tokens",
"description": "Maximum length of the response (1-4096 tokens)" "description": "Maximum length of the response (1-100000 tokens)"
} }
} }
}, },
@@ -0,0 +1,301 @@
{
"config": {
"step": {
"provider": {
"title": "Seleccionar proveedor de IA",
"description": "Elige qué proveedor de servicio de IA utilizar para esta instancia.",
"data": {
"api_provider": "Proveedor de API",
"context_messages": "Número de mensajes de contexto a retener (1-20)",
"max_history_size": "Tamaño máximo del historial de conversación (1-100)"
}
},
"provider": {
"title": "Configuración del proveedor",
"description": "Proporciona los detalles de conexión para tu proveedor de IA elegido.",
"data": {
"name": "Nombre de la instancia (por ejemplo, 'Asistente GPT', 'Ayudante Claude')",
"api_key": "Clave API para autenticación",
"model": "Modelo de IA a utilizar",
"api_endpoint": "URL del endpoint de API personalizado (opcional)",
"temperature": "Creatividad de la respuesta (0-2, menor = más enfocado)",
"max_tokens": "Longitud máxima de la respuesta (1-100000 tokens)",
"request_interval": "Tiempo mínimo entre solicitudes (0.1-60 segundos)",
"api_timeout": "Tiempo de espera de solicitud API en segundos (5-600)",
"context_messages": "Número de mensajes de contexto a retener (1-20)",
"max_history_size": "Tamaño máximo del historial de conversación (1-100)"
}
},
"user": {
"title": "Configurar instancia de IA de texto de HA",
"description": "Configura una nueva instancia de asistente de IA con tu proveedor seleccionado.",
"data": {
"name": "Nombre de la instancia (por ejemplo, 'Asistente GPT', 'Ayudante Claude')",
"api_key": "Clave API para autenticación",
"model": "Modelo de IA a utilizar",
"temperature": "Creatividad de la respuesta (0-2, menor = más enfocado)",
"max_tokens": "Longitud máxima de la respuesta (1-100000 tokens)",
"api_endpoint": "URL del endpoint de API personalizado (opcional)",
"api_provider": "Proveedor de API",
"request_interval": "Tiempo mínimo entre solicitudes (0.1-60 segundos)",
"api_timeout": "Tiempo de espera de solicitud API en segundos (5-600)",
"context_messages": "Número de mensajes de contexto a retener (1-20)",
"max_history_size": "Tamaño máximo del historial de conversación (1-100)"
}
}
},
"error": {
"history_storage_error": "Error al inicializar el almacenamiento del historial. Verifica los permisos.",
"history_rotation_error": "Error durante la rotación del archivo de historial.",
"history_file_access_error": "No se puede acceder al directorio de almacenamiento del historial.",
"name_exists": "Ya existe una instancia con este nombre",
"invalid_name": "Nombre de instancia no válido",
"invalid_auth": "La autenticación falló - verifica tu clave API",
"invalid_api_key": "Clave API no válida - verifica tus credenciales",
"cannot_connect": "Error al conectar con el servicio de API",
"invalid_model": "El modelo seleccionado no está disponible",
"rate_limit": "Límite de tasa excedido",
"context_length": "Longitud del contexto excedida",
"rate_limit_exceeded": "Límite de tasa de API excedido",
"maintenance": "El servicio está en mantenimiento",
"invalid_response": "Respuesta de API no válida recibida",
"api_error": "Ocurrió un error en el servicio de API",
"timeout": "Se agotó el tiempo de la solicitud",
"invalid_instance": "Instancia no válida especificada",
"unknown": "Ocurrió un error inesperado",
"empty": "El nombre no puede estar vacío",
"invalid_characters": "El nombre solo puede contener letras, números, espacios, guiones bajos y guiones",
"name_too_long": "El nombre debe tener 50 caracteres o menos"
},
"abort": {
"already_configured": "Instancia ya configurada"
}
},
"options": {
"step": {
"init": {
"title": "Actualizar configuración de la instancia",
"description": "Modifica la configuración para esta instancia de asistente de IA.",
"data": {
"model": "Modelo de IA",
"temperature": "Creatividad de la respuesta (0-2)",
"max_tokens": "Longitud máxima de la respuesta (1-100000)",
"request_interval": "Intervalo mínimo de solicitud (0.1-60 segundos)",
"api_timeout": "Tiempo de espera de solicitud API en segundos (5-600)",
"context_messages": "Número de mensajes anteriores a incluir en el contexto (1-20)",
"max_history_size": "Tamaño máximo del historial de conversación (1-100)"
}
}
}
},
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (compatible)",
"anthropic": "Anthropic (compatible)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": {
"ask_question": {
"name": "Hacer Pregunta (HA Text AI)",
"description": "Envía una pregunta al modelo de IA y recibe una respuesta detallada. Este servicio ahora devuelve datos de respuesta directamente, eliminando la necesidad de sensores de texto separados y la limitación de 255 caracteres. La respuesta también se almacenará en el historial de conversación.",
"fields": {
"instance": {
"name": "Instancia",
"description": "Nombre de la instancia de IA de Texto de HA a utilizar"
},
"question": {
"name": "Pregunta",
"description": "Tu pregunta o solicitud para el asistente de IA"
},
"context_messages": {
"name": "Mensajes de Contexto",
"description": "Número de mensajes anteriores a incluir en el contexto (1-20)"
},
"system_prompt": {
"name": "Indicaciones del Sistema",
"description": "Indicaciones opcionales para establecer contexto para esta pregunta específica"
},
"model": {
"name": "Modelo",
"description": "Selecciona el modelo de IA a utilizar (opcional, anula la configuración predeterminada)"
},
"temperature": {
"name": "Temperatura",
"description": "Controla la creatividad de la respuesta (0.0-2.0)"
},
"max_tokens": {
"name": "Máx. Tokens",
"description": "Longitud máxima de la respuesta (1-100000 tokens)"
}
}
},
"clear_history": {
"name": "Borrar Historial",
"description": "Elimina todas las preguntas y respuestas almacenadas del historial de conversación",
"fields": {
"instance": {
"name": "Instancia",
"description": "Nombre de la instancia de IA de Texto de HA para borrar el historial"
}
}
},
"get_history": {
"name": "Obtener Historial",
"description": "Recupera el historial de conversación con filtrado y ordenación opcionales",
"fields": {
"instance": {
"name": "Instancia",
"description": "Nombre de la instancia de IA de Texto de HA para obtener historial"
},
"limit": {
"name": "Límite",
"description": "Número de conversaciones a devolver (1-100)"
},
"filter_model": {
"name": "Filtrar Modelo",
"description": "Filtrar conversaciones por modelo de IA específico"
},
"start_date": {
"name": "Fecha de Inicio",
"description": "Filtrar conversaciones a partir de esta fecha/hora"
},
"include_metadata": {
"name": "Incluir Metadatos",
"description": "Incluir información adicional como tokens utilizados, tiempo de respuesta, etc."
