fix: corrige imports e query SQL no endpoint create-dashboard
This commit is contained in:
Jonas Pacheco
parent
c665f6ec40
commit
395d1e5ecb
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# 06-01 PLAN — Schema + API Agent Defs
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## Tasks
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1. **Add `arcadia_agent_defs` table to `shared/schema.ts`**
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- Fields: id, tenantId, userId, name, description, spec (jsonb), status, version, lastTaskId, createdAt, updatedAt
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- Run migration if needed
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2. **Create `server/agent-defs/service.ts`**
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- `createAgentDef()`, `getAgentDef()`, `listAgentDefs()`, `updateAgentDef()`, `deleteAgentDef()`
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- `updateStatus()` helper for draft → assembling → ready → deployed
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- `incrementVersion()` on deploy
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3. **Create `server/agent-defs/routes.ts`**
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- GET `/api/agent-defs` (list by tenantId)
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- POST `/api/agent-defs` (create)
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- PATCH `/api/agent-defs/:id` (update spec/status)
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- DELETE `/api/agent-defs/:id`
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- POST `/api/agent-defs/:id/deploy` (status → deployed, version++)
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- POST `/api/agent-defs/:id/run` (POST to blackboard task)
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4. **Register routes in `server/routes.ts`**
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- Import and registerAgentDefRoutes()
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## Reuse
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- DB functions from existing patterns
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- Blackboard service for task creation (no modification)
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## Done Criteria
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- API responds 200 on all endpoints
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- Status transitions work: draft → assembling → ready → deployed
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- `lastTaskId` links to blackboard_tasks
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# 06-02 PLAN — Design + Assemble Tabs
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## Tasks
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1. **Extend `client/src/pages/DevCenter.tsx` — Design tab**
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- Add "Design" tab to TabsList
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- 3 mode buttons: Markdown Spec | Code Editor | Visual Flow
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- Monaco Editor component (reuse existing from "Desenvolver" tab if possible)
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- Save spec to `arcadia_agent_defs` on blur/button click
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- Form: agent name, description, spec content
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2. **Extend `client/src/pages/DevCenter.tsx` — Assemble tab**
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- List `arcadia_agent_defs` where status = draft
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- "Montar" button per agent → POST `/api/blackboard/task` with spec as context
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- Poll `/api/blackboard/task/:id` every 3s while assembling
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- Show progress (task status) in real-time
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- On complete: update agent status → ready, show generated artifact
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3. **Create `client/src/components/DesignStudio.tsx`** (if modularizing)
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- Or inline in DevCenter tabs
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4. **Create `client/src/components/AssembleLine.tsx`** (if modularizing)
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- Or inline in DevCenter tabs
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## Reuse
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- Monaco Editor config from existing code
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- Polling logic from existing task components
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- Blackboard task fetch logic
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## Done Criteria
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- Design tab allows editing agent spec in 3 modes
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- Assemble tab shows draft agents and polls until complete
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- Status updates in real-time
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- Artifacts visible after assembly
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# 06-03 PLAN — Deploy + Galeria Tabs
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## Tasks
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1. **Extend `client/src/pages/DevCenter.tsx` — Deploy tab**
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- List `arcadia_agent_defs` where status = ready OR deployed
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- "Deploy" button → PATCH `/api/agent-defs/:id/deploy` (status → deployed, version++)
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- "Re-montar" button → PATCH status back to draft
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- Expand row → show last blackboard_artifact details (JSON viewer)
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- Version badge per agent
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2. **Extend `client/src/pages/DevCenter.tsx` — Galeria tab**
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- Grid of cards: deployed agents only
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- Card content: name, description, version, creator, status badge
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- "Executar" button → POST `/api/agent-defs/:id/run` (new blackboard task)
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- "Fork" button → POST create new agent with copied spec (name += " (Copy)")
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- Filter: status dropdown, search by name
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- Empty state message
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3. **Create `client/src/components/OrchestrateCenter.tsx`** (if modularizing)
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- Or inline in DevCenter tabs
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4. **Create `client/src/components/AgentGallery.tsx`** (if modularizing)
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- Or inline in DevCenter tabs
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## Reuse
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- Card/grid layout from AutomationCenter or Skills
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- Status badge from existing components
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- Blackboard task execution logic
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## Done Criteria
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- Deploy tab lists ready/deployed agents
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- Deploy action increments version
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- Re-montar reverts to draft
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- Galeria shows deployed agents only
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- Run/Fork actions work
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- All filters functional
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# ─── MiroFlow — Aplicação Coolify ─────────────────────────────────────────────
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# Conecta aos serviços compartilhados (ollama) via network arcadia-internal
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# Requer: docker-compose.shared.yml rodando
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name: arcadia-miroflow
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services:
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# ── MiroFlow (Cientistas via Ollama) ───────────────────────────────────────────
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miroflow:
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build:
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context: .
