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Added use case description for LLM. #100
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Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
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Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
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FYI I think @alaudazzi was also working on a draft over in elastic/observability-docs#4837 (cross-linking for visibility). |
Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
*TBD |
Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
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Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
*TBD |
Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
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We support OpenAI in all 3 languages. And Bedrock in Python. If we want to go one more level down in granularity - for Bedrock (Python) we support Converse and InvokeModel APIs and plan to start working on support InvokeAgent API. I don't think we need to add these details in the matrix but perhaps it might sense to think of place to add these details.
Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
*TBD |
Acrolinx ScorecardsSelect the total score link to review all feedback on clarity, consistency, tone, brand, terms, spelling, grammar, readability, and inclusive language. You should fix all spelling errors regardless of your total score. Fixing spelling errors helps maintain user trust in overall content quality.
*TBD |
@daniela-elastic I have updated the table of supported technologies. @alaudazzi Any suggestions on the writing style? @trentm, @xrmx, @JonasKunz could you please review if the content is alright and if something that should be mentioned here is missing? |
@alaudazzi, @daniela-elastic, @colleenmcginnis this is an example of how a use case page for LLM observability could look like.