Create app.py

app.py

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+import gradio as gr
+import subprocess
+import os
+import ffmpeg
+# import pymedia.audio.acodec as acodec
+# import pymedia.muxer as muxer
+import random
+import string
+import spaces
+from openai import OpenAI
+import os
+import re
+from math import floor
+
+
+ACCESS_TOKEN = os.getenv("HF_TOKEN")
+
+client = OpenAI(
+    base_url="https://api-inference.huggingface.co/v1/",
+    api_key=ACCESS_TOKEN,
+)
+
+
+def random_name_generator():
+    length = random.randint(10, 15)  # Random length between 10 and 15
+    characters = string.ascii_letters + string.digits  # All alphanumeric characters
+    random_name = ''.join(random.choice(characters) for _ in range(length))
+    return random_name
+
+# Example usage:
+# print(random_name_generator())
+
+@spaces.GPU()
+def outputProducer(inputVideo):
+    print(inputVideo)
+    input_file = ffmpeg.input(inputVideo)
+    name_random = random_name_generator()
+    input_file.output('audio'+name_random+'.mp3', acodec='mp3').run()
+    command2 = ["whisper",'./audio'+name_random+'.mp3']
+    try:
+        retVal = subprocess.check_output(command2)
+    except:
+        retVal = subprocess.check_output("ls")
+    subprocess.run(['rm', 'audio'+name_random+'.mp3'], check=True) 
+    return retVal
+
+def subtitle_it(subtitle_str):
+    # Regular expression to extract time and text
+    pattern = re.compile(
+      r'\[(\d{2}):(\d{2})\.(\d{3})\s*-->\s*(\d{2}):(\d{2})\.(\d{3})\]\s*(.*)'
+    )
+    # List to hold subtitle entries as tuples: (start_time, end_time, text)
+    subtitles = []
+    subtitle_str = subtitle_str.decode('utf-8')  # or replace 'utf-8' with the appropriate encoding if needed
+    max_second = 0  # To determine the size of the list L
+    
+    sub_string = ""
+    # Parse each line
+    for line in subtitle_str.strip().split('\n'):
+        match = pattern.match(line)
+        if match:
+          (
+              start_min, start_sec, start_ms,
+              end_min, end_sec, end_ms,
+              text
+          ) = match.groups()
+          
+          # Convert start and end times to total seconds          
+          sub_string+=text
+          
+          # Update maximum second
+        else:
+          print(f"Line didn't match pattern: {line}")
+    return sub_string
+  # Initialize list L with empty strings
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+    
+    for message in  client.chat.completions.create(
+        model="Qwen/Qwen2.5-72B-Instruct",
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+        messages=messages,
+    ):
+        token = message.choices[0].delta.content
+        
+        response += token
+        yield response
+        
+chatbot = gr.Chatbot(height=600)
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Video(value=None, label="System message"),
+        gr.Slider(minimum=1, maximum=4098, value=1024, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-P",
+        ),
+        
+    ],
+    fill_height=True,
+    chatbot=chatbot
+)
+if __name__ == "__main__":
+    demo.launch()
+
+