Update app.py

app.py

@@ -1,63 +1,39 @@
+import keyfile 
+import streamlit as st
+from langchain_openai import OpenAI
+import getpass
 import os
 import google.generativeai as genai
-import streamlit as st
+import pandas as pd
+
 
-# Create a function for getting a response from Gemini
+genai.configure(api_key=keyfile.GEMINI_API_KEY)
 
+# Creating a function for getting the responses from OpenAI
 def get_response(question):
-    try:
-        # Ensure the API key is correctly retrieved
-        api_key = os.getenv("AIzaSyCUOZsk6wPiJvDeHjfBAoqPo3sGjHFdsN0Y")  # Use environment variable for API key
-        if not api_key:
-            raise ValueError("API key for Gemini is missing.")
-        
-        # Configure API
-        genai.configure(api_key=api_key)
-        
-        # Define the generation configuration
-        generation_config = {
-            "temperature": 1,
-            "top_p": 0.95,
-            "top_k": 40,
-            "max_output_tokens": 8192,
-            "response_mime_type": "text/plain",
-        }
-        
-        # Initialize the model
-        model = genai.GenerativeModel(
-            model_name="gemini-1.5-pro-002",
-            generation_config=generation_config,
-        )
-        
-        # Start a chat session (can be empty or with history)
-        chat_session = model.start_chat(history=[])
-        
-        # Send the message and get the response
-        response = chat_session.send_message(question)
-        
-        # Ensure response is correctly parsed (adjust if needed based on response format)
-        return response.get("text", "No text response found.")
-    
-    except Exception as e:
-        # Handle any exceptions that occur during the process
-        return f"Error: {str(e)}"
+    # os.environ["OPENAI_API_KEY"] = keyfile.OPENAI_API_KEY
+    # llm = OpenAI()
+    # answer = llm.invoke(question)
+    # return answer
+    model = genai.GenerativeModel("gemini-1.5-flash")
+    response = model.generate_content(question)
+    return response.text
 
 # Using Streamlit for generation of page
-st.set_page_config(page_title="Ask GPT", page_icon=":robot:")
-st.header("Ask GPT Application")
+st.set_page_config(page_title = "ASK GPT / GEMINI", page_icon = ":robot:")
+st.header("ASK GPT / GEMINI Application")
 
-# Create function for taking user input
+# Create a function for taking user input
 def get_user_input():
-    text = st.text_input("Ask:", key="input")
-    return text  # Return the user input text
+    text = st.text_input("Ask: ", key = "input")
+    return text
 
-# Display the input and response after submission
 user_input = get_user_input()
+resp = get_response(user_input)
 
-# Submit Button
-submit = st.button("Ask")
+# Submission button
+submit = st.button("Ask!")
 
-if submit and user_input:
-    resp = get_response(user_input)  # Call the get_response function
-    st.subheader("Answer: ")
-    st.write(resp)  # Display the response
+if submit:
+    st.subheader("Answer to the query: ")
+    st.write(resp)