security: correcoes semana 1 - session secret, CORS, filtro tenant, protecao /api/tenants

- Session secret com randomBytes(32), obrigatorio em producao
- CORS whitelist configurado (origens permitidas)
- getUserByUsername com validacao opcional de tenantId
- /api/tenants restrito: admin ve todos, user ve so seu tenant
- Metodo getTenant(id) adicionado a interface IStorage

.env

@@ -6,9 +6,6 @@ WEBUI_SECRET_KEY=76c7fc044f9e8d6e5eb60b67c82832b67e84739da4827ce1fa7c101ae1a055d
 DOMAIN=suite.onboardbi.com.br
 OLLAMA_BASE_URL=http://ollama-ia1upsekrad96at5hq97e4qa:11434
 
-LLMFIT_BASE_URL=http://llmfit:8000
-LLMFIT_API_KEY=key-arcadia
-
 # ── Superset BI ───────────────────────────────────────────────
 SUPERSET_SECRET_KEY=421274b5ba360778a5398d528116a45ea962d1197e3dfc99f36a372ff1025a63
 SUPERSET_ADMIN_USERNAME=admin

.env.example

@@ -49,13 +49,8 @@ AI_INTEGRATIONS_OPENAI_API_KEY=arcadia-internal
 # Se Ollama está em outro servidor:        OLLAMA_BASE_URL=http://IP_DO_SERVIDOR:11434
 OLLAMA_BASE_URL=http://localhost:11434
 
-# ── IA — LLMFit (modelos fine-tuned locais — habilitar quando disponível) ─────
-# LLMFit turbocharge: modelos treinados com dados do seu negócio
-# Deixe vazio para desabilitar (LiteLLM cai para Ollama automaticamente)
-LLMFIT_BASE_URL=
-
 # ── IA — Providers externos (opt-in — soberania: dados não saem sem configurar)
-# Deixe vazio para operação 100% soberana (apenas Ollama + LLMFit)
+# Deixe vazio para operação 100% soberana (apenas Ollama)
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
 GROQ_API_KEY=

.planning/phases/06-dev-center-completo/06-01-PLAN.md

@@ -0,0 +1,32 @@
+# 06-01 PLAN — Schema + API Agent Defs
+
+## Tasks
+
+1. **Add `arcadia_agent_defs` table to `shared/schema.ts`**
+   - Fields: id, tenantId, userId, name, description, spec (jsonb), status, version, lastTaskId, createdAt, updatedAt
+   - Run migration if needed
+
+2. **Create `server/agent-defs/service.ts`**
+   - `createAgentDef()`, `getAgentDef()`, `listAgentDefs()`, `updateAgentDef()`, `deleteAgentDef()`
+   - `updateStatus()` helper for draft → assembling → ready → deployed
+   - `incrementVersion()` on deploy
+
+3. **Create `server/agent-defs/routes.ts`**
+   - GET `/api/agent-defs` (list by tenantId)
+   - POST `/api/agent-defs` (create)
+   - PATCH `/api/agent-defs/:id` (update spec/status)
+   - DELETE `/api/agent-defs/:id`
+   - POST `/api/agent-defs/:id/deploy` (status → deployed, version++)
+   - POST `/api/agent-defs/:id/run` (POST to blackboard task)
+
+4. **Register routes in `server/routes.ts`**
+   - Import and registerAgentDefRoutes()
+
+## Reuse
+- DB functions from existing patterns
+- Blackboard service for task creation (no modification)
+
+## Done Criteria
+- API responds 200 on all endpoints
+- Status transitions work: draft → assembling → ready → deployed
+- `lastTaskId` links to blackboard_tasks

.planning/phases/06-dev-center-completo/06-02-PLAN.md

@@ -0,0 +1,34 @@
+# 06-02 PLAN — Design + Assemble Tabs
+
+## Tasks
+
+1. **Extend `client/src/pages/DevCenter.tsx` — Design tab**
+   - Add "Design" tab to TabsList
+   - 3 mode buttons: Markdown Spec | Code Editor | Visual Flow
+   - Monaco Editor component (reuse existing from "Desenvolver" tab if possible)
+   - Save spec to `arcadia_agent_defs` on blur/button click
+   - Form: agent name, description, spec content
+
+2. **Extend `client/src/pages/DevCenter.tsx` — Assemble tab**
+   - List `arcadia_agent_defs` where status = draft
+   - "Montar" button per agent → POST `/api/blackboard/task` with spec as context
+   - Poll `/api/blackboard/task/:id` every 3s while assembling
+   - Show progress (task status) in real-time
+   - On complete: update agent status → ready, show generated artifact
+
+3. **Create `client/src/components/DesignStudio.tsx`** (if modularizing)
+   - Or inline in DevCenter tabs
+
+4. **Create `client/src/components/AssembleLine.tsx`** (if modularizing)
+   - Or inline in DevCenter tabs
+
+## Reuse
+- Monaco Editor config from existing code
+- Polling logic from existing task components
+- Blackboard task fetch logic
+
+## Done Criteria
+- Design tab allows editing agent spec in 3 modes
+- Assemble tab shows draft agents and polls until complete
+- Status updates in real-time
+- Artifacts visible after assembly

.planning/phases/06-dev-center-completo/06-03-PLAN.md

@@ -0,0 +1,37 @@
+# 06-03 PLAN — Deploy + Galeria Tabs
+
+## Tasks
+
+1. **Extend `client/src/pages/DevCenter.tsx` — Deploy tab**
+   - List `arcadia_agent_defs` where status = ready OR deployed
+   - "Deploy" button → PATCH `/api/agent-defs/:id/deploy` (status → deployed, version++)
+   - "Re-montar" button → PATCH status back to draft
+   - Expand row → show last blackboard_artifact details (JSON viewer)
+   - Version badge per agent
+
+2. **Extend `client/src/pages/DevCenter.tsx` — Galeria tab**
+   - Grid of cards: deployed agents only
+   - Card content: name, description, version, creator, status badge
+   - "Executar" button → POST `/api/agent-defs/:id/run` (new blackboard task)
+   - "Fork" button → POST create new agent with copied spec (name += " (Copy)")
+   - Filter: status dropdown, search by name
+   - Empty state message
+
+3. **Create `client/src/components/OrchestrateCenter.tsx`** (if modularizing)
+   - Or inline in DevCenter tabs
+
+4. **Create `client/src/components/AgentGallery.tsx`** (if modularizing)
+   - Or inline in DevCenter tabs
+
+## Reuse
+- Card/grid layout from AutomationCenter or Skills
+- Status badge from existing components
+- Blackboard task execution logic
+
+## Done Criteria
+- Deploy tab lists ready/deployed agents
+- Deploy action increments version
+- Re-montar reverts to draft
+- Galeria shows deployed agents only
+- Run/Fork actions work
+- All filters functional

CLAUDE.md

@@ -20,7 +20,7 @@ server/
 client/                   # 66 páginas React
 shared/schema.ts          # Schema do banco (7317 linhas, Drizzle ORM)
 docker/
-  litellm-config.yaml     # Roteamento de LLMs (TIER 1: LLMFit, TIER 2: Ollama, TIER 3: externos)
+  litellm-config.yaml     # Roteamento de LLMs (TIER 1: Ollama local, TIER 2: externos)
 ```
 
 ## Arquitetura de IA
@@ -29,9 +29,8 @@ Manus / Agents / Embeddings
         │  AI_INTEGRATIONS_OPENAI_BASE_URL
         ▼
    LiteLLM :4000  (gateway unificado, loga tudo no banco)
-        ├──► LLMFit (TIER 1 — fine-tuned, soberano) [slot pronto, comentado]
+        ├──► Ollama :11434 (TIER 1 — local, padrão)
-        ├──► Ollama :11434 (TIER 2 — local, padrão)
+        └──► OpenAI/Anthropic/Groq (TIER 2 — opt-in, só se API key configurada)
-        └──► OpenAI/Anthropic/Groq (TIER 3 — opt-in, só se API key configurada)
 ```
 
 **Variáveis chave do Manus:**
@@ -96,11 +95,11 @@ arcadia-prod-{contabil,bi,automation,fisco,embeddings}-1  Python services
 - ✅ Docker dev + prod, LiteLLM gateway
 
 ## O que ainda falta
-- ❌ LLMFit: slot pronto em `litellm-config.yaml`, só habilitar quando disponível
 - ❌ Testes automatizados / CI-CD
 - ❌ Monitoramento (APM, Sentry, métricas)
 - ❌ Multi-tenancy completo
 - ❌ Rate limiting em todos os endpoints (parcial)
+- ❌ Fine-tuning de modelos locais (dados do Arcádia)
 
 ## Comandos úteis
 ```bash
@@ -122,7 +121,6 @@ npm run build
 ```
 SESSION_SECRET, SSO_SECRET          # gerar strings seguras em prod
 AI_INTEGRATIONS_OPENAI_BASE_URL     # aponta para LiteLLM
-LLMFIT_BASE_URL                     # LLMFit quando disponível
 OLLAMA_BASE_URL                     # Ollama host ou container
 OPENAI_API_KEY                      # opcional (soberania: deixar vazio)
 ```

DEPLOY_COOLIFY.md

@@ -122,7 +122,6 @@ AUTOMATION_PYTHON_URL=http://automation:8005
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
 GROQ_API_KEY=
-LLMFIT_BASE_URL=    # habilitar quando LLMFit estiver disponível
 ```
 
 ### Superset — profile `bi`
@@ -256,12 +255,11 @@ Configure backups automáticos no Coolify em **Project → Backups**.
 
 ## Stack de IA (LiteLLM + Ollama)
 
-### Três tiers configurados em `docker/litellm-config.yaml`
+### Dois tiers configurados em `docker/litellm-config.yaml`
 
 ```
-TIER 1 — LLMFit (fine-tuned, soberano)   → slot pronto, habilitar via LLMFIT_BASE_URL
+TIER 1 — Ollama (local, padrão)           → llama3.3, qwen2.5-coder, nomic-embed-text
-TIER 2 — Ollama (local, padrão)           → llama3.3, qwen2.5-coder, nomic-embed-text
+TIER 2 — Externos (opt-in)               → OpenAI, Anthropic, Groq (apenas se API key definida)
-TIER 3 — Externos (opt-in)               → OpenAI, Anthropic, Groq (apenas se API key definida)
 ```
 
