Update app.py

app.py

@@ -1,36 +1,19 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
+# Use a pipeline as a high-level helper
+from transformers import pipeline
 import gradio as gr
 
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
-
-def chat_with_history(message, chat_history=None):
-    # Initialize chat history if not provided
-    if chat_history is None:
-        chat_history = []
-
-    # Encode the new user input, add the eos_token, and return a tensor in PyTorch
-    new_user_input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors='pt')
-
-    # Append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([tokenizer.encode(pair[0] + tokenizer.eos_token, return_tensors='pt') for pair in chat_history] + [new_user_input_ids], dim=-1)
-
-    # Generate a response while limiting the total chat history to 1000 tokens
-    chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
-
-    # Decode the last output tokens from bot
-    response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
-
-    # Update the chat history with the new user message and bot response
-    chat_history.append([message, response])
-
-    return response
-
-demo = gr.ChatInterface(
-        fn=chat_with_history,
-        examples=["hey how are you ?", "hola", "Yo!"],
-        title="Multi Chat Bot"
-    )
-
-demo.launch()
+pipe = pipeline("text-generation", model="Gustavosta/MagicPrompt-Stable-Diffusion")
+
+def genPrompt(text: str, total: int):
+  total = int(total)
+  ret = None
+  for i in range(0, total):
+    txt = pipe(text, max_length=1000, min_length=50)[0].get("generated_text").replace("\n", " ")
+    if not ret:
+      ret = txt
+    else:
+      ret = f"{ret}\n\n{txt}"
+  return ret
+
+appli = gr.Interface(fn=genPrompt, inputs=[gr.Text(),gr.Slider(0, 10, 4)], outputs="text")
+appli.launch(debug=True)