App Name Change

app.py

@@ -0,0 +1,161 @@
+import openai
+from openai import Audio
+import os
+import yt_dlp as youtube_dl
+import guidance
+from moviepy.editor import AudioFileClip
+import streamlit as st
+import os
+
+output_dir = "./Chunks"
+output_file = "video_audio.mp3"
+chunk_length = 120 * 15
+transcripts = []
+folder_path = "./Chunks"
+audio_file_path = "./.DownloadedAudio"
+summary_llm = guidance.llms.OpenAI('gpt-3.5-turbo-16k-0613', caching=False)
+
+st.set_page_config(
+    page_title='YouTube Video to Summary',
+    page_icon='🐾',
+    initial_sidebar_state="auto",
+    layout="wide"
+)
+
+st.markdown("<h1 style='text-align: center; color: white;'>YouTube Video to Summary</h1>", unsafe_allow_html=True)
+
+st.sidebar.subheader("Enter Your API Key 🗝️")
+open_api_key = st.sidebar.text_input(
+    "Open API Key", 
+    value=st.session_state.get('open_api_key', ''),
+    help="Get your API key from https://openai.com/",
+    type='password'
+)
+#os.environ["OPENAI_API_KEY"] = open_api_key
+st.session_state['open_api_key'] = open_api_key
+#load_dotenv(find_dotenv())
+
+#Function to download the audio from a youtube video
+def download_audio(url, output_file):
+    ydl_opts = {
+        'format': 'bestaudio/best',
+        'outtmpl': '.DownloadedAudio/' + output_file,
+        'postprocessors': [{
+            'key': 'FFmpegExtractAudio',
+            'preferredcodec': 'mp3',
+            'preferredquality': '192'
+        }],
+        'ffmpeg_location': "C:/ffmpeg/bin"
+    }
+    with youtube_dl.YoutubeDL(ydl_opts) as ydl:
+        ydl.download([url])
+    print("Download Complete")
+
+
+
+# Function to split the audio file into smaller chunks
+def split_audio_file(audio_file_path, chunk_length, output_dir):
+    print("== Splitting audio...")
+    audio = AudioFileClip(audio_file_path)
+    duration = audio.duration
+    chunks = []
+
+    start_time = 0
+    while start_time < duration:
+        end_time = min(start_time + chunk_length, duration)
+        chunk = audio.subclip(start_time, end_time)
+        chunk_file = os.path.join(output_dir, f"chunk_{start_time}-{end_time}.mp3")
+        chunk.write_audiofile(chunk_file)
+        chunks.append(chunk_file)
+        start_time += chunk_length
+
+    return chunks
+
+def transcribe_audio(audio_file_path):
+    with open(audio_file_path, "rb") as audio_file:
+        transcript = openai.Audio.transcribe("whisper-1", audio_file)
+    print(transcript['text'])
+    return transcript['text']
+
+def transcribe_audio_dir(output_dir):
+    global transcripts
+    for filename in os.listdir(output_dir):
+        if filename.endswith(".mp3"):
+            file_path = os.path.join(output_dir, filename)
+            transcript = transcribe_audio(file_path)
+            summary = generate_summary(transcript)
+            transcripts.append(summary)
+            os.remove(file_path)
+    print("Chunk Transcription and Summarization Complete")
+    print(transcripts)
+
+    #Summarize the transcripts using the LLM and write to a file
+
+    output_path = os.path.join(os.getcwd(), "Transcripts", "summary.txt")
+    with open(output_path, "w", encoding="utf-8") as file:
+        for transcript in transcripts:
+            file.write(transcript + "\n")
+
+    return transcripts
+
+def generate_summary(text):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo-16k-0613",
+        messages=[
+        {"role": "system", "content": "You are a world's best Wild Kratts episode summarizer. Condense the transcript text, capturing essential points and core plot points. Include relevant examples, omit excess details, and ensure the summary's length matches the original's complexity."},
+        {"role": "user", "content": f"Please summarize the following text:\n{text}\nSummary:"},
+    ],
+        max_tokens=11000,
+        stop=None,
+        temperature=0.2,
+    )
+    summary = response['choices'][0]['message']['content'].strip()
+    return summary
+
+#download_audio(url, output_file)
+
+import gradio as gr
+
+
+def main():
+    source = st.radio("Select audio source", ["YouTube Video", "Audio File"])
+    if source == "YouTube Video":
+        url = st.text_input(label="Video URL")
+        audio_file = None
+    else:  # Audio File
+        audio_file = st.file_uploader("Upload audio file", type=["mp3", "wav"])
+        url = None
+
+    chunk_length = st.number_input(label="Chunk Length (seconds)", value=900, step=1)
+
+    return url, "default_output", chunk_length, audio_file
+
+def download_and_split_video(url, output_file, chunk_length, transcripts):
+    download_audio(url, output_file)
+    audio_file_path = '.DownloadedAudio/' + f"{output_file}.mp3"
+    split_audio_file(audio_file_path, chunk_length, output_dir)
+    os.remove(audio_file_path)
+    return transcribe_audio_dir(output_dir)
+    #return transcribe_audio_dir(transcripts)
+
+
+if __name__ == "__main__":
+    url, output_file, chunk_length, audio_file = main()  # get the values here
+
+    if open_api_key:  # Check if API key is provided
+        if st.button("Generate Summary"):
+            with st.spinner("Summary Generating..."):
+                if url:  # If YouTube URL is provided
+                    transcripts = download_and_split_video(url, output_file, chunk_length, transcripts)
+                elif audio_file:  # If an audio file is uploaded
+                    audio_file_path = os.path.join('.DownloadedAudio/', output_file)
+                    with open(audio_file_path, "wb") as f:
+                        f.write(audio_file.getvalue())  # Write the content of the uploaded file to a new file
+                    split_audio_file(audio_file_path, chunk_length, output_dir)
+                    transcripts = transcribe_audio_dir(output_dir)
+                    os.remove(audio_file_path)  # Delete saved audio file
+                st.subheader("Summary")
+                for transcript in transcripts:  # Loop through the transcripts list
+                    st.write(transcript)
+    else:  # If API key is not provided
+        st.warning("Please Enter OpenAI API Key")  # Display warning message