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gemini_app.py

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+import streamlit as st
+import google.generativeai as genai
+import pandas as pd
+import os
+import numpy as np
+from dotenv import load_dotenv
+load_dotenv()
+genai.configure(api_key=os.getenv('GEMINI'))
+database_str=''
+with open('database.txt', 'r',encoding='utf-8') as f:
+    database_str = f.read()
+
+
+def generate_response(query):
+    prompt = f'''
+    You are a Course suggestor based on the user requirement and the from the given database which consist of 
+    the course name and description of the course.
+
+    You're tasked to use the description of each course and compare it with the user input and output which course's
+    description matches the user requirement.
+    Output the course name alone which matches the user requirement.
+    you may output a max of 3 courses if you find that are good matches. name of the course should be exactly same as the database provided to you.
+    # Database
+    {database_str}
+
+    # User Input
+    {query}
+
+    # Output : (Course Name with | as splitter)
+    '''
+    model = genai.GenerativeModel("gemini-1.5-flash")
+    response = model.generate_content(prompt)
+
+    return response.text.split("|")
+
+
+# Define session state variables
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+if 'mess' not in st.session_state:
+    st.session_state.mess=[]
+
+
+if st.sidebar.button("RESET"):
+    st.session_state.messages=[]
+    st.session_state.mess=[]
+    
+# User input
+st.title('Analytics Vidhya Course Finder')
+user_input = st.chat_input('Write your message here...')
+
+if user_input:
+    # Append user input to messages
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    st.session_state.mess+=[user_input]
+    # Generate chatbot response
+    bot_response = generate_response(st.session_state.mess)
+    st.session_state.messages.append({"role": "bot", "content": bot_response})
+
+# Display chat messages in correct order
+for message in st.session_state.messages:
+    if message["role"] == "user":
+        with st.chat_message("human"):
+            st.write(message['content'])
+    else:
+        with st.chat_message("ai"):
+            for i in message['content']:
+                st.write('* '+i)

requirements1.txt

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+google-generativeai