Create app.py

app.py

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+import os
+import pdfplumber
+import streamlit as st
+from groq import Groq
+
+# Set the Groq API key (you need to set this beforehand)
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+# Function to extract text from the PDF
+def extract_text_from_pdf(pdf_path):
+    with pdfplumber.open(pdf_path) as pdf:
+        full_text = ""
+        for page in pdf.pages:
+            full_text += page.extract_text()
+    return full_text
+
+# Function to search for relevant information based on the query
+def search_relevant_info(query, text):
+    lower_text = text.lower()
+    lower_query = query.lower()
+
+    if lower_query in lower_text:
+        start = lower_text.find(lower_query)
+        end = start + 1000  # Extracting a portion of the text (adjustable)
+        return text[start:end]
+    else:
+        return "Sorry, I couldn't find any relevant information."
+
+# Function to generate response from Groq API
+def generate_response_with_retrieved_info(query, retrieved_text):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "user",
+                "content": f"Query: {query}\nContext: {retrieved_text}",
+            }
+        ],
+        model="llama3-8b-8192",
+    )
+
+    return chat_completion.choices[0].message.content
+
+# Main chatbot function
+def chatbot(query, pdf_path):
+    # Step 1: Extract text from the PDF
+    extracted_text = extract_text_from_pdf(pdf_path)
+
+    # Step 2: Search for relevant information based on the query
+    retrieved_text = search_relevant_info(query, extracted_text)
+
+    # Step 3: Generate a response using the Groq API
+    response = generate_response_with_retrieved_info(query, retrieved_text)
+
+    return response
+
+# Streamlit UI
+def main():
+    st.title("University Information Chatbot")
+    
+    # Upload PDF
+    pdf_file = st.file_uploader("Upload the University Information PDF", type=["pdf"])
+    
+    if pdf_file:
+        # Text input for user query
+        query = st.text_input("Ask a question about the university:")
+        
+        if query:
+            # Process the query
+            with st.spinner("Searching for relevant information..."):
+                response = chatbot(query, pdf_file)
+                st.write("Response:", response)
+
+if __name__ == "__main__":
+    main()