Create requirements.txt

requirements.txt

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+from fastapi import FastAPI, UploadFile
+import ffmpeg
+from transformers import pipeline
+
+app = FastAPI()
+
+# Load Hugging Face model (example: text-to-video)
+model = pipeline("text-to-video-generation", model="damo-vilab/modelscope-text-to-video-synthesis")
+
+@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}