app.py

import gradio as gr

from langchain_core.prompts import ChatPromptTemplate
from langchain_community.vectorstores import Clickhouse, ClickhouseSettings
from langchain_community.vectorstores import FAISS
from langchain_community.chat_message_histories import ChatMessageHistory
from langchain_core.chat_history import BaseChatMessageHistory
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_core.runnables import ConfigurableFieldSpec
from langchain.schema import Document
from langchain.prompts import PromptTemplate
from langchain_core.output_parsers import JsonOutputParser
from langchain_core.output_parsers import StrOutputParser
from langchain_pinecone import PineconeVectorStore
from typing_extensions import TypedDict
from typing import Dict, List
import warnings

from lib.gradio_custom_theme import DarkTheme
from lib.graph import build_workflow


warnings.filterwarnings("ignore")
from dotenv import load_dotenv

load_dotenv()


def deploy():
    app = build_workflow()

    pdf_open_js = """
    <script>
        function openPdf(src) {
            const opener = document.getElementById("opener");
            opener.src = src;
            console.log("here", src);
            return false;
        }
    </script>
    """

    dark_theme = DarkTheme()
    with gr.Blocks(head=pdf_open_js, fill_height=True, theme=dark_theme) as demo:
        with gr.Row():
            with gr.Column(scale=1):
                chatbot_rag = gr.Chatbot(
                    label=f"RAG: llama3 + документы",
                    height=740,
                    sanitize_html=False,
                    show_copy_button=True,
                )
                chat_input = gr.MultimodalTextbox(
                    interactive=True,
                    file_types=None,
                    placeholder="Введите сообщение...",
                    show_label=False,
                    scale=4,
                )
            with gr.Column(scale=1.5):
                pdf_output = gr.HTML(
                    "<iframe id='opener' width='100%' height='740px' src=''></iframe>"
                )
        # clear = gr.Button("Clear")

        def user_rag(history, message):
            if message["text"] is not None:
                history.append((message["text"], None))
            return history, gr.update(value=None, interactive=False)

        def bot_rag(history):
            result = app.invoke({"question": history[-1][0]})
            form_answer = result["generation"].strip()
            history[-1][1] = form_answer
            return history

        chat_input.submit(
            user_rag, [chatbot_rag, chat_input], [chatbot_rag, chat_input], queue=False
        ).then(bot_rag, chatbot_rag, chatbot_rag).then(
            lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input]
        )

    demo.launch(share=True)


if __name__ == "__main__":
    deploy()