Vercel Sandbox Integration

.dockerignore

@@ -80,7 +80,6 @@ docker-compose*.yml
 cloudbuild.yaml
 
 # Drizzle
-drizzle/
 
 # Scripts
 install.sh

.env.local.example

@@ -24,8 +24,20 @@ GEMINI_3_PRO_API_KEY=your_gemini_3_pro_api_key_here
 # If not set, the `search` tool is skipped and the LLM answers from its own knowledge.
 TAVILY_API_KEY=your_tavily_api_key
 
+# Firecrawl API (https://firecrawl.dev)
+FIRECRAWL_API_KEY=your_firecrawl_api_key
+
 # Supabase Credentials
 NEXT_PUBLIC_SUPABASE_URL=YOUR_SUPABASE_URL_HERE
 NEXT_PUBLIC_SUPABASE_ANON_KEY=YOUR_SUPABASE_ANON_KEY_HERE
 SUPABASE_SERVICE_ROLE_KEY=YOUR_SUPABASE_SERVICE_ROLE_KEY_HERE
 DATABASE_URL=postgresql://postgres:[YOUR-POSTGRES-PASSWORD]@[YOUR-SUPABASE-DB-HOST]:[PORT]/postgres
+
+# Vercel Sandbox (MicroVM Infrastructure)
+# Required for OIDC-based microVM authentication
+# VERCEL_TOKEN: Create a Personal Access Token in Vercel Dashboard > Settings > Tokens
+VERCEL_TOKEN=your_vercel_token
+# VERCEL_TEAM_ID: Found in Vercel Dashboard > Team Settings > General (starts with 'team_')
+VERCEL_TEAM_ID=your_vercel_team_id
+# VERCEL_PROJECT_ID: Found in Vercel Dashboard > [Project] > Settings > General (starts with 'prj_')
+VERCEL_PROJECT_ID=your_vercel_project_id

