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[NL-to-ESQL] update the generated documentation (to 2025/01) #205606

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pgayvallet opened this issue Jan 6, 2025 · 1 comment · Fixed by #205853
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[NL-to-ESQL] update the generated documentation (to 2025/01) #205606

pgayvallet opened this issue Jan 6, 2025 · 1 comment · Fixed by #205853
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Team:AI Infra AppEx AI Infrastructure Team

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@pgayvallet
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It's been a long time since last documentation generation. We should re-generate to get the doc up to date with the latests changes and new functions.

@pgayvallet pgayvallet added the Team:AI Infra AppEx AI Infrastructure Team label Jan 6, 2025
@elasticmachine
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Pinging @elastic/appex-ai-infra (Team:AI Infra)

@pgayvallet pgayvallet self-assigned this Jan 6, 2025
kibanamachine pushed a commit to kibanamachine/kibana that referenced this issue Jan 9, 2025
## Summary

Fix elastic#205606

- Re-generate the internal ES|QL documentation using the generation
script (+ human review)
- Add more scenario to the NL-to-ESQL evaluation suite
- Some prompt engineering
  - improving the system instructions / functions summary
  - add more examples to the summary
  - adapt a few opinionated examples for some specific functions

## Evaluation

- average based on 4 runs for each model/branch tuple
- the new tests were locally added to main to run against the same suite
and properly evaluate the difference

| Model  | before (main) | after (PR) | delta |
| ------------- | ------------- | ------------- | ------------- |
| GPT-4o  | 90.9 | 97.74  | + 6.84 |
| Claude 3.5 Sonnet v2  |  88.58 | 96.49 | +7.91 |
| Gemini 1.5-pro-002  | 88.17  | 94.19 | +6.02 |

Overall, the prompt engineering somewhat significantly improved the
generation efficiency.

(cherry picked from commit 5b96912)
Zacqary pushed a commit to Zacqary/kibana that referenced this issue Jan 9, 2025
## Summary

Fix elastic#205606

- Re-generate the internal ES|QL documentation using the generation
script (+ human review)
- Add more scenario to the NL-to-ESQL evaluation suite  
- Some prompt engineering
  - improving the system instructions / functions summary
  - add more examples to the summary
  - adapt a few opinionated examples for some specific functions 

## Evaluation

- average based on 4 runs for each model/branch tuple
- the new tests were locally added to main to run against the same suite
and properly evaluate the difference

| Model  | before (main) | after (PR) | delta |
| ------------- | ------------- | ------------- | ------------- |
| GPT-4o  | 90.9 | 97.74  | + 6.84 |
| Claude 3.5 Sonnet v2  |  88.58 | 96.49 | +7.91 |
| Gemini 1.5-pro-002  | 88.17  | 94.19 | +6.02 |

Overall, the prompt engineering somewhat significantly improved the
generation efficiency.
CAWilson94 pushed a commit to CAWilson94/kibana that referenced this issue Jan 13, 2025
## Summary

Fix elastic#205606

- Re-generate the internal ES|QL documentation using the generation
script (+ human review)
- Add more scenario to the NL-to-ESQL evaluation suite  
- Some prompt engineering
  - improving the system instructions / functions summary
  - add more examples to the summary
  - adapt a few opinionated examples for some specific functions 

## Evaluation

- average based on 4 runs for each model/branch tuple
- the new tests were locally added to main to run against the same suite
and properly evaluate the difference

| Model  | before (main) | after (PR) | delta |
| ------------- | ------------- | ------------- | ------------- |
| GPT-4o  | 90.9 | 97.74  | + 6.84 |
| Claude 3.5 Sonnet v2  |  88.58 | 96.49 | +7.91 |
| Gemini 1.5-pro-002  | 88.17  | 94.19 | +6.02 |

Overall, the prompt engineering somewhat significantly improved the
generation efficiency.
viduni94 pushed a commit to viduni94/kibana that referenced this issue Jan 23, 2025
## Summary

Fix elastic#205606

- Re-generate the internal ES|QL documentation using the generation
script (+ human review)
- Add more scenario to the NL-to-ESQL evaluation suite  
- Some prompt engineering
  - improving the system instructions / functions summary
  - add more examples to the summary
  - adapt a few opinionated examples for some specific functions 

## Evaluation

- average based on 4 runs for each model/branch tuple
- the new tests were locally added to main to run against the same suite
and properly evaluate the difference

| Model  | before (main) | after (PR) | delta |
| ------------- | ------------- | ------------- | ------------- |
| GPT-4o  | 90.9 | 97.74  | + 6.84 |
| Claude 3.5 Sonnet v2  |  88.58 | 96.49 | +7.91 |
| Gemini 1.5-pro-002  | 88.17  | 94.19 | +6.02 |

Overall, the prompt engineering somewhat significantly improved the
generation efficiency.
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