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import gradio as gr | |
import os | |
import openai | |
from newspaper import Article | |
import json | |
import re | |
from transformers import GPT2Tokenizer | |
import requests | |
# define the text summarizer function | |
def text_prompt(request, system_role, page_url, contraseña, temp): | |
try: | |
headers = {'User-Agent': 'Chrome/83.0.4103.106'} | |
response = requests.get(page_url, headers=headers) | |
html = response.text | |
page = Article('') | |
page.set_html(html) | |
page.parse() | |
except Exception as e: | |
return "", f"--- An error occurred while processing the URL: {e} ---", "" | |
tokenizer = GPT2Tokenizer.from_pretrained("gpt2") | |
sentences = page.text.split('.') | |
tokens = [] | |
page_text = "" | |
for sentence in sentences: | |
tokens.extend(tokenizer.tokenize(sentence)) | |
# Trim text to a maximum of 1800 tokens | |
if len(tokens) > 1800: | |
break | |
page_text += sentence + ". " | |
# Delete the last space | |
page_text = page_text.strip() | |
num_tokens = len(tokens) | |
if num_tokens > 10 and contraseña.startswith("sk-"): | |
openai.api_key = contraseña | |
# get the response from openai API | |
try: | |
response = openai.ChatCompletion.create( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "system", "content": system_role}, | |
{"role": "user", "content": request + "\n\n" + 'Text:\n\n"' + page_text + '\n"'} | |
], | |
max_tokens=2048, | |
temperature=temp, | |
top_p=0.9, | |
) | |
# get the response text | |
response_text = response['choices'][0]['message']['content'] | |
total_tokens = response["usage"]["total_tokens"] | |
# clean the response text | |
response_text = re.sub(r'\s+', ' ', response_text) | |
response_text = "#### "+ page.title + "\n\n" + response_text.strip() | |
total_tokens_str = str(total_tokens) + " (${:.2f} USD)".format(total_tokens/1000*0.002) | |
return page.text, response_text, total_tokens_str | |
except Exception as e: | |
return page.text, f"--- An error occurred while processing the request: {e} ---", num_tokens | |
return page.text, "--- Check API-Key or Min number of tokens:", str(num_tokens) | |
# define the gradio interface | |
iface = gr.Interface( | |
fn=text_prompt, | |
inputs=[gr.Textbox(lines=1, placeholder="Enter your prompt here...", label="Prompt:", type="text"), | |
gr.Textbox(lines=1, placeholder="Enter your system-role description here...", label="System:", type="text"), | |
gr.Textbox(lines=1, placeholder="Enter the Article's URL here...", label="Article's URL to parse:", type="text"), | |
gr.Textbox(lines=1, placeholder="Enter your API-key here...", label="API-Key:", type="password"), | |
gr.Slider(0.0,1.0, value=0.3, label="Temperature:") | |
], | |
outputs=[gr.Textbox(label="Input:"), gr.Markdown(label="Output:"), gr.Markdown(label="Total Tokens:")], | |
examples=[["Summarize the following text as a list:", "Act as a Business Consultant", "https://blog.google/outreach-initiatives/google-org/our-commitment-on-using-ai-to-accelerate-progress-on-global-development-goals/","",0.3], | |
["Generate a summary of the following text. Give me an overview of the main business impact from the text following this template:\n- Summary:\n- Business Impact:\n- Companies:", "Act as a Business Consultant", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7], | |
["Generate the next insights based on the following text. Indicates N/A if the information is not available in the text.\n- Summary:\n- Acquisition Price:\n- Why is this important for the acquirer:\n- Business Line for the acquirer:\n- Tech Focus for the acquired (list):","Act as a Business Consultant", "https://techcrunch.com/2022/09/28/eqt-acquires-billtrust-a-company-automating-the-invoice-to-cash-process-for-1-7b/","",0.3] | |
], | |
title="ChatGPT info extraction from URL", | |
description="This tool allows querying the text retrieved from the URL with newspaper3k lib and using OpenAI's [gpt-3.5-turbo] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the 1.800 token limit for OpenAI queries is not exceeded. Provide a prompt with your request, the description for the system role, the url for text retrieval, your api-key and temperature to process the text." | |
) | |
# error capturing in integration as a component | |
error_message = "" | |
try: | |
iface.queue(concurrency_count=20) | |
iface.launch() | |
except Exception as e: | |
error_message = "An error occurred: " + str(e) | |
iface.outputs[1].value = error_message |