import gradio as gr
import os
from langchain.document_loaders import OnlinePDFLoader
from langchain.text_splitter import CharacterTextSplitter
from anthropic import LanguageModel

# Set API keys from environment variables
os.environ['ANTHROPIC_API_KEY'] = os.getenv("Your_Anthropic_API_Key")

# Initialize the Anthropic model
anthropic_model = LanguageModel(api_key=os.environ['ANTHROPIC_API_KEY'], model="some_model")

pdf_content = ""

def load_pdf(pdf_doc):
    global pdf_content
    try:
        if pdf_doc is None:
            return "No PDF uploaded."

        # Load and split PDF content
        loader = OnlinePDFLoader(pdf_doc.name)
        documents = loader.load()
        text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
        pdf_content = ' '.join(text_splitter.split_documents(documents))

        return "PDF Loaded Successfully."

    except Exception as e:
        return f"Error processing PDF: {e}"

def chat_with_pdf(question):
    context = [{"role": "system", "content": pdf_content}]
    response = anthropic_model.query(question, context=context)
    return response['answer']

# Define Gradio UI
def gradio_interface(pdf_doc, question):
    if not pdf_content:
        return load_pdf(pdf_doc)
    else:
        return chat_with_pdf(question)

gr.Interface(fn=gradio_interface,
             inputs=[gr.File(label="Load a pdf", file_types=['.pdf'], type="file"),
                     gr.Textbox(label="Ask a question about the PDF")],
             outputs="text",
             live=True,
             title="Chat with PDF content using Anthropic",
             description="Upload a .PDF and interactively chat about its content."
            ).launch()