# MVP Demo Runbook This demo proves the MVP flow from user question to persisted diagnosis trace. ## Prerequisites - MySQL, Redis, Milvus/Zilliz, and LLM/embedding configuration are available through the current project configuration. - Security and secret cleanup are intentionally out of scope for this MVP slice. - The `mvp-demo` profile enables mock Prometheus and CLS providers so log and metric tools can return repeatable evidence. ## Start ```powershell mvn spring-boot:run "-Dspring-boot.run.profiles=mvp-demo" ``` The service listens on: ```text http://localhost:9900 ``` ## 1. Run Chat Diagnosis ```powershell $sessionId = "mvp-demo-payment-timeout-001" $body = @{ Id = $sessionId Question = "支付接口最近出现超时,请结合知识库、日志和指标判断可能原因,并给出修复建议。" } | ConvertTo-Json Invoke-RestMethod ` -Method Post ` -Uri "http://localhost:9900/api/chat" ` -ContentType "application/json" ` -Body $body ``` Expected result: - `data.success` is `true`. - `data.sessionId` equals `mvp-demo-payment-timeout-001`. - `data.answer` contains a diagnosis answer. ## 2. Query Trace ```powershell Invoke-RestMethod ` -Method Get ` -Uri "http://localhost:9900/api/diagnosis/$sessionId/trace" ``` Expected result: - `code` is `200`. - `data.session.sessionId` equals the chat session id. - `data.steps` contains planner/executor/verifier records for complex questions. - `data.toolInvocations` contains evidence tool calls such as `lookup_knowledge`, `query_logs`, or `query_metrics`. - `data.session.selfEvaluation` contains verifier or rule evaluation when available. ## 3. Submit Feedback ```powershell $feedback = @{ sessionId = $sessionId feedback = "useful" } | ConvertTo-Json Invoke-RestMethod ` -Method Post ` -Uri "http://localhost:9900/api/feedback" ` -ContentType "application/json" ` -Body $feedback ``` Expected result: - `success` is `true`. - A later trace query shows `data.session.feedback` as `useful`. ## Demo Story The important interview story is: ```text one session id -> user question -> multi-agent execution -> evidence tools -> verifier/self-evaluation -> final answer -> feedback -> trace API for replay and audit ```