Update app.py

app.py

@@ -1,3 +1,37 @@
+import gradio
+from transformers import pipeline
+
+# Initialize the Hugging Face model
+model = pipeline(model='google/flan-t5-base')
+
+
+# Define the chatbot function
+def chatbot(input_text):
+  # Generate a response from the Hugging Face model
+  response = model(input_text, max_length=50, do_sample=True)[0]['generated_text'].strip()
+  
+  # Return the bot response
+  return response
+
+# Define the Gradio interface
+gradio_interface = gradio.Interface(
+    fn=chatbot,
+    inputs='text',
+    outputs='text',
+    title='Chatbot',
+    description='A weird chatbot conversations experience.',
+    examples=[
+        ['Hi, how are you?']
+    ]
+)
+
+# Launch the Gradio interface
+gradio_interface.launch()
+
+
+
+
+
 # from dotenv import load_dotenv
 # from langchain import HuggingFaceHub, LLMChain
 # from langchain import PromptTemplates
@@ -46,27 +80,27 @@
 #     return simptok(data)
 
 
-from hugchat import hugchat
-import gradio as gr
-import time
+# from hugchat import hugchat
+# import gradio as gr
+# import time
 
-# Create a chatbot connection
-chatbot = hugchat.ChatBot(cookie_path="cookies.json")
+# # Create a chatbot connection
+# chatbot = hugchat.ChatBot(cookie_path="cookies.json")
 
-# New a conversation (ignore error)
-id = chatbot.new_conversation()
-chatbot.change_conversation(id)
+# # New a conversation (ignore error)
+# id = chatbot.new_conversation()
+# chatbot.change_conversation(id)
 
 
-def get_answer(data):
-    return chatbot.chat(data)
+# def get_answer(data):
+#     return chatbot.chat(data)
 
-gradio_interface = gr.Interface(
-  fn = get_answer,
-  inputs = "text",
-  outputs = "text"
-)
-gradio_interface.launch()
+# gradio_interface = gr.Interface(
+#   fn = get_answer,
+#   inputs = "text",
+#   outputs = "text"
+# )
+# gradio_interface.launch()
 
 # gradio_interface = gradio.Interface(
 #   fn = responsenew,