63 lines
2.1 KiB
Markdown
63 lines
2.1 KiB
Markdown
# AIOps Query Augmentation
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## What Changed
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Payload-targeted AIOps prompts now include a deterministic recommended knowledge query.
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The query is built from the non-blank payload fields:
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```text
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alertName service severity description timeRange userRequest
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```
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Example:
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```text
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HighCPUUsage payment-service P1 CPU usage is above 80% last_15m
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```
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## Why This Matters
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AIOps payload fields contain high-value retrieval terms:
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- alert name
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- service name
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- severity
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- symptom description
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- time range
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- operator request
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Before this change, the Agent still had to invent its own `lookup_knowledge` query from the full prompt. That can work, but it may omit important terms such as the service name or alert name.
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The new prompt makes the retrieval seed explicit:
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```text
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Recommended lookup_knowledge query: ...
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```
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## Design Choice
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This is prompt-level query augmentation, not hidden retrieval.
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I intentionally did not call `lookup_knowledge` automatically before the Agent runs. The project values traceability: tool calls should appear as Agent actions, with their inputs and outputs recorded in `tool_invocation`.
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So the design is:
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```text
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AIOps payload
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-> deterministic recommended retrieval query
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-> Agent prompt
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-> Agent may call lookup_knowledge explicitly
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-> tool_invocation records the real retrieval action
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```
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## Interview Answer
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If asked how AIOps payload improves RAG retrieval:
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> I do not replace the user query with a broad domain. I extract the high-signal alert terms from the payload, such as alertName, service, severity, symptom, and time range, and put them into a compact recommended lookup query. The Agent still calls `lookup_knowledge` explicitly, so the trace remains auditable, but the retrieval query is less dependent on model improvisation.
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If asked why not auto-call retrieval:
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> Auto-calling retrieval would create hidden evidence before the Agent actually decides to use a tool. For this project, explicit tool invocation is more important because the interview story is about observable Agent execution. Prompt-level augmentation gives the Agent a better query seed without changing the trace contract.
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