Implement event handling patterns for Mistral AI integrations. Use when building async workflows, implementing queues, or handling long-running Mistral AI operations. Trigger with phrases like "mistral events", "mistral async", "mistral queue", "mistral background jobs", "mistral webhook".
Scanned 9/3/2026
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---
name: mistral-webhooks-events
description: |
Implement event handling patterns for Mistral AI integrations.
Use when building async workflows, implementing queues,
or handling long-running Mistral AI operations.
Trigger with phrases like "mistral events", "mistral async",
"mistral queue", "mistral background jobs", "mistral webhook".
allowed-tools: Read, Write, Edit, Bash(curl:*)
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
---
# Mistral AI Events & Async Patterns
## Overview
Implement async patterns and event handling for Mistral AI integrations. Note: Mistral AI does not have native webhooks, so this skill covers async patterns and event-driven architectures.
## Prerequisites
- Mistral AI SDK installed
- Queue system (Redis, SQS, etc.) for async processing
- Event emitter or pub/sub for notifications
- Background job processor (BullMQ, etc.)
## Instructions
### Step 1: Event-Driven Chat Architecture
```typescript
import { EventEmitter } from 'events';
import Mistral from '@mistralai/mistralai';
// Custom event types
interface MistralEvents {
'chat:start': { requestId: string; model: string; timestamp: Date };
'chat:chunk': { requestId: string; content: string; index: number };
'chat:complete': { requestId: string; fullResponse: string; usage: any };
'chat:error': { requestId: string; error: Error };
}
class MistralEventEmitter extends EventEmitter {
private client: Mistral;
constructor() {
super();
this.client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY! });
}
async chat(requestId: string, messages: any[], model = 'mistral-small-latest') {
this.emit('chat:start', { requestId, model, timestamp: new Date() });
try {
const stream = await this.client.chat.stream({ model, messages });
let fullResponse = '';
let index = 0;
for await (const event of stream) {
const content = event.data?.choices?.[0]?.delta?.content;
if (content) {
fullResponse += content;
this.emit('chat:chunk', { requestId, content, index: index++ });
}
}
const usage = { totalTokens: fullResponse.length / 4 }; // Estimate
this.emit('chat:complete', { requestId, fullResponse, usage });
return fullResponse;
} catch (error) {
this.emit('chat:error', { requestId, error: error as Error });
throw error;
}
}
}
// Usage
const mistral = new MistralEventEmitter();
mistral.on('chat:start', ({ requestId, model }) => {
console.log(`[${requestId}] Starting chat with ${model}`);
});
mistral.on('chat:chunk', ({ requestId, content }) => {
process.stdout.write(content);
});
mistral.on('chat:complete', ({ requestId, usage }) => {
console.log(`\n[${requestId}] Complete. Tokens: ${usage.totalTokens}`);
});
mistral.on('chat:error', ({ requestId, error }) => {
console.error(`[${requestId}] Error:`, error.message);
});
await mistral.chat('req-123', [{ role: 'user', content: 'Hello!' }]);
```
### Step 2: Background Job Processing with BullMQ
```typescript
import { Queue, Worker, Job } from 'bullmq';
import Mistral from '@mistralai/mistralai';
import Redis from 'ioredis';
const connection = new Redis(process.env.REDIS_URL);
// Define job types
interface ChatJob {
id: string;
messages: Array<{ role: string; content: string }>;
model: string;
callback?: string; // Webhook URL to call on completion
}
// Create queue
const chatQueue = new Queue<ChatJob>('mistral-chat', { connection });
// Create worker
const chatWorker = new Worker<ChatJob>(
'mistral-chat',
async (job: Job<ChatJob>) => {
const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY! });
const response = await client.chat.complete({
model: job.data.model,
messages: job.data.messages,
});
const result = {
jobId: job.id,
requestId: job.data.id,
content: response.choices?.[0]?.message?.content,
usage: response.usage,
completedAt: new Date().toISOString(),
};
// Call webhook if provided
if (job.data.callback) {
await fetch(job.data.callback, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(result),
});
}
return result;
},
{
connection,
concurrency: 5,
limiter: {
max: 10,
duration: 1000, // Max 10 jobs per second
},
}
);
// Event handlers
chatWorker.on('completed', (job, result) => {
console.log(`Job ${job.id} completed:`, result);
});
chatWorker.on('failed', (job, err) => {
console.error(`Job ${job?.id} failed:`, err.message);
});
// API endpoint to queue jobs
export async function POST(request: Request) {
const body = await request.json();
const job = await chatQueue.add('chat', {
id: crypto.randomUUID(),
messages: body.messages,