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dockerfile: Dockerfile.miroflow
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restart: always
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environment:
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OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
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MIROFLOW_PORT: 8006
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MIROFLOW_RESEARCHER_MODEL: ${MIROFLOW_RESEARCHER_MODEL:-llama3.1:8b}
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networks:
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- arcadia-internal
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- coolify
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labels:
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- "traefik.enable=true"
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- "traefik.docker.network=coolify"
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- "traefik.http.routers.miroflow.entrypoints=https"
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- "traefik.http.routers.miroflow.rule=Host(`${MIROFLOW_DOMAIN:-miroflow.onboardbi.com.br}`)"
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- "traefik.http.routers.miroflow.tls=true"
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- "traefik.http.routers.miroflow.tls.certresolver=letsencrypt"
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- "traefik.http.services.miroflow.loadbalancer.server.port=8006"
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healthcheck:
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test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8006/health')"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 30s
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networks:
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arcadia-internal:
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external: true
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name: arcadia-internal
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coolify:
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external: true
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# ─── Arcádia — Infraestrutura Compartilhada ─────────────────────────────────
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# Serviços base: db, redis, ollama
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# Usado por: superset, miroflow, app, etc.
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name: arcadia-shared
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services:
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# ── Banco de dados com pgvector ─────────────────────────────────────────────
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db:
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image: pgvector/pgvector:pg16
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restart: always
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environment:
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POSTGRES_DB: ${PGDATABASE:-arcadia}
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POSTGRES_USER: ${PGUSER:-arcadia}
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POSTGRES_PASSWORD: ${PGPASSWORD}
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volumes:
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- pgdata:/var/lib/postgresql/data
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- ./docker/init-pgvector.sql:/docker-entrypoint-initdb.d/01-pgvector.sql
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U ${PGUSER:-arcadia}"]
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interval: 10s
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timeout: 5s
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retries: 10
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networks:
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- arcadia-internal
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# ── Redis ────────────────────────────────────────────────────────────────────
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redis:
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image: redis:7-alpine
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restart: always
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command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru
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volumes:
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- redis_data:/data
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networks:
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- arcadia-internal
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# ── Ollama (LLMs locais — soberania total) ────────────────────────────────────
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ollama:
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image: ollama/ollama:latest
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restart: always
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volumes:
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- ollama_models:/root/.ollama
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networks:
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- arcadia-internal
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- coolify
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networks:
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arcadia-internal:
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driver: bridge
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name: arcadia-internal
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coolify:
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external: true
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volumes:
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pgdata:
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external: true
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name: arcadia-prod_pgdata
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redis_data:
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external: true
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name: arcadia-prod_redis_data
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ollama_models:
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# ─── Superset BI — Aplicação Coolify ───────────────────────────────────────
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# Conecta aos serviços compartilhados (db, redis) via network arcadia-internal
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# Requer: docker-compose.shared.yml rodando
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name: arcadia-superset
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services:
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# ── Superset BI ───────────────────────────────────────────────────────────────
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superset:
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image: arcadia-prod-superset:latest
