VANGU / DEVELOPER
Best Practice Guides
Actionable architectural blueprints for terminal agents, editor completions, and high-scale production systems.
1. Autonomous Pair Programming with Claude Code
Claude Code is an autonomous terminal agent capable of analyzing local git repositories, reading/writing files, and running test suites directly. Connect it to Vangu Anthropic endpoint with standard environment variables.
Installation & Environment Setup
Install the official CLI globally, then point the Anthropic base URL to Vangu along with your developer key:
# 1. Claude Code CLI aracını küresel olarak yükleyin
npm install -g @anthropic-ai/claude-code
# 2. Vangu Anthropic ortam değişkenlerini dışa aktarın
export ANTHROPIC_BASE_URL="https://api.vangu.dev/anthropic"
export ANTHROPIC_AUTH_TOKEN="vgu_live_sample_token_67b8a901"
# 3. Projenizin kök dizinine gidip Claude Code'u başlatın
cd ~/projelerim/backend
claude
# Windows PowerShell için ortam değişkeni tanımları
$env:ANTHROPIC_BASE_URL = "https://api.vangu.dev/anthropic"
$env:ANTHROPIC_AUTH_TOKEN = "vgu_live_sample_token_67b8a901"
# Claude Code CLI oturumunu başlatın
claude
Recommended Models & Pro Tips
- Fast & Balanced Coding: Use <code>gpt-5.6-sol</code> (2.0x multiplier) for daily refactoring, bugfixes, and unit tests.
- Complex Architecture & Multi-Step Tasks: Employ flagship <code>gpt-6-astra</code> (4.0x multiplier) for monorepo migrations and deep architectural planning.
- .claudeignore Usage: Add build outputs and environment files to <code>.claudeignore</code> to prevent unnecessary token consumption.
2. Git-Driven Workflows with Codex & Aider CLI
Aider operates directly inside local git repositories, pairing with you to edit code and generate meaningful git commit histories. It integrates seamlessly via Vangu OpenAI-compatible endpoint (<code>https://api.vangu.dev/v1</code>).
Aider Installation & Vangu Codex Binding
# 1. Python pip üzerinden Aider CLI aracını yükleyin
pip install aider-chat
# 2. Vangu Codex uyumlu uç noktayı ve API anahtarını tanımlayın
export OPENAI_API_BASE="https://api.vangu.dev/v1"
export OPENAI_API_KEY="vgu_live_sample_token_67b8a901"
# 3. Sol veya Astra modeliyle otomatik commit modunda başlatın
aider --model openai/gpt-5.6-sol --auto-commits
Productivity Best Practices
- /add Command: Only add files relevant to current prompt (e.g. <code>/add src/auth.js</code>) to preserve quota headroom.
- /test Command: Run <code>/test npm test</code> so Aider inspects failures and self-corrects the code.
- Midnight 00.00 Quota Resets: Daily plan quotas refresh at 00.00 every midnight. Schedule large batch refactorings across daily cycles without extra costs.
3. Triple-Protocol Gateway Architecture
Vangu operates an intelligent edge gateway accepting OpenAI, Anthropic, and Codex payloads concurrently under a single API key without code changes.
Protocol Comparison Matrix
| Protocol | Endpoint URL | Auth Header | Supported Models |
|---|---|---|---|
| OpenAI Chat | `https://api.vangu.dev/v1` | `Authorization: Bearer <KEY>` | Luna, Terra, Sol, Astra |
| Anthropic Messages | `https://api.vangu.dev/anthropic/v1` | `x-api-key: <KEY>` | Terra, Sol, Astra |
| Codex CLI / Responses | `https://api.vangu.dev/v1` | `Authorization: Bearer <KEY>` | Luna, Terra, Sol, Astra |
| Image Generation & Editing | `https://api.vangu.dev/v1/images/...` | `Authorization: Bearer <KEY>` | gpt-image-2, gpt-image-2.5 (Flare & Sunburst) |
Python Multi-Protocol Client Example
import os
from openai import OpenAI
from anthropic import Anthropic
API_KEY = os.environ.get("VANGU_API_KEY", "vgu_live_sample_token_67b8a901")
# 1. OpenAI İstemcisi (Luna / Terra / Sol / Astra)
openai_client = OpenAI(
base_url="https://api.vangu.dev/v1",
api_key=API_KEY
)
# 2. Anthropic İstemcisi (Claude SDK Uyumlu)
anthropic_client = Anthropic(
base_url="https://api.vangu.dev/anthropic",
api_key=API_KEY
)
print("Vangu çoklu protokol geçidi hazır.")
