Upload app.py

app.py

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+import os
+import sqlite3
+import streamlit as st
+import google.generativeai as genai
+from dotenv import load_dotenv
+
+# Load environment variables from .env
+load_dotenv()
+
+# Set up the Google API key for Gemini
+api_key = os.getenv("GOOGLE_API_KEY")
+if api_key is None:
+    st.error("GOOGLE_API_KEY not found in environment variables. Please check your .env file.")
+else:
+    # Configure Google Generative AI API
+    genai.configure(api_key=api_key)
+
+
+# Function to fetch all courses from the SQLite database
+def fetch_all_courses():
+    conn = sqlite3.connect('courses.db')
+    cur = conn.cursor()
+    cur.execute("SELECT title, description, price FROM courses")
+    rows = cur.fetchall()
+    conn.close()
+    return rows
+
+
+# Function to generate a response using Google Generative AI based on user prompt and available courses
+def generate_response(prompt, courses):
+    try:
+        # Prepare a detailed context prompt for the LLM
+        course_details = "\n".join(
+            [f"Title: {course[0]}, Description: {course[1]}, Price: {course[2]}" for course in courses])
+
+        genai_prompt = f"""
+        You are an expert assistant tasked with finding relevant courses based on user queries. 
+        Below are details of available courses:
+
+        {course_details}
+
+        Based on this information, respond to the user's query in the most relevant way:
+        {prompt}
+        """
+
+        # Generate a response using Google Generative AI
+        model = genai.GenerativeModel('gemini-pro')
+        response = model.generate_content([genai_prompt, prompt])
+        return response.text.strip()  # Return the natural language response
+    except Exception as e:
+        st.error(f"Error generating a response: {e}")
+        return None
+
+
+# Streamlit interface
+st.set_page_config(page_title="Smart Search for Courses")
+st.header("Find Relevant Courses on Analytics Vidhya")
+
+# User prompt input
+user_query = st.text_input("Enter your search query (e.g., 'Show me all free courses on machine learning'):")
+
+submit = st.button("Search")
+
+# Fetch all courses from the database
+courses = fetch_all_courses()
+
+# If user submits the query
+if submit and user_query:
+    # Generate a response from Google Generative AI
+    response = generate_response(user_query, courses)
+
+    if response:
+        st.subheader("Search Results:")
+        st.write(response)
+    else:
+        st.write("Could not generate a response. Please try again.")