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restart: always
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environment:
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DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/superset
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SUPERSET_SECRET_KEY: ${SUPERSET_SECRET_KEY}
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SQLALCHEMY_DATABASE_URI: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/superset
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PYTHONPATH: /app/pythonpath
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SUPERSET_ADMIN_USERNAME: ${SUPERSET_ADMIN_USERNAME:-admin}
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SUPERSET_ADMIN_PASSWORD: ${SUPERSET_ADMIN_PASSWORD}
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SUPERSET_ADMIN_EMAIL: ${SUPERSET_ADMIN_EMAIL:-admin@onboardbi.com.br}
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ARCADIA_DATABASE_URL: postgresql+psycopg2://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
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command: ["/bin/bash", "/app/docker/init.sh"]
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volumes:
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- ./docker/superset/superset_config.py:/app/pythonpath/superset_config.py:ro
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- ./docker/superset/init.sh:/app/docker/init.sh:ro
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- superset_home:/app/superset_home
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networks:
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- arcadia-internal
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- coolify
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labels:
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- "traefik.enable=true"
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- "traefik.docker.network=coolify"
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- "traefik.http.routers.superset.entrypoints=https"
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- "traefik.http.routers.superset.rule=Host(`${SUPERSET_DOMAIN:-bi.onboardbi.com.br}`)"
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- "traefik.http.routers.superset.tls=true"
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- "traefik.http.routers.superset.tls.certresolver=letsencrypt"
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- "traefik.http.services.superset.loadbalancer.server.port=8088"
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networks:
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arcadia-internal:
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external: true
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name: arcadia-internal
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coolify:
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external: true
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volumes:
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superset_home:
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external: true
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name: arcadia-prod_superset_home
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/**
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* MiroFlow Bridge para Apache Superset
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*
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* Adaptador que conecta Superset com MiroFlow para análises científicas.
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* Fluxo: SQL (Superset) → MiroFlow (análise) → Enriquecimento de dados → KG (provenance)
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*/
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import type { Request, Response } from "express";
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import { createNode } from "../graph/service";
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import crypto from "crypto";
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interface MiroFlowConfig {
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type?: "exploratory" | "forecast" | "anomaly" | "hypothesis" | "causal";
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horizon?: number; // dias para forecast
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confidence_level?: number; // 0.90, 0.95, 0.99
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methods?: string[]; // ["arima", "prophet", "statistical_test", etc]
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}
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interface SupersetDataset {
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data: Record<string, any>[];
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columns: string[];
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index?: number[];
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}
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interface MiroFlowResult {
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execution_id: string;
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agent: string;
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model: string;
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result: {
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summary: string;
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analysis_type: string;
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descriptive_stats?: Record<string, any>;
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anomalies?: Array<{ index: number; score: number; value: any }>;
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forecast?: { values: number[]; lower_bound: number[]; upper_bound: number[] };
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hypothesis_test?: { p_value: number; result: string };
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confidence_intervals?: Record<string, [number, number]>;
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};
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metadata: {
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execution_time_ms: number;
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rows_analyzed: number;
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columns_used: string[];
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};
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}
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export interface EnrichedDataset extends SupersetDataset {
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_miroflow_analysis: string;
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_miroflow_type: string;
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_confidence_intervals?: Record<string, [number, number]>;
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_anomaly_scores?: Record<number, number>;
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_forecast?: { values: number[]; lower_bound: number[]; upper_bound: number[] };
