Update app.py

app.py

@@ -1,14 +1,12 @@
-import gradio as gr
+from flask import Flask, request, jsonify, send_file, render_template_string
 import requests
 import io
-import random
 import os
-import time
+import random
 from PIL import Image
 from deep_translator import GoogleTranslator
-import json
 
-# Project by Nymbo
+app = Flask(__name__)
 
 API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
 API_TOKEN = os.getenv("HF_READ_TOKEN")
@@ -16,101 +14,127 @@ headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
 # Function to query the API and return the generated image
-def query(prompt, is_negative=False, steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
-    if prompt == "" or prompt is None:
-        return None
+def query(prompt, negative_prompt="", steps=35, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
+    if not prompt:
+        return None, "Prompt is required"
 
     key = random.randint(0, 999)
     
-    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
-    headers = {"Authorization": f"Bearer {API_TOKEN}"}
-    
     # Translate the prompt from Russian to English if necessary
     prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
-    print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
+    print(f'Generation {key} translation: {prompt}')
 
     # Add some extra flair to the prompt
     prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-    print(f'\033[1mGeneration {key}:\033[0m {prompt}')
+    print(f'Generation {key}: {prompt}')
     
-    # Prepare the payload for the API call, including width and height
     payload = {
         "inputs": prompt,
-        "is_negative": is_negative,
+        "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
+            "width": width,
+            "height": height
         }
     }
 
-    # 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}")
-    
+    # Send the request to the API
     try:
-        # Convert the response content into an image
+        response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
+        if response.status_code != 200:
+            return None, f"Error: Failed to get image. Status code: {response.status_code}, Details: {response.text}"
+        
         image_bytes = response.content
         image = Image.open(io.BytesIO(image_bytes))
-        print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
-        return image
+        return image, None
     except Exception as e:
-        print(f"Error when trying to open the image: {e}")
-        return None
-
-# CSS to style the app
-css = """
-#app-container {
-    max-width: 800px;
-    margin-left: auto;
-    margin-right: auto;
-}
-"""
+        return None, f"Error when trying to open the image: {e}"
 
-# Build the Gradio UI with Blocks
-with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
-    # Add a title to the app
-    gr.HTML("<center><h1>FLUX.1-Dev</h1></center>")
-    
-    # Container for all the UI elements
-    with gr.Column(elem_id="app-container"):
-        # Add a text input for the main prompt
-        with gr.Row():
-            with gr.Column(elem_id="prompt-container"):
-                with gr.Row():
-                    text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
-                
-                # Accordion for advanced settings
-                with gr.Row():
-                    with gr.Accordion("Advanced Settings", open=False):
-                        negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
-                        with gr.Row():
-                            width = gr.Slider(label="Width", value=1024, minimum=64, maximum=1216, step=32)
-                            height = gr.Slider(label="Height", value=1024, minimum=64, maximum=1216, step=32)
-                        steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
-                        cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
-                        strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
-                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) # Setting the seed to -1 will make it random
-                        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
-
-        # Add a button to trigger the image generation
-        with gr.Row():
-            text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
-        
-        # Image output area to display the generated image
-        with gr.Row():
-            image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
+# HTML template for the index page
+index_html = """
+<!DOCTYPE html>
+<html lang="ja">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>FLUX.1-Dev Image Generator</title>
+</head>
+<body>
+    <h1>FLUX.1-Dev Image Generator</h1>
+    <form action="/generate" method="get">
+        <label for="prompt">Prompt:</label>
+        <input type="text" id="prompt" name="prompt" placeholder="Enter your prompt" required><br><br>
         
-        # Bind the button to the query function with the added width and height inputs
-        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
+        <label for="negative_prompt">Negative Prompt:</label>
+        <input type="text" id="negative_prompt" name="negative_prompt" value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos"><br><br>
+
+        <label for="width">Width:</label>
+        <input type="number" id="width" name="width" value="1024"><br><br>
+
+        <label for="height">Height:</label>
+        <input type="number" id="height" name="height" value="1024"><br><br>
+
+        <label for="steps">Sampling Steps:</label>
+        <input type="number" id="steps" name="steps" value="35"><br><br>
+
+        <label for="cfgs">CFG Scale:</label>
+        <input type="number" id="cfgs" name="cfgs" value="7"><br><br>
+
+        <label for="sampler">Sampling Method:</label>
+        <select id="sampler" name="sampler">
+            <option value="DPM++ 2M Karras">DPM++ 2M Karras</option>
+            <option value="DPM++ SDE Karras">DPM++ SDE Karras</option>
+            <option value="Euler">Euler</option>
+            <option value="Euler a">Euler a</option>
+            <option value="Heun">Heun</option>
+            <option value="DDIM">DDIM</option>
+        </select><br><br>
+
+        <label for="strength">Strength:</label>
+        <input type="number" id="strength" name="strength" value="0.7" step="0.01" min="0" max="1"><br><br>
+
+        <label for="seed">Seed:</label>
+        <input type="number" id="seed" name="seed" value="-1" step="1"><br><br>
+
+        <button type="submit">Generate Image</button>
+    </form>
+</body>
+</html>
+"""
+
+@app.route('/')
+def index():
+    return render_template_string(index_html)
+
+@app.route('/generate', methods=['GET'])
+def generate_image():
+    # Retrieve query parameters
+    prompt = request.args.get("prompt", "")
+    negative_prompt = request.args.get("negative_prompt", "")
+    steps = int(request.args.get("steps", 35))
+    cfg_scale = float(request.args.get("cfgs", 7))
+    sampler = request.args.get("sampler", "DPM++ 2M Karras")
+    seed = int(request.args.get("seed", -1))
+    strength = float(request.args.get("strength", 0.7))
+    width = int(request.args.get("width", 1024))
+    height = int(request.args.get("height", 1024))
+
+    # Call the query function to generate the image
+    image, error = query(prompt, negative_prompt, steps, cfg_scale, sampler, seed, strength, width, height)
+
+    if error:
+        return jsonify({"error": error}), 500
+
+    # Save the image to a buffer
+    img_io = io.BytesIO()
+    image.save(img_io, 'PNG')
+    img_io.seek(0)
+
+    # Return the image
+    return send_file(img_io, mimetype='image/png')
 
-# Launch the Gradio app
-app.launch(show_api=False, share=False)
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)