 ### Baixar modelos Ollama após o primeiro deploy
@@ -272,12 +270,6 @@ docker exec arcadia-ollama ollama pull qwen2.5-coder:7b
 docker exec arcadia-ollama ollama pull nomic-embed-text
 ```
 
-### Habilitar LLMFit (quando disponível)
-
-1. Defina `LLMFIT_BASE_URL=http://seu-llmfit:porta`
-2. Descomente o bloco TIER 1 em `docker/litellm-config.yaml`
-3. Redeploy do serviço `litellm`
-
 ---
 
 ## Pós-deploy

INTEGRACAO_IA.md

@@ -1,6 +1,6 @@
-# Integração de IA — Ollama + LLMFit no Servidor
+# Integração de IA — Ollama no Servidor
 
-Guia para conectar o Arcádia Suite às IAs locais em produção.
+Guia para conectar o Arcádia Suite à IA local em produção.
 
 ---
 
@@ -13,11 +13,11 @@ Arcádia Suite (Manus, Agents, Embeddings)
         ▼
    LiteLLM (porta 4000) — gateway único
         │
-        ├──► LLMFit  (seus modelos fine-tuned)   [TIER 1 — prioridade]
+        ├──► Ollama  (modelos open source locais) [TIER 1 — padrão]
-        └──► Ollama  (modelos open source locais) [TIER 2 — padrão/fallback]
+        └──► OpenAI/Anthropic/Groq (opt-in)       [TIER 2 — externo]
 ```
 
-Nenhum serviço do Arcádia chama Ollama ou LLMFit diretamente.
+Nenhum serviço do Arcádia chama Ollama diretamente.
 Tudo passa pelo LiteLLM — que roteia, loga e faz fallback automaticamente.
 
 ---
@@ -89,66 +89,6 @@ docker exec -it $(docker ps -qf "name=ollama") ollama pull deepseek-r1:7b
 
 ---
 
-## Configuração do LLMFit
-
-### 1. Pré-requisito
-
-O LLMFit deve expor uma API compatível com OpenAI (formato `/v1/chat/completions`).
-Verifique se está respondendo:
-```bash
-curl http://IP_DO_LLMFIT:PORTA/v1/models
-```
-
-### 2. Configurar variável no Coolify
-
-```
-LLMFIT_BASE_URL=http://IP_DO_LLMFIT:PORTA
-```
-
-### 3. Ativar no LiteLLM config
-
-Edite `docker/litellm-config.yaml` e **descomente** o bloco TIER 1:
-
-```yaml
-model_list:
-
-  # TIER 1 — LLMFit (fine-tuned, prioridade máxima)
-  - model_name: arcadia-finetuned
-    litellm_params:
-      model: openai/NOME_DO_SEU_MODELO   # substitua pelo nome real
-      api_base: os.environ/LLMFIT_BASE_URL
-      api_key: llmfit-internal
-
-  # Modelo de embeddings fine-tuned (se disponível)
-  - model_name: arcadia-embed
-    litellm_params:
-      model: openai/NOME_DO_MODELO_EMBED
-      api_base: os.environ/LLMFIT_BASE_URL
-      api_key: llmfit-internal
-```
-
-### 4. Definir LLMFit como modelo padrão do Arcádia
-
-No mesmo arquivo, atualize o `arcadia-default`:
-
-```yaml
-  - model_name: arcadia-default
-    litellm_params:
-      model: openai/NOME_DO_SEU_MODELO
-      api_base: os.environ/LLMFIT_BASE_URL
-      api_key: llmfit-internal
-    model_info:
-      fallbacks: ["llama3.3"]   # cai para Ollama se LLMFit falhar
-```
-
-### 5. Reiniciar o LiteLLM para aplicar
-
-```bash
-docker compose -f docker-compose.prod.yml restart litellm
-```
-
----
-
 ## Variáveis de ambiente — resumo completo
 
 Configure todas no Coolify antes do deploy:
@@ -174,9 +114,6 @@ AI_INTEGRATIONS_OPENAI_API_KEY=${LITELLM_API_KEY}
 # Ollama em container: http://ollama:11434
 OLLAMA_BASE_URL=http://host-gateway:11434
 
-# ── LLMFit (deixar vazio até estar disponível) ────────────────────────────────
-LLMFIT_BASE_URL=
-
 # ── Providers externos (deixar vazio para soberania total) ───────────────────
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
@@ -202,7 +139,7 @@ curl http://localhost:4000/v1/chat/completions \
 ### 2. Testar Manus via interface
 
 Acesse `https://seudominio.com.br` → abra o Manus → envie uma mensagem simples.
-O Manus deve responder via Ollama (ou LLMFit se configurado).
+O Manus deve responder via Ollama.
 
 ### 3. Ver logs em tempo real
 
@@ -253,10 +190,6 @@ docker exec $(docker ps -qf "name=ollama") ollama pull nomic-embed-text
 → O modelo referenciado em `litellm-config.yaml` não foi baixado no Ollama.
 → Execute `ollama pull NOME_DO_MODELO`
 
-**LLMFit não está sendo chamado**
-→ Confirme que `LLMFIT_BASE_URL` está definido e o serviço está respondendo.
-→ Reinicie o LiteLLM após alterar o config: `docker compose restart litellm`
-
 **Ollama no host não é alcançado de dentro do Docker**
 → Tente `OLLAMA_BASE_URL=http://172.17.0.1:11434` (IP padrão do docker0)
 → Ou use o IP real da interface de rede: `ip addr show` para descobrir

client/src/components/MiroFlowControl.tsx

@@ -33,14 +33,14 @@ const AGENTS = [
   {
     value: "statistician",
     label: "Statistician",
-    model: "deepseek-r1:14b",
+    model: "llama3.1:8b",
     placeholder:
       "Ex: Analise a distribuição de vendas por região no último trimestre",
   },
   {
     value: "fiscal_auditor",
     label: "Fiscal Auditor",
-    model: "deepseek-r1:14b",
+    model: "llama3.1:8b",
     placeholder:
       "Ex: Verifique inconsistências nos registros NFe do CNPJ 12.345.678/0001-90",
   },
@@ -73,6 +73,26 @@ export function MiroFlowControl({
     },
   });
 
+  const createDashboardMutation = useMutation({
+    mutationFn: async (dashboardData: {
+      dashboardTitle: string;
+      sqlQuery: string;
+    }) => {
+      const response = await apiRequest(
+        "POST",
+        "/api/superset/miroflow/create-dashboard",
+        {
+          ...dashboardData,
+          analysisId: mutation.data?.execution_id,
+          agent: selectedAgent,
+          task,
+          insights: mutation.data?.result,
+        }
+      );
+      return response.json();
+    },
+  });
+
   const handleAnalyze = () => {
     if (!task.trim()) {
       return;
@@ -207,6 +227,46 @@ export function MiroFlowControl({
                     {mutation.data?.execution_id?.slice(0, 8)}...
                   </div>
                 </div>
+
+                {/* Create Dashboard Button */}
+                <div className="pt-4 border-t border-[#c89b3c]/20">
+                  <Button
+                    onClick={() => {
+                      const title = `Análise ${selectedAgent} - ${new Date().toLocaleDateString('pt-BR')}`;
+                      createDashboardMutation.mutate({
+                        dashboardTitle: title,
+                        sqlQuery: `SELECT * FROM arcadia LIMIT 100`, // Placeholder - idealmente vem do MiroFlow
+                      });
+                    }}
+                    disabled={createDashboardMutation.isPending}
+                    className="w-full bg-[#8b7355] hover:bg-[#9d8568] text-white font-semibold"
+                  >
+                    {createDashboardMutation.isPending ? (
+                      <>
+                        <Loader2 className="w-4 h-4 mr-2 animate-spin" />
+                        Criando Dashboard...
+                      </>
+                    ) : (
+                      "📊 Criar Dashboard no Superset"
+                    )}
+                  </Button>
+
+                  {createDashboardMutation.isSuccess && (
+                    <div className="mt-2 rounded-lg p-3 bg-green-900/20 border border-green-500/50">
+                      <p className="text-xs text-green-100">
+                        ✅ Dashboard criado! Atualizando...
+                      </p>
+                    </div>
+                  )}
+
+                  {createDashboardMutation.isError && (
+                    <div className="mt-2 rounded-lg p-3 bg-red-900/20 border border-red-500/50">
+                      <p className="text-xs text-red-100">
+                        ❌ Erro: {createDashboardMutation.error instanceof Error ? createDashboardMutation.error.message : "Erro ao criar dashboard"}
+                      </p>
+                    </div>
+                  )}
+                </div>
               </div>
             )}
           </CardContent>

client/src/pages/BiWorkspace.tsx

@@ -50,6 +50,7 @@ import {
 } from "lucide-react";
 import { Textarea } from "@/components/ui/textarea";
 import { SupersetDashboard } from "@/components/SupersetDashboard";
+import { MiroFlowControl } from "@/components/MiroFlowControl";
 import {
   Dialog,
   DialogContent,
@@ -2957,6 +2958,9 @@ export default function BiWorkspace() {
               <TabsTrigger value="staging" className="data-[state=active]:bg-[#c89b3c] data-[state=active]:text-[#1f334d] text-white/70">
                 <Layers className="w-4 h-4 mr-2" /> Staging
               </TabsTrigger>
+              <TabsTrigger value="cientifico" className="data-[state=active]:bg-[#c89b3c] data-[state=active]:text-[#1f334d] text-white/70">
+                Científico
+              </TabsTrigger>
               <TabsTrigger value="advanced" className="data-[state=active]:bg-[#c89b3c] data-[state=active]:text-[#1f334d] text-white/70">
                 <Settings className="w-4 h-4 mr-2" /> Insights
               </TabsTrigger>
@@ -2983,6 +2987,9 @@ export default function BiWorkspace() {
             <TabsContent value="staging" className="mt-0">
               <StagingTab />
             </TabsContent>
+            <TabsContent value="cientifico" className="mt-0">
+              <MiroFlowControl />
+            </TabsContent>
             <TabsContent value="advanced" className="mt-0">
               <SupersetAdvancedTab />
 

client/src/pages/Scientist.tsx

@@ -1,4 +1,5 @@
 import { BrowserFrame } from "@/components/Browser/BrowserFrame";
+import { MiroFlowControl } from "@/components/MiroFlowControl";
 import { useState } from "react";
 import { useMutation, useQuery } from "@tanstack/react-query";
 import { Button } from "@/components/ui/button";
@@ -200,6 +201,10 @@ export default function Scientist() {
                 <Lightbulb className="w-4 h-4 mr-2" />
                 Sugestões
               </TabsTrigger>
+              <TabsTrigger value="scientific" className="data-[state=active]:bg-cyan-500">
+                <Brain className="w-4 h-4 mr-2" />
+                Científico
+              </TabsTrigger>
             </TabsList>
 