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_metadata: {
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analysis_executed_at: string;
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miroflow_execution_id: string;
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miroflow_model: string;
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execution_time_ms: number;
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};
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}
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/**
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* MiroFlowBridge: Proxy entre Superset e MiroFlow
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* Enriquece datasets SQL com análises científicas
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*/
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export class MiroFlowBridge {
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private miroflowBaseUrl: string;
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private miroflowTimeout: number = 300_000; // 5 min
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constructor(miroflowBaseUrl: string = "http://localhost:8006") {
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this.miroflowBaseUrl = miroflowBaseUrl;
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}
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/**
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* Analisa dataset via MiroFlow
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*/
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async analyze(
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dataset: SupersetDataset,
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config: MiroFlowConfig,
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tenantId?: number,
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userId?: number
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): Promise<MiroFlowResult> {
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const controller = new AbortController();
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const timeout = setTimeout(() => controller.abort(), this.miroflowTimeout);
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try {
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const payload = {
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dataset: JSON.stringify(dataset),
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analysis_type: config.type || "exploratory",
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config,
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tenant_id: tenantId,
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user_id: userId,
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source: "superset_bridge",
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};
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const response = await fetch(`${this.miroflowBaseUrl}/analyze`, {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify(payload),
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signal: controller.signal,
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});
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clearTimeout(timeout);
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if (!response.ok) {
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const err = await response.json().catch(() => ({ detail: response.statusText }));
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throw new Error(`MiroFlow error: ${err.detail || response.status}`);
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}
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return await response.json();
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} catch (err: any) {
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clearTimeout(timeout);
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if (err.name === "AbortError") {
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throw new Error("MiroFlow analysis timeout (5 min)");
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}
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throw err;
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}
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}
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/**
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* Enriquece dataset com resultados da análise
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*/
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enrich(dataset: SupersetDataset, result: MiroFlowResult): EnrichedDataset {
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const enriched: EnrichedDataset = {
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...dataset,
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_miroflow_analysis: result.result.summary,
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_miroflow_type: result.result.analysis_type,
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_metadata: {
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analysis_executed_at: new Date().toISOString(),
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miroflow_execution_id: result.execution_id,
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miroflow_model: result.model,
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execution_time_ms: result.metadata.execution_time_ms,
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},
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};
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// Adicionar intervalos de confiança
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if (result.result.confidence_intervals) {
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enriched._confidence_intervals = result.result.confidence_intervals;
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}
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// Adicionar scores de anomalias (mapeados para índices)
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if (result.result.anomalies && result.result.anomalies.length > 0) {
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enriched._anomaly_scores = {};
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result.result.anomalies.forEach((anom) => {
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enriched._anomaly_scores![anom.index] = anom.score;
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});
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}
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// Adicionar forecast
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if (result.result.forecast) {
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enriched._forecast = result.result.forecast;
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}
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return enriched;
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}
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/**
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* Registra análise no Knowledge Graph para provenance
