[cs] Room awarness for climate #2401
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📝 Walkthrough📝 WalkthroughWalkthroughThe changes involve modifications to the Changes
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (15)
responses/cs/HassClimateGetTemperature.yaml (1)
5-7: Approved: Grammatically correct temperature formattingThe changes improve the response by providing a grammatically correct temperature description in Czech. The logic correctly handles the different forms of "degree" (stupeň, stupně, stupňů) based on the temperature value, which is crucial for natural-sounding responses in Czech.
Consider improving readability by breaking the long line into multiple lines:
default: > {% set temperature = state_attr(state.entity_id, 'current_temperature') %} {% set degree_word = 'stupeň' if temperature | int | abs == 1 else 'stupně' if temperature | int | abs in [2,3,4] else 'stupňů' %} {{ temperature }} {{ degree_word }}This change would make the logic easier to read and maintain without affecting the functionality.
sentences/cs/climate_HassClimateSetTemperature.yaml (2)
8-10: Enhanced context-awareness for named climate entities.The new structure
"<obecne_zmenit> teplotu {name} na <teplota>"with the climate domain context is a good addition. It allows for targeting specific named climate entities.Consider adding a comment to clarify that
{name}refers to the name of a climate entity. This would improve code readability:- sentences: - "<obecne_zmenit> teplotu {name} na <teplota>" # {name} refers to a climate entity name requires_context: domain: climate
6-15: Excellent implementation of room-aware climate controls.The changes in this file significantly enhance the room awareness functionality for climate control, aligning perfectly with the PR objectives. The new sentence structures provide:
- Direct area specification
- Named climate entity targeting
- Implicit area reference with optional explicit location
These improvements allow for more natural and flexible command phrasings, enhancing the user experience and the system's ability to interpret user intentions accurately. The use of placeholders (like
<obecne_zmenit>) and context requirements adds robustness to the command interpretation.As you continue to develop this feature, consider the following:
- Ensure that the backend logic can handle these new command structures efficiently.
- Update user documentation to reflect these new command possibilities.
- Consider adding similar flexibility to other climate-related intents for consistency across the system.
sentences/cs/climate_HassClimateGetTemperature.yaml (1)
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1-20: Overall improvements to temperature query patterns. Consider adding documentation.The changes to this file significantly enhance the flexibility and specificity of temperature-related queries for the HassClimateGetTemperature intent. The new sentence patterns align well with the PR objective of introducing room awareness for climate control.
To improve maintainability and clarity, consider adding comments or documentation to explain the purpose and usage of placeholders like
<v>and<tady>. This would be helpful for other developers who might work on this file in the future.Additionally, it might be beneficial to include a brief comment at the top of the file explaining the overall structure and purpose of these sentence patterns, especially for non-Czech speaking developers who might need to maintain this code.
tests/cs/climate_HassClimateGetTemperature.yaml (3)
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1-18: LGTM! Consider adding one more variation.The changes to the kitchen temperature test case look good. The addition of "jak chladno je v kuchyni" (how cold is it in the kitchen) provides a good variation for temperature queries.
Consider adding one more variation to cover all bases:
- jak horko je v kuchyniThis would complement the existing "jak teplo" and "jak chladno" variations.
19-28: Great addition! Consider clarifying the response.The new test case for the living room thermostat is a valuable addition. It covers various ways to ask about the thermostat temperature, which is great for natural language processing.
To improve clarity, consider specifying whether the response refers to the set temperature or the current temperature. For example:
response: "Termostat obývák je nastaven na 20 stupňů"or
response: "Aktuální teplota na termostatu obývák je 20 stupňů"This would make the test case more explicit and potentially catch any discrepancies in the implementation.
29-43: Excellent addition for context-aware queries!This new test case for context-aware temperature queries is a great addition. It covers various ways to ask about the temperature without specifying a room, which aligns well with the PR objective of improving room awareness for climate control.
To further align with the PR objectives and improve consistency, consider:
- Adding a comment to explain the context-aware nature of this test case.
- Modifying the response to include the room name, making it clear that the system is aware of the context. For example:
# Context-aware temperature query - sentences: # ... (existing sentences) intent: name: HassClimateGetTemperature context: area: Obývací pokoj slots: area: Obývací pokoj response: "V obývacím pokoji je 20 stupňů"This change would make it explicit that the system is using the room context in its response, which better demonstrates the room awareness feature.
tests/cs/climate_HassClimateSetTemperature.yaml (5)
6-7: Approved: Enhanced test coverage and response verification.The addition of "zvyš" and "sniž" commands improves the variety of test cases. The new response field "Teplota nastavena" is a good addition for verifying system acknowledgment.
Consider adding more specific responses that include the set temperature, e.g., "Teplota nastavena na 45 stupňů." This would provide more detailed verification of the system's understanding of the command.
