import os
import streamlit as st
from langchain import PromptTemplate, LLMChain
from langchain_together import Together
import pdfplumber

# Set the API key with double quotes
os.environ['TOGETHER_API_KEY'] = "d88cb7414e4039a84d2ed63f1b47daaaa4230c4c53a422045d8a30a9a3bc87d8"

def extract_text_from_pdf(pdf_file, max_pages=16):
    text = ""
    with pdfplumber.open(pdf_file) as pdf:
        for i, page in enumerate(pdf.pages):
            if i >= max_pages:
                break
            text += page.extract_text() + "\n"
    return text

def Bot(text, question):
    chat_template = """
    Based on the provided context: {text}
    Please answer the following question: {Questions}
    Only provide answers that are directly related to the context. If the question is unrelated, respond with "I don't know".
    """
    prompt = PromptTemplate(
        input_variables=['text', 'Questions'],
        template=chat_template
    )
    llama3 = Together(model="meta-llama/Llama-3-70b-chat-hf", max_tokens=50)
    Generated_chat = LLMChain(llm=llama3, prompt=prompt)

    try:
        response = Generated_chat.invoke({
            "text": text,
            "Questions": question
        })

        response_text = response['text']

        response_text = response_text.replace("assistant", "")

        # Post-processing to handle repeated words and ensure completeness
        words = response_text.split()
        seen = set()
        filtered_words = [word for word in words if word.lower() not in seen and not seen.add(word.lower())]
        response_text = ' '.join(filtered_words)
        response_text = response_text.strip()  # Ensuring no extra spaces at the ends
        if not response_text.endswith('.'):
            response_text += '.'

        return response_text
    except Exception as e:
        return f"Error in generating response: {e}"

def ChatBot(document, question):
    greetings = ["hi", "hello", "hey", "greetings", "what's up", "howdy"]
    question_lower = question.lower().strip()
    if question_lower in greetings or any(question_lower.startswith(greeting) for greeting in greetings):
        return "Hello! How can I assist you with the document today?"

    text = extract_text_from_pdf(document)
    response = Bot(text, question)
    return response

st.title("PDF ChatBot")

uploaded_file = st.file_uploader("Upload PDF Document", type="pdf")
question = st.text_input("Ask a Question", placeholder="Type your question here...")

if uploaded_file and question:
    with st.spinner('Processing...'):
        response = ChatBot(uploaded_file, question)
    st.write(response)

# --- Logo ---

st.sidebar.image("profile.jpg", width=200)

st.sidebar.title("Haseeb Ahmed")
st.sidebar.write("AI/ML Engineer")
st.sidebar.markdown("[Visit us at](https://www.linkedin.com/in/muhammad-haseeb-ahmed-1954b5230/)")