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*/
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async registerInKG(
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result: MiroFlowResult,
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dataset: SupersetDataset,
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config: MiroFlowConfig,
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req: Request
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): Promise<void> {
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try {
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const analysisHash = crypto
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.createHash("sha256")
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.update(
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JSON.stringify({
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execution_id: result.execution_id,
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dataset_columns: dataset.columns,
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config,
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result: result.result,
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})
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)
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.digest("hex");
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await createNode({
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type: "miroflow_analysis",
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tenantId: (req.user as any)?.tenantId ?? null,
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data: {
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execution_id: result.execution_id,
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agent: result.agent,
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model: result.model,
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analysis_type: result.result.analysis_type,
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dataset_shape: `${dataset.data.length}x${dataset.columns.length}`,
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columns_analyzed: dataset.columns,
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config,
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summary: result.result.summary,
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execution_time_ms: result.metadata.execution_time_ms,
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analysisHash,
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immutable: true,
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source: "superset_bridge",
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registeredAt: new Date().toISOString(),
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},
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});
|
||||
} catch (kgErr: any) {
|
||||
console.error("[MiroFlow Bridge] Falha ao registrar análise no KG:", kgErr.message);
|
||||
// Não bloqueia a resposta — logging apenas
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Handler Express para POST /api/superset/miroflow/analyze
|
||||
* Superset envia dataset SQL-resultante e config de análise
|
||||
*/
|
||||
async handleAnalyzeRequest(req: Request, res: Response): Promise<void> {
|
||||
if (!req.isAuthenticated()) {
|
||||
res.status(401).json({ error: "Não autenticado" });
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const { dataset, config }: { dataset: SupersetDataset; config: MiroFlowConfig } =
|
||||
req.body;
|
||||
|
||||
if (!dataset || !dataset.data || !dataset.columns) {
|
||||
res.status(400).json({ error: "Dataset inválido: data e columns obrigatórios" });
|
||||
return;
|
||||
}
|
||||
|
||||
// Executar análise no MiroFlow
|
||||
const result = await this.analyze(dataset, config, (req.user as any)?.tenantId, (req.user as any)?.id);
|
||||
|
||||
// Enriquecer dataset
|
||||
const enriched = this.enrich(dataset, result);
|
||||
|
||||
// Registrar no KG (assíncrono, não bloqueia)
|
||||
this.registerInKG(result, dataset, config, req).catch(() => {});
|
||||
|
||||
// Retornar dados enriquecidos
|
||||
res.json({
|
||||
success: true,
|
||||
data: enriched,
|
||||
analysis: result.result,
|
||||
execution_id: result.execution_id,
|
||||
});
|
||||
} catch (err: any) {
|
||||
console.error("[MiroFlow Bridge] Erro:", err.message);
|
||||
res.status(502).json({
|
||||
error: err.message,
|
||||
source: "miroflow_bridge",
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Factory para criar instância do bridge
|
||||
*/
|
||||
export function createMiroFlowBridge(miroflowUrl?: string): MiroFlowBridge {
|
||||
return new MiroFlowBridge(miroflowUrl || process.env.MIROFLOW_URL || "http://localhost:8006");
|
||||
}
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
import type { Express, Request, Response } from "express";
|
||||
import { createMiroFlowBridge } from "./MiroFlowBridge";
|
||||
import { createMiroFlowBridge } from "./MiroFlowBridge.js";
|
||||
|
||||
const SUPERSET_HOST = process.env.SUPERSET_HOST || "localhost";
|
||||
const SUPERSET_PORT = parseInt(process.env.SUPERSET_PORT || "8088", 10);
|
||||
|
|
@ -267,26 +267,19 @@ export function registerSupersetRoutes(app: Express): void {
|
|||
throw new Error("Falha ao adicionar chart ao dashboard");
|
||||
}
|
||||
|
||||
// 5. Salvar referência no banco Arcádia
|
||||
const db = await import("../db/index.js");
|
||||
await db.query(
|
||||
`INSERT INTO miroflow_generated_dashboards
|
||||
(analysis_id, agent, task, insights, dashboard_id, dashboard_title, dataset_name, sql_query, created_by, tenant_id, superset_url)
|
||||
VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11)`,
|
||||
[
|
||||
analysisId,
|
||||
agent || "unknown",
|
||||
task || "",
|
||||
JSON.stringify(insights || {}),
|
||||
dashboardId,
|
||||
dashboardTitle,
|
||||
`miroflow_${analysisId.substring(0, 8)}`,
|
||||
sqlQuery,
|
||||
user.id,
|
||||
user.tenantId || null,
|
||||
`${SUPERSET_URL}/superset/dashboard/${dashboardId}/`,
|
||||
]
|
||||
);
|
||||
// 5. Salvar referência no banco Arcádia (skip se não conseguir)
|
||||
try {
|
||||
const { db } = await import("../../db/index.js");
|
||||
await db.execute(`
|
||||
INSERT INTO miroflow_generated_dashboards
|
||||
(analysis_id, agent, task, insights, dashboard_id, dashboard_title, dataset_name, sql_query, created_by, tenant_id, superset_url)
|
||||
VALUES ('${analysisId}', '${agent}', '${task}', '${JSON.stringify(insights || {}).replace(/'/g, "''")}', ${dashboardId}, '${dashboardTitle.replace(/'/g, "''")}', 'miroflow_${analysisId.substring(0, 8)}', '${sqlQuery.replace(/'/g, "''")}', '${user.id}', ${user.tenantId || null}, '${SUPERSET_URL}/superset/dashboard/${dashboardId}/')
|
||||
ON CONFLICT (analysis_id, dashboard_id) DO NOTHING;
|
||||
`);
|
||||
} catch (dbErr: any) {
|
||||
console.warn("[Superset] Aviso ao salvar referência do dashboard:", dbErr.message);
|
||||
// Não bloqueia - dashboard foi criado mesmo com erro de registro
|
||||
}
|
||||
|
||||
res.json({
|
||||
success: true,
|
||||
|
|
|
|||
Loading…
Reference in New Issue