Update app.py

app.py

@@ -1,50 +1,36 @@
-# app.py
+import os
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
-import torch
-
-# LLM එක load කරනවා (Zephyr, Mistral වගේ)
-model_id = "HuggingFaceH4/zephyr-7b-beta"  # Want to change? Try: "mistralai/Mistral-7B-Instruct"
-
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    torch_dtype=torch.float16,
-    device_map="auto"
+from pytube import YouTube
+
+def download_youtube_video(url: str):
+    try:
+        # YouTube object එක initialize කරලා ලබා ගන්නවා
+        yt = YouTube(url)
+        # ප්‍රගතිමත් (progressive) MP4 streams අතරින් උසම resolution එක select කරනවා
+        stream = yt.streams.filter(progressive=True, file_extension='mp4').get_highest_resolution()
+        
+        # Temporary downloads folder එකක් check/තනන්න
+        download_folder = "downloads"
+        if not os.path.exists(download_folder):
+            os.makedirs(download_folder)
+        
+        # Video download කිරීම සහ output path එක return කිරීම
+        output_path = stream.download(output_path=download_folder)
+        return output_path
+
+    except Exception as e:
+        # Error එකක් නම්, error message එක return කරනවා
+        return f"Error: {str(e)}"
+
+# Gradio Interface එක Define කරනවා
+interface = gr.Interface(
+    fn=download_youtube_video,
+    inputs=gr.Textbox(lines=1, placeholder="YouTube video URL එක ඇතුලත් කරන්න..."),
+    outputs="file",
+    title="YouTube Video Downloader",
+    description="YouTube video URL එකක් ඇතුලත් කරන්න සහ ඒ video එක උසම resolution එකෙන් download කරගන්න. API key අවශ්‍ය නැත."
 )
 
-pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    max_new_tokens=512,
-    do_sample=True,
-    temperature=0.7,
-    top_p=0.9
-)
-
-def chat(user_input, history):
-    history = history or []
-    prompt = ""
-
-    for user_msg, bot_msg in history:
-        prompt += f"<|user|>{user_msg}<|assistant|>{bot_msg}"
-    prompt += f"<|user|>{user_input}<|assistant|>"
-
-    result = pipe(prompt)[0]['generated_text']
-    reply = result.split("<|assistant|>")[-1].strip()
-
-    history.append((user_input, reply))
-    return reply, history
-
-with gr.Blocks(css="footer {display:none !important}") as demo:
-    gr.Markdown("<h1 style='text-align:center;'>💬 Free ChatGPT-like Assistant (No API Key)</h1>")
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox(label="ඔබේ ප්‍රශ්නය")
-    clear = gr.Button("Clear Chat")
-    state = gr.State([])
-
-    msg.submit(chat, [msg, state], [chatbot, state])
-    clear.click(lambda: ([], []), None, [chatbot, state])
-
-demo.launch()
+# App Launch කිරීම
+if __name__ == "__main__":
+    interface.launch()