app.py

import gradio as gr

import subprocess
import sys

def install(package):
    subprocess.check_call([sys.executable, "-m", "pip", "install", package])

install("langchain_community")
install("langchain_openai")
install("langchain")

import  os
from langchain_community.graphs import Neo4jGraph
from langchain.chains import GraphCypherQAChain
from langchain_openai import ChatOpenAI


os.environ["NEO4J_URI"] = "neo4j://localhost:7687"
os.environ["NEO4J_USERNAME"] = "neo4j"
os.environ["NEO4J_PASSWORD"] = "password"


def respond(
    message
):
    graph = Neo4jGraph()

    
    llm = ChatOpenAI(model="gpt-4o", temperature=0)
    chain = GraphCypherQAChain.from_llm(graph=graph, llm=llm, verbose=True)
    response = chain.invoke({"query": message})

    return response['result']

"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""

with gr.Blocks() as demo:
    
    with gr.Tab("Ask my neo4j database"):
        gr.Markdown("### Talk to me !")

        message = gr.Dropdown(label="Your message")
        
        btn_submit = gr.Button("Submit")

        result_ta = gr.TextArea("Here you will find your answer !")

        btn_submit.click(respond, inputs=message, outputs=result_ta)
        
    
demo.launch()