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app.py

@@ -0,0 +1,48 @@
+import streamlit as st
+from transcription import deepgram
+from summary import summarize
+
+
+def main():
+    session_state = st.session_state
+    
+    if 'transcription' not in session_state:
+        session_state.transcription = ""
+    if "summary" not in session_state:
+        session_state.summary=""
+
+
+
+    st.title("Meeting Insights")
+
+
+    audio_file = st.sidebar.file_uploader("Upload your audio file:")
+
+    language = st.sidebar.selectbox(
+        "Select Language",
+        ("English", "French", "Spanish"))
+    if audio_file:
+        if language:
+            st.sidebar.audio(audio_file)
+            if st.sidebar.button("Generate Transcription"):
+                if language=="English":
+                    session_state.transcription=deepgram(audio_file , language="en")
+                elif language=="French":
+                    session_state.transcription=deepgram(audio_file,language="fr")
+                elif language=="Spanish":
+                        session_state.transcription=deepgram(audio_file , language="es")
+
+    
+    
+
+    transcription=st.text_area("Transcription",value=session_state.transcription, height=400)
+    if transcription:
+        st.download_button('Download Transcription', session_state.transcription , file_name="Transcription.txt") 
+        if st.sidebar.toggle("Generate Summary"):
+            session_state.summary=summarize(session_state.transcription)
+            st.text_area("Summary" , value=session_state.summary , height=400)
+
+if __name__ == "__main__":
+    main()
+
+

summary.py

@@ -0,0 +1,19 @@
+from langchain_groq import ChatGroq
+from langchain.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from dotenv import load_dotenv
+
+load_dotenv()
+
+model = ChatGroq(temperature=0, model_name="mixtral-8x7b-32768") #mixtral-8x7b-32768
+
+
+def summarize(transcription):
+    template="""You are provided  with transcription of a meeting between different people. Your task is to summarize this transcription
+    Transcription: {transcription}"""
+
+    prompt = ChatPromptTemplate.from_template(template)
+
+    chain = prompt | model | StrOutputParser()
+    summary=chain.invoke({"transcription":transcription})
+    return summary

transcription.py

@@ -0,0 +1,31 @@
+DEEPGRAM_API_KEY = "133b94c2e717ad8749463de64418ba5fb78efcb3"
+
+
+from deepgram import (
+    DeepgramClient,
+    PrerecordedOptions,
+    FileSource
+)
+import httpx
+def deepgram(buffer_data,language):
+    # STEP 1 Create a Deepgram client using the API key
+    deepgram = DeepgramClient(DEEPGRAM_API_KEY)
+
+    payload: FileSource = {
+        "buffer": buffer_data,
+    }
+
+    #STEP 2: Configure Deepgram options for audio analysis
+    options = PrerecordedOptions(
+        model="nova-2",
+        smart_format=True,
+        language=language,
+        diarize=True,
+
+        
+    )
+    myTimeout = httpx.Timeout(300, connect=10.0)
+    # STEP 3: Call the transcribe_file method with the text payload and options
+    response = deepgram.listen.prerecorded.v("1").transcribe_file(payload, options,timeout=myTimeout)
+    text=response['results']['channels'][0]['alternatives'][0]['paragraphs']['transcript']
+    return text