Update app.py

app.py

@@ -1,4 +1,3 @@
-import os
 import tempfile
 from pathlib import Path
 
@@ -13,7 +12,6 @@ from src.data.utils_asr import PromptASR
 from src.models.llama_inference import inference
 from src.test.vidchapters import get_chapters
 from tools.download.models import download_base_model, download_model
-from tools.download.video import download_url
 
 # Set up proxies
 # from urllib.request import getproxies
@@ -155,80 +153,29 @@ def load_peft(model_name: str = "asr-10k"):
     return True
 
 
-def download_from_url(url, output_path):
-    """Download a video from a URL using yt-dlp and save it to output_path."""
-    try:
-        # Import yt-dlp Python package
-        try:
-            import yt_dlp
-        except ImportError:
-            print("yt-dlp Python package is not installed")
-            return (
-                False,
-                "yt-dlp Python package is not installed. Please install it with 'pip install yt-dlp'.",
-            )
-
-        # Configure yt-dlp options
-        ydl_opts = {
-            "format": "best",
-            "outtmpl": str(output_path),
-            "noplaylist": True,
-            "quiet": True,
-        }
-
-        # Download the video
-        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-            ydl.download([url])
-
-        # Check if the download was successful
-        if not os.path.exists(output_path):
-            return (
-                False,
-                "Download completed but video file not found. Please check the URL.",
-            )
-
-        return True, None
-    except Exception as e:
-        error_msg = f"Error downloading video: {str(e)}"
-        print(error_msg)
-        return False, error_msg
-
-
 @spaces.GPU
-def process_video(
-    video_file, video_url="", model_name: str = "asr-10k", do_sample: bool = False
-):
-    """Process a video file or URL and generate chapters."""
+def process_video(video_file, model_name: str = "asr-10k", do_sample: bool = False):
+    """Process a video file and generate chapters."""
     progress = gr.Progress()
     progress(0, desc="Starting...")
 
     # Check if we have a valid input
-    if video_file is None and not video_url:
-        return "Please upload a video file or provide a URL."
+    if video_file is None:
+        return "Please upload a video file."
 
     # Load the PEFT model
     progress(0.1, desc=f"Loading LoRA parameters from {model_name}...")
     if not load_peft(model_name):
         return "Failed to load model. Please try again."
 
-    # Create a temporary directory to save the uploaded or downloaded video
+    # Create a temporary directory to save the uploaded video
     with tempfile.TemporaryDirectory() as temp_dir:
         temp_video_path = Path(temp_dir) / "temp_video.mp4"
 
-        if video_file is not None:
-            # Using uploaded file
-            progress(0.2, desc="Processing uploaded video...")
-            with open(temp_video_path, "wb") as f:
-                f.write(video_file)
-        else:
-            # Using URL
-            progress(0.2, desc=f"Downloading video from URL: {video_url}...")
-            # success, error_msg = download_from_url(video_url, temp_video_path)
-            sucess, error_msg, video_paths = download_url(video_url, destinationDirectory=temp_dir)
-            if not success:
-                return f"Failed to download video: {error_msg}"
-            assert len(video_paths) == 1, print(f"video_paths has len={len(video_paths)}")
-            temp_video_path = video_paths[0]
+        # Using uploaded file
+        progress(0.2, desc="Processing uploaded video...")
+        with open(temp_video_path, "wb") as f:
+            f.write(video_file)
 
         # Process the video
         progress(0.3, desc="Extracting ASR transcript...")
@@ -299,10 +246,8 @@ note_html = """
 # Clone the repository
 git clone https://github.com/lucas-ventura/chapter-llama.git
 cd chapter-llama
-
 # Install demo dependencies
 python -m pip install -e ".[demo]"
-
 # Launch the demo
 python demo.py</pre>
 <p style="font-size: 1.1em; color: #555; margin-bottom: 10px;">If you find any issues, please report them on our <a href="https://github.com/lucas-ventura/chapter-llama/issues" style="color: #8F68C3; text-decoration: none;">GitHub repository</a>.</p>
@@ -340,19 +285,6 @@ with gr.Blocks(title="Chapter-Llama", head=head) as demo:
                 file_types=["video", "audio"],
                 type="binary",
             )
-            #with gr.Tab("Upload File"):
-            #    video_input = gr.File(
-            #        label="Upload Video or Audio File",
-            #        file_types=["video", "audio"],
-            #        type="binary",
-            #    )
-
-            #with gr.Tab("Video URL"):
-            #    video_url_input = gr.Textbox(
-            #        label="YouTube or Video URL",
-            #        placeholder="https://youtube.com/watch?v=...",
-            #    )
-            video_url_input = ""
 
             model_dropdown = gr.Dropdown(
                 choices=["asr-10k", "asr-1k"],
@@ -367,19 +299,18 @@ with gr.Blocks(title="Chapter-Llama", head=head) as demo:
         with gr.Column():
             status_area = gr.Markdown("**Status:** Ready to process video")
             output_text = gr.Textbox(
-                label="Generated Chapters", lines=12, interactive=False
+                label="Generated Chapters", lines=10, interactive=False
             )
 
-
-    def update_status_and_process(video_file, video_url, model_name, do_sample):
-        if video_file is None and not video_url:
+    def update_status_and_process(video_file, model_name, do_sample):
+        if video_file is None:
             return (
-                "**Status:** No video uploaded or URL provided",
-                "Please upload a video file or provide a URL.",
+                "**Status:** No video uploaded",
+                "Please upload a video file.",
             )
         else:
             return "**Status:** Processing video...", process_video(
-                video_file, video_url, model_name, do_sample
+                video_file, model_name, do_sample
             )
 
     # Load the base model at startup
@@ -397,4 +328,4 @@ with gr.Blocks(title="Chapter-Llama", head=head) as demo:
 
 if __name__ == "__main__":
     # Launch the Gradio app
-    demo.launch()
+    demo.launch()