### OpenAI GPT-4 Configuration Example

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

An example configuration block for setting up the OpenAI GPT-4 provider. It includes essential parameters such as API key, model name, temperature, and token limits for both input and output.

```yaml
Provider: OpenAI
API Key: sk-proj-xxxxxxxxxxxxxxxxxxxxxxx
Model: gpt-4o-mini
Temperature: 0.7
Max Input Tokens: 1000
Max Output Tokens: 800
```

--------------------------------

### OpenRouter Multi-Model Setup Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Sets up connection to OpenRouter, supporting multiple models. Requires an API key and specifies the model, temperature, and token limits. Includes an optional reasoning token budget.

```yaml
Provider: OpenRouter
API Key: sk-or-xxxxxxxxxxxxxxxxxxxxxxx
Model: meta-llama/llama-4-maverick:free
Temperature: 0.7
Max Input Tokens: 500
Max Output Tokens: 500
Reasoning Max Tokens: 100  # Optional reasoning budget
```

--------------------------------

### Google Gemini Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Example configuration for using Google Gemini as the AI provider. This includes the API key, specific Gemini model, temperature, and input/output token limits.

```yaml
Provider: Google
API Key: AIzaSyxxxxxxxxxxxxx
Model: gemini-2.0-flash
Temperature: 0.7
Max Input Tokens: 1000
Max Output Tokens: 800
```

--------------------------------

### OpenAI Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Example configuration for setting up the AI Automation Suggester to use OpenAI as the AI provider. It includes essential parameters like API key, model name, temperature, and token limits.

```yaml
Provider: OpenAI
API Key: sk-proj-xxxxxxxxxxxxx
Model: gpt-4o-mini
Temperature: 0.7
Max Input Tokens: 500
Max Output Tokens: 500
```

--------------------------------

### Suggestions Sensor Template Example (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This YAML snippet shows an example of how to use a Jinja2 template to create a sensor that displays the 'yaml_block' attribute from the AI suggestions sensor.

```yaml
# Entity: sensor.ai_automation_suggestions_{provider_name}
# States:
#   - "No Suggestions" (no suggestions yet)
#   - "Suggestions Available" (suggestions exist)
#   - "New Suggestions Available" (timestamp changed)

# Attributes:
#   suggestions: Full AI response text
#   description: Text portion (without YAML block)
#   yaml_block: Extracted YAML code
#   last_update: ISO timestamp
#   entities_processed: List of entity IDs analyzed
#   entities_processed_count: Integer count
#   provider: Provider name

# Template Usage:
template:
  - sensor:
      - name: "Latest Automation YAML"
        state: >
          {{ state_attr('sensor.ai_automation_suggestions_openai', 'yaml_block') }}
```

--------------------------------

### Configuration Entry Options for AI Providers

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Explains how to configure AI provider settings through the Home Assistant Integrations UI. Shows example options for OpenAI, including API key, model, temperature, and token limits. Notes the priority of configuration sources.

```yaml
# Editable via Settings → Integrations → Configure
# Provider-specific (example for OpenAI):
openai_api_key: string (password)
openai_model: string (default: gpt-4o-mini)
openai_temperature: float (0.0-2.0, default: 0.7)
max_input_tokens: integer (min: 100, default: 500)
max_output_tokens: integer (min: 100, default: 500)

# Priority: entry.options > entry.data > default
```

--------------------------------

### Anthropic Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Configuration example for integrating with Anthropic's AI models. This specifies the provider, API key, model, temperature, and token limits suitable for Anthropic services.

```yaml
Provider: Anthropic
API Key: sk-ant-xxxxxxxxxxxxx
Model: claude-3-7-sonnet-latest
Temperature: 0.7
Max Input Tokens: 800
Max Output Tokens: 600
```

--------------------------------

### HACS Custom Repository Setup

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This snippet shows how to add the AI Automation Suggester as a custom repository in Home Assistant Community Store (HACS). This is the initial step for installing the integration.

```yaml
Repository: https://github.com/ITSpecialist111/ai_automation_suggester
Category: Integration
```

--------------------------------

### LocalAI Private Setup Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Sets up a connection to a self-hosted LocalAI instance. Requires the IP address and port of the LocalAI server, and specifies the model, temperature, and token limits. HTTPS usage can be toggled.

```yaml
Provider: LocalAI
IP Address: 192.168.1.50
Port: 8080
Use HTTPS: false
Model: llama3
Temperature: 0.8
Max Input Tokens: 600
Max Output Tokens: 500
```

