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AnthropicText Chat

Claude Sonnet 5 AI Chat Oyun Alanı ve API

Dengeli kodlama, analiz, yazma ve üretim asistanları için Claude Sonnet 5’i çevrimiçi deneyin. Akışlı yanıtları test edin, token kullanımını inceleyin ve API’yi entegre edin.

GirdiResmi $2.00 1 milyon token basinaAIReiter $1.00 1 milyon token basinaÇıktıResmi $10.00 1 milyon token basinaAIReiter $5.00 1 milyon token basinaCache okumaResmi $0.20 1 milyon token basinaAIReiter $0.10 1 milyon token basinaCache oluşturmaResmi $2.50 1 milyon token basinaAIReiter $1.25 1 milyon token basina
Model türü
API ile çalıştır
PlaygroundReadmeAPI

GIRDI

imagefile[]
Optional input images sent alongside the prompt. Up to 5 files. Images are billed as input tokens.
Let the model reason before answering. The model decides how much thinking each request needs.Default: false
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Install the official Anthropic client — AIReiter speaks the same protocol, so only the base URL changes:

npm install @anthropic-ai/sdk

Set the AIREITER_API_KEY environment variable:

export AIREITER_API_KEY=<paste-your-key-here>

Point the client at AIReiter:

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({
  apiKey: process.env.AIREITER_API_KEY,
  baseURL: "https://aireiter.com/api",
});

Run claude-sonnet-5:

const message = await client.messages.create({
    "model": "claude-sonnet-5",
    "max_tokens": 4096,
    "messages": [
      {
        "role": "user",
        "content": "Explain what an API rate limit is and how to handle a 429 response in code."
      }
    ],
    "output_config": {
      "effort": "medium"
    }
  });

console.log(message.content);

Stream the response instead:

const stream = client.messages.stream({
    "model": "claude-sonnet-5",
    "max_tokens": 4096,
    "messages": [
      {
        "role": "user",
        "content": "Explain what an API rate limit is and how to handle a 429 response in code."
      }
    ],
    "output_config": {
      "effort": "medium"
    }
  });

stream.on("text", (text) => process.stdout.write(text));
const message = await stream.finalMessage();

Install the official Anthropic client — AIReiter speaks the same protocol, so only the base URL changes:

pip install anthropic

Set the AIREITER_API_KEY environment variable:

export AIREITER_API_KEY=<paste-your-key-here>

Point the client at AIReiter:

import os
import anthropic

client = anthropic.Anthropic(
    api_key=os.environ["AIREITER_API_KEY"],
    base_url="https://aireiter.com/api",
)

Run claude-sonnet-5:

message = client.messages.create(
      model = "claude-sonnet-5",
      max_tokens = 4096,
      messages = [
        {
          role = "user",
          content = "Explain what an API rate limit is and how to handle a 429 response in code."
        }
      ],
      output_config = {
        effort = "medium"
      }
)

print(message.content)

Stream the response instead:

with client.messages.stream(
      model = "claude-sonnet-5",
      max_tokens = 4096,
      messages = [
        {
          role = "user",
          content = "Explain what an API rate limit is and how to handle a 429 response in code."
        }
      ],
      output_config = {
        effort = "medium"
      }
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

Set the AIREITER_API_KEY environment variable:

export AIREITER_API_KEY=<paste-your-key-here>

Run claude-sonnet-5 against AIReiter's API:

curl -s -X POST \
  -H "x-api-key: $AIREITER_API_KEY" \
  -H "Content-Type: application/json" \
  "https://aireiter.com/api/v1/messages" \
  -d '{
  "model": "claude-sonnet-5",
  "max_tokens": 4096,
  "messages": [
    {
      "role": "user",
      "content": "Explain what an API rate limit is and how to handle a 429 response in code."
    }
  ],
  "output_config": {
    "effort": "medium"
  }
}'

Add "stream": true to the body to receive the response as server-sent events.

ÇIKTI

Example

A codebase you don't know is a risk, not a hurdle. The plan should burn down that risk in order: understand, run, trace, spike, then make the change small enough that "production-ready" is a property you can demonstrate, not a hope.

Here are the first five steps, with the evidence you collect at each.

Step 1 — Get it building and the baseline green (half day) Read the README, the manifest(s), the CI config, and any architecture docs. Boot the app locally, run the full test suite, run the linter/typechecker. Evidence: The exact commands that reproduce a clean build and a passing test suite from a fresh checkout (recorded output, not memory of it). A one-page map you wrote yourself: where the entry points are, the layers, the build/test toolchain, and the main risks to your feature (e.g. "this touches cron jobs and payments").

Step 2 — Trace the smallest end-to-end slice that resembles your feature (half day) Don't start with your feature. Pick a neighboring one that already works and follow it from entry to persistence. Note the conventions along the way: how errors surface, how config is injected, how logging is done, how tests are written. Evidence: An annotated trace — file → function → what it does — for that slice. A written list of "conventions I must follow" (not intuitions; things you observed in real code). A named shortlist of the 3–5 files you will actually touch. If you can't produce this trace, you're not ready to write code.

