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Mistral reference architecture

Skill jeremylongshore/claude-code-plugins-plus-skills/skills/.curated/mistral-reference-architecture

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npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill mistral-reference-architecture

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'Implement Mistral AI reference architecture with best-practice project layout.

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SKILL.md

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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/mistralai SDK
  • zod for 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

IssueCauseResolution
Config validation errorMissing/invalid env varsCheck Zod error message
Rate limit (429)RPM/TPM exceededMistralServiceError has retryable: true
Auth error (401)Invalid API keyNot retryable, check credentials
Cache ineffectiveHigh temperatureOnly 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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