--------------------------------

### Python Coordinator Data Structure Example

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Defines the structure for storing AI automation suggestions and related metadata. Includes fields for the AI's full response, extracted text, YAML code blocks, timestamps, processed entities, provider details, and error messages.

```python
{
    "suggestions": str,  # Full AI response
    "description": str,  # Text without YAML block
    "yaml_block": str,  # Extracted YAML code
    "last_update": str,  # ISO timestamp
    "entities_processed": list,  # Entity IDs analyzed
    "provider": str,  # Provider name
    "last_error": str | None  # Error message if failed
}
```

--------------------------------

### Service Call to Analyze All Entities

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This service call instructs the AI Automation Suggester to perform a comprehensive analysis of all entities in the smart home setup, with an option to limit the number of sampled entities.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  all_entities: true
  entity_limit: 300
```

--------------------------------

### Service Call for Domain-Focused Analysis

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This service call allows for targeted analysis of specific entity domains (e.g., light, switch, sensor). It can also include a custom prompt to guide the AI's suggestions, along with an entity limit.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  domains:
    - light
    - switch
    - sensor
  entity_limit: 100
  custom_prompt: "Focus on energy-saving automations that turn off lights and switches when rooms are unoccupied."
```

--------------------------------

### Implement Throttling for AI Analysis Automation

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

An example Home Assistant automation that throttles AI analysis calls to prevent excessive API usage. It triggers on state changes and ensures a minimum interval between successful runs.

```yaml
# Avoid excessive API calls with throttling
automation:
  - alias: Throttled AI Analysis
    trigger:
      - platform: event
        event_type: state_changed
    condition:
      - condition: template
        value_template: >
          {{ (now() - state_attr('automation.throttled_ai_analysis', 'last_triggered') | default(now() - timedelta(hours=2))).total_seconds() > 3600 }}
    action:
      - service: ai_automation_suggester.generate_suggestions
        data: {}
```

--------------------------------

### Groq Fast Inference Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Configures the connection to Groq for fast AI inference. Requires a Groq API key and specifies the model, temperature, and token limits.

```yaml
Provider: Groq
API Key: gsk_xxxxxxxxxxxxxxxxxxxxxxx
Model: llama3-8b-8192
Temperature: 0.5
Max Input Tokens: 500
Max Output Tokens: 400
```

--------------------------------

### Adjust Token Budget and Entity Limits

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Instructions for increasing token limits and adjusting entity limits to resolve 'Token Budget Exceeded' errors. Also shows how to check actual usage statistics via sensor attributes.

```yaml
# If prompts are truncated, adjust limits:
# Settings → Integrations → AI Automation Suggester → Configure
Max Input Tokens: 2000  # Increase from default 500
Entity Limit: 100  # Reduce from default 200

# Check actual usage in attributes:
{{ state_attr('sensor.ai_automation_suggestions_openai', 'entities_processed_count') }}
```

--------------------------------

### Azure OpenAI Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Sets up a connection to Azure OpenAI services. Requires Azure resource details, deployment ID, and API key. Configurable temperature and token limits.

```yaml
Provider: OpenAI Azure
Endpoint: myresource.openai.azure.com
Deployment ID: gpt-4-deployment
API Version: 2024-02-15-preview
API Key: xxxxxxxxxxxxxxxxxxxxxxx
Temperature: 0.7
Max Input Tokens: 1000
Max Output Tokens: 800
```

--------------------------------

### Compare AI Provider Suggestions

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

An automation demonstrating how to use multiple AI providers for comparison. It triggers a suggestion generation service for OpenAI and then Anthropic, with a delay in between.

```yaml
automation:
  - alias: Compare Provider Suggestions
    trigger:
      - platform: time
        at: "09:00:00"
    action:
      - service: ai_automation_suggester.generate_suggestions
        target:
          entity_id: sensor.ai_automation_suggestions_openai
        data:
          all_entities: true
      - delay: 30
      - service: ai_automation_suggester.generate_suggestions
        target:
          entity_id: sensor.ai_automation_suggestions_anthropic
        data:
          all_entities: true
```