},
"sort_order": {
"name": "Orden de Clasificación",
"description": "Orden de clasificación para los resultados (más recientes o más antiguos primero)"
}
}
},
"set_system_prompt": {
"name": "Establecer Indicaciones del Sistema",
"description": "Establecer instrucciones de comportamiento del sistema predeterminadas para todas las futuras conversaciones",
"fields": {
"instance": {
"name": "Instancia",
"description": "Nombre de la instancia de IA de Texto de HA para establecer indicaciones del sistema"
},
"prompt": {
"name": "Indicaciones del Sistema",
"description": "Instrucciones que definen cómo debe comportarse y responder la IA"
}
}
}
},
"entity": {
"sensor": {
"ha_text_ai": {
"name": "{name}",
"state": {
"ready": "Listo",
"processing": "Procesando",
"error": "Error",
"disconnected": "Desconectado",
"rate_limited": "Limitado por tasa",
"maintenance": "Mantenimiento",
"initializing": "Inicializando",
"retrying": "Reintentando",
"queued": "En cola"
},
"state_attributes": {
"question": {
"name": "Última Pregunta"
},
"response": {
"name": "Última Respuesta"
},
"model": {
"name": "Modelo Actual"
},
"temperature": {
"name": "Temperatura"
},
"max_tokens": {
"name": "Máx. Tokens"
},
"system_prompt": {
"name": "Indicaciones del Sistema"
},
"response_time": {
"name": "Último Tiempo de Respuesta"
},
"total_responses": {
"name": "Total de Respuestas"
},
"error_count": {
"name": "Conteo de Errores"
},
"last_error": {
"name": "Último Error"
},
"api_status": {
"name": "Estado de API"
},
"tokens_used": {
"name": "Total de Tokens Usados"
},
"average_response_time": {
"name": "Tiempo de Respuesta Promedio"
},
"last_request_time": {
"name": "Último Tiempo de Solicitud"
},
"is_processing": {
"name": "Estado de Procesamiento"
},
"is_rate_limited": {
"name": "Estado Limitado por Tasa"
},
"is_maintenance": {
"name": "Estado de Mantenimiento"
},
"api_version": {
"name": "Versión de API"
},
"endpoint_status": {
"name": "Estado del Endpoint"
},
"performance_metrics": {
"name": "Métricas de Rendimiento"
},
"history_size": {
"name": "Tamaño del Historial"
},
"uptime": {
"name": "Tiempo de Actividad"
},
"total_tokens": {
"name": "Total de Tokens"
},
"prompt_tokens": {
"name": "Tokens de Solicitud"
},
"completion_tokens": {
"name": "Tokens de Finalización"
},
"successful_requests": {
"name": "Solicitudes Exitosas"
},
"failed_requests": {
"name": "Solicitudes Fallidas"
},
"average_latency": {
"name": "Latencia Promedio"
},
"max_latency": {
"name": "Latencia Máxima"
},
"min_latency": {
"name": "Latencia Mínima"
}
}
}
}
}
}
@@ -0,0 +1,292 @@
{
"config": {
"step": {
"provider": {
"title": "प्रदाता सेटिंग्स",
"description": "आपके द्वारा चुने गए एआई प्रदाता के लिए कनेक्शन विवरण प्रदान करें।",
"data": {
"name": "उदाहरण का नाम (जैसे, 'जीपीटी सहायक', 'क्लॉड सहायक')",
"api_key": "प्रमाणीकरण के लिए एपीआई कुंजी",
"model": "उपयोग करने के लिए एआई मॉडल",
"api_endpoint": "कस्टम एपीआई एंडपॉइंट यूआरएल (वैकल्पिक)",
"temperature": "प्रतिक्रिया की रचनात्मकता (0-2, कम = अधिक केंद्रित)",
"max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)",
"request_interval": "अनुरोधों के बीच न्यूनतम समय (0.1-60 सेकंड)",
"api_timeout": "एपीआई अनुरोध टाइमआउट सेकंड में (5-600)",
"context_messages": "रखने के लिए संदर्भ संदेशों की संख्या (1-20)",
"max_history_size": "अधिकतम बातचीत इतिहास आकार (1-100)"
}
},
"user": {
"title": "एचए टेक्स्ट एआई उदाहरण कॉन्फ़िगर करें",
"description": "अपने चुने हुए प्रदाता के साथ एक नया एआई सहायक उदाहरण सेट करें।",
"data": {
"name": "उदाहरण का नाम (जैसे, 'जीपीटी सहायक', 'क्लॉड सहायक')",
"api_key": "प्रमाणीकरण के लिए एपीआई कुंजी",
"model": "उपयोग करने के लिए एआई मॉडल",
"temperature": "प्रतिक्रिया की रचनात्मकता (0-2, कम = अधिक केंद्रित)",
"max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)",
"api_endpoint": "कस्टम एपीआई एंडपॉइंट यूआरएल (वैकल्पिक)",
"api_provider": "एपीआई प्रदाता",
"request_interval": "अनुरोधों के बीच न्यूनतम समय (0.1-60 सेकंड)",
"api_timeout": "एपीआई अनुरोध टाइमआउट सेकंड में (5-600)",
"context_messages": "रखने के लिए संदर्भ संदेशों की संख्या (1-20)",
"max_history_size": "अधिकतम बातचीत इतिहास आकार (1-100)"
}
}
},
"error": {
"history_storage_error": "इतिहास भंडारण प्रारंभ करने में विफल। अनुमतियों की जांच करें।",
"history_rotation_error": "इतिहास फ़ाइल घुमाने के दौरान त्रुटि।",
"history_file_access_error": "इतिहास भंडारण निर्देशिका तक पहुंच नहीं है।",
"name_exists": "इस नाम के साथ एक उदाहरण पहले से मौजूद है",
"invalid_name": "अमान्य उदाहरण नाम",
"invalid_auth": "प्रमाणीकरण विफल - अपनी एपीआई कुंजी की जांच करें",
"invalid_api_key": "अमान्य एपीआई कुंजी - कृपया अपनी क्रेडेंशियल्स की पुष्टि करें",
"cannot_connect": "एपीआई सेवा से कनेक्ट करने में विफल",
"invalid_model": "चुना हुआ मॉडल उपलब्ध नहीं है",
"rate_limit": "रेट सीमा पार",
"context_length": "संदर्भ लंबाई पार",
"rate_limit_exceeded": "एपीआई रेट सीमा पार",
"maintenance": "सेवा रखरखाव में है",
"invalid_response": "अमान्य एपीआई प्रतिक्रिया प्राप्त हुई",
"api_error": "एपीआई सेवा में त्रुटि हुई",
"timeout": "अनुरोध समय सीमा समाप्त",
"invalid_instance": "अमान्य उदाहरण निर्दिष्ट किया गया",
"unknown": "अप्रत्याशित त्रुटि हुई",
"empty": "नाम खाली नहीं हो सकता",
"invalid_characters": "नाम में केवल अक्षर, अंक, रिक्त स्थान, अंडरस्कोर और हाइफन हो सकते हैं",
"name_too_long": "नाम 50 अक्षरों या उससे कम होना चाहिए"
},
"abort": {
"already_configured": "उदाहरण पहले से कॉन्फ़िगर किया गया है"
}
},
"options": {
"step": {
"init": {
"title": "उदाहरण सेटिंग्स अपडेट करें",
"description": "इस एआई सहायक उदाहरण के लिए सेटिंग्स संशोधित करें।",
"data": {
"model": "एआई मॉडल",
"temperature": "प्रतिक्रिया की रचनात्मकता (0-2)",
"max_tokens": "प्रतिक्रिया की अधिकतम लंबाई (1-100000)",
"request_interval": "न्यूनतम अनुरोध अंतराल (0.1-60 सेकंड)",
"api_timeout": "एपीआई अनुरोध टाइमआउट सेकंड में (5-600)",
"context_messages": "संदर्भ में शामिल करने के लिए पिछले संदेशों की संख्या (1-20)",
"max_history_size": "अधिकतम बातचीत इतिहास आकार (1-100)"
}
}
}
},
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (अनुकूलित)",
"anthropic": "Anthropic (अनुकूलित)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": {
"ask_question": {
"name": "प्रश्न पूछें (HA Text AI)",
"description": "AI मॉडल को प्रश्न भेजें और विस्तृत उत्तर प्राप्त करें। यह सेवा अब प्रत्यक्ष रूप से प्रतिक्रिया डेटा वापस करती है, अलग टेक्स्ट सेंसर की आवश्यकता और 255 वर्ण की सीमा को समाप्त करती है। प्रतिक्रिया को बातचीत के इतिहास में भी संग्रहीत किया जाएगा।",
"fields": {
"instance": {
"name": "उदाहरण",
"description": "उपयोग करने के लिए एचए टेक्स्ट एआई उदाहरण का नाम"
},
"question": {
"name": "प्रश्न",
"description": "आपका प्रश्न या एआई सहायक के लिए प्रॉम्प्ट"
},
"context_messages": {
"name": "संदर्भ संदेश",
"description": "संदर्भ में शामिल करने के लिए पिछले संदेशों की संख्या (1-20)"
},
"system_prompt": {
"name": "सिस्टम प्रॉम्प्ट",
