import pdfplumber
import streamlit as st
from groq import Groq

# Replace with your actual API key
API_KEY = "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"

# Initialize the Groq client with the API key
client = Groq(api_key=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()