README.md

metadata

title: PhantomAPI
emoji: 👻
colorFrom: purple
colorTo: indigo
sdk: docker
pinned: false

👻 PhantomAPI

Turn ChatGPT into a FREE OpenAI-Compatible API

The invisible proxy that bridges ChatGPT's free web interface with your AI automation workflows.

Quick Start · n8n Integration · Architecture · Docker

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🌟 What is PhantomAPI?

PhantomAPI is a high-performance proxy server that makes ChatGPT's free web interface behave like the official OpenAI API. It's designed as a drop-in replacement for any tool that speaks the OpenAI protocol — especially n8n.

✨ Key Features

Feature	Description
💸 Zero API Costs	Uses ChatGPT's free web interface via headless browser automation
⚡ Async Architecture	Built on FastAPI with a dedicated browser thread for non-blocking requests
🤖 AI Agent Support	Full tool-calling / function-calling support for n8n Agent nodes
🔒 API Key Auth	Protected with Bearer token authentication
🐳 Docker Ready	Deploy in seconds with docker-compose up
🎨 Built-in GUI	A sleek dark-mode chat interface for quick testing
📐 Clean Architecture	Proper FastAPI structure — routers, schemas, services, utils

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⚙️ How It Works

┌──────────┐     HTTP/JSON      ┌──────────────┐     Playwright     ┌──────────────┐
│   n8n    │ ──────────────────▶ │  PhantomAPI  │ ──────────────────▶ │  ChatGPT     │
│  (or any │ ◀────────────────── │  (FastAPI)   │ ◀────────────────── │  (Web UI)    │
│  client) │   OpenAI Schema     │              │   Scrape Response   │              │
└──────────┘                     └──────────────┘                     └──────────────┘

1. You send a standard OpenAI API request to PhantomAPI
2. PhantomAPI formats your messages into a prompt and types it into ChatGPT's web interface using a stealth browser
3. ChatGPT responds on the web page — PhantomAPI scrapes the text
4. The response is formatted back into the official OpenAI JSON schema and returned to you

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🛠️ Quick Start

Prerequisites

• Python 3.10+
• Google Chrome installed on your system

1. Clone & Install

git clone https://github.com/mrshibly/phantom-api.git
cd phantom-api
pip install -r requirements.txt
python -m playwright install chromium

2. Configure

cp .env.example .env
# Edit .env and set your API_SECRET_KEY

3. Run

python run.py

The server will start on http://localhost:7777.

Endpoint	Description
http://localhost:7777/	Health check
http://localhost:7777/docs	Swagger UI (interactive API docs)
http://localhost:7777/gui	Chat GUI for quick testing

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🔌 Connecting to n8n

Method 1: OpenAI Node (Recommended)

1. In n8n, go to Credentials → New → OpenAI API
2. Set Base URL to: http://127.0.0.1:7777/v1
3. Set API Key to your API_SECRET_KEY from .env
4. Use this credential in any OpenAI or AI Agent node

Docker Tip: If n8n runs in Docker, use http://host.docker.internal:7777/v1

Method 2: HTTP Request Node

1. Add an HTTP Request node
2. Method: POST
3. URL: http://127.0.0.1:7777/v1/chat/completions
4. Authentication: Header Auth → Authorization: Bearer YOUR_KEY
5. Body (JSON):

{
  "model": "gpt-4o-mini",
  "messages": [
    { "role": "user", "content": "Hello, PhantomAPI!" }
  ]
}

---

📐 Architecture

phantom-api/
├── app/
│   ├── main.py              # App factory, CORS, lifespan
│   ├── config.py            # Environment-driven settings
│   ├── dependencies.py      # Auth dependency injection
│   ├── api/v1/
│   │   ├── router.py        # Route aggregator
│   │   ├── chat.py          # POST /v1/chat/completions
│   │   ├── responses.py     # POST /v1/responses
│   │   └── models.py        # GET  /v1/models
│   ├── schemas/
│   │   ├── chat.py          # Request/Response models
│   │   └── responses.py     # Responses API models
│   ├── services/
│   │   └── browser.py       # Playwright browser engine
│   └── utils/
│       ├── prompt.py         # Smart prompt builder
│       └── parser.py         # Tool-call JSON parser
├── static/
│   └── index.html            # Chat GUI
├── tests/
│   └── test_health.py        # Endpoint tests
├── Dockerfile
├── docker-compose.yml
├── requirements.txt
├── .env.example
└── run.py                    # Entry point

---

🐳 Docker Deployment

# Build and run
docker-compose up --build -d

# The server is now running on http://localhost:7777

---

🤗 Hugging Face Spaces Deployment

You can deploy PhantomAPI directly to Hugging Face Spaces for free.

1. Create a New Space: Go to huggingface.co/new-space
2. Select SDK: Choose Docker
3. Choose Template: Select Blank (The existing Dockerfile will be used automatically)
4. Configure Secrets:
   • Go to Settings → Variables and secrets in your Space
   • Add a new Secret named API_SECRET_KEY with your desired token
5. Push Code:

   git remote add hf https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
   git push -u hf main
   

PhantomAPI will automatically start on port 7860.

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🔧 API Reference

POST /v1/chat/completions

Standard OpenAI Chat Completions endpoint. Supports messages, tools, and function calling.

POST /v1/responses

Modern Responses API for newer n8n versions. Accepts input (string or messages) and optional instructions.

GET /v1/models

Returns available model identifiers (used by n8n's model dropdown).

GET /

Health check — returns server status and version.

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📄 License

This project is open-sourced under the MIT License.

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Built with ❤️ by mrshibly

Hugging Face Secrets Set Karein: Hugging Face Space ke Settings -> Variables and secrets mein jayein aur ye add karein:

CHATGPT_SESSION_TOKEN: Isme apna ChatGPT session token dalein (Chrome DevTools -> Application -> Cookies -> __Secure-next-auth.session-token). PROXY_URL: (Optional) Agar IP block ho rahi hai, toh apna proxy URL dalein (e.g., http://username:password@ip:port). Logs Check Karein: Push karne ke baad agar fir bhi fail hota hai, toh mujhe naye logs dikhaiye. Ab logs mein humein saaf dikhega ki browser login page par hai ya Cloudflare par.