"description": "इस विशेष प्रश्न के लिए संदर्भ सेट करने के लिए वैकल्पिक सिस्टम प्रॉम्प्ट"
},
"model": {
"name": "मॉडल",
"description": "उपयोग करने के लिए एआई मॉडल का चयन करें (वैकल्पिक, डिफ़ॉल्ट सेटिंग को ओवरराइड करता है)"
},
"temperature": {
"name": "तापमान",
"description": "प्रतिक्रिया की रचनात्मकता को नियंत्रित करता है (0.0-2.0)"
},
"max_tokens": {
"name": "अधिकतम टोकन",
"description": "प्रतिक्रिया की अधिकतम लंबाई (1-100000 टोकन)"
}
}
},
"clear_history": {
"name": "इतिहास साफ करें",
"description": "बातचीत के इतिहास से सभी संग्रहीत प्रश्नों और प्रतिक्रियाओं को हटाएं",
"fields": {
"instance": {
"name": "उदाहरण",
"description": "इतिहास साफ़ करने के लिए एचए टेक्स्ट एआई उदाहरण का नाम"
}
}
},
"get_history": {
"name": "इतिहास प्राप्त करें",
"description": "वैकल्पिक फ़िल्टरिंग और छंटाई के साथ बातचीत का इतिहास प्राप्त करें",
"fields": {
"instance": {
"name": "उदाहरण",
"description": "इतिहास प्राप्त करने के लिए एचए टेक्स्ट एआई उदाहरण का नाम"
},
"limit": {
"name": "सीमा",
"description": "वापस करने के लिए बातचीत की संख्या (1-100)"
},
"filter_model": {
"name": "फिल्टर मॉडल",
"description": "विशिष्ट एआई मॉडल द्वारा बातचीत को फ़िल्टर करें"
},
"start_date": {
"name": "शुरुआत की तारीख",
"description": "इस दिन/समय से शुरू होने वाली बातचीत को फ़िल्टर करें"
},
"include_metadata": {
"name": "मेटाडेटा शामिल करें",
"description": "उपयोग किए गए टोकन, प्रतिक्रिया समय आदि जैसी अतिरिक्त जानकारी शामिल करें।"
},
"sort_order": {
"name": "छंटाई क्रम",
"description": "परिणामों के लिए छंटाई क्रम (नवीनतम या सबसे पुराना पहले)"
}
}
},
"set_system_prompt": {
"name": "सिस्टम प्रॉम्प्ट सेट करें",
"description": "सभी भविष्य की बातचीत के लिए डिफ़ॉल्ट सिस्टम व्यवहार निर्देश सेट करें",
"fields": {
"instance": {
"name": "उदाहरण",
"description": "सिस्टम प्रॉम्प्ट सेट करने के लिए एचए टेक्स्ट एआई उदाहरण का नाम"
},
"prompt": {
"name": "सिस्टम प्रॉम्प्ट",
"description": "निर्देश जो यह परिभाषित करते हैं कि एआई को कैसे व्यवहार करना चाहिए और प्रतिक्रिया देनी चाहिए"
}
}
}
},
"entity": {
"sensor": {
"ha_text_ai": {
"name": "{name}",
"state": {
"ready": "तैयार",
"processing": "प्रसंस्करण",
"error": "त्रुटि",
"disconnected": "असंयुक्त",
"rate_limited": "रेट सीमित",
"maintenance": "रखरखाव",
"initializing": "प्रारंभिककरण",
"retrying": "पुनः प्रयास कर रहा है",
"queued": "क्यू में"
},
"state_attributes": {
"question": {
"name": "अंतिम प्रश्न"
},
"response": {
"name": "अंतिम प्रतिक्रिया"
},
"model": {
"name": "वर्तमान मॉडल"
},
"temperature": {
"name": "तापमान"
},
"max_tokens": {
"name": "अधिकतम टोकन"
},
"system_prompt": {
"name": "सिस्टम प्रॉम्प्ट"
},
"response_time": {
"name": "अंतिम प्रतिक्रिया का समय"
},
"total_responses": {
"name": "कुल प्रतिक्रियाएं"
},
"error_count": {
"name": "त्रुटियों की संख्या"
},
"last_error": {
"name": "अंतिम त्रुटि"
},
"api_status": {
"name": "एपीआई स्थिति"
},
"tokens_used": {
"name": "कुल उपयोग किए गए टोकन"
},
"average_response_time": {
"name": "औसत प्रतिक्रिया समय"
},
"last_request_time": {
"name": "अंतिम अनुरोध का समय"
},
"is_processing": {
"name": "प्रसंस्करण स्थिति"
},
"is_rate_limited": {
"name": "रेट सीमित स्थिति"
},
"is_maintenance": {
"name": "रखरखाव स्थिति"
},
"api_version": {
"name": "एपीआई संस्करण"
},
"endpoint_status": {
"name": "एंडपॉइंट स्थिति"
},
"performance_metrics": {
"name": "प्रदर्शन मैट्रिक्स"
},
"history_size": {
"name": "इतिहास का आकार"
},
"uptime": {
"name": "अपटाइम"
},
"total_tokens": {
"name": "कुल टोकन"
},
"prompt_tokens": {
"name": "प्रॉम्प्ट टोकन"
},
"completion_tokens": {
"name": "पूर्णता टोकन"
},
"successful_requests": {
"name": "सफल अनुरोध"
},
"failed_requests": {
"name": "विफल अनुरोध"
},
"average_latency": {
"name": "औसत विलंबता"
},
"max_latency": {
"name": "अधिकतम विलंबता"
},
"min_latency": {
"name": "न्यूनतम विलंबता"
}
}
}
}
}
}
@@ -0,0 +1,301 @@
{
"config": {
"step": {
"provider": {
"title": "Seleziona fornitore AI",
"description": "Scegli quale fornitore di servizi AI utilizzare per questa istanza.",
"data": {
"api_provider": "Fornitore API",
"context_messages": "Numero di messaggi di contesto da mantenere (1-20)",
"max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
}
},
"provider": {
"title": "Impostazioni fornitore",
"description": "Fornisci i dettagli di connessione per il tuo fornitore di AI scelto.",
"data": {
"name": "Nome dell'istanza (es. 'Assistente GPT', 'Aiuto Claude')",
"api_key": "Chiave API per l'autenticazione",
"model": "Modello AI da utilizzare",
"api_endpoint": "URL dell'endpoint API personalizzato (opzionale)",
"temperature": "Creatività della risposta (0-2, più basso = più focalizzato)",
"max_tokens": "Lunghezza massima della risposta (1-100000 token)",
"request_interval": "Tempo minimo tra le richieste (0.1-60 secondi)",
"api_timeout": "Timeout della richiesta API in secondi (5-600)",
"context_messages": "Numero di messaggi di contesto da mantenere (1-20)",
"max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
}
},
"user": {
"title": "Configura istanza AI di testo HA",
"description": "Imposta una nuova istanza di assistente AI con il fornitore selezionato.",
"data": {
"name": "Nome dell'istanza (es. 'Assistente GPT', 'Aiuto Claude')",
"api_key": "Chiave API per l'autenticazione",
"model": "Modello AI da utilizzare",
"temperature": "Creatività della risposta (0-2, più basso = più focalizzato)",
"max_tokens": "Lunghezza massima della risposta (1-100000 token)",
"api_endpoint": "URL dell'endpoint API personalizzato (opzionale)",
"api_provider": "Fornitore API",
"request_interval": "Tempo minimo tra le richieste (0.1-60 secondi)",
"api_timeout": "Timeout della richiesta API in secondi (5-600)",
"context_messages": "Numero di messaggi di contesto da mantenere (1-20)",
"max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
}
}
},
"error": {
"history_storage_error": "Impossibile inizializzare la memorizzazione della cronologia. Controlla i permessi.",
"history_rotation_error": "Errore durante la rotazione del file di cronologia.",
"history_file_access_error": "Impossibile accedere alla directory di memorizzazione della cronologia.",
"name_exists": "Esiste già un'istanza con questo nome",
"invalid_name": "Nome dell'istanza non valido",
"invalid_auth": "Autenticazione fallita - controlla la tua chiave API",
"invalid_api_key": "Chiave API non valida - verifica le tue credenziali",
"cannot_connect": "Impossibile connettersi al servizio API",
"invalid_model": "Il modello selezionato non è disponibile",
"rate_limit": "Limite di frequenza superato",
"context_length": "Lunghezza del contesto superata",
"rate_limit_exceeded": "Limite di frequenza API superato",
"maintenance": "Il servizio è in manutenzione",
"invalid_response": "Risposta API non valida ricevuta",
"api_error": "Si è verificato un errore nel servizio API",
"timeout": "Richiesta scaduta",
"invalid_instance": "Istanze specificata non valida",
