chatgradio.py

import gradio as gr

from langchain_upstage import ChatUpstage
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.output_parsers import StrOutputParser
from langchain.schema import AIMessage, HumanMessage


llm = ChatUpstage(streaming=True)

# More general chat
chat_with_history_prompt = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a helpful assistant."),
        MessagesPlaceholder(variable_name="history"),
        ("human", "{message}"),
    ]
)

chain = chat_with_history_prompt | llm | StrOutputParser()


def chat(message, history):
    history_langchain_format = []
    for human, ai in history:
        history_langchain_format.append(HumanMessage(content=human))
        history_langchain_format.append(AIMessage(content=ai))

    generator = chain.stream({"message": message, "history": history_langchain_format})

    assistant = ""
    for gen in generator:
        assistant += gen
        yield assistant


with gr.Blocks() as demo:
    chatbot = gr.ChatInterface(
        chat,
        examples=[
            "How to eat healthy?",
            "Best Places in Korea",
            "How to make a chatbot?",
        ],
        title="Solar Chatbot",
        description="Upstage Solar Chatbot",
    )
    chatbot.chatbot.height = 300

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