> ## Documentation Index
> Fetch the complete documentation index at: https://koreai.mintlify.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Testing and Debugging Guide

This guide covers validating your Search AI configuration through testing and debugging tools to ensure optimal answer quality before deployment.

**Navigation:** Answer Generation > Test Answers

## Testing Answers

### Access Testing

1. Navigate to **Configuration > Answer Generation**.
2. Click **Test Answers**
3. Enter a query
4. Review the generated answer
5. Use debug option to analyze behavior

### Testing Workflow

| Step | Action               | Purpose                              |
| ---- | -------------------- | ------------------------------------ |
| 1    | Enter test query     | Simulate user input                  |
| 2    | Review answer        | Verify response quality and accuracy |
| 3    | Open debug view      | Understand how answer was generated  |
| 4    | Analyze chunks       | Check which content was used         |
| 5    | Refine configuration | Adjust settings based on findings    |

## Debug Information

The debug view provides comprehensive insights into answer generation.

### Debug Components

| Component            | Description                                                     |
| -------------------- | --------------------------------------------------------------- |
| Qualified Chunks     | Chunks selected and used to generate the answer                 |
| Retrieval Details    | How chunks were identified and ranked                           |
| LLM Request/Response | Full prompt sent and response received (for generative answers) |
| Processing Time      | Time taken by each component                                    |

### Agentic RAG Debugging

When Agentic RAG is enabled, an additional **Retrieval** tab appears showing:

| Information    | Description                        |
| -------------- | ---------------------------------- |
| Agent Sequence | Order in which agents were invoked |
| Agent Input    | Data sent to LLM by each agent     |
| Agent Output   | Results returned from each agent   |
| LLM Timing     | Time taken per LLM call            |

## Answer Insights

The Answer Insights feature provides analytics for query-response interactions.

### Available Data

| Feature              | Description                             |
| -------------------- | --------------------------------------- |
| Query Grouping       | View all answers for grouped queries    |
| Search Logs          | Filter logs by answer and channel       |
| Detailed View        | Query overview, debug info, LLM details |
| Performance Tracking | Monitor answer quality over time        |

### Accessing Answer Insights

Navigate to **Analytics > Search AI > Answer Insights**. [Learn More](/ai-for-service/analytics/searchai/answer-insights).

## Debugging Checklist

### Common Issues and Solutions

| Issue                       | Possible Cause         | Solution                                       |
| --------------------------- | ---------------------- | ---------------------------------------------- |
| No results returned         | Content not indexed    | Verify content sources and extraction settings |
| Poor relevance              | Threshold too high/low | Adjust similarity score threshold              |
| Missing information         | Chunks too small       | Increase chunk size or token budgets           |
| Incomplete answers          | Insufficient context   | Increase Top K chunks or token budget          |
| Business rules not applying | Condition mismatch     | Test with debug to verify rule triggers        |
| Slow responses              | Too many LLM calls     | Review Agentic RAG agent usage                 |

### Configuration Verification

| Check              | Location                          | What to Verify                      |
| ------------------ | --------------------------------- | ----------------------------------- |
| Retrieval Strategy | Configuration > Retrieval         | Vector vs. Hybrid selection         |
| Thresholds         | Configuration > Retrieval         | Similarity, proximity, Top K values |
| Answer Type        | Configuration > Answer Generation | Extractive vs. Generative           |
| LLM Settings       | Configuration > Answer Generation | Model, prompt, temperature          |
| Business Rules     | Configuration > Business Rules    | Active rules and conditions         |

## Best Practices

### Testing Strategy

1. **Test incrementally** - Validate each configuration change before moving to the next
2. **Use varied queries** - Test different query types, lengths, and phrasings
3. **Include edge cases** - Test ambiguous queries and boundary conditions
4. **Compare results** - Document before/after when making changes

### Debug Analysis

1. **Review qualified chunks** - Ensure relevant content is being selected
2. **Check chunk rankings** - Verify highest-ranked chunks are most relevant
3. **Analyze LLM prompts** - Confirm context is properly structured
4. **Monitor timing** - Identify performance bottlenecks

### Ongoing Monitoring

1. **Track Answer Insights** - Review analytics regularly
2. **Monitor feedback** - Enable user feedback and review ratings
3. **Iterate configuration** - Continuously refine based on data
4. **Document changes** - Keep records of configuration modifications

## Testing Scenarios

### Scenario 1: Basic Answer Validation

```
1. Enter simple factual query
2. Verify answer accuracy
3. Check source citation
4. Confirm response time acceptable
```

### Scenario 2: Retrieval Quality Check

```
1. Enter query matching specific content
2. Open debug view
3. Verify expected chunks are qualified
4. Check similarity scores
```

### Scenario 3: Business Rule Verification

```
1. Configure test rule with known conditions
2. Enter query that should trigger rule
3. Open debug view
4. Confirm rule was applied correctly
```

### Scenario 4: Agentic RAG Testing

```
1. Enable Agentic RAG
2. Enter complex query
3. Review Retrieval tab in debug
4. Verify agent sequence and outputs
```

## Quick Reference

### Debug Tab Contents

| Tab              | Shows                               |
| ---------------- | ----------------------------------- |
| Qualified Chunks | Selected content for answer         |
| Retrieval        | Agent processing (Agentic RAG only) |
| LLM Details      | Prompt and response data            |

### Key Metrics to Monitor

| Metric          | Healthy Range                 |
| --------------- | ----------------------------- |
| Response Time   | \< 3 seconds (varies by LLM)  |
| Chunk Relevance | Top chunks match query intent |
| Answer Accuracy | Matches source content        |
| User Feedback   | Positive ratings trending up  |

***