import gradio as gr
from rag_engine import recuperar_documentos, generar_respuesta

def ask(query, top_k, umbral):
    docs = recuperar_documentos(query, int(top_k), float(umbral))
    respuesta = generar_respuesta(query, docs)

    if docs:
        docs_formateados = "\n\n---\n\n".join(docs)
    else:
        docs_formateados = "No relevant documents found."

    return respuesta, docs_formateados


with gr.Blocks() as demo:
    gr.Markdown("# RAG Question Answering System")
    gr.Markdown("Ask a question based on the provided documents.")

    query = gr.Textbox(
        label="Your Question",
        placeholder="Type your question..."
    )

    top_k = gr.Slider(1, 5, value=5, step=1, label="Top K Documents")

    umbral = gr.Slider(0.0, 1.0, value=0.55, step=0.05, label="Similarity Threshold")

    respuesta = gr.Textbox(label="Answer", lines=3)

    docs = gr.Textbox(label="Retrieved Documents", lines=6, max_lines=15)

    boton = gr.Button("Enviar")

    boton.click(
        fn=ask,
        inputs=[query, top_k, umbral],
        outputs=[respuesta, docs]
    )


if __name__ == "__main__":
    demo.launch()