             <TabsContent value="knowledge" className="space-y-4">
@@ -827,6 +832,10 @@ export default function Scientist() {
                 </Card>
               )}
             </TabsContent>
+
+            <TabsContent value="scientific" className="space-y-4">
+              <MiroFlowControl />
+            </TabsContent>
           </Tabs>
         </div>
       </div>

docker-compose.miroflow.yml

@@ -0,0 +1,42 @@
+# ─── MiroFlow — Aplicação Coolify ─────────────────────────────────────────────
+# Conecta aos serviços compartilhados (ollama) via network arcadia-internal
+# Requer: docker-compose.shared.yml rodando
+
+name: arcadia-miroflow
+
+services:
+
+  # ── MiroFlow (Cientistas via Ollama) ───────────────────────────────────────────
+  miroflow:
+    build:
+      context: .
+      dockerfile: Dockerfile.miroflow
+    restart: always
+    environment:
+      OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
+      MIROFLOW_PORT: 8006
+      MIROFLOW_RESEARCHER_MODEL: ${MIROFLOW_RESEARCHER_MODEL:-llama3.1:8b}
+    networks:
+      - arcadia-internal
+      - coolify
+    labels:
+      - "traefik.enable=true"
+      - "traefik.docker.network=coolify"
+      - "traefik.http.routers.miroflow.entrypoints=https"
+      - "traefik.http.routers.miroflow.rule=Host(`${MIROFLOW_DOMAIN:-miroflow.onboardbi.com.br}`)"
+      - "traefik.http.routers.miroflow.tls=true"
+      - "traefik.http.routers.miroflow.tls.certresolver=letsencrypt"
+      - "traefik.http.services.miroflow.loadbalancer.server.port=8006"
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8006/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 30s
+
+networks:
+  arcadia-internal:
+    external: true
+    name: arcadia-internal
+  coolify:
+    external: true

docker-compose.prod.yml

@@ -25,6 +25,7 @@ services:
       retries: 10
     networks:
       - arcadia-internal
+      - coolify
 
   # ── Redis ────────────────────────────────────────────────────────────────────
   redis:
@@ -35,6 +36,7 @@ services:
       - redis_data:/data
     networks:
       - arcadia-internal
+      - coolify
 
   # ── App principal ─────────────────────────────────────────────────────────
   app:
@@ -67,6 +69,9 @@ services:
       PLUS_PORT: "8080"
       PLUS_AUTO_START: "false"   # container separado em prod
       SSO_PLUS_BASE_URL: http://plus:8080
+      # ── MiroFlow ──────────────────────────────────────────────────────────
+      MIROFLOW_HOST: miroflow
+      MIROFLOW_PORT: "8006"
       # ── Apache Superset ───────────────────────────────────────────────────
       SUPERSET_HOST: superset
       SUPERSET_ADMIN_USER: ${SUPERSET_ADMIN_USER:-admin}
@@ -142,168 +147,6 @@ services:
     networks:
       - arcadia-internal
 
-  # ── Apache Superset (BI) ─────────────────────────────────────────────────────
-  # Perfil `bi` — suba com: docker compose --profile bi up
-  superset:
-    image: apache/superset:4.1.0
-    restart: always
-    profiles: [bi]
-    environment:
-      SUPERSET_SECRET_KEY: ${SUPERSET_SECRET_KEY}
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/arcadia_superset
-      ARCADIA_DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-      SUPERSET_ADMIN_USER: ${SUPERSET_ADMIN_USER:-admin}
-      SUPERSET_ADMIN_EMAIL: ${SUPERSET_ADMIN_EMAIL:-admin@arcadia.app}
-      SUPERSET_ADMIN_PASSWORD: ${SUPERSET_ADMIN_PASSWORD}
-      SUPERSET_WEBSERVER_PORT: "8088"
-      PYTHONPATH: /app/pythonpath
-    volumes:
-      - ./docker/superset/superset_config.py:/app/pythonpath/superset_config.py:ro
-      - ./docker/superset/init.sh:/app/docker/init.sh:ro
-      - superset_home:/app/superset_home
-    depends_on:
-      db:
-        condition: service_healthy
-    command: ["/bin/bash", "/app/docker/init.sh"]
-    healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8088/health"]
-      interval: 30s
-      timeout: 10s
-      retries: 5
-      start_period: 60s
-    networks:
-      - arcadia-internal
-
-  # ── ERPNext (Frappe Framework) ───────────────────────────────────────────────
-  # Perfil `erpnext` — suba com: docker compose --profile erpnext up
-  erpnext-db:
-    image: mariadb:10.6
-    restart: always
-    profiles: [erpnext]
-    environment:
-      MYSQL_ROOT_PASSWORD: ${ERPNEXT_DB_ROOT_PASSWORD}
-      MYSQL_DATABASE: _frappe
-      MYSQL_USER: frappe
-      MYSQL_PASSWORD: ${ERPNEXT_DB_PASSWORD}
-    volumes:
-      - erpnext_db:/var/lib/mysql
-    command: >
-      --character-set-server=utf8mb4
-      --collation-server=utf8mb4_unicode_ci
-      --skip-character-set-client-handshake
-      --skip-innodb-read-only-compressed
-    healthcheck:
-      test: ["CMD", "mysqladmin", "ping", "-h", "localhost", "-u", "root", "--password=${ERPNEXT_DB_ROOT_PASSWORD}"]
-      interval: 10s
-      timeout: 5s
-      retries: 10
-      start_period: 30s
-    networks:
-      - arcadia-internal
-
-  erpnext:
-    image: frappe/erpnext:version-15
-    restart: always
-    profiles: [erpnext]
-    environment:
-      FRAPPE_SITE_NAME_HEADER: erpnext.local
-      ERPNEXT_DB_ROOT_PASSWORD: ${ERPNEXT_DB_ROOT_PASSWORD}
-      ERPNEXT_ADMIN_PASSWORD: ${ERPNEXT_ADMIN_PASSWORD}
-    volumes:
-      - erpnext_sites:/home/frappe/frappe-bench/sites
-      - erpnext_logs:/home/frappe/frappe-bench/logs
-      - ./docker/erpnext/init.sh:/usr/local/bin/init-erpnext.sh:ro
-    depends_on:
-      erpnext-db:
-        condition: service_healthy
-    command: ["/bin/bash", "/usr/local/bin/init-erpnext.sh"]
-    healthcheck:
-      test: ["CMD-SHELL", "curl -sf http://localhost:8080/api/method/frappe.ping || exit 1"]
-      interval: 30s
-      timeout: 10s
-      retries: 10
-      start_period: 120s
-    networks:
-      - arcadia-internal
-
-  # ── Arcádia Plus (Laravel + MySQL) ──────────────────────────────────────────
-  # Perfil `plus` — suba com: docker compose --profile plus up
-  plus-db:
-    image: mysql:8.0
-    restart: always
-    profiles: [plus]
-    environment:
-      MYSQL_ROOT_PASSWORD: ${PLUS_DB_ROOT_PASSWORD}
-      MYSQL_DATABASE: ${PLUS_DB_DATABASE:-arcadia_plus}
-      MYSQL_USER: ${PLUS_DB_USER:-plus}
-      MYSQL_PASSWORD: ${PLUS_DB_PASSWORD}
-    volumes:
-      - plus_db:/var/lib/mysql
-    command: --default-authentication-plugin=mysql_native_password
-    healthcheck:
-      test: ["CMD", "mysqladmin", "ping", "-h", "localhost", "-u", "root", "--password=${PLUS_DB_ROOT_PASSWORD}"]
-      interval: 10s
-      timeout: 5s
-      retries: 10
-    networks:
-      - arcadia-internal
-
-  plus:
-    image: ${PLUS_IMAGE:-php:8.3-apache}
-    restart: always
-    profiles: [plus]
-    environment:
-      APP_ENV: production
-      APP_KEY: ${PLUS_APP_KEY}
-      APP_URL: https://${DOMAIN}/plus
-      DB_HOST: plus-db
-      DB_DATABASE: ${PLUS_DB_DATABASE:-arcadia_plus}
-      DB_USERNAME: ${PLUS_DB_USER:-plus}
-      DB_PASSWORD: ${PLUS_DB_PASSWORD}
-      SESSION_DRIVER: redis
-      REDIS_HOST: redis
-      ARCADIA_URL: https://${DOMAIN}
-      ARCADIA_SSO_SECRET: ${SSO_SECRET}
-    volumes:
-      - plus_storage:/var/www/html/storage
-    depends_on:
-      plus-db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  # ── Apache Superset (BI) ─────────────────────────────────────────────────────
-  # Perfil `bi` — suba com: docker compose --profile bi up
-  superset:
-    image: apache/superset:4.1.0
-    restart: always
-    profiles: [bi]
-    environment:
-      SUPERSET_SECRET_KEY: ${SUPERSET_SECRET_KEY}
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/arcadia_superset
-      ARCADIA_DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-      SUPERSET_ADMIN_USER: ${SUPERSET_ADMIN_USER:-admin}
-      SUPERSET_ADMIN_EMAIL: ${SUPERSET_ADMIN_EMAIL:-admin@arcadia.app}
-      SUPERSET_ADMIN_PASSWORD: ${SUPERSET_ADMIN_PASSWORD}
-      SUPERSET_WEBSERVER_PORT: "8088"
-      PYTHONPATH: /app/pythonpath
-    volumes:
-      - ./docker/superset/superset_config.py:/app/pythonpath/superset_config.py:ro
-      - ./docker/superset/init.sh:/app/docker/init.sh:ro
-      - superset_home:/app/superset_home
-    depends_on:
-      db:
-        condition: service_healthy
-    command: ["/bin/bash", "/app/docker/init.sh"]
-    healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8088/health"]
-      interval: 30s
-      timeout: 10s
-      retries: 5
-      start_period: 60s
-    networks:
-      - arcadia-internal
-
   # ── ERPNext (Frappe Framework) ───────────────────────────────────────────────
   # Perfil `erpnext` — suba com: docker compose --profile erpnext up
   erpnext-db:
@@ -440,7 +283,7 @@ services:
       - arcadia-internal
 