--------------------------------

### Generic OpenAI Compatible Endpoint Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Configures connection to any OpenAI-compatible API endpoint. Requires the endpoint URL, API key, model name, temperature, and token limits.

```yaml
Provider: Generic OpenAI
Endpoint: https://api.custom-provider.com/v1/chat/completions
API Key: custom-key-xxxxxxxxxxxxxxxxxxxxxxx
Model: custom-model-name
Temperature: 0.7
Max Input Tokens: 500
Max Output Tokens: 500
```

--------------------------------

### Mistral AI Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Configures the connection to Mistral AI services. Requires an API key and specifies the model, temperature, and token limits.

```yaml
Provider: Mistral AI
API Key: xxxxxxxxxxxxxxxxxxxxxxx
Model: mistral-medium
Temperature: 0.7
Max Input Tokens: 800
Max Output Tokens: 600
```

--------------------------------

### Configuration Entry Options

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Describes the configurable options for the AI Automation Suggester integration, editable via the UI.

```APIDOC
## Configuration Entry Options

### Description
Editable via Settings → Integrations → Configure. Provider-specific options may apply.

### Method
CONFIGURATION

### Endpoint
Settings → Integrations → AI Automation Suggester → Configure

### Parameters
#### Provider-Specific Options (Example for OpenAI)
- **openai_api_key** (string) - Password - API key for OpenAI
- **openai_model** (string) - Default: gpt-4o-mini - Model to use for OpenAI
- **openai_temperature** (float) - 0.0-2.0, Default: 0.7 - Sampling temperature
- **max_input_tokens** (integer) - Min: 100, Default: 500 - Maximum input tokens
- **max_output_tokens** (integer) - Min: 100, Default: 500 - Maximum output tokens

### Priority
Configuration is applied in the following order: `entry.options` > `entry.data` > `default` values.
```

--------------------------------

### Local Ollama Provider Configuration

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Configuration details for connecting to a local AI model through Ollama. It requires the IP address, port, HTTPS setting, model name, temperature, and specific Ollama parameters.

```yaml
Provider: Ollama
IP Address: 192.168.1.100
Port: 11434
Use HTTPS: false
Model: llama2
Temperature: 0.7
Disable Think Mode: false
Max Input Tokens: 500
Max Output Tokens: 500
```

--------------------------------

### View AI Integration Logs in Home Assistant

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Provides commands to filter Home Assistant logs for the AI Automation Suggester integration and enable debug logging for the component in `configuration.yaml`.

```bash
# Home Assistant logs filtered for integration
grep "ai_automation_suggester" /config/home-assistant.log

# Enable debug logging in configuration.yaml
logger:
  default: info
  logs:
    custom_components.ai_automation_suggester: debug
```

--------------------------------

### generate_suggestions Service API Reference

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Details the parameters for the `generate_suggestions` service, including optional parameters for specifying the provider configuration, custom prompts, entity filtering, and automation analysis settings.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  provider_config: "config_entry_id"  # Optional: Specific provider
  custom_prompt: "string"  # Optional: Custom instructions
  all_entities: boolean  # Optional: Default false (only new entities)
  domains: list  # Optional: Default [] (all domains)
  entity_limit: integer  # Optional: Default 200, Range 50-1000
  automation_read_yaml: boolean  # Optional: Default false
  automation_limit: integer  # Optional: Default 100, Range 10-500

**Parameters:**
- `provider_config`: Config entry ID for targeting specific provider (when multiple configured)
- `custom_prompt`: Additional instructions appended to system prompt
- `all_entities`: If true, analyzes all entities; if false, only new entities since last run
- `domains`: List of entity domain strings to filter (e.g., ["light", "switch"])
- `entity_limit`: Maximum entities to sample and send to AI provider
- `automation_read_yaml`: If true, reads automations.yaml file (high token usage)
- `automation_limit`: Maximum automations to include in analysis

**Returns:** Updates coordinator data and all associated sensors
```

--------------------------------

### Service Call for Climate Optimization Analysis

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This service call directs the AI to focus on climate control automations by analyzing relevant domains like climate, sensor, and weather. It uses a custom prompt to balance comfort and energy efficiency, with a specified entity limit.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  domains:
    - climate
    - sensor
    - weather
  custom_prompt: "Create smart climate control automations based on occupancy, weather forecasts, and temperature sensors. Balance comfort with energy efficiency."
  entity_limit: 200
```

