Update app.py

app.py

@@ -3,33 +3,38 @@ import requests
 import io
 import random
 import os
-import time
 from PIL import Image
 from deep_translator import GoogleTranslator
-import json
 
-# Project by Nymbo
 API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
-#API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
-API_TOKEN = os.getenv("HF_READ_TOKEN")
-headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
-def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7):
+def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None):
+    # Check if the request is an API call by checking for the presence of the huggingface_api_key
+    is_api_call = huggingface_api_key is not None
+
+    if is_api_call:
+        # Validate the API key if it's an API call
+        if huggingface_api_key == "":
+            raise gr.Error("API key is required for API calls.")
+        
+        headers = {"Authorization": f"Bearer {huggingface_api_key}"}
+    else:
+        # Use the environment variable for the API key in GUI mode
+        API_TOKEN = os.getenv("HF_READ_TOKEN")
+        headers = {"Authorization": f"Bearer {API_TOKEN}"}
+    
     if prompt == "" or prompt is None:
         return None
 
     key = random.randint(0, 999)
-    
-    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
-    headers = {"Authorization": f"Bearer {API_TOKEN}"}
-    
+
     prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
     print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
 
     prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
     print(f'\033[1mGeneration {key}:\033[0m {prompt}')
-    
+
     # If seed is -1, generate a random seed and use it
     if seed == -1:
         seed = random.randint(1, 1000000000)
@@ -55,11 +60,15 @@ def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Ka
         image_bytes = response.content
         image = Image.open(io.BytesIO(image_bytes))
         print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
-        # Return both the image and the seed used
-        return image, seed
+
+        # Save the image to a file and return the file path and seed
+        output_path = f"./output_{key}.png"
+        image.save(output_path)
+        
+        return output_path, seed
     except Exception as e:
         print(f"Error when trying to open the image: {e}")
-        return None
+        return None, None
 
 css = """
 #app-container {
@@ -84,12 +93,16 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
                         method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
                         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)
+                        huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key")
 
         with gr.Row():
             text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
         with gr.Row():
-            image_output,_ = gr.Image(type="pil", label="Image Output", elem_id="gallery")
+            # Define two outputs: one for the image file path and one for the seed
+            image_output = gr.Textbox(label="Image File Path", elem_id="gallery")
+            seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output")
         
-        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength], outputs=image_output)
+        # Adjust the click function to include the API key as an input
+        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key], outputs=[image_output, seed_output])
 
 app.launch(show_api=True, share=False)