   # ── LiteLLM (gateway unificado de LLM — soberania dos dados) ─────────────────
-  # Roteia: LLMFit (fine-tuned) → Ollama (local) → externo (opt-in)
+  # Roteia: Ollama (local) → externo (opt-in)
   litellm:
     image: ghcr.io/berriai/litellm:main-latest
     restart: always
@@ -454,9 +297,6 @@ services:
       # Ollama: se instalado no host use http://host-gateway:11434
       # Se usar container Docker, mantém http://ollama:11434
       OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
-      # LLMFit: URL do serviço de modelos fine-tuned
-      LLMFIT_BASE_URL: ${LLMFIT_BASE_URL:-}
-      LLMFIT_API_KEY: ${LLMFIT_API_KEY:-}
       # Providers externos opcionais (soberania: só habilitados se configurados)
       ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-}
       GROQ_API_KEY: ${GROQ_API_KEY:-}
@@ -478,10 +318,8 @@ services:
       - ollama_models:/root/.ollama
     networks:
       - arcadia-internal
-    # Remova 'profiles: [ai]' para ativar por padrão no deploy
-    profiles: [ai]
 
-  # ── Open WebUI (interface para Ollama + LLMFit) ───────────────────────────────
+  # ── Open WebUI (interface para Ollama) ───────────────────────────────
   open-webui:
     image: ghcr.io/open-webui/open-webui:main
     restart: always
@@ -539,7 +377,37 @@ services:
       - "traefik.http.routers.superset.tls=true"
       - "traefik.http.routers.superset.tls.certresolver=letsencrypt"
       - "traefik.http.services.superset.loadbalancer.server.port=8088"
-    profiles: [bi]
+
+  # ── MiroFlow (Cientistas via Ollama) ───────────────────────────────────────────
+  miroflow:
+    build:
+      context: .
+      dockerfile: Dockerfile.miroflow
+    restart: always
+    environment:
+      OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
+      MIROFLOW_PORT: 8006
+      MIROFLOW_RESEARCHER_MODEL: ${MIROFLOW_RESEARCHER_MODEL:-llama3.1:8b}
+    depends_on:
+      ollama:
+        condition: service_started
+    networks:
+      - arcadia-internal
+      - coolify
+    labels:
+      - "traefik.enable=true"
+      - "traefik.docker.network=coolify"
+      - "traefik.http.routers.miroflow.entrypoints=https"
+      - "traefik.http.routers.miroflow.rule=Host(`${MIROFLOW_DOMAIN:-miroflow.onboardbi.com.br}`)"
+      - "traefik.http.routers.miroflow.tls=true"
+      - "traefik.http.routers.miroflow.tls.certresolver=letsencrypt"
+      - "traefik.http.services.miroflow.loadbalancer.server.port=8006"
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8006/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 30s
 
 networks:
   arcadia-internal:

docker-compose.prod.yml.bak

@@ -1,237 +0,0 @@
-# ─── Arcádia Suite — Produção (Coolify) ───────────────────────────────────────
-# Este arquivo é usado pelo Coolify para deploy automático.
-# NÃO inclui volumes de código-fonte — só artefatos de build.
-# Configurar no Coolify: Environment Variables para todas as vars ${...}
-
-name: arcadia-prod
-
-services:
-
-  # ── Banco de dados com pgvector ─────────────────────────────────────────────
-  db:
-    image: pgvector/pgvector:pg16
-    restart: always
-    environment:
-      POSTGRES_DB: ${PGDATABASE:-arcadia}
-      POSTGRES_USER: ${PGUSER:-arcadia}
-      POSTGRES_PASSWORD: ${PGPASSWORD}
-    volumes:
-      - pgdata:/var/lib/postgresql/data
-      - ./docker/init-pgvector.sql:/docker-entrypoint-initdb.d/01-pgvector.sql
-    healthcheck:
-      test: ["CMD-SHELL", "pg_isready -U ${PGUSER:-arcadia}"]
-      interval: 10s
-      timeout: 5s
-      retries: 10
-    networks:
-      - arcadia-internal
-
-  # ── Redis ────────────────────────────────────────────────────────────────────
-  redis:
-    image: redis:7-alpine
-    restart: always
-    command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru
-    volumes:
-      - redis_data:/data
-    networks:
-      - arcadia-internal
-
-  # ── App principal ─────────────────────────────────────────────────────────
-  app:
-    build:
-      context: .
-      dockerfile: Dockerfile
-    restart: always
-    environment:
-      NODE_ENV: production
-      PORT: 5000
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-      REDIS_URL: redis://redis:6379
-      DOCKER_MODE: "true"
-      CONTABIL_PYTHON_URL: http://contabil:8003
-      BI_PYTHON_URL: http://bi:8004
-      AUTOMATION_PYTHON_URL: http://automation:8005
-      FISCO_PYTHON_URL: http://fisco:8002
-      PYTHON_SERVICE_URL: http://embeddings:8001
-      SESSION_SECRET: ${SESSION_SECRET}
-      SSO_SECRET: ${SSO_SECRET}
-      OPENAI_API_KEY: ${OPENAI_API_KEY:-}
-      LITELLM_BASE_URL: http://litellm:4000
-      LITELLM_API_KEY: ${LITELLM_API_KEY}
-      OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
-      # ── Manus Agent — aponta para LiteLLM como gateway unificado ──────────
-      # LiteLLM roteia para Ollama (local), LLMFit (fine-tuned) ou externo
-      AI_INTEGRATIONS_OPENAI_BASE_URL: http://litellm:4000/v1
-      AI_INTEGRATIONS_OPENAI_API_KEY: ${LITELLM_API_KEY}
-    ports:
-      - "5000:5000"
-    depends_on:
-      db:
-        condition: service_healthy
-      redis:
-        condition: service_started
-    networks:
-      - arcadia-internal
-      - arcadia-public
-    labels:
-      - "traefik.enable=true"
-      - "traefik.http.routers.arcadia.rule=Host(`${DOMAIN}`)"
-      - "traefik.http.routers.arcadia.tls=true"
-      - "traefik.http.routers.arcadia.tls.certresolver=letsencrypt"
-
-  # ── Microserviços Python ─────────────────────────────────────────────────────
-  contabil:
-    build:
-      context: .
-      dockerfile: Dockerfile.python
-    restart: always
-    environment:
-      SERVICE_NAME: contabil
-      SERVICE_PORT: 8003
-      CONTABIL_PORT: 8003
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  bi:
-    build:
-      context: .
-      dockerfile: Dockerfile.python
-    restart: always
-    environment:
-      SERVICE_NAME: bi
-      SERVICE_PORT: 8004
-      BI_PORT: 8004
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  automation:
-    build:
-      context: .
-      dockerfile: Dockerfile.python
-    restart: always
-    environment:
-      SERVICE_NAME: automation
-      SERVICE_PORT: 8005
-      AUTOMATION_PORT: 8005
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  fisco:
-    build:
-      context: .
-      dockerfile: Dockerfile.python
-    restart: always
-    environment:
-      SERVICE_NAME: fisco
-      SERVICE_PORT: 8002
-      FISCO_PORT: 8002
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  embeddings:
-    build:
-      context: .
-      dockerfile: Dockerfile.python
-    restart: always
-    environment:
-      SERVICE_NAME: embeddings
-      SERVICE_PORT: 8001
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  # ── LiteLLM (gateway unificado de LLM — soberania dos dados) ─────────────────
-  # Roteia: LLMFit (fine-tuned) → Ollama (local) → externo (opt-in)
-  litellm:
-    image: ghcr.io/berriai/litellm:main-latest
-    restart: always
-    volumes:
-      - ./docker/litellm-config.yaml:/app/config.yaml
-    command: ["--config", "/app/config.yaml", "--port", "4000"]
-    environment:
-      OPENAI_API_KEY: ${OPENAI_API_KEY:-}
-      LITELLM_MASTER_KEY: ${LITELLM_API_KEY}
-      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
-      # Ollama: se instalado no host use http://host-gateway:11434
-      # Se usar container Docker, mantém http://ollama:11434
-      OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
-      # LLMFit: URL do serviço de modelos fine-tuned
-      LLMFIT_BASE_URL: ${LLMFIT_BASE_URL:-}
-      # Providers externos opcionais (soberania: só habilitados se configurados)
-      ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-}
-      GROQ_API_KEY: ${GROQ_API_KEY:-}
-    depends_on:
-      db:
-        condition: service_healthy
-    networks:
-      - arcadia-internal
-
-  # ── Ollama (LLMs locais — soberania total) ────────────────────────────────────
-  # OPÇÃO A (padrão): Ollama como container Docker
-  # OPÇÃO B: Ollama no host → comente este serviço e defina
-  #          OLLAMA_BASE_URL=http://host-gateway:11434 nas env vars
-  ollama:
-    image: ollama/ollama:latest
-    restart: always
-    volumes:
-      - ollama_models:/root/.ollama
-    networks:
-      - arcadia-internal
-    # Remova 'profiles: [ai]' para ativar por padrão no deploy
-    profiles: [ai]
-
-  # ── Open WebUI (interface para Ollama + LLMFit) ───────────────────────────────
-  open-webui:
-    image: ghcr.io/open-webui/open-webui:main
-    restart: always
-    environment:
-      # Pode apontar para LiteLLM para ter acesso a todos os modelos via WebUI
-      OLLAMA_BASE_URL: ${OLLAMA_BASE_URL:-http://ollama:11434}
-      OPENAI_API_BASE_URL: http://litellm:4000/v1
-      OPENAI_API_KEY: ${LITELLM_API_KEY}
-      WEBUI_SECRET_KEY: ${WEBUI_SECRET_KEY}
-    volumes:
-      - open_webui_data:/app/backend/data
-    depends_on:
-      - litellm
-    networks:
-      - arcadia-internal
-      - arcadia-public
-    labels:
-      - "traefik.enable=true"
-      - "traefik.http.routers.webui.rule=Host(`ai.${DOMAIN}`)"
-      - "traefik.http.routers.webui.tls=true"
-      - "traefik.http.routers.webui.tls.certresolver=letsencrypt"
-      - "traefik.http.services.webui.loadbalancer.server.port=8080"
-    profiles: [ai]
-
-networks:
-  arcadia-internal:
-    driver: bridge
-  arcadia-public:
-    driver: bridge
-
-volumes:
-  pgdata:
-  redis_data:
-  ollama_models:
-  open_webui_data:

docker-compose.shared.yml

@@ -0,0 +1,62 @@
+# ─── Arcádia — Infraestrutura Compartilhada ─────────────────────────────────
+# Serviços base: db, redis, ollama
+# Usado por: superset, miroflow, app, etc.
+
+name: arcadia-shared
+
+services:
+
+  # ── Banco de dados com pgvector ─────────────────────────────────────────────
+  db:
+    image: pgvector/pgvector:pg16
+    restart: always
+    environment:
+      POSTGRES_DB: ${PGDATABASE:-arcadia}
+      POSTGRES_USER: ${PGUSER:-arcadia}
+      POSTGRES_PASSWORD: ${PGPASSWORD}
+    volumes:
+      - pgdata:/var/lib/postgresql/data
+      - ./docker/init-pgvector.sql:/docker-entrypoint-initdb.d/01-pgvector.sql
+    healthcheck:
+      test: ["CMD-SHELL", "pg_isready -U ${PGUSER:-arcadia}"]
+      interval: 10s
+      timeout: 5s
+      retries: 10
+    networks:
+      - arcadia-internal
+
+  # ── Redis ────────────────────────────────────────────────────────────────────
+  redis:
+    image: redis:7-alpine
+    restart: always
+    command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru
+    volumes:
+      - redis_data:/data
+    networks:
+      - arcadia-internal
+
+  # ── Ollama (LLMs locais — soberania total) ────────────────────────────────────
+  ollama:
+    image: ollama/ollama:latest
+    restart: always
+    volumes:
+      - ollama_models:/root/.ollama
+    networks:
+      - arcadia-internal
+      - coolify
+
+networks:
+  arcadia-internal:
+    driver: bridge
+    name: arcadia-internal
+  coolify:
+    external: true
+
+volumes:
+  pgdata:
+    external: true
+    name: arcadia-prod_pgdata
+  redis_data:
+    external: true
+    name: arcadia-prod_redis_data
+  ollama_models:

docker-compose.superset.yml

@@ -0,0 +1,49 @@
+# ─── Superset BI — Aplicação Coolify ───────────────────────────────────────
+# Conecta aos serviços compartilhados (db, redis) via network arcadia-internal
+# Requer: docker-compose.shared.yml rodando
+
+name: arcadia-superset
+
+services:
+
+  # ── Superset BI ───────────────────────────────────────────────────────────────
+  superset:
+    image: arcadia-prod-superset:latest
+    restart: always
+    environment:
+      DATABASE_URL: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/superset
+      SUPERSET_SECRET_KEY: ${SUPERSET_SECRET_KEY}
+      SQLALCHEMY_DATABASE_URI: postgresql://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/superset
+      PYTHONPATH: /app/pythonpath
+      SUPERSET_ADMIN_USERNAME: ${SUPERSET_ADMIN_USERNAME:-admin}
+      SUPERSET_ADMIN_PASSWORD: ${SUPERSET_ADMIN_PASSWORD}
+      SUPERSET_ADMIN_EMAIL: ${SUPERSET_ADMIN_EMAIL:-admin@onboardbi.com.br}
+      ARCADIA_DATABASE_URL: postgresql+psycopg2://${PGUSER:-arcadia}:${PGPASSWORD}@db:5432/${PGDATABASE:-arcadia}
+    command: ["/bin/bash", "/app/docker/init.sh"]
+    volumes:
+      - ./docker/superset/superset_config.py:/app/pythonpath/superset_config.py:ro
+      - ./docker/superset/init.sh:/app/docker/init.sh:ro
+      - superset_home:/app/superset_home
+    networks:
+      - arcadia-internal
+      - coolify
+    labels:
+      - "traefik.enable=true"
+      - "traefik.docker.network=coolify"
+      - "traefik.http.routers.superset.entrypoints=https"
+      - "traefik.http.routers.superset.rule=Host(`${SUPERSET_DOMAIN:-bi.onboardbi.com.br}`)"
+      - "traefik.http.routers.superset.tls=true"
+      - "traefik.http.routers.superset.tls.certresolver=letsencrypt"
+      - "traefik.http.services.superset.loadbalancer.server.port=8088"
+
+networks:
+  arcadia-internal:
+    external: true
+    name: arcadia-internal
+  coolify:
+    external: true
+
+volumes:
+  superset_home:
+    external: true
+    name: arcadia-prod_superset_home

docker/litellm-config.yaml

@@ -3,29 +3,15 @@
 #
 # ESTRATÉGIA DE SOBERANIA DOS DADOS:
 # ┌─────────────────────────────────────────────────────────────────────────┐
-# │  TIER 1 (soberania total): LLMFit — modelos fine-tuned locais           │
+# │  TIER 1 (soberania total): Ollama — modelos open source no servidor     │
-# │  TIER 2 (soberania total): Ollama — modelos open source no servidor     │
+# │  TIER 2 (opt-in): Providers externos — só com configuração explícita    │
-# │  TIER 3 (opt-in): Providers externos — só com configuração explícita    │
 # └─────────────────────────────────────────────────────────────────────────┘
 # O Manus, Autonomous Agents e todos os serviços chamam APENAS este proxy.
 # Nunca chamam APIs externas diretamente.
 
 model_list:
 
-  # ── TIER 1: LLMFit (modelos fine-tuned locais — máxima soberania) ────────────
+  # ── TIER 1: Ollama (LLMs locais — soberania total) ───────────────────────────
-  - model_name: arcadia-finetuned
-    litellm_params:
-      model: openai/llama3.2:3b
-      api_base: os.environ/LLMFIT_BASE_URL
-      api_key: os.environ/LLMFIT_API_KEY
-
-  - model_name: arcadia-embed
-    litellm_params:
-      model: openai/nomic-embed-text:latest
-      api_base: os.environ/LLMFIT_BASE_URL
-      api_key: os.environ/LLMFIT_API_KEY
-
-  # ── TIER 2: Ollama (LLMs locais — soberania total) ───────────────────────────
   - model_name: llama3.2
     litellm_params:
       model: ollama/llama3.2:3b
@@ -42,7 +28,7 @@ model_list:
       model: ollama/nomic-embed-text
       api_base: os.environ/OLLAMA_BASE_URL
 
-  # ── TIER 3: OpenAI (opt-in — só ativo se OPENAI_API_KEY configurado) ─────────
+  # ── TIER 2: OpenAI (opt-in — só ativo se OPENAI_API_KEY configurado) ─────────
   - model_name: gpt-4o
     litellm_params:
       model: openai/gpt-4o
@@ -53,34 +39,30 @@ model_list:
       model: openai/gpt-4o-mini
       api_key: os.environ/OPENAI_API_KEY
 
-  # ── TIER 3: Anthropic (opt-in — descomente para habilitar) ───────────────────
+  # ── TIER 2: Anthropic (opt-in — descomente para habilitar) ───────────────────
   # - model_name: claude-sonnet
   #   litellm_params:
   #     model: anthropic/claude-sonnet-4-6
   #     api_key: os.environ/ANTHROPIC_API_KEY
 
-  # ── TIER 3: Groq (opt-in — inferência rápida sem dados persistidos) ──────────
+  # ── TIER 2: Groq (opt-in — inferência rápida sem dados persistidos) ──────────
   # - model_name: groq-llama
   #   litellm_params:
   #     model: groq/llama-3.3-70b-versatile
   #     api_key: os.environ/GROQ_API_KEY
 
   # ── Modelo padrão do Arcádia (Manus usa este) ─────────────────────────────────
-  # Prioridade: LLMFit (TIER 1) → Ollama (TIER 2 — fallback)
   - model_name: arcadia-default
     litellm_params:
-      model: openai/llama3.2:3b
+      model: ollama/llama3.2:3b
-      api_base: os.environ/LLMFIT_BASE_URL
+      api_base: os.environ/OLLAMA_BASE_URL
-      api_key: os.environ/LLMFIT_API_KEY
 
 router_settings:
   routing_strategy: least-busy
-  fallbacks:
+    fallbacks:
     - {"gpt-4o": ["llama3.2"]}
     - {"gpt-4o-mini": ["llama3.2"]}
     - {"arcadia-default": ["llama3.2"]}
-    - {"arcadia-finetuned": ["llama3.2"]}
-    - {"arcadia-embed": ["nomic-embed-text"]}
 
 litellm_settings:
   drop_params: true

docker/superset/init.sh

@@ -3,20 +3,21 @@
 # Executado ao iniciar o container
 set -e
 
-SUPERSET_ADMIN_USER="${SUPERSET_ADMIN_USER:-admin}"
+SUPERSET_ADMIN_USER="${SUPERSET_ADMIN_USERNAME:-${SUPERSET_ADMIN_USER:-admin}}"
 SUPERSET_ADMIN_EMAIL="${SUPERSET_ADMIN_EMAIL:-admin@arcadia.app}"
 SUPERSET_ADMIN_PASSWORD="${SUPERSET_ADMIN_PASSWORD:-arcadia2026}"
 ARCADIA_DB_URL="${ARCADIA_DATABASE_URL:-postgresql://arcadia:arcadia123@db:5432/arcadia}"
 
 echo "[Superset Init] Aguardando PostgreSQL..."
-until python -c "
+cat > /tmp/pgcheck.py << 'EOF'
 import psycopg2, os, sys
+url = os.environ.get('SQLALCHEMY_DATABASE_URI', 'postgresql://arcadia:arcadia123@db:5432/superset')
 try:
-    url = os.environ.get('DATABASE_URL', 'postgresql://arcadia:arcadia123@db:5432/arcadia_superset')
     psycopg2.connect(url)
-    sys.exit(0)
+except Exception:
-except: sys.exit(1)
+    sys.exit(1)
-" 2>/dev/null; do
+EOF
+until python /tmp/pgcheck.py 2>/dev/null; do
   sleep 2
 done
 echo "[Superset Init] PostgreSQL disponível!"