--------------------------------

### AI Security Analysis Script

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A script employing the AI Automation Suggester for security hardening analysis. It targets relevant security domains and includes a custom prompt for detecting threats, implementing defense-in-depth, and ensuring reliability.

```yaml
script:
  ai_security_analysis:
    sequence:
      - service: ai_automation_suggester.generate_suggestions
        data:
          domains: ["binary_sensor", "lock", "alarm_control_panel", "camera"]
          custom_prompt: |
            Review security setup and suggest automations to:
            1. Detect unusual access patterns
            2. Implement defense-in-depth strategies
            3. Add redundant monitoring for critical sensors
            4. Create fail-safe behaviors for network/power loss
            Prioritize reliability and minimize false positives.
          entity_limit: 200
```

--------------------------------

### AI Energy Analysis Script

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A script that utilizes the AI Automation Suggester to analyze energy consumption patterns. It specifies target domains and a custom prompt focused on energy savings and ROI estimation.

```yaml
script:
  ai_energy_analysis:
    sequence:
      - service: ai_automation_suggester.generate_suggestions
        data:
          domains: ["light", "switch", "climate", "sensor"]
          custom_prompt: |
            Analyze energy consumption patterns and suggest automations to:
            1. Reduce vampire power draw
            2. Optimize HVAC scheduling based on occupancy
            3. Implement smart lighting schedules
            4. Add solar production optimization if applicable
            Focus on measurable energy savings with ROI estimates.
          entity_limit: 250
```

--------------------------------

### AI Automation Suggester - Weekly Review Automation (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This automation performs a full system analysis every Sunday at 3 AM. It generates suggestions for all entities, reads automation YAML, and sends a persistent notification upon completion.

```yaml
alias: AI Automation Suggester - Weekly Review
description: Full system analysis every Sunday
trigger:
  - platform: time
    at: "03:00:00"
condition:
  - condition: time
    weekday:
      - sun
action:
  - service: ai_automation_suggester.generate_suggestions
    data:
      all_entities: true
      automation_read_yaml: true
      automation_limit: 100
      entity_limit: 500
  - service: persistent_notification.create
    data:
      title: "Weekly AI Automation Review Complete"
      message: "Check sensor.ai_automation_suggestions_* for recommendations"
      notification_id: "weekly_ai_review"
mode: single
```

--------------------------------

### Debug AI Suggestion Service Call

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Tests the `generate_suggestions` service with specific parameters for debugging. Allows setting entity limits, specifying domains, and providing a custom prompt.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  all_entities: false
  entity_limit: 10  # Very small for testing
  domains:
    - light  # Single domain for simplicity
  custom_prompt: "Just say hello and confirm you can see my lights"
```

--------------------------------

### Calculate Total AI Token Budget

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A template sensor that calculates the total token budget by summing the 'max_input_tokens' and 'max_output_tokens' for a given AI provider. It assumes the existence of 'sensor.max_input_tokens_{provider_name}' and 'sensor.max_output_tokens_{provider_name}' entities.

```yaml
template:
  - sensor:
      - name: "Total AI Token Budget"
        unit_of_measurement: "tokens"
        state: >
          {{ states('sensor.max_input_tokens_openai') | int +
             states('sensor.max_output_tokens_openai') | int }}
```

--------------------------------

### Service Call for Security-Focused Analysis

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This service call focuses the AI's analysis on security-related domains such as binary sensors, alarm control panels, locks, and cameras. It includes a custom prompt to prioritize reliable security automations and an entity limit.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  domains:
    - binary_sensor
    - alarm_control_panel
    - lock
    - camera
  custom_prompt: "Suggest security automations including intrusion detection, door/window monitoring, and alarm triggers. Prioritize reliability and fail-safe behaviors."
  entity_limit: 150
```

--------------------------------

### Displaying Automation Description on Dashboard

Source: https://github.com/itspecialist111/ai_automation_suggester/blob/main/README.md

This Jinja2 template snippet shows how to retrieve and display the human-readable description of AI-generated automations from the integration's sensor. It is useful for presenting suggestions to users on a Home Assistant dashboard.

```jinja
{{ state_attr('sensor.ai_automation_suggestions_<provider_name>', 'description') }}
```

