POST /api/analyze submits an analysis job and returns job_id instantly.
GET /api/analyze/{job_id} returns progress + result; frontend polls every 2s.
Analysis runs as asyncio.create_task in the background — each HTTP request
completes in milliseconds, well within the 30s GCP Load Balancer limit.
- Add backend/app/services/job_store.py: in-memory AnalysisJob store with
30-min TTL cleanup
- Add backend/app/api/analysis_routes.py: POST + GET /api/analyze endpoints
with full analysis pipeline (hash check, DB persistence, PDF pages, etc.)
- Remove backend/app/websocket/: handlers.py, manager.py, __init__.py
- Update backend/app/main.py: wire analysis_router, store analysis_service
in app.state, drop all WebSocket imports and endpoint
- Update frontend/services/geminiService.ts: replace WS with fetch+poll;
function signatures unchanged so App.tsx / WIPReviewer.tsx need no edits
- Remove VITE_BACKEND_WS_URL from vite.config.ts, deploy.sh, .env.deploy.example
- Update cloudrun.yaml: remove WebSocket-specific session affinity annotation
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
74 lines
3.2 KiB
YAML
74 lines
3.2 KiB
YAML
apiVersion: serving.knative.dev/v1
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kind: Service
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metadata:
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name: modcomms-backend
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annotations:
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# Allow unauthenticated access (frontend connects directly)
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run.googleapis.com/ingress: all
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spec:
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template:
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metadata:
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annotations:
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# Keep 1 instance warm to prevent cold-start latency
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autoscaling.knative.dev/minScale: "1"
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autoscaling.knative.dev/maxScale: "10"
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# Each instance handles up to 10 concurrent analyses
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autoscaling.knative.dev/target: "10"
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run.googleapis.com/execution-environment: gen2
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spec:
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# 10-minute timeout — analysis (4 agents + lead agent) can take 2-3 minutes
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# for large multi-page PDFs; 600s gives headroom without being excessive
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timeoutSeconds: 600
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# Gemini API calls are I/O-bound; 10 concurrent slots prevents queuing at low traffic
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containerConcurrency: 10
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containers:
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- image: gcr.io/YOUR_PROJECT_ID/modcomms-backend:latest
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ports:
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- containerPort: 8000
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startupProbe:
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httpGet:
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path: /health
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port: 8000
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initialDelaySeconds: 5
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periodSeconds: 5
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failureThreshold: 10
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resources:
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limits:
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# 2 vCPU + 4Gi RAM: handles PDF rasterisation and parallel agent calls
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cpu: "2"
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memory: 4Gi
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env:
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# ── Gemini ────────────────────────────────────────────────────────
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- name: GEMINI_API_KEY
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valueFrom:
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secretKeyRef:
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name: gemini-api-key
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key: latest
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# ── Database ─────────────────────────────────────────────────────
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- name: DATABASE_URL
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valueFrom:
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secretKeyRef:
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name: database-url
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key: latest
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# ── Azure AD auth ─────────────────────────────────────────────────
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- name: AZURE_TENANT_ID
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valueFrom:
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secretKeyRef:
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name: azure-tenant-id
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key: latest
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- name: AZURE_CLIENT_ID
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valueFrom:
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secretKeyRef:
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name: azure-client-id
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key: latest
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# ── App settings ──────────────────────────────────────────────────
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- name: CORS_ORIGINS
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value: "https://YOUR_FRONTEND_DOMAIN"
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- name: HOST
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value: "0.0.0.0"
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- name: PORT
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value: "8000"
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# ── Dev/staging only ──────────────────────────────────────────────
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# Uncomment to disable Azure AD auth (e.g. staging environment):
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# - name: DISABLE_AUTH
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# value: "true"
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