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| import gradio as gr | |
| import os | |
| import openai | |
| import newspaper | |
| import json | |
| import re | |
| from transformers import GPT2Tokenizer | |
| # define the text summarizer function | |
| def text_prompt(request, page_url, contraseña, temp): | |
| try: | |
| page = newspaper.Article(url=page_url) | |
| page.download() | |
| page.parse() | |
| except Exception as e: | |
| return "", f"--- An error occurred while processing the URL: {e} ---", "" | |
| tokenizer = GPT2Tokenizer.from_pretrained("gpt2") | |
| tokens = tokenizer.tokenize(page.text) | |
| num_tokens = len(tokens) | |
| if num_tokens > 10 and num_tokens < 2000: | |
| openai.api_key = contraseña | |
| # get the response from openai API | |
| try: | |
| response = openai.Completion.create( | |
| engine="text-davinci-003", | |
| prompt=request + "\n\n" + page.text, | |
| max_tokens=2048, | |
| temperature=temp, | |
| top_p=0.9, | |
| ) | |
| # get the response text | |
| response_text = response.choices[0].text | |
| # clean the response text | |
| response_text = re.sub(r'\s+', ' ', response_text) | |
| return page.text, response_text, num_tokens | |
| except Exception as e: | |
| return page.text, f"--- An error occurred while processing the request: {e} ---", num_tokens | |
| return page.text, "--- Max number of tokens ---", 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 the URL here...", label="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.Textbox(label="Output:"), gr.Textbox(label="Tokens:")], | |
| examples=[["Summarize the following text in Chinese, and give 5 keywords:","https://openai.com/blog/planning-for-agi-and-beyond","",0.5], | |
| ["Generate a summary of the following text. Give me an overview of main business impact from the text following this template:\n- Summary:\n- Business Impact:\n- Companies:", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7] | |
| ], | |
| title="Information Extraction Interface:", | |
| # description="This tool allows querying the text retrieved from the URL using OpenAI's [text-davinci-003] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the 2000 token limit for OpenAI queries is not exceeded. Provide a prompt with your request, the url for text retrieval, your api-key and temperature to process the text." | |
| ) | |
| error_message = "" | |
| try: | |
| iface.launch() | |
| except Exception as e: | |
| error_message = "An error occurred: " + str(e) | |
| iface.outputs[1].value = error_message |