import gradio as gr
from PyPDF2 import PdfReader
import docx

def extract_text_from_uploaded_file(file_path):
    if file_path.endswith(".pdf"):
        try:
            reader = PdfReader(file_path)
            return "\n".join(page.extract_text() or "" for page in reader.pages)
        except Exception as e:
            return f"[Error extracting PDF text: {e}]"
    elif file_path.endswith(".txt"):
        try:
            with open(file_path, "r", encoding="utf-8") as f:
                return f.read()
        except Exception as e:
            return f"[Error reading text file: {e}]"
    elif file_path.endswith(".docx"):
        try:
            doc = docx.Document(file_path)
            return "\n".join([p.text for p in doc.paragraphs])
        except Exception as e:
            return f"[Error reading DOCX: {e}]"
    else:
        return "[Unsupported file type for text extraction]"

def create_ui(agent):
    with gr.Blocks(theme=gr.themes.Soft()) as demo:
        gr.Markdown("<h1 style='text-align: center;'>💊 TxAgent: Therapeutic Reasoning</h1>")
        chatbot = gr.Chatbot(label="TxAgent", height=600, type="messages")

        file_upload = gr.File(label="Upload Medical File", file_types=[".pdf", ".txt", ".docx"])
        message_input = gr.Textbox(placeholder="Ask a biomedical question...", show_label=False)
        send_button = gr.Button("Send", variant="primary")
        conversation_state = gr.State([])

        def handle_chat(message, history, conversation, uploaded_file):
            file_text = ""
            if uploaded_file:
                file_text = extract_text_from_uploaded_file(uploaded_file.name)

            # Append file text to the question
            if file_text:
                message += f"\n\n[Document Content Extracted from Upload]:\n{file_text}"

            generator = agent.run_gradio_chat(
                message=message,
                history=history,
                temperature=0.3,
                max_new_tokens=1024,
                max_token=8192,
                call_agent=False,
                conversation=conversation,
                max_round=30
            )
            for update in generator:
                yield update

        inputs = [message_input, chatbot, conversation_state, file_upload]
        send_button.click(fn=handle_chat, inputs=inputs, outputs=chatbot)
        message_input.submit(fn=handle_chat, inputs=inputs, outputs=chatbot)

        gr.Examples(
            examples=[
                ["Upload the files"],
            ],
            inputs=message_input,
        )

    return demo