--- name: mistral-deploy-integration-c67a9171b835 description: | Deploy Mistral AI integrations to Vercel, Fly.io, and Cloud Run platforms. Use when deploying Mistral AI-powered applications to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy mistral", "mistral Vercel", "mistral production deploy", "mistral Cloud Run", "mistral Fly.io". allowed-tools: Read, Write, Edit, Bash(vercel:*), Bash(fly:*), Bash(gcloud:*) version: 1.0.0 license: MIT author: Jeremy Longshore --- # Mistral AI Deploy Integration ## Overview Deploy Mistral AI-powered applications to popular platforms with proper secrets management. ## Prerequisites - Mistral AI API keys for production environment - Platform CLI installed (vercel, fly, or gcloud) - Application code ready for deployment - Environment variables documented ## Vercel Deployment ### Environment Setup ```bash # Add Mistral secrets to Vercel vercel env add MISTRAL_API_KEY production # Enter your API key when prompted # Or use CLI with secret vercel secrets add mistral-api-key "your-api-key" # Link to project vercel link # Deploy preview vercel # Deploy production vercel --prod ``` ### vercel.json Configuration ```json { "env": { "MISTRAL_API_KEY": "@mistral-api-key" }, "functions": { "api/**/*.ts": { "maxDuration": 60 } }, "regions": ["iad1", "sfo1"] } ``` ### Vercel Edge Function Example ```typescript // api/chat/route.ts (Next.js App Router) import { NextRequest } from 'next/server'; import Mistral from '@mistralai/mistralai'; const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY!, }); export async function POST(request: NextRequest) { const { messages } = await request.json(); const stream = await client.chat.stream({ model: 'mistral-small-latest', messages, }); const encoder = new TextEncoder(); const readable = new ReadableStream({ async start(controller) { for await (const event of stream) { const content = event.data?.choices?.[0]?.delta?.content; if (content) { controller.enqueue(encoder.encode(`data: ${JSON.stringify({ content })}\n\n`)); } } controller.enqueue(encoder.encode('data: [DONE]\n\n')); controller.close(); }, }); return new Response(readable, { headers: { 'Content-Type': 'text/event-stream', 'Cache-Control': 'no-cache', 'Connection': 'keep-alive', }, }); } ``` ## Fly.io Deployment ### fly.toml Configuration ```toml app = "my-mistral-app" primary_region = "iad" [env] NODE_ENV = "production" LOG_LEVEL = "info" [http_service] internal_port = 3000 force_https = true auto_stop_machines = true auto_start_machines = true min_machines_running = 1 [http_service.concurrency] type = "connections" hard_limit = 100 soft_limit = 80 [[services.http_checks]] interval = 10000 timeout = 2000 path = "/health" ``` ### Deploy to Fly.io ```bash # Set Mistral secrets fly secrets set MISTRAL_API_KEY="your-api-key" # Deploy fly deploy # View logs fly logs # Scale fly scale count 2 --region iad ``` ## Google Cloud Run ### Dockerfile ```dockerfile FROM node:20-slim AS builder WORKDIR /app COPY package*.json ./ RUN npm ci --only=production COPY . . RUN npm run build FROM node:20-slim WORKDIR /app COPY --from=builder /app/dist ./dist COPY --from=builder /app/node_modules ./node_modules COPY --from=builder /app/package.json ./ ENV NODE_ENV=production EXPOSE 8080 CMD ["node", "dist/index.js"] ``` ### Deploy Script ```bash #!/bin/bash # deploy-cloud-run.sh PROJECT_ID="${GOOGLE_CLOUD_PROJECT}" SERVICE_NAME="mistral-service" REGION="us-central1" # Create secret in Secret Manager echo -n "your-api-key" | gcloud secrets create mistral-api-key --data-file=- # Grant Cloud Run access to secret gcloud secrets add-iam-policy-binding mistral-api-key \ --member="serviceAccount:${PROJECT_ID}-compute@developer.gserviceaccount.com" \ --role="roles/secretmanager.secretAccessor" # Build and push image gcloud builds submit --tag gcr.io/$PROJECT_ID/$SERVICE_NAME # Deploy to Cloud Run gcloud run deploy $SERVICE_NAME \ --image gcr.io/$PROJECT_ID/$SERVICE_NAME \ --region $REGION \ --platform managed \ --allow-unauthenticated \ --set-secrets="MISTRAL_API_KEY=mistral-api-key:latest" \ --memory 512Mi \ --cpu 1 \ --timeout 60s \ --concurrency 80 ``` ## Environment Configuration Pattern ```typescript // config/mistral.ts interface MistralConfig { apiKey: string; model: string; timeout: number; maxRetries: number; } export function getMistralConfig(): MistralConfig { const env = process.env.NODE_ENV || 'development'; return { apiKey: process.env.MISTRAL_API_KEY!, model: process.env.MISTRAL_MODEL || 'mistral-small-latest', timeout: parseInt(process.env.MISTRAL_TIMEOUT || '30000'), maxRetries: parseInt(process.env.MISTRAL_MAX_RETRIES || '3'), }; } ``` ## Health Check Endpoint ```typescript // api/health.ts import Mistral from '@mistralai/mistralai'; export async function GET() { const start = Date.now(); try { const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY! }); await client.models.list(); return Response.json({ status: 'healthy', services: { mistral: { connected: true, latencyMs: Date.now() - start, }, }, timestamp: new Date().toISOString(), }); } catch (error) { return Response.json({ status: 'degraded', services: { mistral: { connected: false, latencyMs: Date.now() - start, error: 'Connection failed', }, }, timestamp: new