mistral-reference-architecture
Implement Mistral AI reference architecture with best-practice project layout. Use when designing new Mistral AI integrations, reviewing project structure, or establishing architecture standards for Mistral AI applications. Trigger with phrases like "mistral architecture", "mistral best practices", "mistral project structure", "how to organize mistral", "mistral layout".
Install
mkdir -p .claude/skills/mistral-reference-architecture && curl -L -o skill.zip "https://mcp.directory/api/skills/download/4785" && unzip -o skill.zip -d .claude/skills/mistral-reference-architecture && rm skill.zipInstalls to .claude/skills/mistral-reference-architecture
About this skill
Mistral AI Reference Architecture
Overview
Production-ready architecture patterns for Mistral AI integrations: layered project structure, singleton client, Zod-validated config, custom error classes, service layer with caching, health checks, prompt templates, and model routing.
Prerequisites
- TypeScript/Node.js project (ESM)
@mistralai/mistralaiSDKzodfor config validation- Testing framework (Vitest)
Layer Architecture
API Layer (Routes, Controllers, Middleware)
|
Service Layer (Business Logic, Orchestration)
|
Mistral Layer (Client, Config, Errors, Prompts)
|
Infrastructure Layer (Cache, Queue, Monitoring)
Instructions
Step 1: Directory Structure
src/
├── mistral/
│ ├── client.ts # Singleton client factory
│ ├── config.ts # Zod-validated config
│ ├── errors.ts # Custom error classes
│ ├── types.ts # Shared types
│ └── prompts.ts # Prompt templates
├── services/
│ ├── chat.service.ts # Chat with caching + retry
│ ├── embed.service.ts # Embeddings + search
│ └── rag.service.ts # RAG pipeline
├── api/
│ ├── chat.route.ts # HTTP endpoints
│ └── health.route.ts # Health check
└── config/
├── base.ts # Shared config
├── development.ts # Dev overrides
└── production.ts # Prod overrides
Step 2: Config with Zod Validation
// src/mistral/config.ts
import { z } from 'zod';
const MistralConfigSchema = z.object({
apiKey: z.string().min(10, 'MISTRAL_API_KEY required'),
defaultModel: z.string().default('mistral-small-latest'),
timeoutMs: z.number().default(30_000),
maxRetries: z.number().default(3),
cache: z.object({
enabled: z.boolean().default(true),
ttlMs: z.number().default(3_600_000),
maxSize: z.number().default(5000),
}).default({}),
});
export type MistralConfig = z.infer<typeof MistralConfigSchema>;
export function loadConfig(): MistralConfig {
return MistralConfigSchema.parse({
apiKey: process.env.MISTRAL_API_KEY,
defaultModel: process.env.MISTRAL_MODEL,
timeoutMs: process.env.MISTRAL_TIMEOUT ? Number(process.env.MISTRAL_TIMEOUT) : undefined,
});
}
Step 3: Singleton Client
// src/mistral/client.ts
import { Mistral } from '@mistralai/mistralai';
import { loadConfig, type MistralConfig } from './config.js';
let _client: Mistral | null = null;
let _config: MistralConfig | null = null;
export function getMistralClient(): Mistral {
if (!_client) {
_config = loadConfig();
_client = new Mistral({
apiKey: _config.apiKey,
timeoutMs: _config.timeoutMs,
maxRetries: _config.maxRetries,
});
}
return _client;
}
export function getConfig(): MistralConfig {
if (!_config) loadConfig();
return _config!;
}
export function resetClient(): void {
_client = null;
_config = null;
}
Step 4: Custom Error Classes
// src/mistral/errors.ts
export type MistralErrorCode =
| 'AUTH_ERROR'
| 'RATE_LIMIT'
| 'BAD_REQUEST'
| 'SERVICE_ERROR'
| 'TIMEOUT'
| 'CONTEXT_OVERFLOW';
export class MistralServiceError extends Error {
constructor(
message: string,
public readonly code: MistralErrorCode,
public readonly status: number,
public readonly retryable: boolean,
) {
super(message);
this.name = 'MistralServiceError';
}
static fromApiError(error: any): MistralServiceError {
const status = error.status ?? error.statusCode ?? 500;
if (status === 401) return new MistralServiceError('Authentication failed', 'AUTH_ERROR', 401, false);
if (status === 429) return new MistralServiceError('Rate limit exceeded', 'RATE_LIMIT', 429, true);
