Design a Feedback Loop from User Ratings into Retrieval Tuning
A ready-to-use prompt to design a feedback loop from user ratings into retrieval tuning, producing a structured draft you can act on directly rather than a vague suggestion.
When to use this
Use before committing time to design a feedback loop from user ratings into retrieval tuning by hand, to get a first structured pass to react to.
Prompt template
Act as a retrieval-augmented generation specialist. Separate retrieval quality from generation quality wherever possible, and be explicit about what data (gold passages, labeled queries, usage logs) each recommendation requires.
Task: Design a feedback loop from user ratings into retrieval tuning.
Context to use:
- What the corpus contains: {{corpus_description}}
- What questions it needs to answer: {{use_case}}
- Constraints: {{constraints}}
Response format:
1. Brief recommendation or approach
2. Main deliverable, organized into clear sections
3. Assumptions and unresolved questions
4. Validation or quality checklistCustomize
What the corpus contains is required
What questions it needs to answer is required
Preview
Act as a retrieval-augmented generation specialist. Separate retrieval quality from generation quality wherever possible, and be explicit about what data (gold passages, labeled queries, usage logs) each recommendation requires.
Task: Design a feedback loop from user ratings into retrieval tuning.
Context to use:
- What the corpus contains: {{corpus_description}} missing
- What questions it needs to answer: {{use_case}} missing
- Constraints:
Response format:
1. Brief recommendation or approach
2. Main deliverable, organized into clear sections
3. Assumptions and unresolved questions
4. Validation or quality checklistUsage instructions
Provide as much real context as you have; leave a field blank only if it genuinely doesn't apply, and check the assumptions list afterward.
Example output
A short recommendation, a structured deliverable broken into clear sections, a list of assumptions, and a validation checklist, all specific to the design a feedback loop from user ratings into retrieval tuning scenario described above.
Limitations
Treat the output as a structured starting point; it does not replace review from someone with direct context on the system.
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