Step 3 — Spike the core path (day 2) Build the ugly version: hardcoded values, no error handling, no tests. The purpose is to confirm the path you traced in step 2 is real and to surface what you didn't know you didn't know. Evidence: A working spike demonstrating the feature's central data path, alongside a list of every assumption the spike broke and what you corrected. That correction list is the most valuable document in this whole plan.

Step 4 — Write the contract before the code (half of day 2 / day 3) Once the spike proves the path, pin down what production needs: the inputs/outputs, the error cases, where it sits in the conventions from step 2. Then write the tests — they'll be red, but they're the specification. Evidence: A one-to-two-page design doc, an agreed interface/API shape (with the team if there is one), and a red test suite that encodes intended behavior. If you can't write the contract without consulting the code, you haven't finished step 2.

Step 5 — Implement in small, verified increments (days 3–4) Replace the spike with the real thing in small commits, each one keeping the suite green, leaning on the existing patterns. Run lint/tests/typecheck per commit — CI, not just locally — and exercise the actual path against a real instance (staging or a local environment that isn't stubbed). Evidence: A branch with progressive commits, each green in CI; coverage on the new code; something that proves it works against reality (a test result, a log trace, a screenshot); and a review by at least one person who knows the codebase. The review counts as evidence — an unfamiliar codebase has tribal knowledge you cannot extract from the files alone.

Steps 6+ would be the things that actually make it "shipped": a migration plan and its rollback, feature flagging, observability, the release and post-release verification. But the first five get you to a reviewed, green, working slice in staging — which is the point at which you can say "this will work in production" with evidence behind it, instead of a guess.

{
  "model": "claude-sonnet-5",
  "input": {
    "model": "claude-sonnet-5",
    "max_tokens": 4096,
    "messages": [
      {
        "role": "user",
        "content": "Explain what an API rate limit is and how to handle a 429 response in code."
      }
    ],
    "output_config": {
      "effort": "medium"
    }
  },
  "output": "A codebase you don't know is a risk, not a hurdle. The plan should burn down that risk in order: understand, run, trace, spike, then make the change small enough that \"production-ready\" is a property you can demonstrate, not a hope.\n\nHere are the first five steps, with the evidence you collect at each.\n\n**Step 1 — Get it building and the baseline green (half day)**\nRead the README, the manifest(s), the CI config, and any architecture docs. Boot the app locally, run the full test suite, run the linter/typechecker.\n*Evidence:* The exact commands that reproduce a clean build and a passing test suite from a fresh checkout (recorded output, not memory of it). A one-page map you wrote yourself: where the entry points are, the layers, the build/test toolchain, and the main risks to your feature (e.g. \"this touches cron jobs and payments\").\n\n**Step 2 — Trace the smallest end-to-end slice that resembles your feature (half day)**\nDon't start with your feature. Pick a neighboring one that already works and follow it from entry to persistence. Note the conventions along the way: how errors surface, how config is injected, how logging is done, how tests are written.\n*Evidence:* An annotated trace — file → function → what it does — for that slice. A written list of \"conventions I must follow\" (not intuitions; things you observed in real code). A named shortlist of the 3–5 files you will actually touch. If you can't produce this trace, you're not ready to write code.\n\n**Step 3 — Spike the core path (day 2)**\nBuild the ugly version: hardcoded values, no error handling, no tests. The purpose is to confirm the path you traced in step 2 is real and to surface what you didn't know you didn't know.\n*Evidence:* A working spike demonstrating the feature's central data path, alongside a list of every assumption the spike broke and what you corrected. That correction list is the most valuable document in this whole plan.\n\n**Step 4 — Write the contract before the code (half of day 2 / day 3)**\nOnce the spike proves the path, pin down what production needs: the inputs/outputs, the error cases, where it sits in the conventions from step 2. Then write the tests — they'll be red, but they're the specification.\n*Evidence:* A one-to-two-page design doc, an agreed interface/API shape (with the team if there is one), and a red test suite that encodes intended behavior. If you can't write the contract without consulting the code, you haven't finished step 2.\n\n**Step 5 — Implement in small, verified increments (days 3–4)**\nReplace the spike with the real thing in small commits, each one keeping the suite green, leaning on the existing patterns. Run lint/tests/typecheck per commit — CI, not just locally — and exercise the actual path against a real instance (staging or a local environment that isn't stubbed).\n*Evidence:* A branch with progressive commits, each green in CI; coverage on the new code; something that proves it works against reality (a test result, a log trace, a screenshot); and a review by at least one person who knows the codebase. The review counts as evidence — an unfamiliar codebase has tribal knowledge you cannot extract from the files alone.\n\nSteps 6+ would be the things that actually make it \"shipped\": a migration plan and its rollback, feature flagging, observability, the release and post-release verification. But the first five get you to a reviewed, green, working slice in staging — which is the point at which you can say \"this will work in production\" with evidence behind it, instead of a guess.",
  "metrics": {
    "input_tokens": 134,
    "output_tokens": 2354,
    "generated_in_seconds": 42.7
  },
  "example": true
}
Generated in
42.7 seconds
Girdi Token
134
Çıktı Token
2354
Tokens per second
55.13 tokens / second
Time to first token
-

Model ayrıntıları

Aynı model anahtarını Playground'da, API isteklerinde ve dahili iş akışlarında kullanın.

