app.py

import gradio as gr
from llama_index.core import Settings
from documents_prep import load_all_documents
from index_retriever import create_vector_index, create_query_engine
from utils import get_llm_model, get_embedding_model, get_reranker_model, answer_question
from my_logging import log_message
from config import *
# Global state
query_engine = None
reranker = None

def initialize_system():
    """Initialize RAG system"""
    global query_engine, reranker
    
    log_message("="*60)
    log_message("INITIALIZING SYSTEM")
    log_message("="*60)
    
    # Setup models
    llm = get_llm_model(GOOGLE_API_KEY)
    embed_model = get_embedding_model()
    reranker = get_reranker_model()
    
    Settings.llm = llm
    Settings.embed_model = embed_model
    
    log_message("✓ Models loaded")
    
    # Load documents
    documents = load_all_documents(
        repo_id=HF_REPO_ID,
        hf_token=HF_TOKEN,
        json_dir=JSON_FILES_DIR,
        table_dir=TABLE_DATA_DIR,
        image_dir=IMAGE_DATA_DIR
    )
    
    # Create index
    vector_index = create_vector_index(documents)
    query_engine = create_query_engine(vector_index)
    
    log_message("="*60)
    log_message("SYSTEM READY")
    log_message("="*60)
    
    return "✅ System initialized"

def ask_question(question):
    """Handle question from UI"""
    if not question.strip():
        return "Пожалуйста, введите вопрос", ""
    
    if query_engine is None:
        return "❌ Система не инициализирована", ""
    
    answer, sources = answer_question(question, query_engine, reranker)
    
    return answer, sources
def create_interface():
    """Create Gradio UI"""
    # Auto-initialize system before UI starts
    status_msg = initialize_system()

    with gr.Blocks(title="AIEXP - RAG System", theme=gr.themes.Soft()) as demo:
        gr.Markdown("""
        # AIEXP - AI Expert для нормативной документации
        ## Упрощенная версия RAG системы
        """)

        gr.Markdown("### Задайте вопрос")

        with gr.Row():
            question = gr.Textbox(
                label="Ваш вопрос",
                placeholder="Введите вопрос...",
                lines=3
            )

        ask_btn = gr.Button("Найти ответ", variant="primary")

        gr.Examples(
            examples=[
                "О чем таблица А.12 в ГОСТ Р 59023.4-2020?",
                "Какая температура подогрева для стали 20 толщиной до 100 мм?",
                "Что показано на рисунке Л.2 в ГОСТ Р 50.04.07-2022?"
            ],
            inputs=question
        )

        with gr.Row():
            answer = gr.Textbox(
                label="Ответ",
                lines=10
            )
            sources = gr.Textbox(
                label="Источники",
                lines=10
            )

        # Event handlers
        ask_btn.click(
            fn=ask_question,
            inputs=question,
            outputs=[answer, sources]
        )

        question.submit(
            fn=ask_question,
            inputs=question,
            outputs=[answer, sources]
        )

    return demo

if __name__ == "__main__":
    demo = create_interface()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True
    )