Upload 3 files

app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+from utils import *
+
+
+# Define the Streamlit app
+def main():
+    st.title("Customer Care Call Summarization")
+
+    # Upload multiple files
+    uploaded_files = st.file_uploader("Upload recorded .mp3 files", type=["mp3"], accept_multiple_files=True)
+
+    if uploaded_files:
+        st.write("Uploaded Files:")
+
+        # Display uploaded files and buttons in a tabular form
+        for uploaded_file in uploaded_files:
+            file_name = uploaded_file.name
+            
+
+            col1, col2, col3 = st.columns([0.1, 1, 2])
+            with col1:
+                st.write("-")
+            with col2:
+                st.write(file_name)
+            with col3:
+                send_button = st.button(f"Send Email for {file_name}")
+
+                if send_button:
+                    email_summary(file_name)
+                    st.success(f"Send email for: {file_name}")
+
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()

utils.py

@@ -0,0 +1,43 @@
+import whisper
+from langchain.llms import OpenAI
+from langchain.agents import initialize_agent
+from langchain.agents.agent_toolkits import ZapierToolkit
+from langchain.utilities.zapier import ZapierNLAWrapper
+import os
+
+# get from https://platform.openai.com/
+os.environ["OPENAI_API_KEY"] = "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"
+
+# get from https://nla.zapier.com/docs/authentication/ & https://actions.zapier.com/credentials/ after logging in):
+os.environ["ZAPIER_NLA_API_KEY"] = "sk-ak-iPp3rBjaP9PpjRDpDhIXtsXsCj"
+
+
+def email_summary(file):
+
+
+    # large language model
+    llm = OpenAI(temperature=0)
+
+    # Initializing zapier
+    zapier = ZapierNLAWrapper()
+    toolkit = ZapierToolkit.from_zapier_nla_wrapper(zapier)
+
+    # The agent used here is a "zero-shot-react-description" agent. 
+    # Zero-shot means the agent functions on the current action only — it has no memory. 
+    # It uses the ReAct framework to decide which tool to use, based solely on the tool's description.
+    agent = initialize_agent(toolkit.get_tools(), llm, agent="zero-shot-react-description", verbose=True)
+
+
+    # specify a model, here its BASE
+    model = whisper.load_model("base")
+
+   
+
+    # transcribe audio file
+    result = model.transcribe(file)
+    print(result["text"])
+
+    # Send email using zapier
+    agent.run("Send an Email to sharathraju489@gmail.com via gmail summarizing the following text provided below : "+result["text"])
+
+