6 Providers, 25+ Models

One API for Every LLM

Route to OpenAI, Anthropic, Google, Groq, Together, and DeepSeek through a single endpoint. OpenAI-compatible. BYO keys. Caching and retries built in.

View Examples List Models

OpenAI

Anthropic

Google Gemini

Groq

Together AI

DeepSeek

Terminal

# Same API, any model — just change the model name
$ curl -X POST agent-llm.167.148.41.86.nip.io/api/chat \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role":"user","content":"Hello!"}],
    "provider_key": "sk-..."
  }'

{
  "choices": [{ "message": { "content": "Hello! How can I help?" } }],
  "provider": "openai",
  "model": "gpt-4o-mini",
  "usage": { "total_tokens": 25 },
  "cached": false
}

Why Use a Router?

One integration, every provider. Switch models without changing code.

🔄

OpenAI-Compatible

Drop-in replacement at /v1/chat/completions. Change one URL in your existing code and any provider works instantly.

🔑

Bring Your Own Keys

Use your own provider API keys. Pass per-request or store securely. We never log your keys permanently.

⚡

Response Caching

Identical requests with temperature=0 are cached for 5 minutes. Save money and reduce latency on repeated calls.

🔄

Automatic Retries

Failed requests are retried once with a 1-second delay. Handles transient errors without retry logic in your code.

📊

Cost Tracking

Track token usage per provider. The /health endpoint shows total requests, tokens, and per-provider breakdowns.

🌍

6 Providers

OpenAI GPT-4o, Claude, Gemini, Groq Llama, Together AI Mixtral, DeepSeek. All through one API, one auth pattern.

Available Models

25+ models across 6 providers. All accessible through one endpoint.

Provider	Models	Key Format
OpenAI	gpt-4o, gpt-4o-mini, gpt-4-turbo, gpt-3.5-turbo, o1, o1-mini	sk-...
Anthropic	claude-opus-4-6, claude-sonnet-4-6, claude-haiku-4-5	sk-ant-...
Google	gemini-2.0-flash, gemini-2.0-pro, gemini-1.5-pro	AIza...
Groq	llama-3.3-70b, llama-3.1-8b, mixtral-8x7b, gemma2-9b	gsk_...
Together AI	meta-llama/Llama-3.3-70B, mistralai/Mixtral-8x22B	tok_...
DeepSeek	deepseek-chat, deepseek-reasoner	sk-...

Integration Examples

Switch models by changing one string. Same code, any provider.

# Use any model — just change "model"
curl -X POST http://agent-llm.167.148.41.86.nip.io/api/chat \
  -H "Content-Type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "messages": [{"role":"user","content":"Explain DeFi in one paragraph"}],
    "provider_key": "sk-ant-..."
  }'

# OpenAI-compatible endpoint (drop-in replacement)
curl -X POST http://agent-llm.167.148.41.86.nip.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "X-Provider-Key: sk-..." \
  -d '{"model":"gpt-4o-mini","messages":[{"role":"user","content":"Hello"}]}'

# List all available models
curl http://agent-llm.167.148.41.86.nip.io/api/models

import requests

API = "http://agent-llm.167.148.41.86.nip.io"

# Chat with any model
resp = requests.post(f"{API}/api/chat", json={
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "Explain AI agents"}],
    "provider_key": "sk-..."
})
data = resp.json()
print(data["choices"][0]["message"]["content"])
print(f"Tokens: {data['usage']['total_tokens']}")

# Switch to Claude — same code, different model
resp = requests.post(f"{API}/api/chat", json={
    "model": "claude-sonnet-4-6",
    "messages": [{"role": "user", "content": "Explain AI agents"}],
    "provider_key": "sk-ant-..."
})

# Compare outputs, same API
print(resp.json()["choices"][0]["message"]["content"])

const API = "http://agent-llm.167.148.41.86.nip.io";

// Works as OpenAI drop-in replacement
const res = await fetch(`${API}/v1/chat/completions`, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "X-Provider-Key": "sk-..."
  },
  body: JSON.stringify({
    model: "gpt-4o-mini",
    messages: [{ role: "user", content: "Hello" }]
  })
});

const { choices, usage } = await res.json();
console.log(choices[0].message.content);
console.log(`Tokens: ${usage.total_tokens}`);

// Switch to Groq for fast inference
const fast = await fetch(`${API}/api/chat`, {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    model: "llama-3.3-70b-versatile",
    messages: [{ role: "user", content: "What is DeFi?" }],
    provider_key: "gsk_..."
  })
}).then(r => r.json());