"unknown": "Si è verificato un errore imprevisto",
"empty": "Il nome non può essere vuoto",
"invalid_characters": "Il nome può contenere solo lettere, numeri, spazi, trattini bassi e trattini",
"name_too_long": "Il nome deve essere lungo 50 caratteri o meno"
},
"abort": {
"already_configured": "Istanze già configurata"
}
},
"options": {
"step": {
"init": {
"title": "Aggiorna impostazioni dell'istanza",
"description": "Modifica le impostazioni per questa istanza di assistente AI.",
"data": {
"model": "Modello AI",
"temperature": "Creatività della risposta (0-2)",
"max_tokens": "Lunghezza massima della risposta (1-100000)",
"request_interval": "Intervallo minimo di richiesta (0.1-60 secondi)",
"api_timeout": "Timeout della richiesta API in secondi (5-600)",
"context_messages": "Numero di messaggi precedenti da includere nel contesto (1-20)",
"max_history_size": "Dimensione massima della cronologia delle conversazioni (1-100)"
}
}
}
},
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (compatibile)",
"anthropic": "Anthropic (compatibile)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": {
"ask_question": {
"name": "Fai una domanda (HA Text AI)",
"description": "Invia una domanda al modello AI e ricevi una risposta dettagliata. Questo servizio ora restituisce i dati di risposta direttamente, eliminando la necessità di sensori di testo separati e la limitazione di 255 caratteri. La risposta sarà anche memorizzata nella cronologia delle conversazioni.",
"fields": {
"instance": {
"name": "Istanze",
"description": "Nome dell'istanza HA Text AI da utilizzare"
},
"question": {
"name": "Domanda",
"description": "La tua domanda o richiesta per l'assistente AI"
},
"context_messages": {
"name": "Messaggi di contesto",
"description": "Numero di messaggi precedenti da includere nel contesto (1-20)"
},
"system_prompt": {
"name": "Prompt di sistema",
"description": "Prompt di sistema opzionale per impostare il contesto per questa specifica domanda"
},
"model": {
"name": "Modello",
"description": "Seleziona il modello AI da utilizzare (opzionale, sovrascrive l'impostazione predefinita)"
},
"temperature": {
"name": "Temperatura",
"description": "Controlla la creatività della risposta (0.0-2.0)"
},
"max_tokens": {
"name": "Token massimi",
"description": "Lunghezza massima della risposta (1-100000 token)"
}
}
},
"clear_history": {
"name": "Cancella cronologia",
"description": "Elimina tutte le domande e risposte memorizzate dalla cronologia delle conversazioni",
"fields": {
"instance": {
"name": "Istanze",
"description": "Nome dell'istanza HA Text AI per cui cancellare la cronologia"
}
}
},
"get_history": {
"name": "Ottieni cronologia",
"description": "Recupera la cronologia delle conversazioni con opzioni di filtro e ordinamento",
"fields": {
"instance": {
"name": "Istanze",
"description": "Nome dell'istanza HA Text AI da cui recuperare la cronologia"
},
"limit": {
"name": "Limite",
"description": "Numero di conversazioni da restituire (1-100)"
},
"filter_model": {
"name": "Filtra modello",
"description": "Filtra le conversazioni per modello AI specifico"
},
"start_date": {
"name": "Data di inizio",
"description": "Filtra le conversazioni a partire da questa data/ora"
},
"include_metadata": {
"name": "Includi metadati",
"description": "Includi informazioni aggiuntive come token utilizzati, tempo di risposta, ecc."
},
"sort_order": {
"name": "Ordine di ordinamento",
"description": "Ordine di ordinamento per i risultati (più recenti o più vecchi per primi)"
}
}
},
"set_system_prompt": {
"name": "Imposta prompt di sistema",
"description": "Imposta le istruzioni di comportamento predefinite per tutte le future conversazioni",
"fields": {
"instance": {
"name": "Istanze",
"description": "Nome dell'istanza HA Text AI per cui impostare il prompt di sistema"
},
"prompt": {
"name": "Prompt di sistema",
"description": "Istruzioni che definiscono come l'AI dovrebbe comportarsi e rispondere"
}
}
}
},
"entity": {
"sensor": {
"ha_text_ai": {
"name": "{name}",
"state": {
"ready": "Pronto",
"processing": "Elaborazione",
"error": "Errore",
"disconnected": "Disconnesso",
"rate_limited": "Limite di frequenza",
"maintenance": "Manutenzione",
"initializing": "Inizializzazione",
"retrying": "Riprova",
"queued": "In coda"
},
"state_attributes": {
"question": {
"name": "Ultima domanda"
},
"response": {
"name": "Ultima risposta"
},
"model": {
"name": "Modello attuale"
},
"temperature": {
"name": "Temperatura"
},
"max_tokens": {
"name": "Token massimi"
},
"system_prompt": {
"name": "Prompt di sistema"
},
"response_time": {
"name": "Ultimo tempo di risposta"
},
"total_responses": {
"name": "Risposte totali"
},
"error_count": {
"name": "Conteggio errori"
},
"last_error": {
"name": "Ultimo errore"
},
"api_status": {
"name": "Stato API"
},
"tokens_used": {
"name": "Token totali utilizzati"
},
"average_response_time": {
"name": "Tempo medio di risposta"
},
"last_request_time": {
"name": "Ultimo tempo di richiesta"
},
"is_processing": {
"name": "Stato di elaborazione"
},
"is_rate_limited": {
"name": "Stato limite di frequenza"
},
"is_maintenance": {
"name": "Stato di manutenzione"
},
"api_version": {
"name": "Versione API"
},
"endpoint_status": {
"name": "Stato dell'endpoint"
},
"performance_metrics": {
"name": "Metriche di prestazione"
},
"history_size": {
"name": "Dimensione della cronologia"
},
"uptime": {
"name": "Tempo di attività"
},
"total_tokens": {
"name": "Token totali"
},
"prompt_tokens": {
"name": "Token di prompt"
},
"completion_tokens": {
"name": "Token di completamento"
},
"successful_requests": {
"name": "Richieste riuscite"
},
"failed_requests": {
"name": "Richieste fallite"
},
"average_latency": {
"name": "Latenza media"
},
"max_latency": {
"name": "Latenza massima"
},
"min_latency": {
"name": "Latenza minima"
}
}
}
}
}
}
@@ -2,99 +2,134 @@
"config": { "config": {
"step": { "step": {
"provider": { "provider": {
"title": "Выбор поставщика ИИ", "title": "Выбор провайдера ИИ",
"description": "Выберите поставщика услуг ИИ для этой инстанции.", "description": "Выберите сервис искусственного интеллекта для этого экземпляра.",
"data": { "data": {
"api_provider": оставщик API", "api_provider": ровайдер API",
"context_messages": "Количество контекстных сообщений для сохранения (1-20)" "context_messages": "Количество сохраняемых контекстных сообщений (1-20)",
"max_history_size": "Максимальный размер истории разговора (1-100)"
}
},
"provider": {
"title": "Настройки провайдера",
"description": "Укажите параметры подключения для выбранного провайдера ИИ.",
"data": {
"name": "Название экземпляра (например, 'GPT Помощник', 'Клод Ассистент')",
"api_key": "API-ключ для аутентификации",
"model": "Модель ИИ для использования",