docker/superset/superset_config.py

@@ -9,8 +9,8 @@ SECRET_KEY = os.environ.get("SUPERSET_SECRET_KEY", "change-in-production-use-ope
 
 # ── Banco de metadados do Superset ────────────────────────────────────────────
 SQLALCHEMY_DATABASE_URI = os.environ.get(
-    "DATABASE_URL",
+    "SQLALCHEMY_DATABASE_URI",
-    "postgresql://arcadia:arcadia123@db:5432/arcadia_superset"
+    os.environ.get("DATABASE_URL", "postgresql://arcadia:arcadia123@db:5432/superset")
 )
 
 # ── CORS — permite o gateway Arcádia (:5000) chamar a API ────────────────────

migrations/miroflow_dashboards.sql

@@ -0,0 +1,39 @@
+-- MiroFlow Generated Dashboards
+-- Rastreia dashboards criados pelo MiroFlow baseado em análises
+
+CREATE TABLE IF NOT EXISTS miroflow_generated_dashboards (
+  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
+
+  -- Análise que criou este dashboard
+  analysis_id VARCHAR(255),
+  agent VARCHAR(50) NOT NULL CHECK (agent IN ('statistician', 'fiscal_auditor', 'researcher')),
+  task TEXT NOT NULL,
+  insights JSONB,
+
+  -- Dashboard no Superset
+  dashboard_id INT NOT NULL,
+  dashboard_title VARCHAR(255) NOT NULL,
+  dataset_name VARCHAR(255),
+
+  -- SQL sugerido/criado
+  sql_query TEXT,
+
+  -- Auditoria
+  created_by UUID,
+  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+  tenant_id INT,
+
+  -- Referência
+  superset_url VARCHAR(512),
+
+  -- Soft delete
+  deleted_at TIMESTAMP,
+
+  -- Constraints
+  CONSTRAINT unique_analysis_dashboard UNIQUE (analysis_id, dashboard_id) DEFERRABLE INITIALLY DEFERRED
+);
+
+CREATE INDEX idx_miroflow_dashboards_analysis ON miroflow_generated_dashboards(analysis_id);
+CREATE INDEX idx_miroflow_dashboards_created_at ON miroflow_generated_dashboards(created_at DESC);
+CREATE INDEX idx_miroflow_dashboards_dashboard_id ON miroflow_generated_dashboards(dashboard_id);
+CREATE INDEX idx_miroflow_dashboards_tenant ON miroflow_generated_dashboards(tenant_id);

script/build.ts

@@ -55,7 +55,7 @@ async function buildAll() {
     define: {
       "process.env.NODE_ENV": '"production"',
     },
-    minify: true,
+    minify: false,
     external: externals,
     logLevel: "info",
   });

server/auth.ts

@@ -30,12 +30,14 @@ async function comparePasswords(supplied: string, stored: string) {
   return timingSafeEqual(hashedBuf, suppliedBuf);
 }
 
-if (!process.env.SESSION_SECRET) {
+// CORREÇÃO: Session secret seguro - obrigatório em produção
-  console.warn("[auth] WARNING: SESSION_SECRET env var not set. Using insecure fallback. Set SESSION_SECRET in production.");
+const SESSION_SECRET = process.env.SESSION_SECRET || 
-}
+  (process.env.NODE_ENV === 'production' 
+    ? (() => { throw new Error('SESSION_SECRET obrigatório em produção'); })()
+    : randomBytes(32).toString('hex'));
 
 const sessionSettings: session.SessionOptions = {
-  secret: process.env.SESSION_SECRET || `arcadia-dev-${Math.random().toString(36)}`,
+  secret: SESSION_SECRET,
   resave: false,
   saveUninitialized: false,
   store: storage.sessionStore,

server/communication/engine.ts

@@ -6,9 +6,26 @@ import ws from "ws";
 neonConfig.webSocketConstructor = ws;
 
 const app = express();
-const PORT = 8006;
+const PORT = process.env.PORT || 8006;
 
-app.use(cors());
+// CORREÇÃO: CORS restrito - whitelist de origens permitidas
+const allowedOrigins = [
+  'http://localhost:5000',
+  'https://localhost:5000',
+  process.env.FRONTEND_URL,
+  process.env.DOMAIN ? `https://${process.env.DOMAIN}` : null,
+].filter(Boolean);
+
+app.use(cors({
+  origin: (origin, callback) => {
+    if (!origin || allowedOrigins.includes(origin)) {
+      callback(null, true);
+    } else {
+      callback(new Error('CORS não permitido'));
+    }
+  },
+  credentials: true
+}));
 app.use(express.json());
 
 const pool = new Pool({ connectionString: process.env.DATABASE_URL });

server/miroflow/ANALYZE_ENDPOINT.md

@@ -0,0 +1,39 @@
+# MiroFlow /analyze Endpoint
+
+## Como funciona
+
+O botão "Analisar" no BiWorkspace (tab Científico) chama `POST /api/miroflow/analyze`.
+
+O handler vive em `engine-proxy.ts` e chama diretamente o Ollama com o model `deepseek-r1:14b` (fallback: `llama3.2:3b`).
+
+## Fluxo
+
+```
+BiWorkspace → POST /api/miroflow/analyze
+  → engine-proxy.ts (Node, host)
+    → ollama-ia1upsekrad96at5hq97e4qa:11434/api/chat
+      → deepseek-r1:14b
+    ← { result, model, execution_id, duration_ms }
+  ← resposta ao frontend
+```
+
+## Agentes disponíveis
+
+| Agent | System prompt |
+|-------|--------------|
+| `statistician` | Análise estatística e descritiva |
+| `fiscal_auditor` | Compliance tributário brasileiro |
+| `researcher` | Correlações e inteligência de negócios |
+
+## Infraestrutura
+
+- O container `ollama-ia1upsekrad96at5hq97e4qa` precisa estar na rede `arcadia-prod_arcadia-internal`.
+- Comando para reconectar se necessário:
+  ```bash
+  docker network connect arcadia-prod_arcadia-internal ollama-ia1upsekrad96at5hq97e4qa
+  ```
+- Tempo médio de resposta: ~2-3 min (deepseek-r1:14b).
+
+## Variável de ambiente
+
+`OLLAMA_BASE_URL` sobrescreve o hostname padrão do Ollama.

server/miroflow/engine-proxy.ts

@@ -1,12 +1,69 @@
 import type { Express, Request, Response } from "express";
-import crypto from "crypto";
+import { randomUUID } from "node:crypto";
-import { createNode } from "../graph/service";
 
 const MIROFLOW_HOST = process.env.MIROFLOW_HOST || "localhost";
 const MIROFLOW_PORT = parseInt(process.env.MIROFLOW_PORT || "8006", 10);
 const MIROFLOW_URL = `http://${MIROFLOW_HOST}:${MIROFLOW_PORT}`;
-const MIROFLOW_TIMEOUT = 300_000; // 5 minutos — deepseek-r1:14b pode levar 60-120s
+const MIROFLOW_TIMEOUT = 600_000; // 10 minutos
-const MIROFLOW_HEALTH_TIMEOUT = 5_000; // 5 segundos para health check
+const MIROFLOW_HEALTH_TIMEOUT = 5_000;
+
+const OLLAMA_URL = process.env.OLLAMA_BASE_URL || "http://ollama-ia1upsekrad96at5hq97e4qa:11434";
+
+const AGENT_CONFIGS: Record<string, { model: string; system: string }> = {
+  statistician: {
+    model: "deepseek-r1:14b",
+    system:
+      "Você é um estatístico especializado em análise de dados empresariais. " +
+      "Responda em português brasileiro. Forneça análises quantitativas claras, " +
+      "com estatísticas descritivas, padrões e insights acionáveis. Seja preciso e objetivo.",
+  },
+  fiscal_auditor: {
+    model: "deepseek-r1:14b",
+    system:
+      "Você é um auditor fiscal especializado em compliance tributário brasileiro. " +
+      "Responda em português brasileiro. Identifique inconsistências, riscos fiscais " +
+      "e recomende ações corretivas. Cite legislação quando relevante.",
+  },
+  researcher: {
+    model: "deepseek-r1:14b",
+    system:
+      "Você é um pesquisador analítico especializado em inteligência de negócios. " +
+      "Responda em português brasileiro. Identifique correlações, tendências e " +
+      "hipóteses baseadas em dados. Apresente achados de forma estruturada.",
+  },
+};
+
+const FALLBACK_MODEL = "llama3.2:3b";
+
+async function callLLM(model: string, system: string, prompt: string): Promise<string> {
+  const controller = new AbortController();
+  const timeout = setTimeout(() => controller.abort(), 300_000);
+  try {
+    const resp = await fetch(`${OLLAMA_URL}/api/chat`, {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        model,
+        messages: [
+          { role: "system", content: system },
+          { role: "user", content: prompt },
+        ],
+        stream: false,
+      }),
+      signal: controller.signal,
+    });
+    clearTimeout(timeout);
+    if (!resp.ok) {
+      const err = await resp.json().catch(() => ({ error: resp.statusText }));
+      throw new Error(err?.error ?? `Ollama error: ${resp.status}`);
+    }
+    const data: any = await resp.json();
+    return data.message?.content ?? "";
+  } catch (err: any) {
+    clearTimeout(timeout);
+    throw err;
+  }
+}
 
 async function proxyToMiroFlow(path: string, method: string = "GET", body?: object): Promise<any> {
   const timeoutMs = path === "/health" ? MIROFLOW_HEALTH_TIMEOUT : MIROFLOW_TIMEOUT;
@@ -27,41 +84,11 @@ async function proxyToMiroFlow(path: string, method: string = "GET", body?: obje
     return await response.json();
   } catch (err: any) {
     clearTimeout(timeout);
-    if (err.name === "AbortError") throw new Error("MiroFlow timeout (300s)");
+    if (err.name === "AbortError") throw new Error("MiroFlow timeout (600s)");
     throw err;
   }
 }
 
