mistral-core-workflow-a

# Mistral AI Core Workflow A: Chat Completions ## Overview Primary money-path workflow for Mistral AI: Chat completions with streaming support. ## Prerequisites - Completed `mistral-install-auth` setup - Understanding of Mistral AI models - Valid API credentials configured ## Instructions ### Step 1: Basic Chat Completion **TypeScript** ```typescript import Mistral from '@mistralai/mistralai'; const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY, }); async function basicChat(userMessage: string): Promise { const response = await client.chat.complete({ model: 'mistral-small-latest', messages: [ { role: 'system', content: 'You are a helpful assistant.' }, { role: 'user', content: userMessage }, ], }); return response.choices?.[0]?.message?.content ?? ''; } // Usage const answer = await basicChat('What is the capital of France?'); console.log(answer); // Paris is the capital of France... ``` ### Step 2: Multi-Turn Conversation ```typescript interface Message { role: 'system' | 'user' | 'assistant'; content: string; } class MistralConversation { private messages: Message[] = []; private client: Mistral; private model: string; constructor(systemPrompt: string, model = 'mistral-small-latest') { this.client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY }); this.model = model; this.messages.push({ role: 'system', content: systemPrompt }); } async chat(userMessage: string): Promise { this.messages.push({ role: 'user', content: userMessage }); const response = await this.client.chat.complete({ model: this.model, messages: this.messages, }); const assistantMessage = response.choices?.[0]?.message?.content ?? ''; this.messages.push({ role: 'assistant', content: assistantMessage }); return assistantMessage; } getHistory(): Message[] { return [...this.messages]; } clearHistory(): void { const systemMessage = this.messages[0]; this.messages = [systemMessage]; } } // Usage const conv = new MistralConversation('You are a helpful coding assistant.'); const response1 = await conv.chat('How do I create a list in Python?'); const response2 = await conv.chat('How do I add items to it?'); ``` ### Step 3: Streaming Responses ```typescript async function streamingChat( userMessage: string, onChunk: (chunk: string) => void ): Promise { const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY }); const stream = await client.chat.stream({ model: 'mistral-small-latest', messages: [ { role: 'user', content: userMessage }, ], }); let fullResponse = ''; for await (const event of stream) { const content = event.data?.choices?.[0]?.delta?.content; if (content) { fullResponse += content; onChunk(content); } } return fullResponse; } // Usage const response = await streamingChat( 'Write a short poem about coding.', (chunk) => process.stdout.write(chunk) ); ``` ### Step 4: With Generation Parameters ```typescript interface ChatConfig { temperature?: number; // 0-1, default 0.7 maxTokens?: number; // Max tokens to generate topP?: number; // Nucleus sampling, 0-1 randomSeed?: number; // For reproducibility safePrompt?: boolean; // Enable safety checks } async function configuredChat( messages: Message[], config: ChatConfig = {} ): Promise<{ content: string; usage: any }> { const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY }); const response = await client.chat.complete({ model: 'mistral-large-latest', messages, temperature: config.temperature ?? 0.7, maxTokens: config.maxTokens, topP: config.topP, randomSeed: config.randomSeed, safePrompt: config.safePrompt ?? false, }); return { content: response.choices?.[0]?.message?.content ?? '', usage: response.usage, }; } // Example: Deterministic output const result = await configuredChat( [{ role: 'user', content: 'Summarize quantum computing in 2 sentences.' }], { temperature: 0, randomSeed: 42, maxTokens: 100 } ); ``` ### Step 5: Model Selection ```typescript type MistralModel = | 'mistral-large-latest' // Most capable, complex reasoning | 'mistral-medium-latest' // Balanced | 'mistral-small-latest' // Fast, cost-effective | 'open-mistral-7b' // Open source | 'open-mixtral-8x7b'; // Open source MoE function selectModel(task: 'complex' | 'balanced' | 'fast'): MistralModel { switch (task) { case 'complex': return 'mistral-large-latest'; case 'balanced': return 'mistral-medium-latest'; case 'fast': return 'mistral-small-latest'; } } ``` ## Output - Chat completions with configurable parameters - Multi-turn conversation management - Real-time streaming responses - Model selection based on task ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | 401 Unauthorized | Invalid API key | Check MISTRAL_API_KEY | | 429 Rate Limited | Too many requests | Implement backoff | | 400 Bad Request | Invalid parameters | Check model/message format | | Context Exceeded | Too many tokens | Reduce conversation history | ## Examples ### Express.js Streaming Endpoint ```typescript import express from 'express'; import Mistral from '@mistralai/mistralai'; const app = express(); const client = new Mistral({ apiKey: process.env.MISTRAL_API_KEY }); app.post('/chat/stream', async (req, res) => { res.setHeader('Content-Type', 'text/event-stream'); res.setHeader('Cache-Control', 'no-cache'); res.setHeader('Connection', 'keep-alive'); const stream = await client.chat.stream({ model: 'mistral-small-latest', messages: req.body.messages, }); for await (const event of stream) { const content = event.data?.choices?.[0]?.delta?.content; if (content) { res.write(`data: ${JSON.stringify({ content })}\n\n`); } } res.write('data: [DONE]\n\n'); res.end(); }); ``` ### Token Usage Tracking ```typescript let totalTokens = 0; async function trackedChat(messages: Message[]): Promise { const response = await client.chat.complete({ model: 'mistral-small-latest', messages, }); if (response.usage) { totalTokens += response.usage.totalTokens || 0; console.log(`Tokens used: ${response.usage.totalTokens}, Total: ${totalTokens}`); } return response.choices?.[0]?.message?.content ?? ''; } ``` ## Resources - [Mistral AI Chat Completions](https://docs.mistral.ai/api/#tag/chat) - [Mistral AI Models](https://docs.mistral.ai/getting-started/models/) - [Mistral AI Streaming](https://docs.mistral.ai/capabilities/completion/#streaming) ## Next Steps For embeddings and function calling, see `mistral-core-workflow-b`.