Create app.py

app.py

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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):
+    page = newspaper.Article(url=page_url)
+    page.download()
+    page.parse()
+
+    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
+        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 response_text, num_tokens
+    return "--- Something went wrong! ---", 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:", 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="Output:"), gr.Textbox(label="Tokens:")],
+    examples=[["Summarize the following text as a list:","https://blog.google/outreach-initiatives/google-org/our-commitment-on-using-ai-to-accelerate-progress-on-global-development-goals/","",0.3],
+            ["Extract the main topics of the following text:", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7]
+    ]
+)
+iface.launch()