completed

.gitattributes

@@ -32,4 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,8 @@
+/downloads
+
+# Environment
+/.env
+/.venv
+
+# git
+/.git

aa.py

@@ -0,0 +1,29 @@
+from openai import OpenAI
+client = OpenAI(
+    api_key="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"
+)
+
+response = client.chat.completions.create(
+  model="gpt-4o",
+  messages=[
+    {
+      "role": "system",
+      "content": [
+        {
+          "type": "text",
+          "text": "Create detailed and formatted markdown notes for the following content:"
+        }
+      ]
+    }
+  ],
+  response_format={
+    "type": "text"
+  },
+  temperature=1,
+  max_tokens=16383,
+  top_p=1,
+  frequency_penalty=0,
+  presence_penalty=0
+)
+
+print(response)

app.py

@@ -1,4 +1,110 @@
 import streamlit as st
+import yt_dlp
+import whisper
+import os
+from openai import OpenAI
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# App title
+st.title("Youtube Video Summarizer/Notes Maker by Anurag")
+
+# Input fields for YouTube video URL and OpenAI API key
+video_url = st.text_input("Enter a valid YouTube video URL:")
+api_key = st.text_input("Enter your OpenAI API Key:", type="password")
+
+# Option to choose between formatted markdown notes or summarization
+option = st.radio("Select an option:", ["Create formatted markdown notes", "Summarize video with a given length"])
+
+# Input field for summary length if "Summarize" is selected
+summary_length = None
+if option == "Summarize video with a given length":
+    summary_length = st.slider("Select summary length (words):", min_value=50, max_value=500, step=50)
+
+# Function to download audio using yt-dlp
+def download_audio_with_ytdlp(video_url, output_path="downloads"):
+    os.makedirs(output_path, exist_ok=True)
+    ydl_opts = {
+        'format': 'bestaudio/best',
+        'outtmpl': f'{output_path}/%(id)s.%(ext)s',
+        'postprocessors': [{
+            'key': 'FFmpegExtractAudio',
+            'preferredcodec': 'mp3',
+            'preferredquality': '192',
+        }],
+    }
+    with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+        info_dict = ydl.extract_info(video_url, download=True)
+        audio_file = f"{output_path}/{info_dict['id']}.mp3"
+    return audio_file
+
+# Whisper transcription function
+def transcribe_audio(audio_file):
+    model = whisper.load_model("base")
+    result = model.transcribe(audio_file)
+    return result["text"]
+
+# Button to start processing
+if st.button("Generate"):
+    if not video_url or not api_key:
+        st.error("Please provide both a valid YouTube URL and OpenAI API Key.")
+    else:
+        try:
+            # Download audio using yt-dlp
+            st.info("Downloading audio...")
+            audio_file = download_audio_with_ytdlp(video_url)
+            st.success(f"Audio downloaded successfully! File: {audio_file}")
+
+            # Transcribe audio using Whisper
+            st.info("Transcribing audio...")
+            transcript = transcribe_audio(audio_file)
+            st.success("Audio transcribed successfully!")
+
+            # OpenAI API configuration
+            client = OpenAI(api_key=api_key)
+
+            # Prompt based on user selection
+            if option == "Create formatted markdown notes":
+                system_message = "Generate detailed and well-structured markdown notes from the following transcript."
+            else:
+                system_message = f"Summarize the following transcript into approximately {summary_length} words."
+
+            # Call OpenAI chat completion API
+            st.info("Processing with OpenAI...")
+            try:
+                response = client.chat.completions.create(
+                    model="gpt-4o",
+                    messages=[
+                        {
+                            "role": "system",
+                            "content": [
+                                {
+                                    "type": "text",
+                                    "text": system_message
+                                }
+                            ]
+                        },
+                        {
+                            "role": "user",
+                            "content": transcript
+                        }
+                    ],
+                    response_format={
+                        "type": "text"
+                    },
+                    temperature=1,
+                    max_tokens=16383,
+                    top_p=1,
+                    frequency_penalty=0,
+                    presence_penalty=0
+                )
+
+                # Extract the generated content
+                output = response['choices'][0]['message']['content']
+                st.success("Output generated successfully!")
+                st.text_area("Generated Output:", output, height=300)
+
+            except Exception as e:
+                st.error(f"Error with OpenAI API: {e}")
+
+
+        except Exception as e:
+            st.error(f"An error occurred: {e}")