"api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)",
"temperature": "Креативность ответа (0-2, меньше = более сфокусированно)",
"max_tokens": "Максимальная длина ответа (1-100000 токенов)",
"request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
"api_timeout": "Таймаут API-запроса в секундах (5-600)",
"context_messages": "Количество сохраняемых контекстных сообщений (1-20)",
"max_history_size": "Максимальный размер истории разговора (1-100)"
} }
}, },
"user": { "user": {
"title": "Настройка инстанции HA Text AI", "title": "Настройка экземпляра текстового ИИ для Home Assistant",
"description": "Настройте новую инстанцию помощника ИИ с выбранным вами поставщиком.", "description": "Настройте новый экземпляр ИИ-помощника с выбранным провайдером.",
"data": { "data": {
"name": "Имя инстанции (например, 'GPT Assistant', 'Claude Helper')", "name": "Название экземпляра (например, 'GPT Помощник', 'Клод Ассистент')",
"api_key": "API-ключ для аутентификации", "api_key": "API-ключ для аутентификации",
"model": "Используемая модель ИИ", "model": "Модель ИИ для использования",
"temperature": "Креативность ответа (0-2, чем ниже, тем больше фокусировки)", "temperature": "Креативность ответа (0-2, меньше = более сфокусированно)",
"max_tokens": "Максимальная длина ответа (1-4096 токенов)", "max_tokens": "Максимальная длина ответа (1-100000 токенов)",
"api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)", "api_endpoint": "Пользовательский URL-адрес конечной точки API (необязательно)",
"api_provider": оставщик API", "api_provider": ровайдер API",
"request_interval": "Минимальное время между запросами (0,1-60 секунд)", "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
"context_messages": "Количество контекстных сообщений для сохранения (1-20)", "api_timeout": "Таймаут API-запроса в секундах (5-600)",
"context_messages": "Количество сохраняемых контекстных сообщений (1-20)",
"max_history_size": "Максимальный размер истории разговора (1-100)" "max_history_size": "Максимальный размер истории разговора (1-100)"
} }
} }
}, },
"error": { "error": {
"name_exists": "Инстанция с таким именем уже существует", "history_storage_error": "Не удалось инициализировать хранилище истории. Проверьте разрешения.",
"invalid_name": "Некорректное имя инстанции", "history_rotation_error": "Ошибка при ротации файла истории.",
"invalid_auth": "Аутентификация не удалась - проверьте ваш API-ключ", "history_file_access_error": "Невозможно получить доступ к директории хранения истории.",
"invalid_api_key": "Неверный API-ключ - проверьте ваши учетные данные", "name_exists": "Экземпляр с таким именем уже существует",
"cannot_connect": "Не удалось подключиться к службе API", "invalid_name": "Недопустимое имя экземпляра",
"invalid_auth": "Ошибка аутентификации - проверьте API-ключ",
"invalid_api_key": "Недопустимый API-ключ - пожалуйста, проверьте учетные данные",
"cannot_connect": "Не удалось подключиться к сервису API",
"invalid_model": "Выбранная модель недоступна", "invalid_model": "Выбранная модель недоступна",
"rate_limit": "Превышен лимит запросов", "rate_limit": "Превышен лимит запросов",
"context_length": "Превышена длина контекста", "context_length": "Превышена длина контекста",
"rate_limit_exceeded": "Превышен лимит запросов API", "rate_limit_exceeded": "Превышен лимит запросов API",
"maintenance": "Сервис находится на техническом обслуживании", "maintenance": "Сервис находится на техническом обслуживании",
"invalid_response": "Получен неверный ответ API", "invalid_response": "Получен некорректный ответ API",
"api_error": "Произошла ошибка службы API", "api_error": "Произошла ошибка сервиса API",
"timeout": "Запрос превысил время ожидания", "timeout": "Время ожидания запроса истекло",
"invalid_instance": "Указана неверная инстанция", "invalid_instance": "Указан некорректный экземпляр",
"unknown": "Произошла непредвиденная ошибка", "unknown": "Произошла непредвиденная ошибка",
"empty": "Имя не может быть пустым", "empty": "Имя не может быть пустым",
"invalid_characters": "Имя может содержать только буквы, цифры, пробелы, подчеркивания и дефисы", "invalid_characters": "Имя может содержать только буквы, цифры, пробелы, подчеркивания и дефисы",
"name_too_long": "Имя должно быть не более 50 символов" "name_too_long": "Имя должно быть не длиннее 50 символов"
},
"abort": {
"already_configured": "Экземпляр уже настроен"
} }
}, },
"options": { "options": {
"step": { "step": {
"init": { "init": {
"title": "Обновление настроек инстанции", "title": "Обновление настроек экземпляра",
"description": "Измените настройки для этой инстанции помощника ИИ.", "description": "Измените настройки для этого экземпляра ИИ-помощника.",
"data": { "data": {
"model": "Модель ИИ", "model": "Модель ИИ",
"temperature": "Креативность ответа (0-2)", "temperature": "Креативность ответа (0-2)",
"max_tokens": "Максимальная длина ответа (1-4096)", "max_tokens": "Максимальная длина ответа (1-100000)",
"request_interval": "Минимальный интервал между запросами (0,1-60 секунд)", "request_interval": "Минимальный интервал между запросами (0.1-60 секунд)",
"api_timeout": "Таймаут API-запроса в секундах (5-600)",
"context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)", "context_messages": "Количество предыдущих сообщений для включения в контекст (1-20)",
"max_history_size": "Максимальный размер истории разговора (1-100)" "max_history_size": "Максимальный размер истории разговора (1-100)"
} }
} }
} }
}, },
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (совместимый)",
"anthropic": "Anthropic (совместимый)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": { "services": {
"ask_question": { "ask_question": {
"name": "Задать вопрос (HA Text AI)", "name": "Задать вопрос (HA Text AI)",
"description": "Отправьте вопрос модели ИИ и получите подробный ответ. Ответ будет сохранен в истории разговора и может быть извлечен позже.", "description": "Отправить вопрос модели ИИ и получить подробный ответ. Сервис теперь возвращает данные ответа напрямую, устраняя необходимость в отдельных текстовых сенсорах и ограничение в 255 символов. Ответ также будет сохранен в истории разговора.",
"fields": { "fields": {
"instance": { "instance": {
"name": "Инстанция", "name": "Экземпляр",
"description": "Имя используемой инстанции HA Text AI" "description": "Название экземпляра текстового ИИ для использования"
}, },
"question": { "question": {
"name": "Вопрос", "name": "Вопрос",
"description": "Ваш вопрос или запрос к помощнику ИИ" "description": "Ваш вопрос или запрос к ИИ-помощнику"
}, },
"context_messages": { "context_messages": {
"name": "Контекстные сообщения", "name": "Контекстные сообщения",
"description": "Количество предыдущих сообщений для включения в контекст (1-20)" "description": "Количество предыдущих сообщений для включения в контекст (1-20)"
