README.md

metadata

title: KAI API Gateway
emoji: 🦀
colorFrom: indigo
colorTo: purple
sdk: docker
pinned: false
app_port: 7860

KAI API

Free AI Proxy API — no signup, no API keys required on the AI side.

Send a message, get an AI response from GPT-4o, Claude, Llama, Mistral, and more.

Quick Start

# Create + activate virtual environment
cd KAI_API
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run the server
uvicorn main:app --host 0.0.0.0 --port 8000

# Open interactive docs
open http://localhost:8000/docs

API Endpoints

POST /chat — Send a message

curl -X POST http://localhost:8000/chat \
  -H "Content-Type: application/json" \
  -d '{
    "message": "What is quantum computing?",
    "model": "gpt-4o-mini",
    "provider": "auto"
  }'

Response:

{
  "response": "Quantum computing is...",
  "model": "gpt-4o-mini",
  "provider": "g4f",
  "timestamp": "2026-02-11T21:30:00Z"
}

Parameters:

Parameter	Type	Required	Description
message	string	✅	Your prompt/question
model	string	❌	Model to use (default: gpt-4o-mini)
provider	string	❌	auto, g4f, or pollinations
system_prompt	string	❌	System instructions for the AI

GET /models — List available models

curl http://localhost:8000/models

GET /health — Health check

curl http://localhost:8000/health

Providers

Provider	Models	How it works
g4f	GPT-4o, GPT-4o-mini, Claude 3.5, Llama, Mixtral	Routes through third-party sites, no API key
Pollinations	OpenAI, Mistral, Llama, DeepSeek, Claude	Free public AI API, no auth

Architecture

• Stateless: Every request creates a fresh session — no conversation history
• Multi-provider fallback: If g4f fails, Pollinations picks up
• Provider priority: g4f → Pollinations

Integration Examples

Python

import requests

response = requests.post("http://localhost:8000/chat", json={
    "message": "Explain AI in one sentence"
})
print(response.json()["response"])

JavaScript

const response = await fetch("http://localhost:8000/chat", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({ message: "Explain AI in one sentence" })
});
const data = await response.json();
console.log(data.response);