Also applies to: 16-16
33-36: Approved: Added support for specific thermostat targeting.The new test cases effectively cover scenarios where a specific thermostat is targeted in the command. The addition of the "name" slot in the intent structure correctly captures this information.
Consider adding a test case where the thermostat name is mentioned at the end of the sentence, e.g., "nastav teplotu na 45°C na termostat obývák". This would ensure the intent can handle different word orders in Czech sentences.
Also applies to: 42-43
44-56: Approved: Added support for contextual temperature setting.The new test case effectively handles scenarios where the user doesn't explicitly mention the area, using contextual words like "tady" and "tu". The use of a context field with a default area is a good approach to handle these situations.
Consider adding a test case where the context is different from the default "Obývací pokoj" to ensure the system can handle various room contexts correctly.
57-70: Approved: Comprehensive coverage of contextual Celsius commands.This test case effectively combines contextual area awareness with various ways of specifying Celsius temperatures. The intent structure correctly captures all necessary information including context, temperature unit, and area.
Consider parameterizing the test cases to reduce repetition and make it easier to add new variations. For example, you could define a list of temperature units and area contexts, then generate test cases programmatically. This would make the test suite more maintainable and extensible.
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1-70: Overall: Significant improvements in test coverage and intent handling.The changes to this file greatly enhance the test suite for the HassClimateSetTemperature intent. Key improvements include:
- Added support for contextual commands using words like "tady" and "tu".
- Introduced test cases for specific thermostat targeting.
- Expanded coverage of different ways to specify Celsius temperatures.
- Added response verification to all test cases.
These changes will result in a more robust and flexible climate control system that can handle a wider variety of user inputs in Czech.
As the test suite grows, consider implementing a more structured approach to organizing test cases, possibly using a custom test runner or a behavior-driven development (BDD) framework. This could help in managing the increasing complexity of test scenarios and make it easier to add new variations in the future.
sentences/cs/_common.yaml (3)
329-329: LGTM: AddedupravitcommandThe addition of the
upravitcommand enhances the natural language understanding capabilities by providing another synonym for changing settings. The pattern "uprav[it]" correctly matches both imperative and infinitive forms.Consider adding a comment explaining the meaning of
upravitfor non-Czech speakers, e.g.:upravit: "uprav[it]" # to adjust/modify
330-330: LGTM: Addedobecne_zmenitcommand for general change patternsThe addition of the
obecne_zmenitcommand creates a comprehensive pattern for changing settings, encompassing various synonyms. This enhances the flexibility of natural language inputs for modifying settings.Consider adding a comment explaining the purpose of
obecne_zmenitfor clarity, e.g.:obecne_zmenit: "(<nastavit>|<zvysit>|<ztlumit>|<zmenit>|<upravit>)" # general pattern for changing settings
353-353: LGTM: Addedtadycommand for location referenceThe addition of the
tadycommand, which matches both "tady" and "tu" (meaning "here" or "this"), aligns well with the PR objective of introducing room awareness for climate control. This allows users to refer to the current location in their commands.Consider adding a comment explaining the meaning of
tadyfor non-Czech speakers, e.g.:tady: "(tady|tu)" # here/this (for location reference)
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📒 Files selected for processing (6)
- responses/cs/HassClimateGetTemperature.yaml (1 hunks)
- sentences/cs/_common.yaml (2 hunks)
- sentences/cs/climate_HassClimateGetTemperature.yaml (1 hunks)
- sentences/cs/climate_HassClimateSetTemperature.yaml (1 hunks)
- tests/cs/climate_HassClimateGetTemperature.yaml (2 hunks)
- tests/cs/climate_HassClimateSetTemperature.yaml (3 hunks)
🔇 Additional comments (11)
responses/cs/HassClimateGetTemperature.yaml (1)
5-7: Verify implementation of room awarenessThe current changes improve the temperature reporting format, which is great. However, the PR objectives mention "room awareness for climate", which isn't directly addressed in this file.
To ensure we're meeting the PR objectives, please verify:
- Is room awareness implemented in other files of this PR?
- If not, should we modify this response to include room information?