4. Exponential Backoff & Fault Tolerance
Under high concurrency, network micro-jitter or rate-limits must be absorbed using exponential backoff with randomized jitter to safeguard pipeline stability.
HTTP Status Codes & Renewal Policy
- HTTP 429 (Quota Limit): Returned when daily quota is exhausted. Daily quotas reset automatically at 00:00 midnight (UTC+3). The <code>X-RateLimit-Reset</code> header denotes the exact epoch.
- HTTP 429 (Concurrency Limit): Returned when active concurrent limit (10 concurrent requests) peaks. New requests are accepted as soon as an in-flight call completes.
- HTTP 503 (Service Busy): Temporary node rebalancing. Resolves rapidly via backoff retries.
Resilient Python Retry Implementation
import time
import random
import requests
def call_vangu_resilient(payload, max_retries=5):
url = "https://api.vangu.dev/v1/chat/completions"
headers = {
"Authorization": "Bearer vgu_live_sample_token_67b8a901",
"Content-Type": "application/json"
}
for attempt in range(max_retries):
resp = requests.post(url, json=payload, headers=headers, timeout=30)
if resp.status_code == 200:
return resp.json()
if resp.status_code == 429:
# Retry-After başlığını kontrol et veya üstel bekleme süresi hesapla
retry_after = float(resp.headers.get("Retry-After", 2 ** attempt))
jitter = random.uniform(0.1, 0.5)
sleep_time = retry_after + jitter
print(f"[Vangu] 429 Alındı. Yeniden deneniyor (Deneme {attempt + 1}/{max_retries})...")
time.sleep(sleep_time)
continue
if resp.status_code >= 500:
time.sleep((2 ** attempt) + random.uniform(0.1, 0.3))
continue
resp.raise_for_status()
raise RuntimeError("Vangu isteği maksimum deneme sayısına ulaştı.")
5. Instant Streaming with Server-Sent Events (SSE)
Enable SSE streaming to display generated text before the full response is complete. First-token and total response times vary by model, input length and provider load.
Vanilla JavaScript (Fetch & ReadableStream)
async function streamVangu(prompt) {
const res = await fetch("https://api.vangu.dev/v1/chat/completions", {
method: "POST",
headers: {
"Content-Type": "application/json",
"Authorization": "Bearer vgu_live_sample_token_67b8a901"
},
body: JSON.stringify({
model: "gpt-5.6-luna", // Hızlı yanıtlar için en ekonomik model
stream: true,
messages: [{ role: "user", content: prompt }]
})
});
const reader = res.body.getReader();
const decoder = new TextDecoder();
while (true) {
const { done, value } = await reader.read();
if (done) break;
const chunk = decoder.decode(value);
const lines = chunk.split("\n");
for (const line of lines) {
if (line.startsWith("data: ") && !line.includes("[DONE]")) {
const json = JSON.parse(line.slice(6));
const token = json.choices[0]?.delta?.content || "";
process.stdout.write(token);
}
}
}
}
// streamVangu("Asenkron programlama nedir?");
6. Token Savings & Model Tiering Strategy
Rather than directing all calls to apex flagships, tiered model routing combined with lean prompt hygiene preserves up to 40% daily quota headroom.
Vangu Model Tiering & Use-Case Matrix
| Model | Price Multiplier | Recommended Workloads | Response Time |
|---|---|---|---|
| gpt-5.6-luna / gpt-6-luna | 1.0x (Lowest Cost) | Classification, JSON parsing, rapid summarization | Varies by request |
| gpt-6.1-terra | 1.5x (Standard) | Visual reasoning, natural writing, translation | Varies by request |
| gpt-5.6-terra | 1.5x (Standard) | Conversational agents, content generation, translation | Varies by request |
| gpt-5.6-sol / gpt-6-sol | 2.0x (Advanced) | Code generation, refactoring with Aider/Claude Code | Varies by request |
| gpt-6-astra | 4.0x (Flagship) | Complex architectural synthesis, deep reasoning | Varies by request |
| gpt-image-2 | Standard Quota | 1024x1024 graphic rendering, marketing assets | Varies by request |
| gpt-image-2.5 | HD Visuals | High-fidelity cinematic generation | Varies by request |
Image Generation Note (Unlimited Tier)
Our Unlimited plans include a dedicated weekly allowance of 100 images covering both <code>gpt-image-2</code> and <code>gpt-image-2.5</code>.