}, },
"system_prompt": { "system_prompt": {
"name": "Системный запрос", "name": "Системный промпт",
"description": "Необязательный системный запрос для установки контекста для этого конкретного вопроса" "description": "Необязательный системный промпт для установки контекста для этого конкретного вопроса"
}, },
"model": { "model": {
"name": "Модель", "name": "Модель",
"description": "Выберите модель ИИ для использования (необязательно, переопределяет настройку по умолчанию)" "description": "Выберите модель ИИ для использования (необязательно, переопределяет настройки по умолчанию)"
}, },
"temperature": { "temperature": {
"name": "Температура", "name": "Температура",
"description": "Управляет креативностью ответа (0.0-2.0)" "description": "Управление креативностью ответа (0.0-2.0)"
}, },
"max_tokens": { "max_tokens": {
"name": "Макс. токенов", "name": "Максимум токенов",
"description": "Максимальная длина ответа (1-4096 токенов)" "description": "Максимальная длина ответа (1-100000 токенов)"
} }
} }
}, },
@@ -103,18 +138,18 @@
"description": "Удалить все сохраненные вопросы и ответы из истории разговора", "description": "Удалить все сохраненные вопросы и ответы из истории разговора",
"fields": { "fields": {
"instance": { "instance": {
"name": "Инстанция", "name": "Экземпляр",
"description": "Имя инстанции HA Text AI, для которой нужно очистить историю" "description": "Название экземпляра текстового ИИ для очистки истории"
} }
} }
}, },
"get_history": { "get_history": {
"name": "Получить историю", "name": "Получить историю",
"description": "Извлечь историю разговора с возможностью фильтрации и сортировки", "description": "Получить историю разговора с дополнительной фильтрацией и сортировкой",
"fields": { "fields": {
"instance": { "instance": {
"name": "Инстанция", "name": "Экземпляр",
"description": "Имя инстанции HA Text AI, из которой нужно получить историю" "description": "Название экземпляра текстового ИИ для получения истории"
}, },
"limit": { "limit": {
"name": "Лимит", "name": "Лимит",
@@ -122,33 +157,33 @@
}, },
"filter_model": { "filter_model": {
"name": "Фильтр модели", "name": "Фильтр модели",
"description": "Фильтрация разговоров по определенной модели ИИ" "description": "Фильтрация разговоров по конкретной модели ИИ"
}, },
"start_date": { "start_date": {
"name": "Дата начала", "name": "Начальная дата",
"description": "Фильтрация разговоров, начиная с этой даты/времени" "description": "Фильтрация разговоров, начиная с указанной даты/времени"
}, },
"include_metadata": { "include_metadata": {
"name": "Включить метаданные", "name": "Включить метаданные",
"description": "Включить дополнительную информацию, такую как использованные токены, время ответа и т.д." "description": "Включить дополнительную информацию, например, использованные токены, время ответа и т.д."
}, },
"sort_order": { "sort_order": {
"name": "Порядок сортировки", "name": "Порядок сортировки",
"description": "Порядок сортировки результатов (самые новые или самые старые)" "description": "Порядок сортировки результатов (сначала новые или старые)"
} }
} }
}, },
"set_system_prompt": { "set_system_prompt": {
"name": "Установить системный запрос", "name": "Установить системный промпт",
"description": "Установить инструкции по умолчанию для поведения системы для всех будущих разговоров", "description": "Установить инструкции по умолчанию для поведения ИИ во всех будущих разговорах",
"fields": { "fields": {
"instance": { "instance": {
"name": "Инстанция", "name": "Экземпляр",
"description": "Имя инстанции HA Text AI, для которой нужно установить системный запрос" "description": "Название экземпляра текстового ИИ для установки системного промпта"
}, },
"prompt": { "prompt": {
"name": "Системный запрос", "name": "Системный промпт",
"description": "Инструкции, определяющие, как ИИ должен себя вести и отвечать" "description": "Инструкции, определяющие, как ИИ должен вести себя и отвечать"
} }
} }
} }
@@ -182,10 +217,10 @@
"name": "Температура" "name": "Температура"
}, },
"max_tokens": { "max_tokens": {
"name": "Макс. токенов" "name": "Максимум токенов"
}, },
"system_prompt": { "system_prompt": {
"name": "Системный запрос" "name": "Системный промпт"
}, },
"response_time": { "response_time": {
"name": "Время последнего ответа" "name": "Время последнего ответа"
@@ -203,7 +238,7 @@
"name": "Статус API" "name": "Статус API"
}, },
"tokens_used": { "tokens_used": {
"name": "Использовано токенов всего" "name": "Всего использовано токенов"
}, },
"average_response_time": { "average_response_time": {
"name": "Среднее время ответа" "name": "Среднее время ответа"
@@ -215,10 +250,10 @@
"name": "Статус обработки" "name": "Статус обработки"
}, },
"is_rate_limited": { "is_rate_limited": {
"name": "Статус ограничения запросов" "name": "Статус лимита запросов"
}, },
"is_maintenance": { "is_maintenance": {
"name": "Статус технического обслуживания" "name": "Статус обслуживания"
}, },
"api_version": { "api_version": {
"name": "Версия API" "name": "Версия API"
@@ -227,7 +262,7 @@
"name": "Статус конечной точки" "name": "Статус конечной точки"
}, },
"performance_metrics": { "performance_metrics": {
"name": "Метрики производительности" "name": "Показатели производительности"
}, },
"history_size": { "history_size": {
"name": "Размер истории" "name": "Размер истории"
@@ -239,16 +274,16 @@
"name": "Всего токенов" "name": "Всего токенов"
}, },
"prompt_tokens": { "prompt_tokens": {
"name": "Токены запроса" "name": "Токены промпта"
}, },
"completion_tokens": { "completion_tokens": {
"name": "Токены завершения" "name": "Токены завершения"
}, },
"successful_requests": { "successful_requests": {
"name": "Успешных запросов" "name": "Успешные запросы"
}, },
"failed_requests": { "failed_requests": {
"name": "Неудачных запросов" "name": "Неудачные запросы"
}, },
"average_latency": { "average_latency": {
"name": "Средняя задержка" "name": "Средняя задержка"
@@ -0,0 +1,292 @@
{
"config": {
"step": {
"provider": {
"title": "Подешавања провајдера",
"description": "Обезбедите детаље о вези за изабраног AI провајдера.",
"data": {
"name": "Име инстанце (нпр. 'GPT Асистент', 'Claude Помоћник')",
"api_key": "API кључ за аутентификацију",
"model": "AI модел који ће се користити",
"api_endpoint": "Прилагођени URL API крајње тачке (опционо)",
"temperature": "Креативност одговора (0-2, нижа = фокусираније)",
"max_tokens": "Максимална дужина одговора (1-100000 токена)",
"request_interval": "Минимално време између захтева (0.1-60 секунди)",
"api_timeout": "Временско ограничење API захтева у секундама (5-600)",
"context_messages": "Број контекстуалних порука које треба задржати (1-20)",
