Update app.py

app.py

@@ -20,35 +20,57 @@
 
 
 # Sample code for AI language model interaction
-from transformers import GPT2Tokenizer, GPT2LMHeadModel
-import gradio
+# from transformers import GPT2Tokenizer, GPT2LMHeadModel
+# import gradio
 
 
-def simptok(data):
-    # Load pre-trained model and tokenizer (using the transformers library)
-    model_name = "gpt2"
-    tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-    model = GPT2LMHeadModel.from_pretrained(model_name)
+# def simptok(data):
+#     # Load pre-trained model and tokenizer (using the transformers library)
+#     model_name = "gpt2"
+#     tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+#     model = GPT2LMHeadModel.from_pretrained(model_name)
     
-    # User input
-    user_input = data
+#     # User input
+#     user_input = data
     
-    # Tokenize input
-    input_ids = tokenizer.encode(user_input, return_tensors="pt")
+#     # Tokenize input
+#     input_ids = tokenizer.encode(user_input, return_tensors="pt")
     
-    # Generate response
-    output = model.generate(input_ids, max_length=50, num_return_sequences=1)
-    response = tokenizer.decode(output[0], skip_special_tokens=True)
-    return response
+#     # Generate response
+#     output = model.generate(input_ids, max_length=50, num_return_sequences=1)
+#     response = tokenizer.decode(output[0], skip_special_tokens=True)
+#     return response
+
+
+# def responsenew(data):
+#     return simptok(data)
+
 
+from hugchat import hugchat
+import gradio as gr
+import time
 
-def responsenew(data):
-    return simptok(data)
+# Create a chatbot connection
+chatbot = hugchat.ChatBot(cookie_path="cookies.json")
 
+# New a conversation (ignore error)
+id = chatbot.new_conversation()
+chatbot.change_conversation(id)
 
-gradio_interface = gradio.Interface(
-  fn = responsenew,
+
+def get_answer(data):
+    return chatbot.chat(data)
+
+gradio_interface = gr.Interface(
+  fn = get_answer,
   inputs = "text",
   outputs = "text"
 )
 gradio_interface.launch()
+
+# gradio_interface = gradio.Interface(
+#   fn = responsenew,
+#   inputs = "text",
+#   outputs = "text"
+# )
+# gradio_interface.launch()