Model ID
claude-sonnet-5
Sağlayıcı
Anthropic
Protokol
Anthropic Messages
Bağlam penceresi
1,000,000 token
Maksimum çıktı
128,000 token
Girdi Token
100 credits / 1 Mn token
Çıktı Token
500 credits / 1 Mn token
Önbellek okuma
10 credits / 1 Mn token
Önbellek yazma
125 credits / 1 Mn token

Claude Sonnet 5 ile Neler Yapabilirsiniz

Her isteği varsayılan olarak en yüksek maliyetli katmana yönlendirmeden güçlü günlük kaliteye ihtiyaç duyan ekipler için dengeli bir üretim modeli olarak Claude Sonnet 5’i seçin.

Üretim Kodlama

Günlük geliştirme sırasında özellikler uygulayın, aşina olmadığınız kodu açıklayın ve düzeltmeleri yineleyin.

Dengeli Analiz

Öncelikli modele özgü bir iş akışının ek yükü olmadan seçenekleri karşılaştırın ve kanıtları özetleyin.

Müşteri Asistanları

Net, iyi yapılandırılmış yanıtlar gerektiren faydalı destek ve dahili asistanları güçlendirin.

Yapılandırılmış İçerik

Spesifikasyonlar, özetler, sürüm notları ve yeniden kullanılabilir operasyonel dokümantasyon üretin.

Claude Sonnet 5 Kullanım Alanları

Üretim işlerinin geniş orta segmenti için en uygun seçenek: ciddi görevler için yeterince yetenekli ve tekrar eden kullanım için yeterince pratiktir.
01

Ürün Geliştirme

Kod, testler, dokümantasyon ve uygulama kararları arasında geçiş yapın.

02

Dahili Bilgi Asistanları

Operasyonel soruları net ve kullanışlı bir formatta yanıtlayın.

03

Destek Otomasyonu

Doğru yanıtlar taslaklayın ve belirsiz vakaları üst seviyeye yönlendirin.

04

İçerik Üretimi

Günlük iş ihtiyaçları için yapılandırılmış, yeniden kullanılabilir taslaklar oluşturun.

Claude Sonnet 5 Nasıl Kullanılır

Modeli üç basit adımda test edin.

01

Ayarlarınızı Seçin

Modelin desteklediği yanıt kontrollerini ve yükleme seçeneklerini ayarlayın.

02

Bir İstem Gönderin

Görevi açıklayın, ilgili bağlamı ekleyin ve akış halinde gelen yanıtı ile token kullanımını inceleyin.

03

API'ye Bağlanın

Belgelendirilmiş endpoint'i ve API key'inizi kullanarak aynı modeli ürününüze entegre edin.

Claude Sonnet 5 API ile Geliştirin

Öngörülebilir kontroller ve kullanım raporlamasıyla etkileşimli bir testten üretim entegrasyonuna geçin.

Tanıdık Protokoller

Bu model için yapılandırılmış API protokolünü kullanın; varsa streaming dahil.

Kullanım Görünürlüğü

Her yanıttan sonra giriş tokenlarını, çıkış tokenlarını ve tüketilen kredileri takip edin.

Modele Özel Kontroller

Genel varsayılanlara güvenmek yerine desteklenen üretim parametrelerini iletin.

Tek Hesap ve Bakiye

Desteklenen metin modellerini aynı AIReiter hesabı ve faturalandırma sistemi üzerinden test edin ve kullanın.

Claude Sonnet 5 SSS

Çevrimiçi playground, fiyatlandırma ve API erişimi hakkında sık sorulan sorular.

/ 01

Claude Sonnet 5’i ne zaman seçmeliyim?

Kodlama, analiz, asistanlar ve yapılandırılmış yazım için dengeli bir üretim modeli olarak seçin.

/ 02

Sonnet 5, Opus katmanlarından nasıl farklıdır?

Sonnet, her görevi bir öncelikli katmana yönlendirmeden güçlü günlük yetenek gerektiğinde pratik varsayılan seçenektir.

/ 03

Claude Sonnet 5 yanıtları akışlı olarak verebilir mi?

Evet. Oyun alanı çıktıyı akışlı olarak verir ve tamamlandıktan sonra kullanımı raporlar.

/ 04

Claude Sonnet 5 nasıl fiyatlandırılır?

Mevcut giriş ve çıkış token oranları playground'un üstünde gösterilir.

/ 05

Claude Sonnet 5'i bir API üzerinden entegre edebilir miyim?

Evet. Bağlantılı API belgelerini açın ve görüntülenen model kimliğini gönderin.

AIREITER

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