--------------------------------

### Service Call for Multi-Provider Targeting

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

When multiple AI provider configurations are set up, this service call allows specifying which configuration entry ID to use for generating suggestions, ensuring targeted analysis.

```yaml
# When multiple providers configured, specify which to use
service: ai_automation_suggester.generate_suggestions
data:
  provider_config: "01234567890abcdef"  # Config entry ID
  all_entities: true
```

--------------------------------

### Display AI Automation Description with Markdown Card

Source: https://github.com/itspecialist111/ai_automation_suggester/blob/main/custom_components/dashboard/seperate dashboard.txt

This markdown card displays the current status and description for AI automation suggestions. It fetches the status from 'sensor.ai_automation_suggestions_google', displays the last update time, and shows a detailed description attribute from the same sensor. If no description is available, it shows a default message.

```yaml
type: markdown
    title: 🤖 AI Suggestion — Description
    content: >
      **Status:** {{ states('sensor.ai_automation_suggestions_google')
      }}

      **Last update:** {{ 
      state_attr('sensor.ai_automation_suggestions_google', 
      'last_update') }}

      ---

      {{ state_attr('sensor.ai_automation_suggestions_google',
      'description') or '_No description yet._' }}
```

--------------------------------

### Displaying Automation YAML Block on Dashboard

Source: https://github.com/itspecialist111/ai_automation_suggester/blob/main/README.md

This Jinja2 template snippet demonstrates how to fetch and display the YAML code block for AI-generated automations. This allows users to easily view or copy the automation configuration directly from their Home Assistant dashboard.

```jinja
{{ state_attr('sensor.ai_automation_suggestions_<provider_name>', 'yaml_block') }}
```

--------------------------------

### Button Card to Trigger AI Suggestions in Lovelace (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A Lovelace button card that, when tapped, calls the `ai_automation_suggester.generate_suggestions` service. This allows for manual triggering of AI suggestions with specific parameters.

```yaml
type: button
name: Generate AI Suggestions
icon: mdi:robot-happy-outline
tap_action:
  action: call-service
  service: ai_automation_suggester.generate_suggestions
  service_data:
    all_entities: true
    entity_limit: 200
```

--------------------------------

### Service Call for Deep Automation Review

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This advanced service call enables a deep review of existing automations by reading the actual YAML content. It's designed to identify redundancies, inefficiencies, and suggest consolidations, with options for entity and automation limits.

```yaml
service: ai_automation_suggester.generate_suggestions
data:
  all_entities: true
  automation_read_yaml: true
  automation_limit: 50
  custom_prompt: "Review my existing automations for redundancy, inefficiency, or potential improvements. Suggest consolidations where multiple automations could be combined."
```

--------------------------------

### Basic Service Call to Generate Suggestions

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A simple service call to trigger the AI Automation Suggester to generate new automation suggestions. It uses default settings and processes only newly added entities.

```yaml
service: ai_automation_suggester.generate_suggestions
data: {}
```

--------------------------------

### AI Automation Suggester - New Entity Detection Automation (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This automation triggers when entity states change, designed to analyze new devices and entities. It is throttled to run at most once per hour to prevent excessive API calls.

```yaml
alias: AI Automation Suggester - New Entity Detection
description: Automatically analyze new devices and entities
trigger:
  - platform: event
    event_type: state_changed
condition:
  - condition: template
    value_template: >
      {{ (now() - state_attr('automation.ai_automation_suggester_new_entity_detection', 'last_triggered') | default(now() - timedelta(hours=2), true)).total_seconds() > 3600 }}
action:
  - service: ai_automation_suggester.generate_suggestions
    data: {}
mode: single
```

--------------------------------

### generate_suggestions Service

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Calls the AI service to generate suggestions based on provided parameters.

```APIDOC
## Service: generate_suggestions

### Description
Calls the AI service to generate suggestions based on provided parameters.

### Method
SERVICE CALL

### Endpoint
ai_automation_suggester.generate_suggestions

### Parameters
#### Service Data Parameters
- **provider_config** (string) - Optional - Config entry ID for targeting specific provider (when multiple configured)
- **custom_prompt** (string) - Optional - Additional instructions appended to system prompt
- **all_entities** (boolean) - Optional - Default false (only new entities)
- **domains** (list) - Optional - Default [] (all domains)
- **entity_limit** (integer) - Optional - Default 200, Range 50-1000
- **automation_read_yaml** (boolean) - Optional - Default false
- **automation_limit** (integer) - Optional - Default 100, Range 10-500

### Request Example
```yaml
service: ai_automation_suggester.generate_suggestions
data:
  provider_config: "config_entry_id"
  custom_prompt: "string"
  all_entities: false
  domains: ["light", "switch"]
  entity_limit: 100
  automation_read_yaml: true
  automation_limit: 50
```

### Response
#### Success Response
- Updates coordinator data and all associated sensors
```

