Update app.py

app.py

@@ -1,116 +0,0 @@
-import speech_recognition as sr
-from pydub import AudioSegment
-import gradio as gr
-from os import path
-import requests
-import openai
-from openai import OpenAI
-
-prompt = "Type and press Enter"
-
-
-def record_text(audio_file,api_key):
-    client = OpenAI(api_key = api_key)
-    input_file = audio_file
-    output_file = "converted_sound.mp3"
-    sound = AudioSegment.from_wav(input_file) 
-    sound.export(output_file, format="mp3")
-    audio_file = "converted_sound.mp3"
-    audio_file = open(audio_file, "rb") 
-    transcript = client.audio.transcriptions.create(
-        model="whisper-1", 
-        file=audio_file,
-        response_format="text"
-        )
-    return transcript
-    # return(str(path.getsize(audio_file)/1000000)+'mb')
-    # sound = audio_file
-    # sound_type = sound.split(".")
-    # if sound_type[-1] == 'mp3':
-    #     input_file = sound
-    #     output_file = "con_sound.wav"
-        
-    #     # convert mp3 file to wav file 
-    #     sound = AudioSegment.from_mp3(input_file) 
-    #     sound.export(output_file, format="wav")
-    #     sound = "con_sound.wav"
-    
-    # MyText = ""
-    # with sr.AudioFile(sound) as source:
-    #     r.adjust_for_ambient_noise(source)
-    #     print("Converting audio file to text..")
-    #     audio2 = r.record(source, duration=None)  # Use record instead of listen
-        
-    #     MyText = r.recognize_google(audio2, language="en-US", key=None, show_all=False)
-    #     MyText = MyText.lower()
-    # return (MyText)
-
-
-def api_calling(audio_file, prompt, api_key):
-    audio_text = record_text(audio_file,api_key)
-    if len(prompt) == 0:
-        prompt = "Apply proper punctuations, upper case and lower case to the provided text."
-        return audio_text
-    else:
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}"
-        }
-        payload = {
-            "model": "gpt-3.5-turbo",
-            "messages": [
-                {
-                    "role": "user",
-                    "content": [
-                        {
-                            "type": "text",
-                            "text": prompt
-                        },
-                        {
-                            "type": "text",
-                            "text": audio_text
-                        }
-                    ]
-                }
-            ],
-            "max_tokens": 1000
-        }
-        response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
-        audio_text_res = response.json()
-        return audio_text_res["choices"][0]["message"]["content"]
-
-
-
-def message_and_history(audio_text,input, history, api_key):
-    video = VideoFileClip(mp4_file)
-    audio = video.audio
-    audio.write_audiofile(mp3_file)
-    history = history or []
-    output_text = api_calling(mp3_file,input,api_key)
-    
-    if len(input) == 0:
-        input = "Speech from the video."
-        history.append((input, output_text))
-    else:
-        history.append((input, output_text))
-    
-    return history, history
-
-
-block = gr.Blocks(theme=gr.themes.Soft(primary_hue="slate"))
-with block:
-    gr.Markdown("""<h1><center>Stock-Analysis</center></h1> """)
-    with gr.Row():
-        with gr.Column(scale=0.5):
-            vid_input = gr.Video(type="filepath", label="Upload .mp4 file", sources="upload")
-            api_input = gr.Textbox(label="Enter Api-key")
-            upload_button = gr.Button(value="Upload & Start Chat", interactive=True, variant="primary")
-        with gr.Column():
-            chatbot = gr.Chatbot(label="Ask questions about the Video")
-            message = gr.Textbox(label="User", placeholder=prompt)
-            state = gr.State()
-            
-    upload_button.click(message_and_history, inputs=[vid_input,message, state, api_input], outputs=[chatbot, state])
-    message.submit(message_and_history, inputs=[vid_input,message, state, api_input], outputs=[chatbot, state])
-    message.submit(lambda: None, None, message, queue=False)
-block.launch()