-async function registerExecutionInKG(req: Request, execData: any, inputBody: any): Promise<void> {
-  try {
-    const auditHash = crypto
-      .createHash("sha256")
-      .update(JSON.stringify({
-        execution_id: execData.execution_id,
-        agent: execData.agent,
-        model: execData.model,
-        input: inputBody,
-        output: execData.result,
-      }))
-      .digest("hex");
-
-    await createNode({
-      type: "miroflow_execution",
-      tenantId: (req.user as any)?.tenantId ?? null,
-      data: {
-        ...execData,
-        input: inputBody,
-        auditHash,
-        immutable: true,
-        registeredAt: new Date().toISOString(),
-      },
-    });
-  } catch (kgErr: any) {
-    // KG failure não deve bloquear a resposta ao cliente
-    console.error("[MiroFlow] Falha ao registrar no KG:", kgErr.message);
-  }
-}
-
 export function registerMiroFlowRoutes(app: Express): void {
   app.get("/api/miroflow/health", async (_req: Request, res: Response) => {
     try {
@@ -73,19 +100,50 @@ export function registerMiroFlowRoutes(app: Express): void {
   });
 
   app.post("/api/miroflow/analyze", async (req: Request, res: Response) => {
-    if (!req.isAuthenticated()) {
+    console.log("[MiroFlow] POST /api/miroflow/analyze - começando");
-      return res.status(401).json({ error: "Não autenticado" });
-    }
     try {
-      const inputBody = {
+      const { agent = "statistician", task, context } = req.body as {
-        ...req.body,
+        agent?: string;
-        tenant_id: (req.user as any)?.tenantId ?? null,
+        task: string;
+        context?: Record<string, unknown>;
       };
-      const data = await proxyToMiroFlow("/analyze", "POST", inputBody);
+
-      // Registrar no KG de forma assíncrona (não bloqueia a resposta)
+      if (!task?.trim()) {
-      registerExecutionInKG(req, data, req.body).catch(() => {});
+        return res.status(400).json({ error: "Campo 'task' é obrigatório" });
-      res.json(data);
+      }
+
+      const agentKey = AGENT_CONFIGS[agent] ? agent : "statistician";
+      const cfg = AGENT_CONFIGS[agentKey];
+
+      let prompt = task;
+      if (context && Object.keys(context).length > 0) {
+        const ctxStr = Object.entries(context)
+          .filter(([, v]) => v != null)
+          .map(([k, v]) => `${k}: ${v}`)
+          .join("\n");
+        if (ctxStr) prompt = `Contexto disponível:\n${ctxStr}\n\nTarefa: ${task}`;
+      }
+
+      const start = Date.now();
+      let model = cfg.model;
+      let result: string;
+
+      try {
+        result = await callLLM(model, cfg.system, prompt);
+      } catch {
+        model = FALLBACK_MODEL;
+        result = await callLLM(model, cfg.system, prompt);
+      }
+
+      res.json({
+        execution_id: randomUUID(),
+        agent: agentKey,
+        model,
+        result,
+        duration_ms: Date.now() - start,
+      });
     } catch (err: any) {
+      console.error("[MiroFlow] erro:", err.message);
       res.status(502).json({ error: err.message });
     }
   });

server/modules/miroflow

@@ -1 +1 @@
-Subproject commit 9d180f1eeb5e301c440ad7ce8b12c14222779040
+Subproject commit fe1a7397fbb5a3eee145feb2fac94f620ef43f3e

server/routes.ts

@@ -182,11 +182,22 @@ export async function registerRoutes(
   // Arcádia Plus - SSO routes (proxy already registered at top)
   app.use("/api/plus/sso", plusSsoRoutes);
 
+  // CORREÇÃO: /api/tenants protegido - apenas admin vê todos
   app.get("/api/tenants", async (req: any, res) => {
     if (!req.isAuthenticated()) {
       return res.status(401).json({ error: "Authentication required" });
     }
     try {
+      // Se não for admin, retornar apenas o tenant do usuário
+      if (req.user?.role !== 'admin') {
+        if (req.user?.tenantId) {
+          const tenant = await storage.getTenant(req.user.tenantId);
+          return res.json(tenant ? [tenant] : []);
+        }
+        return res.status(403).json({ error: "Access denied" });
+      }
+      
+      // Admin vê todos
       const tenants = await storage.getTenants();
       res.json(tenants);
     } catch (error) {

server/storage.ts

@@ -15,7 +15,7 @@ export interface IStorage {
   sessionStore: session.Store;
   
   getUser(id: string): Promise<User | undefined>;
-  getUserByUsername(username: string): Promise<User | undefined>;
+  getUserByUsername(username: string, tenantId?: number): Promise<User | undefined>;
   createUser(user: InsertUser): Promise<User>;
   getEnrichedUser(user: User): Promise<any>;
   
@@ -28,6 +28,7 @@ export interface IStorage {
   getUserApplications(userId: string): Promise<Application[]>;
   assignApplicationToUser(userId: string, applicationId: string): Promise<void>;
   removeApplicationFromUser(userId: string, applicationId: string): Promise<void>;
+  getTenant(id: number): Promise<{ id: number; name: string; slug: string; tenantType?: string; plan?: string; status?: string } | undefined>;
   getTenants(): Promise<{ id: number; name: string; slug: string }[]>;
 }
 
@@ -46,8 +47,21 @@ export class DatabaseStorage implements IStorage {
     return user;
   }
 
-  async getUserByUsername(username: string): Promise<User | undefined> {
+  // CORREÇÃO: getUserByUsername com validação de tenant
+  async getUserByUsername(username: string, tenantId?: number): Promise<User | undefined> {
     const [user] = await db.select().from(users).where(eq(users.username, username));
+    
+    // Se tenantId foi passado, validar que usuário pertence a esse tenant
+    if (tenantId && user) {
+      const [tenantUser] = await db.select()
+        .from(tenantUsers)
+        .where(and(
+          eq(tenantUsers.userId, user.id),
+          eq(tenantUsers.tenantId, tenantId)
+        ));
+      if (!tenantUser) return undefined;
+    }
+    
     return user;
   }
 
@@ -146,6 +160,19 @@ export class DatabaseStorage implements IStorage {
     return enriched;
   }
 
+  // CORREÇÃO: getTenant para buscar tenant específico
+  async getTenant(id: number): Promise<{ id: number; name: string; slug: string; tenantType?: string; plan?: string; status?: string } | undefined> {
+    const [tenant] = await db.select({ 
+      id: tenants.id, 
+      name: tenants.name, 
+      slug: tenants.slug,
+      tenantType: tenants.tenantType,
+      plan: tenants.plan,
+      status: tenants.status
+    }).from(tenants).where(eq(tenants.id, id));
+    return tenant;
+  }
+
   async getTenants(): Promise<{ id: number; name: string; slug: string }[]> {
     const result = await db.select({ 
       id: tenants.id, 

server/superset/MiroFlowBridge.ts

@@ -0,0 +1,251 @@
+/**
+ * MiroFlow Bridge para Apache Superset
+ *
+ * Adaptador que conecta Superset com MiroFlow para análises científicas.
+ * Fluxo: SQL (Superset) → MiroFlow (análise) → Enriquecimento de dados → KG (provenance)
+ */
+
+import type { Request, Response } from "express";
+import { createNode } from "../graph/service";
+import crypto from "crypto";
+
+interface MiroFlowConfig {
+  type?: "exploratory" | "forecast" | "anomaly" | "hypothesis" | "causal";
+  horizon?: number; // dias para forecast
+  confidence_level?: number; // 0.90, 0.95, 0.99
+  methods?: string[]; // ["arima", "prophet", "statistical_test", etc]
+}
+
+interface SupersetDataset {
+  data: Record<string, any>[];
+  columns: string[];
+  index?: number[];
+}
+
+interface MiroFlowResult {
+  execution_id: string;
+  agent: string;
+  model: string;
+  result: {
+    summary: string;
+    analysis_type: string;
+    descriptive_stats?: Record<string, any>;
+    anomalies?: Array<{ index: number; score: number; value: any }>;
+    forecast?: { values: number[]; lower_bound: number[]; upper_bound: number[] };
+    hypothesis_test?: { p_value: number; result: string };
+    confidence_intervals?: Record<string, [number, number]>;
+  };
+  metadata: {
+    execution_time_ms: number;
+    rows_analyzed: number;
+    columns_used: string[];
+  };
+}
+
+export interface EnrichedDataset extends SupersetDataset {
+  _miroflow_analysis: string;
+  _miroflow_type: string;
+  _confidence_intervals?: Record<string, [number, number]>;
+  _anomaly_scores?: Record<number, number>;
+  _forecast?: { values: number[]; lower_bound: number[]; upper_bound: number[] };
+  _metadata: {
+    analysis_executed_at: string;
+    miroflow_execution_id: string;
+    miroflow_model: string;
+    execution_time_ms: number;
+  };
+}
+
+/**
+ * MiroFlowBridge: Proxy entre Superset e MiroFlow
+ * Enriquece datasets SQL com análises científicas
+ */
+export class MiroFlowBridge {
+  private miroflowBaseUrl: string;
+  private miroflowTimeout: number = 300_000; // 5 min
+
+  constructor(miroflowBaseUrl: string = "http://localhost:8006") {
+    this.miroflowBaseUrl = miroflowBaseUrl;
+  }
+
+  /**
+   * Analisa dataset via MiroFlow
+   */
+  async analyze(
+    dataset: SupersetDataset,
+    config: MiroFlowConfig,
+    tenantId?: number,
+    userId?: number
+  ): Promise<MiroFlowResult> {
+    const controller = new AbortController();
+    const timeout = setTimeout(() => controller.abort(), this.miroflowTimeout);
+
+    try {
+      const payload = {
+        dataset: JSON.stringify(dataset),
+        analysis_type: config.type || "exploratory",
+        config,
+        tenant_id: tenantId,
+        user_id: userId,
+        source: "superset_bridge",
+      };
+
+      const response = await fetch(`${this.miroflowBaseUrl}/analyze`, {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify(payload),
+        signal: controller.signal,
+      });
+
+      clearTimeout(timeout);
+
+      if (!response.ok) {
+        const err = await response.json().catch(() => ({ detail: response.statusText }));
+        throw new Error(`MiroFlow error: ${err.detail || response.status}`);
+      }
+
+      return await response.json();
+    } catch (err: any) {
+      clearTimeout(timeout);
+      if (err.name === "AbortError") {
+        throw new Error("MiroFlow analysis timeout (5 min)");
+      }
+      throw err;
+    }
+  }
+
+  /**
+   * Enriquece dataset com resultados da análise
+   */
+  enrich(dataset: SupersetDataset, result: MiroFlowResult): EnrichedDataset {
+    const enriched: EnrichedDataset = {
+      ...dataset,
+      _miroflow_analysis: result.result.summary,
+      _miroflow_type: result.result.analysis_type,
+      _metadata: {
+        analysis_executed_at: new Date().toISOString(),
+        miroflow_execution_id: result.execution_id,
+        miroflow_model: result.model,
+        execution_time_ms: result.metadata.execution_time_ms,
+      },
+    };
+
+    // Adicionar intervalos de confiança
+    if (result.result.confidence_intervals) {
+      enriched._confidence_intervals = result.result.confidence_intervals;
+    }
+
+    // Adicionar scores de anomalias (mapeados para índices)
+    if (result.result.anomalies && result.result.anomalies.length > 0) {
+      enriched._anomaly_scores = {};
+      result.result.anomalies.forEach((anom) => {
+        enriched._anomaly_scores![anom.index] = anom.score;
+      });
+    }
+
+    // Adicionar forecast
+    if (result.result.forecast) {
+      enriched._forecast = result.result.forecast;
+    }
+
+    return enriched;
+  }
+
+  /**
+   * Registra análise no Knowledge Graph para provenance
+   */
+  async registerInKG(
+    result: MiroFlowResult,
+    dataset: SupersetDataset,
+    config: MiroFlowConfig,
+    req: Request
+  ): Promise<void> {
+    try {
+      const analysisHash = crypto
+        .createHash("sha256")
+        .update(
+          JSON.stringify({
+            execution_id: result.execution_id,
+            dataset_columns: dataset.columns,
+            config,
+            result: result.result,
+          })
+        )
+        .digest("hex");
+
+      await createNode({
+        type: "miroflow_analysis",
+        tenantId: (req.user as any)?.tenantId ?? null,
+        data: {
+          execution_id: result.execution_id,
+          agent: result.agent,
+          model: result.model,
+          analysis_type: result.result.analysis_type,
+          dataset_shape: `${dataset.data.length}x${dataset.columns.length}`,
+          columns_analyzed: dataset.columns,
+          config,
+          summary: result.result.summary,
+          execution_time_ms: result.metadata.execution_time_ms,
+          analysisHash,
+          immutable: true,
+          source: "superset_bridge",
+          registeredAt: new Date().toISOString(),
+        },
+      });
+    } 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");
+}

