Update app.py

app.py

@@ -1,18 +1,13 @@
 import gradio as gr
-import requests
-import io
 import random
 import os
-import time
 from PIL import Image
-import json
 from typing import Optional
+from huggingface_hub import InferenceClient
 
 # Project by Nymbo
 
-API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-Krea-dev"
 API_TOKEN = os.getenv("HF_READ_TOKEN")
-headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
 # Function to query the API and return the generated image
@@ -53,44 +48,53 @@ def flux_krea_generate(
 
     key = random.randint(0, 999)
     
-    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
-    headers = {"Authorization": f"Bearer {API_TOKEN}"}
-
     # Add some extra flair to the prompt
     enhanced_prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
     print(f'\033[1mGeneration {key}:\033[0m {enhanced_prompt}')
     
-    # Prepare the payload for the API call, including width and height
-    payload = {
-        "inputs": enhanced_prompt,
-        "is_negative": False,
-        "steps": steps,
-        "cfg_scale": cfg_scale,
-        "seed": seed if seed != -1 else random.randint(1, 1000000000),
-        "strength": strength,
-        "parameters": {
-            "width": width,  # Pass the width to the API
-            "height": height  # Pass the height to the API
-        }
-    }
-
-    # Send the request to the API and handle the response
-    response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
-    if response.status_code != 200:
-        print(f"Error: Failed to get image. Response status: {response.status_code}")
-        print(f"Response content: {response.text}")
-        if response.status_code == 503:
-            raise gr.Error(f"{response.status_code} : The model is being loaded")
-        raise gr.Error(f"{response.status_code}")
-    
     try:
-        # Convert the response content into an image
-        image_bytes = response.content
-        image = Image.open(io.BytesIO(image_bytes))
-        print(f'\033[1mGeneration {key} completed!\033[0m ({enhanced_prompt})')
-        return image
+        # Initialize the Hugging Face Inference Client
+        # Try different providers in order of preference
+        providers = ["auto", "replicate", "fal-ai"]
+        
+        for provider in providers:
+            try:
+                client = InferenceClient(
+                    api_key=API_TOKEN,
+                    provider=provider
+                )
+                
+                # Generate the image using the proper client
+                image = client.text_to_image(
+                    prompt=enhanced_prompt,
+                    negative_prompt=negative_prompt,
+                    model="black-forest-labs/FLUX.1-Krea-dev",
+                    width=width,
+                    height=height,
+                    num_inference_steps=steps,
+                    guidance_scale=cfg_scale,
+                    seed=seed if seed != -1 else random.randint(1, 1000000000)
+                )
+                
+                print(f'\033[1mGeneration {key} completed with {provider}!\033[0m ({enhanced_prompt})')
+                return image
+                
+            except Exception as provider_error:
+                print(f"Provider {provider} failed: {provider_error}")
+                if provider == providers[-1]:  # Last provider
+                    raise provider_error
+                continue
+        
     except Exception as e:
-        print(f"Error when trying to open the image: {e}")
+        print(f"Error during image generation: {e}")
+        if "404" in str(e):
+            raise gr.Error("Model not found. Please ensure the FLUX.1-Krea-dev model is accessible with your API token.")
+        elif "503" in str(e):
+            raise gr.Error("The model is currently being loaded. Please try again in a moment.")
+        elif "401" in str(e) or "403" in str(e):
+            raise gr.Error("Authentication failed. Please check your HF_READ_TOKEN environment variable.")
+        else:
+            raise gr.Error(f"Image generation failed: {str(e)}")
         return None
 
 # CSS to style the app