if (status === 400) return new MistralServiceError(error.message, 'BAD_REQUEST', 400, false);
if (status >= 500) return new MistralServiceError('Service error', 'SERVICE_ERROR', status, true);
return new MistralServiceError(error.message, 'SERVICE_ERROR', status, false);
}
}
Step 5: Service Layer with Caching
// src/services/chat.service.ts
import { createHash } from 'crypto';
import { LRUCache } from 'lru-cache';
import { getMistralClient, getConfig } from '../mistral/client.js';
import { MistralServiceError } from '../mistral/errors.js';
const cache = new LRUCache<string, any>({ max: 5000, ttl: 3_600_000 });
export class ChatService {
async complete(messages: any[], options?: {
model?: string;
temperature?: number;
maxTokens?: number;
}) {
const config = getConfig();
const model = options?.model ?? config.defaultModel;
const temperature = options?.temperature ?? 0.7;
// Cache deterministic requests
if (temperature === 0 && config.cache.enabled) {
const key = createHash('sha256').update(JSON.stringify({ model, messages })).digest('hex');
const cached = cache.get(key);
if (cached) return cached;
const result = await this.executeChat(model, messages, { ...options, temperature: 0 });
cache.set(key, result);
return result;
}
return this.executeChat(model, messages, options);
}
async *stream(messages: any[], model?: string) {
const client = getMistralClient();
try {
const stream = await client.chat.stream({
model: model ?? getConfig().defaultModel,
messages,
});
for await (const event of stream) {
const text = event.data?.choices?.[0]?.delta?.content;
if (text) yield text;
}
} catch (error: any) {
throw MistralServiceError.fromApiError(error);
}
}
private async executeChat(model: string, messages: any[], options: any = {}) {
const client = getMistralClient();
try {
return await client.chat.complete({ model, messages, ...options });
} catch (error: any) {
throw MistralServiceError.fromApiError(error);
}
}
}
Step 6: Health Check
// src/api/health.route.ts
import { getMistralClient } from '../mistral/client.js';
export async function checkMistralHealth() {
const start = performance.now();
try {
const client = getMistralClient();
const models = await client.models.list();
const latencyMs = Math.round(performance.now() - start);
return {
status: latencyMs > 5000 ? 'degraded' : 'healthy',
latencyMs,
modelCount: models.data?.length ?? 0,
};
} catch (error: any) {
return {
status: 'unhealthy',
latencyMs: Math.round(performance.now() - start),
error: error.message,
};
}
}
Step 7: Prompt Templates
// src/mistral/prompts.ts
interface PromptTemplate {
name: string;
system: string;
userTemplate: (input: string) => string;
model: string;
maxTokens: number;
}
export const PROMPTS: Record<string, PromptTemplate> = {
summarize: {
name: 'summarize',
system: 'Summarize the text in 2-3 sentences. Be factual and concise.',
userTemplate: (text) => `Summarize:\n\n${text}`,
model: 'mistral-small-latest',
maxTokens: 200,
},
classify: {
name: 'classify',
system: 'Classify the input. Reply with one word only.',
userTemplate: (text) => text,
model: 'mistral-small-latest',
maxTokens: 10,
},
codeReview: {
name: 'codeReview',
system: 'Review code for bugs, security issues, and improvements. Be specific.',
userTemplate: (code) => `Review this code:\n\`\`\`\n${code}\n\`\`\``,
model: 'mistral-large-latest',
maxTokens: 1000,
},
};
Error Handling
| Issue | Cause | Resolution |
|---|---|---|
| Config validation error | Missing/invalid env vars | Check Zod error message |
| Rate limit (429) | RPM/TPM exceeded | MistralServiceError has retryable: true |
| Auth error (401) | Invalid API key | Not retryable, check credentials |
| Cache ineffective | High temperature | Only cache temperature=0 requests |
Resources
Output
- Layered directory structure with clear separation
- Zod-validated configuration from environment
- Singleton client with lazy initialization
- Custom error classes with retryability
- Service layer with caching and streaming
- Health check endpoint
- Reusable prompt templates
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