Create app.py

app.py

@@ -1,51 +1,22 @@
-import gradio as gr
-from transformers import pipeline
+# Use a base image with GPU support
+FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
 
-# Load model
-model = pipeline("text-to-video-generation", model="damo-vilab/modelscope-text-to-video-synthesis")
+# Install Python and system dependencies
+RUN apt-get update && apt-get install -y \
+    python3 python3-pip ffmpeg git curl
 
-def generate_video(prompt):
-    result = model(prompt)
-    output_file = "generated_video.mp4"
-    with open(output_file, "wb") as f:
-        f.write(result["video"])
-    return output_file
+# Install Python dependencies
+COPY requirements.txt /app/requirements.txt
+RUN pip3 install --no-cache-dir -r /app/requirements.txt
 
-# Create Gradio interface
-iface = gr.Interface(
-    fn=generate_video,
-    inputs="text",
-    outputs="file",
-    title="AI Video Creator",
-    description="Generate videos using AI from text input."
-)
-iface.launch()
-from fastapi import FastAPI, UploadFile
-import ffmpeg
-from transformers import pipeline
+# Copy application code
+COPY . /app
 
-app = FastAPI()
+# Set the working directory
+WORKDIR /app
 
-# Load Hugging Face model (example: text-to-video)
-model = pipeline("text-to-video-generation", model="damo-vilab/modelscope-text-to-video-synthesis")
+# Expose app port
+EXPOSE 8000
 
-@app.post("/generate_video/")
-async def generate_video(prompt: str):
-    # Generate video from text
-    result = model(prompt)
-    output_file = "generated_video.mp4"
-    with open(output_file, "wb") as f:
-        f.write(result["video"])
-
-    return {"message": "Video generated successfully!", "file_path": output_file}
-
-@app.post("/upload_video/")
-async def upload_video(file: UploadFile):
-    input_file = f"uploaded_{file.filename}"
-    with open(input_file, "wb") as f:
-        f.write(file.file.read())
-    
-    # Example: Trim video using FFmpeg
-    trimmed_file = "trimmed_video.mp4"
-    ffmpeg.input(input_file).output(trimmed_file, ss=0, t=10).run()
-    return {"message": "Video uploaded and trimmed!", "file_path": trimmed_file}
+# Start the application
+CMD ["python3", "app.py"]