Create app.py

app.py

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+import gradio as gr
+from gradio_client import Client
+import os
+import shutil
+import tempfile
+import zipfile
+
+def generate_frame(client, prompt, frame_number, total_frames):
+    adjusted_prompt = f"{prompt} - frame {frame_number} of {total_frames}"
+    
+    result = client.predict(
+        prompt=adjusted_prompt,
+        is_negative="(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",
+        steps=35,
+        cfg_scale=7,
+        sampler="DPM++ 2M Karras",
+        seed=-1,
+        strength=0.7,
+        huggingface_api_key="",
+        use_dev=True,
+        enhance_prompt_style="Cartoon",
+        enhance_prompt_option=True,
+        nemo_enhance_prompt_style="Cartoon",
+        use_mistral_nemo=True,
+        api_name="/query"
+    )
+    return result
+
+def generate_video_frames(prompt, num_frames, progress=gr.Progress()):
+    client = Client("K00B404/FLUX.1-Dev-Serverless-darn-enhanced-prompt")
+    
+    with tempfile.TemporaryDirectory() as temp_dir:
+        frame_paths = []
+        for i in progress.tqdm(range(num_frames)):
+            tmp_image_path, used_seed, enhanced_prompt = generate_frame(client, prompt, i+1, num_frames)
+            
+            destination_path = os.path.join(temp_dir, f"frame_{i:03d}.png")
+            shutil.copy(tmp_image_path, destination_path)
+            frame_paths.append(destination_path)
+            
+            yield f"Generated frame {i+1}/{num_frames}\nSeed: {used_seed}\nEnhanced prompt: {enhanced_prompt}"
+        
+        zip_path = os.path.join(temp_dir, "video_frames.zip")
+        with zipfile.ZipFile(zip_path, 'w') as zipf:
+            for file in frame_paths:
+                zipf.write(file, os.path.basename(file))
+        
+        yield f"Generated {num_frames} frames. Downloading ZIP file..."
+        return zip_path
+
+def launch_interface(prompt, num_frames):
+    output = generate_video_frames(prompt, num_frames)
+    return output
+
+# Define the Gradio interface
+iface = gr.Interface(
+    fn=launch_interface,
+    inputs=[
+        gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
+        gr.Slider(minimum=1, maximum=50, step=1, label="Number of Frames", value=10)
+    ],
+    outputs=[
+        gr.Textbox(label="Progress", lines=5),
+        gr.File(label="Download Frames")
+    ],
+    title="Video Frame Generator",
+    description="Generate a series of video frames using the FLUX.1 model.",
+    allow_flagging="never"
+)
+
+# Launch the interface
+iface.launch()