Here's a script to check for room-related changes in other files:
If room awareness is not implemented elsewhere, consider modifying this response to include room information, for example:
default: > {% set temperature = state_attr(state.entity_id, 'current_temperature') %} {% set room = state_attr(state.entity_id, 'friendly_name') %} {% if temperature is not none %} {% set rounded_temp = (temperature | float | round(1)) %} {% set degree_word = 'stupeň' if rounded_temp | abs == 1 else 'stupně' if rounded_temp | abs in [2,3,4] else 'stupňů' %} V místnosti {{ room }} je {{ rounded_temp }} {{ degree_word }} {% else %} Omlouvám se, ale nemohu zjistit aktuální teplotu v místnosti {{ room }}. {% endif %}This assumes that the 'friendly_name' attribute contains the room name. Adjust as necessary based on how room information is stored in your system.
sentences/cs/climate_HassClimateSetTemperature.yaml (1)
6-6: Improved flexibility for temperature setting commands.The new sentence structure
"<obecne_zmenit> teplotu <area> na <teplota>"enhances the command's flexibility by using a general change placeholder (<obecne_zmenit>). This allows for various verbs to be used for temperature adjustment while maintaining a consistent structure.sentences/cs/climate_HassClimateGetTemperature.yaml (3)
6-8: LGTM! Well-structured sentences for general temperature inquiries.The first set of sentences is well-designed, covering various ways to ask about temperature in a specified area. The use of optional elements and alternatives provides good flexibility for natural language processing.
14-20: LGTM! Well-structured sentences for location-specific temperature inquiries. Clarification needed.The third set of sentences is well-designed for querying temperature at a specific location. The context requirement for the area slot is appropriate.
Could you please clarify the purpose and usage of the
<tady>placeholder? It's not immediately clear what this represents or how it's intended to be used in the sentence structure.To verify the usage of this placeholder, we can run the following script:
#!/bin/bash # Description: Check for other occurrences and potential definitions of the <tady> placeholder # Search for <tady> placeholder in YAML files echo "Occurrences of <tady> placeholder in YAML files:" rg --type yaml "<tady>" -C 2 # Search for potential definitions or explanations of tady echo "\nPotential definitions or explanations of tady:" rg --type yaml "tady:" -C 2This will help us understand if this placeholder is used consistently across the project and if there's any documentation explaining its purpose.
9-14: LGTM! Well-structured sentences for querying set temperature. Clarification needed.The second set of sentences is well-designed for querying the set temperature of specific entities. The context requirement for the climate domain is appropriate.
Could you please clarify the purpose and usage of the
<v>placeholder before{name}? It's not immediately clear what this represents or how it's intended to be used in the sentence structure.To verify the usage of this placeholder, we can run the following script:
This will help us understand if this placeholder is used consistently across the project and if there's any documentation explaining its purpose.
tests/cs/climate_HassClimateGetTemperature.yaml (1)
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1-43: Overall, excellent improvements to room awareness and language processing!The changes in this file significantly enhance the test coverage for the
HassClimateGetTemperatureintent, aligning well with the PR objectives of improving room awareness for climate control. The additions cater to various scenarios, including:
- Specific room queries (kitchen)
- Thermostat queries (living room)
- Context-aware queries (current room)
These improvements contribute positively to the natural language processing capabilities of the system, allowing for more flexible and natural user interactions. The variety of phrases used in each test case will help ensure robust handling of different query formulations.
To further enhance the PR:
- Consider implementing the suggested minor additions and clarifications in each test case.
- Ensure that the implementation correctly handles the context-aware queries as demonstrated in the test cases.
- If not already done, consider adding similar improvements to other related intents (e.g.,
HassClimateSetTemperature) to maintain consistency across the climate control feature set.Great work on improving the room awareness functionality for climate control!
tests/cs/climate_HassClimateSetTemperature.yaml (1)
19-21: Approved: Comprehensive coverage of Celsius unit variations.The new test cases effectively cover different ways of specifying temperature in Celsius, enhancing the robustness of the intent recognition. The consistent use of the response field and the correct inclusion of the "temperature_unit" slot in the intent structure are commendable.
Also applies to: 31-31
sentences/cs/_common.yaml (4)
325-325: LGTM: Simplified pattern fornastavitThe new pattern "nastav[it]" is a more concise way to match both "nastav" and "nastavit". This change maintains the existing functionality while simplifying the regex pattern.
326-326: LGTM: Optimized pattern forzmenitThe new pattern "změ(ň|nit)" is a more efficient way to match both "změň" and "změnit". This change maintains the existing functionality while optimizing the regex pattern by factoring out the common prefix.
331-331: LGTM: Improved flexibility for temperature inputThe modified pattern for
teplotanow allows for optional spaces around the degree symbol and temperature unit. This change improves the robustness of temperature input recognition, accommodating various ways users might input temperatures.
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325-353: Overall assessment: Excellent enhancements to Czech language command recognitionThe changes in this file significantly improve the natural language processing capabilities for Czech climate control commands. The modifications to existing patterns and the addition of new commands (like
upravit,obecne_zmenit, andtady) collectively enhance the system's ability to understand and respond to a wider variety of user inputs. These improvements align well with the PR objective of introducing room awareness for climate control and make the system more robust and user-friendly for Czech-speaking users.
Add room awarness for climate.
Format text so it sounds less robotic
Summary by CodeRabbit
New Features
Bug Fixes
Tests