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mistral-sdk-patterns Apply production-ready Mistral AI SDK patterns for TypeScript and Python.
Use when implementing Mistral integrations, refactoring SDK usage,
or establishing team coding standards for Mistral AI.
Trigger with phrases like "mistral SDK patterns", "mistral best practices",
"mistral code patterns", "idiomatic mistral".
설치로 이동 Skills Marketplace 커뮤니티가 만든 AI 스킬을 발견하고 탐색하세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill mistral-sdk-patterns명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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Zip 다운로드 다운로드 중... 이 저장소의 다른 Skills Implement user sign-up and sign-in flows with Clerk.
Use when building authentication UI, customizing sign-in experience,
or implementing OAuth social login.
Trigger with phrases like "clerk sign-in", "clerk sign-up",
"clerk login flow", "clerk OAuth", "clerk social login".
Implement session management and middleware with Clerk.
Use when managing user sessions, configuring route protection,
or implementing token refresh and custom JWT templates.
Trigger with phrases like "clerk session", "clerk middleware",
"clerk route protection", "clerk token", "clerk JWT".
Configure enterprise SSO, role-based access control, and organization management.
Use when implementing SSO integration, configuring role-based permissions,
or setting up organization-level controls.
Trigger with phrases like "clerk SSO", "clerk RBAC",
"clerk enterprise", "clerk roles", "clerk permissions", "clerk organizations".
jeremylongshore
jeremylongshore/claude-code-plugins-plus-skills
GitHub 저장소 열기 name mistral-sdk-patterns description Apply production-ready Mistral AI SDK patterns for TypeScript and Python.
Use when implementing Mistral integrations, refactoring SDK usage,
or establishing team coding standards for Mistral AI.
Trigger with phrases like "mistral SDK patterns", "mistral best practices",
"mistral code patterns", "idiomatic mistral".
allowed-tools Read, Write, Edit version 1.12.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","mistral","python","typescript"] compatibility Designed for Claude Code, also compatible with Codex and OpenClaw
Mistral SDK Patterns
Overview
Production-ready patterns for the Mistral AI SDK. Covers singleton client, retry/backoff, structured output, streaming, function calling, batch embeddings, and async Python — all with proper error handling. SDK is ESM-only for TypeScript (@mistralai/mistralai), sync+async for Python (mistralai).
Prerequisites
@mistralai/mistralai (TypeScript) or mistralai (Python) installedMISTRAL_API_KEY environment variable set
Instructions
Step 1: Singleton Client with Configuration
TypeScript
import { Mistral } from '@mistralai/mistralai' ;
let _client : Mistral | null = null ;
export function getMistralClient (Mistral {
if (!_client) {
const apiKey = process.env .MISTRAL_API_KEY ;
if (!apiKey) throw new Error ('MISTRAL_API_KEY not set' );
_client = new Mistral ({
apiKey,
timeoutMs : 30_000 ,
maxRetries : 3 ,
});
}
return _client;
}
export function resetClient (void {
_client = null ;
}
import os
from mistralai import Mistral
_client = None
def get_client () -> Mistral:
global _client
if _client is None :
api_key = os.environ.get("MISTRAL_API_KEY" )
if not api_key:
raise RuntimeError("MISTRAL_API_KEY not set" )
_client = Mistral(api_key=api_key, timeout_ms=30_000 , max_retries=3 )
return _client
Step 2: Structured Output with JSON Schema import { z } from 'zod' ;
const TicketSchema = z.object ({
category : z.enum (['bug' , 'feature' , 'question' ]),
severity : z.enum (['low' , 'medium' , 'high' , 'critical' ]),
summary : z.string (),
});
type Ticket = z.infer <typeof TicketSchema >;
async function classifyTicket (text : string Promise <Ticket > {
const client = getMistralClient ();
const response = await client.chat .complete ({
model : 'mistral-small-latest' ,
messages : [
{ role : 'system' , content : 'Classify the support ticket.' },
{ role : 'user' , content : text },
],
responseFormat : {
type : 'json_schema' ,
jsonSchema : {
name : 'ticket_classification' ,
schema : {
type : 'object' ,
properties : {
category : { type : 'string' , enum : ['bug' , 'feature' , 'question' ] },
severity : { type : 'string' , enum : ['low' , 'medium' , 'high' , 'critical' ] },
summary : { type : 'string' },
},
required : ['category' , 'severity' , 'summary' ],
},
},
},
});
const raw = JSON .parse (response.choices ?.[0 ]?.message ?.content ?? '{}' );
return TicketSchema .parse (raw);
}
Step 3: Streaming with Accumulated Result interface StreamResult {
content : string ;
finishReason : string ;
}
async function streamWithAccumulation (
messages : Array <{ role: string ; content: string }>,
onChunk : (text: string ) => void ,
): Promise <StreamResult > {
const client = getMistralClient ();
const stream = await client.chat .stream ({
model : 'mistral-small-latest' ,
messages,
});
let content = '' ;
let finishReason = '' ;
for await (const event of stream) {
const delta = event.data ?.choices ?.[0 ];
if (delta?.delta ?.content ) {
content += delta.delta .content ;
onChunk (delta.delta .content );
}
if (delta?.finishReason ) {
finishReason = delta.finishReason ;
}
}
return { content, finishReason };
}
Step 4: Python Async Pattern import asyncio
from mistralai import Mistral
async def process_batch (prompts: list [str ], model: str = "mistral-small-latest" ):
"""Process multiple prompts concurrently with semaphore for rate limiting."""
