Prioritize blocks with the most matches

Oct 13, 2025 by sorusgentrification.com 113 views

Description

In the current implementation of Hexabot, blocks can be triggered by Natural Language Understanding (NLU) entities, such as intent, keyword entity values, and more. However, when multiple blocks match based on NLU entities, there is no clear prioritization strategy in place. This feature request aims to address this issue by prioritizing the block with the highest number of matching NLU entities, ensuring that the most relevant block is triggered.

Acceptance Criteria

To ensure that the proposed solution meets the requirements, the following acceptance criteria must be met:

Prioritize blocks with the most matches: When multiple blocks match based on NLU entities, the block with the most matches should be triggered.
Trait entities take priority: Trait entities should take priority over other entity types in determining the next block.
Fallback to explicit priority: If multiple blocks have the same number of matching entities, the system should fallback to an explicitly configured priority (if available).
Existing NLU-based block triggering mechanism remains functional: The existing NLU-based block triggering mechanism should remain functional and unaffected by the proposed changes.
Unit tests for prioritization logic: Add unit tests to validate the prioritization logic and ensure that it works as expected.

Benefits of Prioritizing Blocks with the Most Matching NLU Entities

Prioritizing blocks with the most matching NLU entities offers several benefits, including:

Improved accuracy: By prioritizing the block with the most matches, the system can improve the accuracy of its responses and provide more relevant information to users.
Enhanced user experience: When the system triggers the most relevant block, users are more likely to receive the information they need, leading to a better user experience.
Increased efficiency: By prioritizing blocks with the most matches, the system can reduce the number of unnecessary blocks that are triggered, leading to increased efficiency and reduced processing time.

Implementation Plan

To implement the proposed solution, the following steps can be taken:

Analyze the current NLU-based block triggering mechanism: Study the current implementation of the NLU-based block triggering mechanism to understand how it works and identify areas for improvement.
Develop a prioritization strategy: Design a prioritization strategy that takes into account the number of matching NLU entities and the type of entities (trait entities should take priority).
Implement the prioritization logic: Implement the prioritization logic in the system, ensuring that it meets the acceptance criteria and does not affect the existing NLU-based block triggering mechanism.
Add unit tests for prioritization logic: Write unit tests to validate the prioritization logic and ensure that it works as expected.
Test and refine the implementation: Test the implementation thoroughly and refine it as needed to ensure that it meets the requirements and provides the expected benefits.

Conclusion

Prioritizing blocks with the most matching NLU entities is a crucial feature that can improve the accuracy and relevance of the system's responses. By implementing a prioritization strategy that takes into account the number of matching NLU entities and the type of entities, the system can provide a better user experience and increase efficiency. The proposed implementation plan outlines the steps necessary to implement the prioritization logic and ensure that it meets the acceptance criteria.

Future Work

Future work on this feature can include:

Refining the prioritization strategy: Continuously refine the prioritization strategy to improve its accuracy and relevance.
Expanding the scope of prioritization: Expand the scope of prioritization to include other factors, such as user preferences and context.
Integrating with other features: Integrate the prioritization logic with other features, such as sentiment analysis and entity recognition.

Reproduction Steps

To reproduce the issue, follow these steps:

# Clone the repository
git clone https://github.com/hexabot/hexabot.git

# Navigate to the repository
cd hexabot

# Run the test
npm run test

Logs

No logs are available for this issue.

Browsers

No response.

OS

Frequently Asked Questions

This section provides answers to frequently asked questions about prioritizing blocks with the most matching NLU entities.

Q: What is the current issue with block triggering in Hexabot?

A: The current issue is that when multiple blocks match based on NLU entities, there is no clear prioritization strategy in place. This can lead to irrelevant blocks being triggered, affecting the accuracy and relevance of the system's responses.

Q: How does the proposed solution address the issue?

A: The proposed solution prioritizes the block with the highest number of matching NLU entities, ensuring that the most relevant block is triggered. Trait entities are given higher priority over other entity types, and if multiple blocks have the same number of matching entities, the system falls back to an explicitly configured priority (if available).

Q: What are the benefits of prioritizing blocks with the most matching NLU entities?

A: The benefits include improved accuracy, enhanced user experience, and increased efficiency. By prioritizing the most relevant block, the system can provide more accurate and relevant information to users, leading to a better user experience and reduced processing time.

Q: How does the proposed solution affect the existing NLU-based block triggering mechanism?

A: The proposed solution does not affect the existing NLU-based block triggering mechanism. The existing mechanism remains functional and unaffected by the changes.

Q: What are the acceptance criteria for the proposed solution?

A: The acceptance criteria include:

Prioritizing blocks with the most matches
Trait entities taking priority over other entity types
Fallback to explicit priority if multiple blocks have the same number of matching entities
Existing NLU-based block triggering mechanism remaining functional
Unit tests for prioritization logic

Q: How can the proposed solution be implemented?

A: The implementation plan includes:

Analyzing the current NLU-based block triggering mechanism
Developing a prioritization strategy
Implementing the prioritization logic
Adding unit tests for prioritization logic
Testing and refining the implementation

Q: What are the future work plans for this feature?

A: Future work plans include refining the prioritization strategy, expanding the scope of prioritization, and integrating the prioritization logic with other features.

Q: How can I reproduce the issue?

A: To reproduce the issue, follow these steps:

# Clone the repository
git clone https://github.com/hexabot/hexabot.git

# Navigate to the repository
cd hexabot

# Run the test
npm run test

Q: Are there any logs available for this issue?

A: No logs are available for this issue.

Q: What browsers and OS are affected by this issue?

A: No response.

Q: How can I get involved in the development of this feature?

A: You can get involved by contributing to the Hexabot repository, providing feedback, and participating in discussions.