--------------------------------

### AI Suggestions When Everyone Home Automation (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This automation generates AI suggestions when all family members arrive home between 5 PM and 10 PM. It focuses on welcome home automations and evening comfort scenarios.

```yaml
alias: AI Suggestions When Everyone Home
description: Generate suggestions when all family members arrive home
trigger:
  - platform: state
    entity_id: group.family
    to: "home"
condition:
  - condition: time
    after: "17:00:00"
    before: "22:00:00"
action:
  - service: ai_automation_suggester.generate_suggestions
    data:
      domains:
        - light
        - media_player
        - climate
      custom_prompt: "Focus on welcome home automations and evening comfort scenarios"
mode: single
```

--------------------------------

### AI Energy Optimization During Peak Hours Automation (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

This automation provides energy-saving suggestions during expensive peak electricity hours, specifically when the electricity price exceeds $0.30. It suggests aggressive energy-saving automations focusing on reducing consumption without sacrificing critical comfort or security.

```yaml
alias: AI Energy Optimization During Peak Hours
description: Get energy-saving suggestions during expensive peak hours
trigger:
  - platform: time
    at: "14:00:00"  # Peak rate starts
condition:
  - condition: template
    value_template: "{{ states('sensor.electricity_price') | float > 0.30 }}"
action:
  - service: ai_automation_suggester.generate_suggestions
    data:
      all_entities: true
      entity_limit: 200
      custom_prompt: "Suggest aggressive energy-saving automations for peak electricity hours. Focus on reducing consumption without sacrificing security or critical comfort."
mode: single
```

--------------------------------

### Monitor AI Provider Connection Status

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

Checks the connection status of the AI provider using Home Assistant sensors. The sensor reports states like 'initializing', 'connected', 'disconnected', or 'error'. The last error message can also be retrieved.

```yaml
# Monitor status sensor
sensor.ai_provider_status_openai
# States:
#   - initializing: First run
#   - connected: Working normally
#   - disconnected: Cannot reach provider
#   - error: Error occurred

# Check error details
sensor.last_error_message_openai
```

--------------------------------

### Display AI Suggestions in Lovelace Dashboard (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A Lovelace markdown card to display the latest AI automation suggestions. It shows the description, YAML code block, last update timestamp, and the count of entities processed.

```yaml
type: markdown
title: AI Automation Suggestions
content: |
  ## Latest Suggestions
  {{ state_attr('sensor.ai_automation_suggestions_openai', 'description') }}

  ## YAML Code
  ```yaml
  {{ state_attr('sensor.ai_automation_suggestions_openai', 'yaml_block') }}
  ```

  **Last Updated:** {{ state_attr('sensor.ai_automation_suggestions_openai', 'last_update') }}
  **Entities Analyzed:** {{ state_attr('sensor.ai_automation_suggestions_openai', 'entities_processed_count') }}
```

--------------------------------

### AI Provider Status Card for Lovelace Dashboard (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A Lovelace entities card to display the status of the AI provider. It includes information such as the provider name, model in use, token limits, and the last error message.

```yaml
type: entities
title: AI Provider Status
entities:
  - entity: sensor.ai_provider_status_openai
    name: OpenAI Status
  - entity: sensor.ai_model_in_use_openai
    name: Model
  - entity: sensor.max_input_tokens_openai
    name: Input Token Limit
  - entity: sensor.max_output_tokens_openai
    name: Output Token Limit
  - entity: sensor.last_error_message_openai
    name: Last Error
```

