agregar app

app.py

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+# Load model directly
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+import torch
+
+""" from huggingface_hub import login
+
+login(token="token", add_to_git_credential=True) """
+
+model_name = "microsoft/DialoGPT-large"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+model.generation_config.pad_token_id = model.generation_config.eos_token_id
+
+chat_history_ids = None
+
+def generate_response(user_input, history = []):
+    global chat_history_ids  # Para modificar la variable global
+    new_user_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')
+
+    if len(history) > 0:
+        bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1)
+    else:
+        bot_input_ids = new_user_input_ids
+    
+    chat_history_ids = model.generate(bot_input_ids, max_length=10000, pad_token_id=tokenizer.eos_token_id)
+
+    response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
+
+    # Para depuración
+    #print("user", new_user_input_ids)
+    #print("bot",chat_history_ids[:, bot_input_ids.shape[-1]:][0])
+    #print(chat_history_ids)
+        
+    return response
+
+
+chatbot_interface = gr.ChatInterface(fn=generate_response)
+
+demo = gr.TabbedInterface([
+    chatbot_interface
+], ["chatbot"])
+
+
+demo.launch()

requirements.txt

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+transformers
+gradio
+torch