Date().toISOString(), }, { status: 503 }); } } ``` ## Instructions ### Step 1: Choose Deployment Platform Select the platform that best fits your infrastructure needs. ### Step 2: Configure Secrets Store Mistral API keys securely using the platform's secrets management. ### Step 3: Deploy Application Use the platform CLI to deploy your application. ### Step 4: Verify Health Test the health check endpoint to confirm Mistral connectivity. ## Output - Application deployed to production - Mistral secrets securely configured - Health check endpoint functional - Environment-specific configuration in place ## Error Handling | Issue | Cause | Solution | |-------|-------|----------| | Secret not found | Missing configuration | Add secret via platform CLI | | Deploy timeout | Large build | Increase build timeout | | Health check fails | Wrong API key | Verify environment variable | | Cold start slow | No warm-up | Configure minimum instances | ## Examples ### Quick Deploy Script ```bash #!/bin/bash # Platform-agnostic deploy helper case "$1" in vercel) vercel env add MISTRAL_API_KEY production <<< "$MISTRAL_API_KEY" vercel --prod ;; fly) fly secrets set MISTRAL_API_KEY="$MISTRAL_API_KEY" fly deploy ;; cloudrun) gcloud run deploy mistral-app \ --set-env-vars="MISTRAL_API_KEY=$MISTRAL_API_KEY" ;; *) echo "Usage: $0 {vercel|fly|cloudrun}" ;; esac ``` ## Resources - [Vercel Documentation](https://vercel.com/docs) - [Fly.io Documentation](https://fly.io/docs) - [Cloud Run Documentation](https://cloud.google.com/run/docs) - [Mistral AI API Reference](https://docs.mistral.ai/api/) ## Next Steps For event handling, see `mistral-webhooks-events`. --- Source attribution: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/mistral-pack/skills/mistral-deploy-integration/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License (with OpenAI/Anthropic Rider) Copyright (c) 2026 Jeffrey Emanuel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: ADDITIONAL RIDER / RESTRICTION (OpenAI / Anthropic): This rider is part of the "conditions" of this License. In the event of any conflict between this rider and any other portion of this License, this rider controls. "Restricted Parties" means OpenAI, L.L.C.; Anthropic, PBC; any of their respective Affiliates; and any person or entity acting directly or indirectly on behalf of, for the benefit of, or under the direction of any of the foregoing (including any officer, director, employee, contractor, agent, consultant, service provider, or representative). Notwithstanding any other provision of this License, no rights are granted to any Restricted Party. Any purported license, sublicense, assignment, transfer, or other permission to any Restricted Party is null and void absent the express prior written permission of Jeffrey Emanuel. You may not provide, disclose, distribute, sublicense, sell, lease, lend, host, make available, or otherwise permit access to the Software or any derivative work of the Software (as defined in applicable copyright law) (collectively, "Derivative Works") to or for any Restricted Party. For purposes of this rider, "use" includes, without limitation: copying, modifying, merging, publishing, distributing, sublicensing, selling, transferring, making available, hosting, deploying, executing, benchmarking, testing, analyzing, indexing, or incorporating the Software or any Derivative Works into any dataset, training corpus, evaluation harness, or pipeline for machine learning or other automated systems. This rider applies to the Software and all Derivative Works. As a condition of use, you agree that this rider is a precondition to exercising any rights under this License, and you agree that any distribution of the Software or any Derivative Works must include this rider provision unmodified. Any breach of this rider automatically and immediately terminates the permissions granted by this License. Upon termination, you must immediately cease all use and distribution of the Software and any Derivative Works and destroy all copies under your control. You agree that a breach of this rider would cause irreparable harm and that Jeffrey Emanuel may seek injunctive or other equitable relief to enforce this rider, in addition to any other remedies available at law. To the maximum extent permitted by applicable law, the prevailing party in any action to enforce this rider shall be entitled to recover reasonable attorneys' fees and costs. For purposes of this rider, "Affiliate" means any entity that directly or indirectly controls, is controlled by, or is under common control with the specified party. "Control" means ownership of more than 50% of the voting securities or other ownership interest, or the power to direct management or policies by contract or otherwise. 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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/mistral-pack/skills/mistral-deploy-integration/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Product Management Roles: Backend Developer, DevOps / SRE, Growth Product Manager, ML / AI Engineer, Product Manager Specialties: API, Backend Tools: Vercel Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 74f657984bdc9ff64fce7d1957274df43170d2fe5c33e757f221543bf89f6941