--------------------------------

### Alert on AI Provider Failure

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

An automation designed to alert users if an AI provider enters an 'error' state and remains in that state for a defined period (10 minutes). It uses a persistent notification to report the error.

```yaml
automation:
  - alias: Alert on AI Provider Failure
    trigger:
      - platform: state
        entity_id: sensor.ai_provider_status_openai
        to: "error"
        for:
          minutes: 10
    action:
      - service: notify.persistent_notification
        data:
          title: "AI Provider Error"
          message: >
            Provider has been in error state for 10 minutes.
            Error: {{ states('sensor.last_error_message_openai') }}
```

--------------------------------

### Display Suggested Automation YAML with Markdown Card

Source: https://github.com/itspecialist111/ai_automation_suggester/blob/main/custom_components/dashboard/seperate dashboard.txt

This markdown card renders suggested automation code in YAML format. It retrieves the YAML code block from the 'yaml_block' attribute of the 'sensor.ai_automation_suggestions_google' entity. If the 'yaml_block' attribute is present and not empty, it displays the code within a YAML code block; otherwise, it shows a message indicating that no raw code was found.

```yaml
type: markdown
    title: 📝 Suggested Automation YAML
    content: >
      {% set code = 
      state_attr('sensor.ai_automation_suggestions_google', 
      'yaml_block') %}

      {% if code %} ```yaml {{ code }} ``` {% else %} _No YAML
      block found. The most recent AI reply did not contain raw code._ {% 
      endif %}
```

--------------------------------

### Display AI Automation Status with Template Chips

Source: https://github.com/itspecialist111/ai_automation_suggester/blob/main/custom_components/dashboard/seperate dashboard.txt

This snippet configures a Home Assistant mushroom chips card to display the status of AI automation suggestions. It uses a template chip to show 'Suggestions Available' or 'All Good' based on the 'sensor.ai_automation_suggestions_google' entity, with color coding for visual cues. It also includes entity chips for update status and a toggle for new entity detection.

```yaml
type: vertical-stack
cards:
  - type: custom:mushroom-chips-card
    alignment: start
    chips:
      - type: template
        entity: sensor.ai_automation_suggestions_google
        icon: mdi:cloud-check
        icon_color: >
          {{ 'yellow' if states(entity) == 'Suggestions Available' else
          'green' }}
        content: >
          {{ 'Suggestions_Available' if states(entity) == 'Suggestions
          Available' else 'All_Good' }}
      - type: entity
        entity: update.ai_automation_suggester_update
        name: AI_Suggester
        icon_color: '{{ ''red'' if is_state(entity,''on'') else ''green'' }}'
      - type: template
        entity: automation.ai_suggestions_new_entity_detection
        icon: mdi:robot
        icon_color: '{{ ''teal'' if is_state(entity,''on'') else ''grey'' }}'
        content: >
          {{ 'New-Entity_Detection_ON' if is_state(entity,'on') else
          'New-Entity_Detection_OFF' }}
        tap_action:
          action: toggle
```

--------------------------------

### Conditional AI Provider Error Display in Lovelace (YAML)

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A Lovelace conditional card that displays an error message if the AI provider status sensor is in an 'error' state. It shows the current status and the last error message.

```yaml
type: conditional
conditions:
  - entity: sensor.ai_provider_status_openai
    state: "error"
card:
  type: markdown
  content: |
    ## AI Provider Error
    **Status:** {{ states('sensor.ai_provider_status_openai') }}
    **Error:** {{ states('sensor.last_error_message_openai') }}

    Check your API key and network connectivity.
```

--------------------------------

### Check AI Provider Health Status

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

A template sensor to determine if an AI provider is in a 'connected' state. It checks the state of the 'sensor.ai_provider_status_{provider_name}' entity. This is useful for monitoring the operational status of AI services.

```yaml
template:
  - binary_sensor:
      - name: "AI Provider Healthy"
        state: >
          {{ states('sensor.ai_provider_status_openai') == 'connected' }}
```

--------------------------------

### Notify on AI Model Change

Source: https://context7.com/itspecialist111/ai_automation_suggester/llms.txt

An automation that triggers a notification whenever the AI model in use changes. It monitors the 'sensor.ai_model_in_use_{provider_name}' entity and sends a message to the mobile app.

```yaml
automation:
  - alias: Notify on Model Change
    trigger:
      - platform: state
        entity_id: sensor.ai_model_in_use_openai
    action:
      - service: notify.mobile_app
        data:
          message: "AI model changed to {{ states('sensor.ai_model_in_use_openai') }}"
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.