Minutes of Meetings

app.py

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+import os
+import streamlit as st
+from groq import Groq
+from dotenv import load_dotenv
+from datetime import datetime  # Import datetime module
+
+# Load environment variables
+load_dotenv()
+
+# Ensure 'data' folder exists (use lowercase 'data' for consistency)
+if not os.path.exists("data"):
+    os.makedirs("data")
+
+# Function to get speech transcription from audio
+def get_speech_transcription(audio_file):
+    client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+    
+    # Read the audio file content
+    transcription = client.audio.transcriptions.create(
+        file=(audio_file.name, audio_file.read()),
+        model="whisper-large-v3",  # Use the appropriate model
+        response_format="verbose_json",
+    )
+
+    return transcription.text
+
+# Function to get Groq completions for the transcript
+def get_groq_completions(user_content):
+    client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+    
+    prompt = f"""
+    You will be provided with a transcript of a meeting. 
+    Summarize the key points from the transcript in a structured format.
+    If any new topics are discussed, make them as a title and corresponding discussion will be description using number points also add time how much time they discuss on those topics.
+
+    \n{user_content}
+    """
+    
+    completion = client.chat.completions.create(
+        model="llama-3.2-90b-text-preview",
+        messages=[
+            {
+                "role": "system",
+                "content": "You are a helpful AI assistant."
+            },
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ],
+        temperature=0.8,
+        max_tokens=6000,
+        top_p=1,
+        stream=True,
+        stop=None,
+    )
+
+    result = ""
+    for chunk in completion:
+        result += chunk.choices[0].delta.content or ""
+
+    return result
+
+# Function to save the user content in a file
+def save_user_content(email, content):
+    # Get the current date and time
+    current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+    
+    # Create filename using email and current timestamp
+    filename = f"{email}_{current_time}.txt"
+    
+    file_path = os.path.join("data", filename)  # Ensure 'data' directory is used
+    with open(file_path, "w") as f:
+        f.write(content)
+    
+    return file_path  # Return the file path for confirmation
+
+# Streamlit interface
+def main():
+    # Add project title
+    st.title("Minutes of Meetings")  # Add title here
+    st.sidebar.title("Upload Options")
+    
+    # User email input
+    email = st.sidebar.text_input("Please enter your email address:")
+    
+    # Sidebar options
+    upload_option = st.sidebar.selectbox("Choose how to provide the content:", 
+                                          ("Upload Audio File", "Upload Text File", "Paste Text"))
+    
+    user_content = ""
+    
+    # Conditional logic based on sidebar selection
+    if upload_option == "Upload Audio File":
+        audio_file = st.sidebar.file_uploader("Upload an audio file", type=["mp3", "wav", "m4a"])
+        
+        if audio_file and st.sidebar.button("Generate MoM from Audio"):
+            if not email:
+                st.warning("Please enter your email address.")
+                return
+            st.info("Transcribing audio... Please wait.")
+            user_content = get_speech_transcription(audio_file)
+            st.success("Audio transcribed successfully!")
+            
+    elif upload_option == "Upload Text File":
+        text_file = st.sidebar.file_uploader("Upload a text file", type=["txt"])
+        
+        if text_file and st.sidebar.button("Generate MoM from Text File"):
+            if not email:
+                st.warning("Please enter your email address.")
+                return
+            user_content = text_file.read().decode("utf-8")
+            st.success("Text file uploaded successfully!")
+            
+    elif upload_option == "Paste Text":
+        user_content = st.sidebar.text_area("Paste your text here:")
+        
+        if st.sidebar.button("Generate MoM from Pasted Text"):
+            if not email:
+                st.warning("Please enter your email address.")
+                return
+            if not user_content:
+                st.warning("Please paste some text before generating the MoM.")
+                return
+    
+    if user_content:
+        st.info("Generating MoM... Please wait.")
+        
+        # Save user content and get file path
+        file_path = save_user_content(email, user_content)
+        
+        # Generate MoM
+        generated_mom = get_groq_completions(user_content)
+        
+        # Display the generated MoM
+        st.markdown("### Generated MoM:")
+        st.text_area("", value=generated_mom, height=500)
+
+if __name__ == "__main__":
+    main()