app.py

import os
import spaces
import urllib.parse
import requests
import gradio as gr
from transformers import pipeline

SEARCH_TEMPLATE = "https://en.wikipedia.org/w/api.php?action=opensearch&search=%s&limit=1&namespace=0&format=json"
CONTENT_TEMPLATE = "https://en.wikipedia.org/w/api.php?format=json&action=query&prop=extracts&exintro&explaintext&redirects=1&titles=%s"

summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")

@spaces.GPU
def search_wikipedia(query):
 query = urllib.parse.quote_plus(query)
 data = requests.get(SEARCH_TEMPLATE % query).json()
 if data and data[1]:
 page = urllib.parse.quote_plus(data[1][0])
 content = requests.get(CONTENT_TEMPLATE % page).json()
 content = list(content["query"]["pages"].values())[0]["extract"]
 summary = summarizer(content, max_length=150, min_length=50, do_sample=False)[0]['summary_text']
 source = data[3][0]
 return summary, source
 else:
 return "No results found.", ""

def chatbot_response(message, history):
 summary, source = search_wikipedia(message)
 response = f"Here's a summary of the top Wikipedia result:\n\n{summary}"
 if source:
 response += f"\n\nSource: {source}"
 history.append((message, response))
 return history

demo = gr.Blocks()

with demo:
 gr.Markdown("# Wikipedia Chatbot")
 gr.Markdown("This chatbot queries the Wikipedia API and summarizes the top result.")

 chatbot = gr.Chatbot()
 msg = gr.Textbox(label="Enter your query")
 clear = gr.Button("Clear")

 msg.submit(chatbot_response, [msg, chatbot], chatbot).then(
 lambda: gr.update(value=""), None, [msg], queue=False
 )
 clear.click(lambda: None, None, chatbot, queue=False)

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