"max_history_size": "Максимална величина историје разговора (1-100)"
}
},
"user": {
"title": "Конфигуришите HA Text AI инстанцу",
"description": "Подесите нову AI асистент инстанцу са изабраним провајдером.",
"data": {
"name": "Име инстанце (нпр. 'GPT Асистент', 'Claude Помоћник')",
"api_key": "API кључ за аутентификацију",
"model": "AI модел који ће се користити",
"temperature": "Креативност одговора (0-2, нижа = фокусираније)",
"max_tokens": "Максимална дужина одговора (1-100000 токена)",
"api_endpoint": "Прилагођени URL API крајње тачке (опционо)",
"api_provider": "API провајдер",
"request_interval": "Минимално време између захтева (0.1-60 секунди)",
"api_timeout": "Временско ограничење API захтева у секундама (5-600)",
"context_messages": "Број контекстуалних порука које треба задржати (1-20)",
"max_history_size": "Максимална величина историје разговора (1-100)"
}
}
},
"error": {
"history_storage_error": "Неуспела инициализација складишта историје. Проверите дозволе.",
"history_rotation_error": "Грешка током ротације историјских датотека.",
"history_file_access_error": "Немогуће приступити директоријуму складишта историје.",
"name_exists": "Инстанца са овим именом већ постоји",
"invalid_name": "Неважеће име инстанце",
"invalid_auth": "Аутентификација није успела - проверите ваш API кључ",
"invalid_api_key": "Неважећи API кључ - молимо проверите ваше акредитиве",
"cannot_connect": "Неуспело повезивање са API сервисом",
"invalid_model": "Изабрани модел није доступан",
"rate_limit": "Пређена граница захтева",
"context_length": "Дужина контекста пређена",
"rate_limit_exceeded": "Пређена граница API захтева",
"maintenance": "Сервис је у одржавању",
"invalid_response": "Примљен неважећи API одговор",
"api_error": "Дошло је до грешке у API сервису",
"timeout": "Време захтева је истекло",
"invalid_instance": "Неважећа инстанца је назначена",
"unknown": "Дошло је до неочекиване грешке",
"empty": "Име не може бити празно",
"invalid_characters": "Име може садржавати само слова, цифре, размаке, подцрта и цртице",
"name_too_long": "Име мора бити 50 знакова или мање"
},
"abort": {
"already_configured": "Инстанца је већ конфигурисана"
}
},
"options": {
"step": {
"init": {
"title": "Ажурирајте подешавања инстанце",
"description": "Измените подешавања за ову AI асистент инстанцу.",
"data": {
"model": "AI модел",
"temperature": "Креативност одговора (0-2)",
"max_tokens": "Максимална дужина одговора (1-100000)",
"request_interval": "Минимално време између захтева (0.1-60 секунди)",
"api_timeout": "Временско ограничење API захтева у секундама (5-600)",
"context_messages": "Број претходних порука које треба укључити у контекст (1-20)",
"max_history_size": "Максимална величина историје разговора (1-100)"
}
}
}
},
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI (компатибилан)",
"anthropic": "Anthropic (компатибилан)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": {
"ask_question": {
"name": "Поставите питање (HA Text AI)",
"description": "Пошаљите питање AI моделу и добијте детаљан одговор. Овај сервис сада враћа податке одговора директно, елиминишући потребу за засебним текстуалним сензорима и ограничење од 255 карактера. Одговор ће такође бити сачуван у историји разговора.",
"fields": {
"instance": {
"name": "Инстанца",
"description": "Име HA Text AI инстанце коју ћете користити"
},
"question": {
"name": "Питање",
"description": "Ваше питање или упит за AI асистента"
},
"context_messages": {
"name": "Контекстуалне поруке",
"description": "Број претходних порука које треба укључити у контекст (1-20)"
},
"system_prompt": {
"name": "Системски упит",
"description": "Опционални системски упит за постављање контекста за ово конкретно питање"
},
"model": {
"name": "Модел",
"description": "Изаберите AI модел који ћете користити (опционо, надмашује подразумевану поставку)"
},
"temperature": {
"name": "Температура",
"description": "Контролише креативност одговора (0.0-2.0)"
},
"max_tokens": {
"name": "Максимални токени",
"description": "Максимална дужина одговора (1-100000 токена)"
}
}
},
"clear_history": {
"name": "Обриши историју",
"description": "Избришите све сачуване питања и одговоре из историје разговора",
"fields": {
"instance": {
"name": "Инстанца",
"description": "Име HA Text AI инстанце за коју желите да обришете историју"
}
}
},
"get_history": {
"name": "Добијте историју",
"description": "Повратите историју разговора уз опционално филтрирање и сортирање",
"fields": {
"instance": {
"name": "Инстанца",
"description": "Име HA Text AI инстанце из које желите да добијете историју"
},
"limit": {
"name": "Лимит",
"description": "Број разговора које треба вратити (1-100)"
},
"filter_model": {
"name": "Филтер модел",
"description": "Филтрирајте разговоре по одређеном AI моделу"
},
"start_date": {
"name": "Датум почетка",
"description": "Филтрирајте разговоре који почињу од овог датума/времена"
},
"include_metadata": {
"name": "Укључи метаподатке",
"description": "Укључите додатне информације као што су коришћени токени, време одговора итд."
},
"sort_order": {
"name": "Редослед сортирања",
"description": "Редослед сортирања за резултате (најновији или најстарији први)"
}
}
},
"set_system_prompt": {
"name": "Поставите системски упит",
"description": "Поставите подразумеване инструкције за системско понашање за све будуће разговоре",
"fields": {
"instance": {
"name": "Инстанца",
"description": "Име HA Text AI инстанце за коју желите да поставите системски упит"
},
"prompt": {
"name": "Системски упит",
"description": "Инструкције које дефинишу како AI треба да се понаша и одговара"
}
}
}
},
"entity": {
"sensor": {
"ha_text_ai": {
"name": "{name}",
"state": {
"ready": "Спремно",
"processing": "Обрада",
"error": "Грешка",
"disconnected": "Прекључено",
"rate_limited": "Ограничење захтева",
"maintenance": "Одржавање",
"initializing": "Инициализује се",
"retrying": "Покушава поново",
"queued": "У реду"
},
"state_attributes": {
"question": {
"name": "Последње питање"
},
"response": {
"name": "Последњи одговор"
},
"model": {
"name": "Тренутни модел"
},
"temperature": {
"name": "Температура"
},
"max_tokens": {
"name": "Максимални токени"
},
"system_prompt": {
"name": "Системски упит"
},
"response_time": {
"name": "Време последњег одговора"
},
"total_responses": {
"name": "Укупно одговора"
},
"error_count": {
"name": "Број грешака"
},
"last_error": {
"name": "Последња грешка"
},
"api_status": {
"name": "Статус API"
},
"tokens_used": {
"name": "Укупно коришћени токени"
},
"average_response_time": {
"name": "Просечно време одговора"
},
"last_request_time": {
"name": "Време последњег захтева"
},
"is_processing": {
"name": "Статус обраде"
},
"is_rate_limited": {
"name": "Статус ограничења захтева"
},
"is_maintenance": {
"name": "Статус одржавања"
},