CLOUD_DEPLOYMENT.md

@@ -0,0 +1,97 @@
+# Cloud Deployment Guide for QCX
+
+This guide provides instructions for deploying the QCX stack (Next.js, PostgreSQL with pgvector/PostGIS, and Qdrant) to various cloud platforms.
+
+## Infrastructure Overview
+
+The application consists of:
+1.  **QCX Web App**: Next.js application running on Bun.
+2.  **PostgreSQL**: Database with `pgvector` and `PostGIS` extensions.
+3.  **Qdrant**: High-performance vector database (optional, for advanced vector search).
+
+---
+
+## 1. Deploying with Docker Compose (VPS / EC2 / Compute Engine)
+
+The easiest way to deploy the entire stack is using `docker-compose`.
+
+1.  **Clone the repository** on your server.
+2.  **Create a `.env` file** based on the environment variables in `docker-compose.yaml`.
+3.  **Run the stack**:
+    ```bash
+    docker-compose up -d --build
+    ```
+
+---
+
+## 2. Deploying to Render
+
+Render is a great choice for managed services.
+
+### PostgreSQL (Managed)
+1.  Create a **New PostgreSQL** instance on Render.
+2.  **Note**: Standard Render Postgres does not include `pgvector` or `PostGIS` by default on all plans. You may need to use a Docker-based Postgres on Render or ensure your plan supports these extensions.
+3.  If using Render's managed Postgres, run the extensions command manually via a SQL client:
+    ```sql
+    CREATE EXTENSION IF NOT EXISTS postgis;
+    CREATE EXTENSION IF NOT EXISTS vector;
+    ```
+
+### Web Service
+1.  Create a **New Web Service** pointing to your repository.
+2.  Select **Docker** as the runtime.
+3.  Specify the **Dockerfile path** as `Dockerfile`.
+4.  Add environment variables:
+    *   `DATABASE_URL`: Your Render Postgres connection string.
+    *   `EXECUTE_MIGRATIONS`: `true`
+    *   `NEXT_PUBLIC_MAPBOX_ACCESS_TOKEN`: Your Mapbox token.
+    *   (Add other necessary API keys like Google, xAI, etc.)
+
+### Qdrant (Optional)
+1.  Create a **New Private Service** or **Web Service**.
+2.  Select **Docker** as the runtime.
+3.  Use the image: `qdrant/qdrant:latest`.
+4.  Set `QDRANT_URL` in your Web Service to point to this service.
+
+---
+
+## 3. Deploying to Google Cloud (GCP)
+
+### Cloud Run
+1.  **Build and Push** the image to Google Artifact Registry:
+    ```bash
+    docker build -t gcr.io/YOUR_PROJECT/qcx .
+    docker push gcr.io/YOUR_PROJECT/qcx
+    ```
+2.  **Deploy to Cloud Run**:
+    ```bash
+    gcloud run deploy qcx --image gcr.io/YOUR_PROJECT/qcx --platform managed
+    ```
+
+### Cloud SQL
+1.  Create a **Cloud SQL for PostgreSQL** instance (version 15+).
+2.  Cloud SQL supports both `pgvector` and `postgis`. Enable them via:
+    ```sql
+    CREATE EXTENSION IF NOT EXISTS postgis;
+    CREATE EXTENSION IF NOT EXISTS vector;
+    ```
+
+---
+
+## 4. Vector Database Options
+
+QCX is configured to support two vector database options:
+
+1.  **PostgreSQL (pgvector)**: Integrated into the main database. Best for smaller datasets and simplicity.
+2.  **Qdrant**: Dedicated vector database. Recommended for large-scale production use cases requiring high performance and advanced filtering.
+
+To use Qdrant, ensure the `QDRANT_URL` environment variable is set in your application environment.
+
+---
+
+## 5. Security Checklist
+
+*   [ ] Change default passwords in `docker-compose.yaml`.
+*   [ ] Use SSL for database connections in production (`ssl=true` in `DATABASE_URL`).
+*   [ ] Set `NODE_ENV=production`.
+*   [ ] Ensure all sensitive API keys are stored as secrets, not committed to code.

Dockerfile

@@ -36,8 +36,7 @@ FROM oven/bun:1.3.5-alpine AS runner
 WORKDIR /app
 
 # Create non-root group and user, with nextjs belonging to nodejs group
-RUN addgroup -g 1001 -S nodejs \
-    && adduser -S -u 1001 -G nodejs nextjs
+RUN addgroup -g 1001 -S nodejs     && adduser -S -u 1001 -G nodejs nextjs
 
 # Environment variables
 ENV NODE_ENV=production
@@ -52,15 +51,27 @@ COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static
 # Copy public folder
 COPY --from=builder --chown=nextjs:nodejs /app/public ./public
 
+# Copy migration files and entrypoint
+# Note: In standalone mode, we need to ensure all migration dependencies are available.
+# We copy the entire project source temporarily to a different folder if needed,
+# or just ensure drizzle and lib/db are available for the migration script.
+COPY --from=builder --chown=nextjs:nodejs /app/drizzle ./drizzle
+COPY --from=builder --chown=nextjs:nodejs /app/lib/db/migrate.ts ./lib/db/migrate.ts
+COPY --from=builder --chown=nextjs:nodejs /app/package.json ./package.json
+COPY --chown=nextjs:nodejs docker-entrypoint.sh ./docker-entrypoint.sh
+RUN chmod +x docker-entrypoint.sh
+
 # Switch to non-root user
 USER nextjs
 
 # Expose port
 EXPOSE 3000
 
 # Health check (uses Bun to fetch; adjust /api/health if your endpoint differs)
-HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3 \
-    CMD ["bun", "--eval", "fetch('http://localhost:3000/api/health').then(r => r.ok ? process.exit(0) : process.exit(1)).catch(() => process.exit(1))"]
+HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3     CMD ["bun", "--eval", "fetch('http://localhost:3000/api/health').then(r => r.ok ? process.exit(0) : process.exit(1)).catch(() => process.exit(1))"]
+
+# Use entrypoint script to handle migrations
+ENTRYPOINT ["./docker-entrypoint.sh"]
 
