Unified LLM Gateway: OpenAI-Compatible Multi-Model API Proxy with Asia Low-Latency Nodes

Overview

https://api.taotok.io is a production-grade LLM API gateway deployed on Hong Kong edge infrastructure, providing protocol conversion for GPT, Claude, Gemini, and other mainstream LLMs under a single OpenAI-compatible endpoint. It abstracts heterogeneous native API formats of different model vendors, unifies request/response schema, and integrates built-in traffic governance, token statistics, and multi-key failover scheduling.

Core technical capabilities:

• Full OpenAI v1 protocol compatibility, zero modification for existing OpenAI SDK business code
• Native adapter for Claude Messages API, Gemini GenerateContent, cross-protocol transparent conversion
• Asia regional low-latency nodes, TLS 1.3 full-link encryption, 99.9% service uptime SLA
• Layered traffic control: global rate limit, per-key quota isolation, CORS whitelist & CSP security policy
• Real-time token consumption metrics, request log aggregation, multi-dimensional billing based on model & token volume
• Multi-pool upstream key scheduling: automatic failover when upstream triggers 429/account risk control

Quick Integration Code Samples

1. cURL Test Model List Endpoint

export API_KEY="sk-xxxxxxxxxxxxxxxxxxxx"
curl https://api.taotok.io/v1/models \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json"

Returns structured model metadata including GPT-4o, Claude 3 Opus, Gemini Advanced, model context window limits and routing labels.

2. cURL Chat Completion Synchronous Request

curl https://api.taotok.io/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
        {"role": "system", "content": "You are a backend development engineer"},
        {"role": "user", "content": "Implement a token statistical middleware for LLM gateway"}
    ],
    "temperature": 0.6,
    "max_tokens": 1024
}'

3. Python OpenAI SDK Standard Access

from openai import OpenAI

# Override base_url to taotok unified gateway endpoint
client = OpenAI(
    api_key="sk-xxxxxxxxxxxxxxxxxxxx",
    base_url="https://api.taotok.io/v1"
)

def sync_chat():
    resp = client.chat.completions.create(
        model="claude-3-opus",
        messages=[
            {"role": "user", "content": "Explain multi-key load balancing logic for LLM proxy"}
        ],
        stream=False
    )
    # Parse token usage statistics
    prompt_tokens = resp.usage.prompt_tokens
    completion_tokens = resp.usage.completion_tokens
    print(f"Input tokens: {prompt_tokens}, Output tokens: {completion_tokens}")
    print(resp.choices[0].message.content)

sync_chat()

4. Node.js SDK Access

import OpenAI from "openai";

const openai = new OpenAI({
    apiKey: "sk-xxxxxxxxxxxxxxxxxxxx",
    baseURL: "https://api.taotok.io/v1"
});

async function streamChat() {
    const stream = await openai.chat.completions.create({
        model: "gemini-advanced",
        messages: [{ role: "user", content: "Write a stream response parser for SSE" }],
        stream: true
    });
    for await (const chunk of stream) {
        process.stdout.write(chunk.choices[0]?.delta?.content || "");
    }
}

streamChat();

Traffic Governance Technical Design

The gateway builds a multi-layer upstream key pool scheduler:

• Classify upstream keys by vendor, region, risk level
• Real-time error counting, automatic offline of high-failure-rate upstream channels
• Request weight distribution to disperse single-key traffic, reduce upstream risk trigger probability
• Independent quota configuration for each business sub-key, to avoid cross-business token overrun

Token Metrics & Billing Logic

All requests record prompt_tokens and completion_tokens separately, with persistent log storage. The backend provides aggregated API for consumption statistics, supporting custom billing rules based on model dimension, which can be docked to internal financial settlement systems.

Deployment Scenarios

• Global SaaS unified LLM access layer
• Multi-model research batch testing platform
• Cross-regional low-delay AI agent service
• Multi-tenant business isolation LLM calling middleware