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import os
import gradio as gr
import hpqa
from langchain.chains import RetrievalQA
from langchain_core.vectorstores import VectorStoreRetriever
from langchain_openai import OpenAI
os.environ["OPENAI_API_KEY"] = ""
index_path = "data/hpqa_faiss_index_500"
examples = [
"How would you sneak into Hogwarts without being detected?",
"Why did Snape kill Dumbledore?",
"Who is the most badass wizard in the world?",
"Who would win a fight between Dumbledore and a grizzly bear?",
"How many siblings does Hermione have?",
"Why are the Dursleys so mean to Harry?",
def api(question, temperature, api_key=None):
if api_key is None or len(api_key) == 0:
return "You must provide an OpenAI API key to use this demo πŸ‘‡"
if len(question) == 0:
return ""
document_store = hpqa.load_document_store(index_path, openai_api_key=api_key)
chain = RetrievalQA.from_llm(
llm=OpenAI(temperature=temperature, openai_api_key=api_key),
response = chain.invoke(question)
return response["result"].strip()
demo = gr.Blocks()
with demo:
gr.Markdown("# πŸͺ„ The GPT Who Lived: Harry Potter QA with GPT πŸ€–")
with gr.Row():
with gr.Column():
question = gr.Textbox(lines=4, label="Question")
temperature = gr.Slider(0.0, 2.0, 0.7, step=0.1, label="🍺 Butterbeer Consumed")
with gr.Row():
clear = gr.Button("Clear")
btn = gr.Button("Submit", variant="primary")
with gr.Column():
answer = gr.Textbox(lines=4, label="Answer")
openai_api_key = gr.Textbox(type="password", label="OpenAI API key"), [question, temperature, openai_api_key], answer) _: "", question, question)
gr.Examples(examples, question)
gr.Markdown("πŸ’» Checkout the `hpqa` source code on [GitHub](")