 # Run the standalone server with Bun (fully compatible in Bun 1.3+)
 CMD ["bun", "server.js"]

Dockerfile.db

@@ -0,0 +1,21 @@
+FROM postgres:16-alpine
+
+# Install build dependencies and pgvector
+RUN apk add --no-cache --virtual .build-deps \
+    git \
+    build-base \
+    clang15 \
+    llvm15-dev \
+    postgis-dev \
+    postgresql-dev \
+    && git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git /tmp/pgvector \
+    && cd /tmp/pgvector \
+    && make \
+    && make install \
+    && apk add --no-cache postgis \
+    && rm -rf /tmp/pgvector \
+    && apk del .build-deps
+
+# Use the default entrypoint
+ENTRYPOINT ["docker-entrypoint.sh"]
+CMD ["postgres"]

app/actions.tsx

@@ -14,7 +14,7 @@ import { Section } from '@/components/section'
 import { FollowupPanel } from '@/components/followup-panel'
 import { inquire, researcher, taskManager, querySuggestor, resolutionSearch, type DrawnFeature } from '@/lib/agents'
 import { writer } from '@/lib/agents/writer'
-import { saveChat, getSystemPrompt } from '@/lib/actions/chat'
+import { saveChat, getSystemPrompt, generateReportContext } from '@/lib/actions/chat'
 import { Chat, AIMessage } from '@/lib/types'
 import { UserMessage } from '@/components/user-message'
 import { BotMessage } from '@/components/message'
@@ -27,6 +27,7 @@ import { CopilotDisplay } from '@/components/copilot-display'
 import RetrieveSection from '@/components/retrieve-section'
 import { VideoSearchSection } from '@/components/video-search-section'
 import { MapQueryHandler } from '@/components/map/map-query-handler'
+import { SandboxSection } from '@/components/sandbox-section'
 
 // Define the type for related queries
 type RelatedQueries = {
@@ -50,6 +51,20 @@ async function submit(formData?: FormData, skip?: boolean) {
     console.error('Failed to parse drawnFeatures:', e);
   }
 
+  if (action === 'generate_report_context') {
+    const messagesString = formData?.get('messages');
+    if (typeof messagesString !== 'string') {
+      return { title: 'QCX Intelligence Analysis', summary: 'Automated executive summary is currently unavailable.' };
+    }
+    try {
+      const messages = JSON.parse(messagesString) as AIMessage[];
+      return await generateReportContext(messages);
+    } catch (e) {
+      console.error('Failed to parse messages for report context:', e);
+      return { title: 'QCX Intelligence Analysis', summary: 'Automated executive summary is currently unavailable.' };
+    }
+  }
+
   if (action === 'resolution_search') {
     const file_mapbox = formData?.get('file_mapbox') as File;
     const file_google = formData?.get('file_google') as File;
@@ -897,6 +912,22 @@ export const getUIStateFromAIState = (aiState: AIState): UIState => {
                   ),
                   isCollapsed: isCollapsed.value
                 }
+              case 'sandbox': {
+                const logs = createStreamableValue(toolOutput.logs)
+                logs.done(toolOutput.logs)
+                return {
+                  id,
+                  component: (
+                    <SandboxSection
+                      logs={logs.value}
+                      previewUrl={toolOutput.previewUrl}
+                      exitCode={toolOutput.exitCode}
+                      error={toolOutput.error}
+                    />
+                  ),
+                  isCollapsed: isCollapsed.value
+                }
+              }
               default:
                 console.warn(
                   `Unhandled tool result in getUIStateFromAIState: ${name}`