model: body.model || 'mistral-small-latest',
callback: body.callback,
}, {
attempts: 3,
backoff: { type: 'exponential', delay: 1000 },
});
return Response.json({
jobId: job.id,
status: 'queued',
statusUrl: `/api/jobs/${job.id}`,
});
}
```
### Step 3: Webhook Notification System
```typescript
import crypto from 'crypto';
interface WebhookPayload {
event: string;
timestamp: string;
data: any;
}
class WebhookNotifier {
private secret: string;
constructor(secret: string) {
this.secret = secret;
}
private sign(payload: string): string {
return crypto
.createHmac('sha256', this.secret)
.update(payload)
.digest('hex');
}
async notify(url: string, event: string, data: any): Promise<boolean> {
const payload: WebhookPayload = {
event,
timestamp: new Date().toISOString(),
data,
};
const body = JSON.stringify(payload);
const signature = this.sign(body);
try {
const response = await fetch(url, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-Webhook-Signature': signature,
'X-Webhook-Timestamp': payload.timestamp,
},
body,
});
return response.ok;
} catch (error) {
console.error('Webhook failed:', error);
return false;
}
}
}
// Usage
const notifier = new WebhookNotifier(process.env.WEBHOOK_SECRET!);
// After Mistral completion
await notifier.notify(
'https://yourapp.com/webhooks/mistral',
'chat.completed',
{
requestId: 'req-123',
content: response.choices?.[0]?.message?.content,
usage: response.usage,
}
);
```
### Step 4: Server-Sent Events (SSE) for Real-Time Updates
```typescript
// api/chat/stream/route.ts
import Mistral from '@mistralai/mistralai';
export async function POST(request: Request) {
const { messages } = await request.json();
const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY! });
const stream = await client.chat.stream({
model: 'mistral-small-latest',
messages,
});
const encoder = new TextEncoder();
const readable = new ReadableStream({
async start(controller) {
// Send initial event
controller.enqueue(encoder.encode(`event: start\ndata: {"status":"started"}\n\n`));
try {
let tokenCount = 0;
for await (const event of stream) {
const content = event.data?.choices?.[0]?.delta?.content;
if (content) {
tokenCount++;
controller.enqueue(
encoder.encode(`event: chunk\ndata: ${JSON.stringify({ content, tokenCount })}\n\n`)
);
}
}
// Send completion event
controller.enqueue(
encoder.encode(`event: complete\ndata: ${JSON.stringify({ totalTokens: tokenCount })}\n\n`)
);
} catch (error: any) {
controller.enqueue(
encoder.encode(`event: error\ndata: ${JSON.stringify({ error: error.message })}\n\n`)
);
}
controller.close();
},
});
return new Response(readable, {
headers: {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
},
});
}
```
### Step 5: Client-Side SSE Consumption
```typescript
// Client-side JavaScript
function streamChat(messages: any[]): EventSource {
const eventSource = new EventSource('/api/chat/stream', {
// Note: EventSource doesn't support POST directly
// Use fetch with ReadableStream instead, or use a library
});
eventSource.addEventListener('start', (e) => {
console.log('Stream started');
});
eventSource.addEventListener('chunk', (e) => {
const { content } = JSON.parse(e.data);
process.stdout.write(content);
});
eventSource.addEventListener('complete', (e) => {
const { totalTokens } = JSON.parse(e.data);
console.log(`\nComplete. Tokens: ${totalTokens}`);
eventSource.close();
});
eventSource.addEventListener('error', (e) => {
console.error('Stream error:', e);
eventSource.close();
});
return eventSource;
}
```
## Output
- Event-driven Mistral AI integration
- Background job processing
- Webhook notification system
- Real-time streaming with SSE
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Job stuck in queue | Worker crashed | Implement job timeout and retry |
| Webhook failed | Network/auth issue | Retry with exponential backoff |
| SSE disconnected | Client timeout | Implement reconnection logic |
| Event backpressure | Too many events | Implement buffering |
## Examples
### Python Async Pattern
```python
import asyncio
from mistralai import Mistral
async def process_batch(prompts: list[str]):
client = Mistral(api_key=os.environ.get("MISTRAL_API_KEY"))
async def process_one(prompt: str):
response = await client.chat.complete_async(
model="mistral-small-latest",
messages=[{"role": "user", "content": prompt}]
)
return response.choices[0].message.content
results = await asyncio.gather(*[process_one(p) for p in prompts])
return results
```
## Resources
- [BullMQ Documentation](https://docs.bullmq.io/)
- [Server-Sent Events MDN](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events)
- [Mistral AI Streaming](https://docs.mistral.ai/capabilities/completion/#streaming)
## Next Steps
For performance optimization, see `mistral-performance-tuning`.
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