"api_version": {
"name": "Верзија API"
},
"endpoint_status": {
"name": "Статус крајње тачке"
},
"performance_metrics": {
"name": "Перформансне метрике"
},
"history_size": {
"name": "Величина историје"
},
"uptime": {
"name": "Уптиме"
},
"total_tokens": {
"name": "Укупно токена"
},
"prompt_tokens": {
"name": "Токени упита"
},
"completion_tokens": {
"name": "Токени завршетка"
},
"successful_requests": {
"name": "Успешни захтеви"
},
"failed_requests": {
"name": "Неуспешни захтеви"
},
"average_latency": {
"name": "Просечна латенција"
},
"max_latency": {
"name": "Максимална латенција"
},
"min_latency": {
"name": "Минимална латенција"
}
}
}
}
}
}
@@ -0,0 +1,292 @@
{
"config": {
"step": {
"provider": {
"title": "提供者设置",
"description": "提供所选AI提供者的连接详细信息。",
"data": {
"name": "实例名称(例如,'GPT助手''Claude助手'",
"api_key": "用于身份验证的API密钥",
"model": "要使用的AI模型",
"api_endpoint": "自定义API端点URL(可选)",
"temperature": "响应创造力(0-2,越低越专注)",
"max_tokens": "最大响应长度(1-100000个标记)",
"request_interval": "请求之间的最小时间(0.1-60秒)",
"api_timeout": "API请求超时时间(5-600秒)",
"context_messages": "保留的上下文消息数量(1-20",
"max_history_size": "最大对话历史大小(1-100"
}
},
"user": {
"title": "配置HA文本AI实例",
"description": "使用所选提供者设置新的AI助手实例。",
"data": {
"name": "实例名称(例如,'GPT助手''Claude助手'",
"api_key": "用于身份验证的API密钥",
"model": "要使用的AI模型",
"temperature": "响应创造力(0-2,越低越专注)",
"max_tokens": "最大响应长度(1-100000个标记)",
"api_endpoint": "自定义API端点URL(可选)",
"api_provider": "API提供者",
"request_interval": "请求之间的最小时间(0.1-60秒)",
"api_timeout": "API请求超时时间(5-600秒)",
"context_messages": "保留的上下文消息数量(1-20",
"max_history_size": "最大对话历史大小(1-100"
}
}
},
"error": {
"history_storage_error": "无法初始化历史存储。检查权限。",
"history_rotation_error": "历史文件轮换时出错。",
"history_file_access_error": "无法访问历史存储目录。",
"name_exists": "具有此名称的实例已存在",
"invalid_name": "无效的实例名称",
"invalid_auth": "身份验证失败 - 检查您的API密钥",
"invalid_api_key": "无效的API密钥 - 请验证您的凭据",
"cannot_connect": "无法连接到API服务",
"invalid_model": "所选模型不可用",
"rate_limit": "超出速率限制",
"context_length": "上下文长度超出限制",
"rate_limit_exceeded": "API速率限制超出",
"maintenance": "服务正在维护中",
"invalid_response": "收到无效的API响应",
"api_error": "发生API服务错误",
"timeout": "请求超时",
"invalid_instance": "指定的实例无效",
"unknown": "发生意外错误",
"empty": "名称不能为空",
"invalid_characters": "名称只能包含字母、数字、空格、下划线和连字符",
"name_too_long": "名称必须少于50个字符"
},
"abort": {
"already_configured": "实例已配置"
}
},
"options": {
"step": {
"init": {
"title": "更新实例设置",
"description": "修改此AI助手实例的设置。",
"data": {
"model": "AI模型",
"temperature": "响应创造力(0-2",
"max_tokens": "最大响应长度(1-100000",
"request_interval": "最小请求间隔(0.1-60秒)",
"api_timeout": "API请求超时时间(5-600秒)",
"context_messages": "要包含在上下文中的先前消息数量(1-20)",
"max_history_size": "最大对话历史大小(1-100"
}
}
}
},
"selector": {
"api_provider": {
"options": {
"openai": "OpenAI(兼容)",
"anthropic": "Anthropic(兼容)",
"deepseek": "DeepSeek",
"gemini": "Google Gemini"
}
}
},
"services": {
"ask_question": {
"name": "提问 (HA Text AI)",
"description": "向AI模型发送问题并获得详细回答。此服务现在直接返回响应数据,消除了对单独文本传感器的需要和255字符限制。响应也将存储在对话历史中。",
"fields": {
"instance": {
"name": "实例",
"description": "要使用的HA文本AI实例名称"
},
"question": {
"name": "问题",
"description": "您对AI助手的问题或提示"
},
"context_messages": {
"name": "上下文消息",
"description": "要包含在上下文中的先前消息数量(1-20)"
},
"system_prompt": {
"name": "系统提示",
"description": "可选的系统提示,用于为此特定问题设置上下文"
},
"model": {
"name": "模型",
"description": "选择要使用的AI模型(可选,覆盖默认设置)"
},
"temperature": {
"name": "温度",
"description": "控制响应创造力(0.0-2.0"
},
"max_tokens": {
"name": "最大标记数",
"description": "响应的最大长度(1-100000个标记)"
}
}
},
"clear_history": {
"name": "清除历史",
"description": "删除对话历史中存储的所有问题和响应",
"fields": {
"instance": {
"name": "实例",
"description": "要清除历史的HA文本AI实例名称"
}
}
},
"get_history": {
"name": "获取历史",
"description": "检索对话历史,可选的过滤和排序",
"fields": {
"instance": {
"name": "实例",
"description": "要获取历史的HA文本AI实例名称"
},
"limit": {
"name": "限制",
"description": "要返回的对话数量(1-100"
},
"filter_model": {
"name": "过滤模型",
"description": "按特定AI模型过滤对话"
},
"start_date": {
"name": "开始日期",
"description": "过滤从此日期/时间开始的对话"
},
"include_metadata": {
"name": "包含元数据",
"description": "包括额外信息,如使用的标记、响应时间等。"
},
"sort_order": {
"name": "排序顺序",
"description": "结果的排序顺序(最新或最旧优先)"
}
}
},
"set_system_prompt": {
"name": "设置系统提示",
"description": "为所有未来的对话设置默认的系统行为指令",
"fields": {
"instance": {
"name": "实例",
"description": "要设置系统提示的HA文本AI实例名称"
},
"prompt": {
"name": "系统提示",
"description": "定义AI应如何行为和响应的指令"
}
}
}
},
"entity": {
"sensor": {
"ha_text_ai": {
"name": "{name}",
"state": {
"ready": "准备就绪",
"processing": "处理中",
"error": "错误",
"disconnected": "已断开连接",
"rate_limited": "速率限制",
"maintenance": "维护中",
"initializing": "初始化中",
"retrying": "重试中",
"queued": "排队中"
},
"state_attributes": {
"question": {
"name": "最后问题"
},
"response": {
"name": "最后响应"
},
"model": {
"name": "当前模型"
},
"temperature": {
"name": "温度"
},
"max_tokens": {
"name": "最大标记数"
},
"system_prompt": {
"name": "系统提示"
},
"response_time": {
"name": "最后响应时间"
},
"total_responses": {
"name": "总响应数"
},
"error_count": {
"name": "错误计数"
},
"last_error": {
"name": "最后错误"
},
"api_status": {
"name": "API状态"
},
"tokens_used": {
"name": "总使用标记数"
},
"average_response_time": {
"name": "平均响应时间"
},
"last_request_time": {
"name": "最后请求时间"
},
"is_processing": {
"name": "处理状态"
},
"is_rate_limited": {
"name": "速率限制状态"
},
"is_maintenance": {
"name": "维护状态"
},
"api_version": {
"name": "API版本"
},
"endpoint_status": {
"name": "端点状态"
},
"performance_metrics": {
"name": "性能指标"
},
"history_size": {
"name": "历史大小"
},
"uptime": {
"name": "正常运行时间"
},
"total_tokens": {
"name": "总标记数"
},
"prompt_tokens": {
"name": "提示标记数"
},
"completion_tokens": {
"name": "完成标记数"
},
"successful_requests": {
"name": "成功请求数"
},
"failed_requests": {
"name": "失败请求数"
},
"average_latency": {
"name": "平均延迟"
},
"max_latency": {
"name": "最大延迟"
},
"min_latency": {
"name": "最小延迟"
}
}
}
}
}
}
+2 -2
View File
@@ -1,5 +1,5 @@
{ {
"name": "HA text AI", "name": "HA Text AI",
"render_readme": true, "render_readme": true,
"homeassistant": "2024.11.0" "homeassistant": "2024.12.0"
} }
+28 -23
View File
@@ -1,25 +1,30 @@
``` ```
ha-text-ai/ ha_text_ai/
├── __init__.py
├── custom_components/ ├── api_client.py
├── ha_text_ai/ ├── config_flow.py
│ ├── __init__.py ├── const.py
│ ├── config_flow.py ├── coordinator.py
├── coordinator.py ├── icons
│ ├── manifest.json │   ├── dark_icon.png
│ ├── sensor.py │   ├── dark_icon@2x.png
│ ├── services.yaml │   ├── dark_logo.png
│ ├── const.py │   ├── dark_logo@2x.png
│ └── api_client.py │   ├── icon.png
   ├── icon@2x.png
├── translations/ │   ├── logo.png
│ ├── en.json │   └── logo@2x.png
│ ├── de.json ├── manifest.json
│ └── ru.json ├── sensor.py
├── services.yaml
└── icons/ └── translations
├── icon.png ├── de.json
├── icon@2x.png ├── en.json
├── logo.png ├── es.json
└── logo@2x.png ├── hi.json
├── it.json
├── ru.json
├── sr.json
└── zh.json
``` ```