client = Mistral(api_key=os.environ["MISTRAL_API_KEY" ])
semaphore = asyncio.Semaphore(5 )
async def process_one (prompt: str ) -> str :
async with semaphore:
response = await client.chat.complete_async(
model=model,
messages=[{"role" : "user" , "content" : prompt}],
)
return response.choices[0 ].message.content
results = await asyncio.gather(*[process_one(p) for p in prompts])
return results
Step 5: Retry with Exponential Backoff async function withRetry<T>(
fn : () => Promise <T>,
maxRetries = 3 ,
): Promise <T> {
for (let attempt = 0 ; attempt <= maxRetries; attempt++) {
try {
return await fn ();
} catch (error : any ) {
const status = error.status ?? error.statusCode ;
const retryable = status === 429 || status >= 500 ;
if (!retryable || attempt === maxRetries) throw error;
const retryAfter = error.headers ?.get ?.('retry-after' );
const delay = retryAfter
? parseInt (retryAfter) * 1000
: Math .min (1000 * 2 ** attempt, 30_000 );
console .warn (`Attempt ${attempt + 1 } failed (${status} ), retrying in ${delay} ms` );
await new Promise (r =>setTimeout (r, delay));
}
}
throw new Error ('Unreachable' );
}
const response = await withRetry (() =>
client.chat .complete ({
model : 'mistral-large-latest' ,
messages : [{ role : 'user' , content : 'Hello' }],
})
);
Step 6: Token Usage Tracking interface UsageStats {
totalPromptTokens : number ;
totalCompletionTokens : number ;
totalRequests : number ;
costUsd : number ;
}
const PRICING : Record <string , { input : number ; output : number }> = {
'mistral-small-latest' : { input : 0.1 , output : 0.3 },
'mistral-large-latest' : { input : 0.5 , output : 1.5 },
'mistral-embed' : { input : 0.1 , output : 0 },
'codestral-latest' : { input : 0.3 , output : 0.9 },
};
class UsageTracker {
private stats : UsageStats = { totalPromptTokens : 0 , totalCompletionTokens : 0 , totalRequests : 0 , costUsd : 0 };
record (model : string , usage : { promptTokens ?: number ; completionTokens ?: number }): void {
const pt = usage.promptTokens ?? 0 ;
const ct = usage.completionTokens ?? 0 ;
this .stats .totalPromptTokens += pt;
this .stats .totalCompletionTokens += ct;
this .stats .totalRequests ++;
const p = PRICING [model] ?? PRICING ['mistral-small-latest' ];
this .stats .costUsd += (pt / 1e6 ) * p.input + (ct / 1e6 ) * p.output ;
}
report (): UsageStats { return { ...this .stats }; }
}
Error Handling Error Cause Solution 401 UnauthorizedInvalid API key Verify MISTRAL_API_KEY 429 Too Many RequestsRate limit hit Use built-in retry or custom backoff 400 Bad RequestInvalid model or params Check model name and parameter values ERR_REQUIRE_ESMCommonJS import SDK is ESM-only; use import syntax Timeout Large prompt or slow network Increase timeoutMs
Resources
Output
Singleton client pattern for TypeScript and Python
Structured output with JSON Schema validation
Streaming with accumulation
Retry/backoff for resilient API calls
Token usage tracking with cost estimation
