Update app.py

app.py

@@ -11,76 +11,42 @@ import json
 # Project by Nymbo
 
 API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
+API_TOKEN = os.getenv("HF_READ_TOKEN")
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
 timeout = 100
 
-
-def _translate_text(text: str | None) -> str | None:
-    """Translate user input to English when possible while failing gracefully."""
-    if not text:
-        return text
-    try:
-        translator = GoogleTranslator(source="auto", target="en")
-        translated = translator.translate(text)
-        return translated or text
-    except Exception as exc:
-        print(f"Translation failed, using original text: {exc}")
-        return text
-
-
 # Function to query the API and return the generated image
-def query(prompt, negative_prompt, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
-    if not prompt:
-        raise gr.Error("Please provide a prompt before generating an image.")
-
-    api_token = os.getenv("HF_READ_TOKEN")
-    if not api_token:
-        raise gr.Error("Missing HF_READ_TOKEN environment variable.")
+def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, width=1024, height=1024):
+    if prompt == "" or prompt is None:
+        return None
 
-    headers = {"Authorization": f"Bearer {api_token}"}
     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}')
 
-    translated_prompt = _translate_text(prompt) or prompt
-    translated_negative = _translate_text(negative_prompt) or negative_prompt
-
-    if translated_prompt != prompt:
-        print(f"\033[1mGeneration {key} translation:\033[0m {translated_prompt}")
-
-    if translated_negative and translated_negative != negative_prompt:
-        print(f"\033[1mGeneration {key} negative translation:\033[0m {translated_negative}")
-
-    final_prompt = f"{translated_prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-    print(f"\033[1mGeneration {key}:\033[0m {final_prompt}")
-
-    try:
-        seed_int = int(seed)
-    except (TypeError, ValueError):
-        seed_int = -1
-    seed_value = seed_int if seed_int >= 0 else random.randint(1, 1_000_000_000)
-
-    parameters = {
-        "negative_prompt": translated_negative or None,
-        "num_inference_steps": int(steps),
-        "guidance_scale": float(cfg_scale),
-        "scheduler": sampler,
-        "seed": int(seed_value),
-        "strength": float(strength),
-        "width": int(width),
-        "height": int(height),
-    }
-    parameters = {k: v for k, v in parameters.items() if v is not None}
-
+    # 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}')
+    
+    # Prepare the payload for the API call, including width and height
     payload = {
-        "inputs": final_prompt,
-        "parameters": parameters,
-        "steps": int(steps),
-        "cfg_scale": float(cfg_scale),
-        "seed": int(seed_value),
-        "strength": float(strength),
+        "inputs": prompt,
+        "is_negative": is_negative,
+        "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
+        }
     }
 
-    if translated_negative:
-        payload["negative_prompt"] = translated_negative
-
     # 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:
@@ -144,24 +110,7 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
             image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
         
         # 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,
-            show_api=False,
-        )
+        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, width, height], outputs=image_output)
 
 # Launch the Gradio app
-launch_kwargs = {"show_api": False}
-if os.getenv("SPACE_ID"):
-    launch_kwargs.update(
-        {
-            "share": True,
-            "server_name": "0.0.0.0",
-            "server_port": int(os.getenv("PORT", "7860")),
-        }
-    )
-else:
-    launch_kwargs["share"] = False
-
-app.launch(**launch_kwargs)
+app.launch(show_api=False, share=False)