server/superset/routes.ts

@@ -1,4 +1,5 @@
 import type { Express, Request, Response } from "express";
+import { createMiroFlowBridge } from "./MiroFlowBridge.js";
 
 const SUPERSET_HOST = process.env.SUPERSET_HOST || "localhost";
 const SUPERSET_PORT = parseInt(process.env.SUPERSET_PORT || "8088", 10);
@@ -6,6 +7,8 @@ const SUPERSET_URL = `http://${SUPERSET_HOST}:${SUPERSET_PORT}`;
 const ADMIN_USER = process.env.SUPERSET_ADMIN_USER || "admin";
 const ADMIN_PASS = process.env.SUPERSET_ADMIN_PASSWORD || "arcadia2026";
 
+const miroflowBridge = createMiroFlowBridge();
+
 // Cache do service token (válido por 50 min)
 let cachedToken: string | null = null;
 let tokenExpiry = 0;
@@ -105,4 +108,183 @@ export function registerSupersetRoutes(app: Express): void {
     if (!req.isAuthenticated()) return res.status(401).json({ error: "Not authenticated" });
     res.redirect("/superset/login");
   });
+
+  // ============================================================================
+  // MiroFlow Bridge Routes
+  // ============================================================================
+
+  /**
+   * POST /api/superset/miroflow/analyze
+   * Enriquece dataset Superset com análises científicas via MiroFlow
+   *
+   * Request body:
+   * {
+   *   "dataset": { "data": [...], "columns": [...] },
+   *   "config": { "type": "forecast|anomaly|exploratory", "horizon": 30, "confidence_level": 0.95 }
+   * }
+   *
+   * Response:
+   * {
+   *   "success": true,
+   *   "data": { ...enriched dataset with _miroflow_analysis, _anomaly_scores, etc },
+   *   "analysis": { "summary": "...", "analysis_type": "..." },
+   *   "execution_id": "uuid"
+   * }
+   */
+  app.post("/api/superset/miroflow/analyze", async (req: Request, res: Response) => {
+    await miroflowBridge.handleAnalyzeRequest(req, res);
+  });
+
+  /**
+   * GET /api/superset/miroflow/health
+   * Verifica conexão com MiroFlow bridge
+   */
+  app.get("/api/superset/miroflow/health", async (_req: Request, res: Response) => {
+    try {
+      const miroflowUrl = process.env.MIROFLOW_URL || "http://localhost:8006";
+      const response = await fetch(`${miroflowUrl}/health`, {
+        signal: AbortSignal.timeout(5_000),
+      });
+      const data = await response.json();
+      res.json({
+        online: response.ok,
+        miroflow: data,
+        bridge: "operational",
+        endpoints: {
+          analyze: "/api/superset/miroflow/analyze",
+          health: "/api/superset/miroflow/health",
+        },
+      });
+    } catch (err: any) {
+      res.json({
+        online: false,
+        error: err.message,
+        bridge: "offline",
+      });
+    }
+  });
+
+  /**
+   * POST /api/superset/miroflow/create-dashboard
+   * Cria um dashboard no Superset baseado em análise MiroFlow
+   */
+  app.post("/api/superset/miroflow/create-dashboard", async (req: Request, res: Response) => {
+    if (!req.isAuthenticated()) {
+      return res.status(401).json({ error: "Não autenticado" });
+    }
+
+    try {
+      const { dashboardTitle, sqlQuery, analysisId, agent, task, insights } = req.body;
+
+      if (!dashboardTitle || !sqlQuery || !analysisId) {
+        return res.status(400).json({ error: "dashboardTitle, sqlQuery e analysisId são obrigatórios" });
+      }
+
+      const token = await getServiceToken();
+      const user = req.user as any;
+
+      // 1. Criar dataset no Superset
+      const datasetResp = await fetch(`${SUPERSET_URL}/api/v1/datasets/`, {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+          "Authorization": `Bearer ${token}`,
+        },
+        body: JSON.stringify({
+          database: 1, // ID do banco "Arcádia Suite"
+          table_name: `miroflow_${analysisId.substring(0, 8)}`,
+          sql: sqlQuery,
+        }),
+      });
+
+      if (!datasetResp.ok) {
+        const err = await datasetResp.json().catch(() => ({ detail: "Erro ao criar dataset" }));
+        throw new Error(`Falha ao criar dataset: ${err.detail}`);
+      }
+
+      const dataset = await datasetResp.json();
+      const datasetId = dataset.id;
+
+      // 2. Criar chart automático
+      const chartResp = await fetch(`${SUPERSET_URL}/api/v1/chart/`, {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+          "Authorization": `Bearer ${token}`,
+        },
+        body: JSON.stringify({
+          datasource_id: datasetId,
+          datasource_type: "table",
+          chart_type: "table", // Começar com table, depois adicionar mais tipos
+          name: `${dashboardTitle} - Dados`,
+          description: `Criado via MiroFlow Analysis (${agent})`,
+        }),
+      });
+
+      if (!chartResp.ok) {
+        const err = await chartResp.json().catch(() => ({ detail: "Erro ao criar chart" }));
+        throw new Error(`Falha ao criar chart: ${err.detail}`);
+      }
+
+      const chart = await chartResp.json();
+      const chartId = chart.id;
+
+      // 3. Criar dashboard
+      const dashboardResp = await fetch(`${SUPERSET_URL}/api/v1/dashboard/`, {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+          "Authorization": `Bearer ${token}`,
+        },
+        body: JSON.stringify({
+          dashboard_title: dashboardTitle,
+          description: `Análise MiroFlow - ${agent} - ${new Date().toLocaleString('pt-BR')}`,
+        }),
+      });
+
+      if (!dashboardResp.ok) {
+        const err = await dashboardResp.json().catch(() => ({ detail: "Erro ao criar dashboard" }));
+        throw new Error(`Falha ao criar dashboard: ${err.detail}`);
+      }
+
+      const dashboard = await dashboardResp.json();
+      const dashboardId = dashboard.id;
+
+      // 4. Adicionar chart ao dashboard
+      const updateResp = await fetch(`${SUPERSET_URL}/api/v1/dashboard/${dashboardId}`, {
+        method: "PUT",
+        headers: {
+          "Content-Type": "application/json",
+          "Authorization": `Bearer ${token}`,
+        },
+        body: JSON.stringify({
+          dashboard_title: dashboardTitle,
+          slices: [chartId],
+        }),
+      });
+
+      if (!updateResp.ok) {
+        throw new Error("Falha ao adicionar chart ao dashboard");
+      }
+
+      // 5. Salvar referência no banco Arcádia (TODO: implementar com prepared statements)
+      // Por enquanto apenas retorna dashboard criado
+      console.log(`[Superset] Dashboard criado: ID=${dashboardId}, título="${dashboardTitle}"`);
+
+      res.json({
+        success: true,
+        dashboardId,
+        dashboardUrl: `${SUPERSET_URL}/superset/dashboard/${dashboardId}/`,
+        message: `Dashboard "${dashboardTitle}" criado com sucesso!`,
+      });
+    } catch (err: any) {
+      console.error("[Superset] Erro ao criar dashboard:", err.message);
+      res.status(502).json({
+        error: err.message,
+        source: "superset_create_dashboard",
+      });
+    }
+  });
+
+  console.log("[Superset] MiroFlow Bridge registered at /api/superset/miroflow");
 }