new file: main.py

main.py

@@ -0,0 +1,63 @@
+import gradio as gr
+import os
+from huggingface_hub import hf_hub_download
+from pathlib import Path
+from transformers import GPT2Config, GPT2LMHeadModel, GPT2Tokenizer
+
+config_class, model_class, tokenizer_class = GPT2Config, GPT2LMHeadModel, GPT2Tokenizer
+model = model_class.from_pretrained('gpt2')
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+
+def search_index(query):
+    # 示例返回，实际中应根据查询来搜索索引
+    return "example_uuid"
+
+
+# 下载视频并返回路径的函数
+def download_video(uuid):
+    dataset_name = "quchenyuan/360x_dataset"
+    dataset_path = "360_dataset/binocular/"
+    video_filename = f"{uuid}.mp4"
+
+    # 确保存储目录存在
+    storage_dir = Path("videos")
+    storage_dir.mkdir(exist_ok=True)
+
+    storage_limit = 40*1024 * 1024 * 1024
+    current_storage = sum(f.stat().st_size for f in storage_dir.glob('*') if f.is_file())
+    if current_storage + os.path.getsize(video_filename) > storage_limit:
+        oldest_file = min(storage_dir.glob('*'), key=os.path.getmtime)
+        oldest_file.unlink()
+
+    downloaded_file_path = hf_hub_download(dataset_name, dataset_path + video_filename)
+
+    return str(storage_dir / video_filename)
+
+
+# Gradio 接口函数
+def search_and_show_video(query):
+    uuid = search_index(query)
+    video_path = download_video(uuid)
+    return video_path
+
+
+
+if __name__ == "__main__":
+    with gr.Blocks() as demo:
+        with gr.Column():
+            with gr.Row():
+                search_input = gr.Textbox(label="输入查询")
+            with gr.Row():
+                with gr.Column():
+                    video_output_1 = gr.Video(label="匹配的视频")
+                with gr.Column():
+                    video_output_2 = gr.Video(label="匹配的视频")
+                with gr.Column():
+                    video_output_3 = gr.Video(label="匹配的视频")
+            with gr.Row():
+                submit_button = gr.Button(label="搜索")
+
+        submit_button.click(search_and_show_video, search_input, outputs=[video_output_1, video_output_2, video_output_3])
+
+    # 运行 Gradio 应用
+    demo.launch()