Update README with API integration instructions for n8n

README.md

@@ -10,62 +10,154 @@ pinned: false
 short_description: Text-to-Image generation using Tencent HunyuanImage-3.0
 ---
 
-# 🎨 HunyuanImage-3.0 Text-to-Image Generation
+# 🎨 HunyuanImage-3.0 Text-to-Image with Inference API
 
-This Space provides an interface for the **Tencent HunyuanImage-3.0** model, a powerful native multimodal model for image generation.
+This Space provides an interface for the **Tencent HunyuanImage-3.0** model using Hugging Face Inference API (paid from your account balance).
 
-## About HunyuanImage-3.0
+## ✅ What's New
 
-HunyuanImage-3.0 is a groundbreaking model that:
-- Features 80B total parameters with 13B activated per token (MoE architecture)
-- Unifies multimodal understanding and generation in an autoregressive framework
-- Achieves performance comparable to leading closed-source models
-- Supports intelligent prompt understanding and automatic elaboration
+- **Real image generation** using HF Inference API
+- **n8n integration** via REST API endpoint
+- **Base64 image output** for easy integration
+- **Automatic token-based authentication**
 
-## ⚠️ Important Notes
+## 🔧 Setup Instructions
 
-**Hardware Requirements:**
-- Direct inference requires **3×80GB GPU memory** (240GB total)
-- ZeroGPU is insufficient for full model inference
-- For production use, consider:
-  - Using Inference API endpoints
-  - Deploying on appropriate hardware (4×80GB GPUs recommended)
-  - Using inference providers like FAL AI
+### 1. Get Your HF Token
+1. Go to [Hugging Face Settings > Access Tokens](https://huggingface.co/settings/tokens)
+2. Create a new token with `write` permissions
+3. Copy the token (starts with `hf_...`)
 
-**Current Implementation:**
-This Space demonstrates the UI structure and configuration. For actual inference:
-1. The model needs to be loaded with proper hardware
-2. Or integrate with Inference API/providers
-3. Or use model quantization techniques
+### 2. Set Your Token in Space
+1. Go to [Settings](https://huggingface.co/spaces/Alae65/HunyuanImage-3/settings)
+2. Find "Variables and secrets" section
+3. Click "Replace" next to HF_TOKEN
+4. Paste your actual token (replace the placeholder)
+5. Click "Save"
 
-## Model Information
+### 3. Restart the Space
+After setting the token, click "Restart space" in Settings.
 
-- **Model:** [tencent/HunyuanImage-3.0](https://huggingface.co/tencent/HunyuanImage-3.0)
-- **Architecture:** Autoregressive MoE (64 experts)
-- **Parameters:** 80B total, 13B active per token
-- **License:** tencent-hunyuan-community
-- **Paper:** [arXiv:2509.23951](https://arxiv.org/abs/2509.23951)
+## 📡 API Endpoint for n8n Integration
+
+### Using the Gradio API
+
+The Space provides a REST API that can be called from n8n using the HTTP Request node.
+
+**Endpoint URL:**
+```
+https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate
+```
+
+### n8n HTTP Node Configuration
+
+1. Add an **HTTP Request** node in n8n
+2. Configure as follows:
+
+**Method:** POST
+
+**URL:**
+```
+https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate
+```
+
+**Body (JSON):**
+```json
+{
+  "data": [
+    "A serene mountain landscape with a crystal clear lake",
+    42,
+    50
+  ]
+}
+```
+
+**Parameters:**
+- `data[0]` (string): Your image prompt
+- `data[1]` (integer): Seed number (for reproducibility)
+- `data[2]` (integer): Number of inference steps (10-100)
+
+**Response Format:**
+The API returns a JSON with:
+```json
+{
+  "success": true,
+  "image_base64": "iVBORw0KGgoAAAANSUhEUg...",
+  "seed": 42,
+  "status": "Success!",
+  "prompt": "A serene mountain landscape..."
+}
+```
+
+### Example n8n Workflow
 
-## Features
+1. **Trigger** → Webhook or Schedule
+2. **HTTP Request** → Call HunyuanImage API
+3. **Code** → Decode base64 image if needed
+4. **Save or Send** → Store image or send via email/Slack
+
+### Python Example
+
+```python
+import requests
+import base64
+from PIL import Image
+from io import BytesIO
+
+url = "https://alae65-hunyuanimage-3.hf.space/gradio_api/call/api_generate"
+
+payload = {
+    "data": [
+        "A beautiful sunset over the ocean",
+        42,
+        50
+    ]
+}
+
+response = requests.post(url, json=payload)
+result = response.json()
+
+if result.get("success"):
+    # Decode base64 image
+    image_data = base64.b64decode(result["image_base64"])
+    image = Image.open(BytesIO(image_data))
+    image.save("output.png")
+    print("Image saved successfully!")
+```
+
+## 🎯 Features
 
 - 🎯 Advanced prompt understanding
-- 🖼️ Multiple resolution support (auto, 1024x1024, 1280x768, 768x1280)
+- 🖼️ Multiple resolution support
 - 🎲 Seed control for reproducibility
-- ⚙️ Configurable diffusion steps
+- ⚙️ Configurable diffusion steps (10-100)
 - 📝 Example prompts included
+- 🔌 REST API for n8n and automation
+- 📦 Base64 image encoding
 
-## API Endpoint (Coming Soon)
+## 💰 Pricing
 
-This Space will support API endpoints for integration with n8n and other workflow tools.
+This Space uses the **Hugging Face Inference API** which is billed based on usage:
+- Cost is deducted from your HF account balance
+- You mentioned having $9 credit available
+- Check [Billing Settings](https://huggingface.co/settings/billing) for details
+
+## 📚 Model Information
+
+- **Model:** [tencent/HunyuanImage-3.0](https://huggingface.co/tencent/HunyuanImage-3.0)
+- **Architecture:** Autoregressive MoE (64 experts)
+- **Parameters:** 80B total, 13B active per token
+- **License:** tencent-hunyuan-community
+- **Paper:** [arXiv:2509.23951](https://arxiv.org/abs/2509.23951)
 
-## Links
+## 🔗 Links
 
 - [Official Website](https://hunyuan.tencent.com/image)
 - [GitHub Repository](https://github.com/Tencent-Hunyuan/HunyuanImage-3.0)
 - [Technical Paper](https://arxiv.org/pdf/2509.23951)
 - [Model Card](https://huggingface.co/tencent/HunyuanImage-3.0)
 
-## Citation
+## 📝 Citation
 
 ```bibtex
 @article{cao2025hunyuanimage,