Update app.py

app.py

@@ -8,9 +8,13 @@ from groq import Groq
 st.title("Audio/Video Transcription and Summarization")
 st.write("Upload your audio or video file, and this app will transcribe the audio and provide a summary of the transcription.")
 
-# Get the API key from user input (You may want to use Streamlit secrets management)
-GROQ_API_KEY = st.text_input("Enter your Groq API Key:")
-os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+# # Retrieve the API key from environment variables or Streamlit secrets
+# GROQ_API_KEY = os.getenv("GROQ_API_KEY") or st.secrets["GROQ_API_KEY"]
+# os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+
+# Set your Groq API key here or use environment variable
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+# client = Groq(api_key=GROQ_API_KEY)
 
 # Create a temporary directory if it does not exist
 temp_dir = "temp"
@@ -41,44 +45,96 @@ def summarize_text(text):
     """Summarizes text using Groq API."""
     client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
     response = client.chat.completions.create(
-        messages=[{"role": "user", "content": f"Summarize the following text: {text}"}],
-        model="llama3-8b-8192"
-    )
-    summary = response.choices[0].message.content
-    return summary
-
-# Complete function to process audio or video
-def process_media(media_file):
-    """Processes audio or video: extracts audio, transcribes it, and summarizes the transcription."""
-    # Save the uploaded file to a temporary path
-    temp_file_path = os.path.join(temp_dir, media_file.name)
-    with open(temp_file_path, "wb") as f:
-        f.write(media_file.getbuffer())
-
-    # Determine if the file is a video or audio based on the file extension
-    if media_file.name.endswith(('.mp4', '.mov', '.avi', '.mkv')):
-        # Step 1: Extract audio from video
-        audio_path = extract_audio(temp_file_path)
-    else:
-        audio_path = temp_file_path  # If it's already audio, use it as is
-
-    # Step 2: Transcribe audio to text
-    transcription = transcribe_audio(audio_path)
-    st.write("### Transcription:")
-    st.write(transcription)
+
+
+
+
+
+
+
+
+
+# import os
+# import ffmpeg
+# import whisper
+# import streamlit as st
+# from groq import Groq
+
+# # Set the title and description of the app
+# st.title("Audio/Video Transcription and Summarization")
+# st.write("Upload your audio or video file, and this app will transcribe the audio and provide a summary of the transcription.")
+
+# # Get the API key from user input (You may want to use Streamlit secrets management)
+# GROQ_API_KEY = st.text_input("Enter your Groq API Key:")
+# os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+
+# # Create a temporary directory if it does not exist
+# temp_dir = "temp"
+# os.makedirs(temp_dir, exist_ok=True)
+
+# # Upload the audio or video file
+# uploaded_file = st.file_uploader("Choose an audio or video file...", type=["mp4", "mov", "avi", "mkv", "wav", "mp3"])
+
+# # Function to extract audio from video
+# def extract_audio(video_path, audio_path="temp/temp_audio.wav"):
+#     """Extracts audio from video."""
+#     try:
+#         # Run ffmpeg command with stderr capture for better error handling
+#         ffmpeg.input(video_path).output(audio_path).run(overwrite_output=True, capture_stdout=True, capture_stderr=True)
+#     except ffmpeg.Error as e:
+#         st.error("FFmpeg error encountered: " + e.stderr.decode())
+#     return audio_path
+
+# # Function to transcribe audio to text using Whisper model
+# def transcribe_audio(audio_path):
+#     """Transcribes audio to text using Whisper model."""
+#     model = whisper.load_model("base")  # Load the Whisper model
+#     result = model.transcribe(audio_path)
+#     return result["text"]
+
+# # Function to summarize text using Groq API
+# def summarize_text(text):
+#     """Summarizes text using Groq API."""
+#     client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+#     response = client.chat.completions.create(
+#         messages=[{"role": "user", "content": f"Summarize the following text: {text}"}],
+#         model="llama3-8b-8192"
+#     )
+#     summary = response.choices[0].message.content
+#     return summary
+
+# # Complete function to process audio or video
+# def process_media(media_file):
+#     """Processes audio or video: extracts audio, transcribes it, and summarizes the transcription."""
+#     # Save the uploaded file to a temporary path
+#     temp_file_path = os.path.join(temp_dir, media_file.name)
+#     with open(temp_file_path, "wb") as f:
+#         f.write(media_file.getbuffer())
+
+#     # Determine if the file is a video or audio based on the file extension
+#     if media_file.name.endswith(('.mp4', '.mov', '.avi', '.mkv')):
+#         # Step 1: Extract audio from video
+#         audio_path = extract_audio(temp_file_path)
+#     else:
+#         audio_path = temp_file_path  # If it's already audio, use it as is
+
+#     # Step 2: Transcribe audio to text
+#     transcription = transcribe_audio(audio_path)
+#     st.write("### Transcription:")
+#     st.write(transcription)
     
-    # Step 3: Summarize transcription
-    summary = summarize_text(transcription)
-    st.write("### Summary:")
-    st.write(summary)
+#     # Step 3: Summarize transcription
+#     summary = summarize_text(transcription)
+#     st.write("### Summary:")
+#     st.write(summary)
     
-    # Clean up temporary files if needed
-    os.remove(temp_file_path)
-    if media_file.name.endswith(('.mp4', '.mov', '.avi', '.mkv')):
-        os.remove(audio_path)
-
-# Run the app
-if uploaded_file is not None and GROQ_API_KEY:
-    process_media(uploaded_file)
-else:
-    st.warning("Please upload a file and enter your Groq API key.")
+#     # Clean up temporary files if needed
+#     os.remove(temp_file_path)
+#     if media_file.name.endswith(('.mp4', '.mov', '.avi', '.mkv')):
+#         os.remove(audio_path)
+
+# # Run the app
+# if uploaded_file is not None and GROQ_API_KEY:
+#     process_media(uploaded_file)
+# else:
+#     st.warning("Please upload a file and enter your Groq API key.")