app.py

import os
import requests
import streamlit as st
from langchain.chains import SequentialChain, LLMChain
from langchain.prompts import PromptTemplate
from langchain_groq import ChatGroq
from langchain.document_loaders import PDFPlumberLoader
from langchain_experimental.text_splitter import SemanticChunker
from langchain_huggingface import HuggingFaceEmbeddings
from langchain_chroma import Chroma

# Set API Keys
os.environ["GROQ_API_KEY"] = st.secrets.get("GROQ_API_KEY", "")

# Load LLM models
llm_judge = ChatGroq(model="deepseek-r1-distill-llama-70b")
rag_llm = ChatGroq(model="mixtral-8x7b-32768")

st.title("❓")

# Options for PDF input
pdf_source = st.radio("How would you like to provide a PDF?", ["Upload a PDF", "Enter a PDF URL"], index=0)

if pdf_source == "Upload a PDF":
    uploaded_file = st.file_uploader("Upload your PDF file", type="pdf")
    if uploaded_file:
        with open("temp.pdf", "wb") as f:
            f.write(uploaded_file.getbuffer())
        pdf_path = "temp.pdf"

elif pdf_source == "Enter a PDF URL":
    pdf_url = st.text_input("Enter PDF URL:")
    if pdf_url:
        try:
            response = requests.get(pdf_url)
            if response.status_code == 200:
                with open("temp.pdf", "wb") as f:
                    f.write(response.content)
                pdf_path = "temp.pdf"
                st.success("✅ PDF Downloaded Successfully!")
            else:
                st.error("❌ Failed to download PDF. Check the URL.")
                pdf_path = None
        except Exception as e:
            st.error(f"Error downloading PDF: {e}")
            pdf_path = None
else:
    pdf_path = None