Delete app.py

app.py

@@ -1,143 +0,0 @@
-# -*- coding: utf-8 -*-
-"""nino bot
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1UgXple_p_R-0mq9p5vhOmFPo9cgdayJy
-"""
-
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-print("Starting app.py")
-
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-print("Imports successful")
-
-model_name = "microsoft/DialoGPT-small"
-print(f"Loading model {model_name}...")
-
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-model.eval()
-
-print("Model loaded successfully")
-
-# your rest of the code...
-
-with gr.Blocks() as demo:
-    # ... UI components ...
-
-demo.launch()
-
-
-
-
-
-
-model_name = "microsoft/DialoGPT-small"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-
-rules = {
-  "hi": "Hello! How can I help you today?",
-    "hello": "Hi there! How can I assist you?",
-    "hey": "Hey! What can I do for you?",
-    "how are you": "I'm just a bot, but I'm doing great! 😊 How about you?",
-    "good morning": "Good morning! Hope you have a wonderful day!",
-    "good afternoon": "Good afternoon! How can I help you?",
-    "good evening": "Good evening! What can I do for you?",
-    "bye": "Goodbye! Have a nice day! 👋",
-    "thank you": "You're welcome! 😊",
-    "thanks": "No problem! Happy to help!",
-    "what is your name": "I'm your friendly chatbot assistant.",
-    "help": "Sure! Ask me anything or type 'bye' to exit.",
-    "what can you do": "I can answer simple questions and chat with you. Try saying hi!",
-    "tell me a joke": "Why did the computer show up at work late? It had a hard drive!",
-    "what time is it": "Sorry, I don't have a clock yet. But you can check your device's time!",
-    "where are you from": "I'm from the cloud, here to assist you anytime!",
-    "what is ai": "AI stands for Artificial Intelligence, which is intelligence demonstrated by machines.",
-    "who created you": "I was created by a talented developer using Python and machine learning!",
-    "how can i learn programming": "Start with basics like Python. There are many free tutorials online to get you started!",
-    'ok':'ok',
-    'who are you?':'I am nino',
-    'hi nino' : 'hi there',
-}
-
-def respond(user_input, history):
-    if history is None:
-        history = []
-
-    user_input_clean = user_input.lower().strip()
-
-    if user_input_clean in rules:
-        bot_reply = rules[user_input_clean]
-    else:
-        prompt = ""
-        # Build the prompt including the conversation history
-        for user_msg, bot_msg in history:
-             # Ensure bot_msg is not None before adding to prompt
-            if bot_msg is not None:
-                prompt += f"{user_msg} {tokenizer.eos_token}\n{bot_msg} {tokenizer.eos_token}\n"
-            else:
-                 # If bot_msg is None, just add the user message
-                 prompt += f"{user_msg} {tokenizer.eos_token}\n"
-        # Add the current user input
-        prompt += f"{user_input} {tokenizer.eos_token}\n"
-
-        inputs = tokenizer(prompt, return_tensors="pt")
-        outputs = model.generate(
-            **inputs,
-            max_new_tokens=100,
-            pad_token_id=tokenizer.eos_token_id,
-            do_sample=True,
-            temperature=0.7,
-            top_p=0.9,
-        )
-
-        generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-        # Extract the newly generated bot response from the full text
-        # This assumes the model output starts with the prompt
-        bot_reply = generated_text[len(prompt):].strip()
-
-
-        if len(bot_reply) < 5 or bot_reply.lower() in ["", "idk", "i don't know", "huh"]:
-            bot_reply = "I'm not sure how to respond to that. Can you rephrase it?"
-
-    # Append the new interaction to the history
-    history.append((user_input, bot_reply))
-    return history, history
-
-def save_chat(history):
-    # Ensure history is not None before attempting to save
-    if history is not None:
-        with open("chat_history.txt", "w", encoding="utf-8") as f:
-            for user_msg, bot_msg in history:
-                # Ensure bot_msg is not None before writing
-                if bot_msg is not None:
-                    f.write(f"You: {user_msg}\nBot: {bot_msg}\n\n")
-                else:
-                    f.write(f"You: {user_msg}\nBot: (No response)\n\n")
-
-
-# New function to process input, respond, save, and clear the textbox
-def process_input(user_input, history):
-    # Get the updated history and bot response
-    updated_history, _ = respond(user_input, history)
-
-    save_chat(updated_history)
-
-    
-    return updated_history, "", updated_history 
-
-with gr.Blocks() as demo:
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox(placeholder="Type your message here...")
-    state = gr.State([]) 
-
-    
-    msg.submit(process_input, inputs=[msg, state], outputs=[chatbot, msg, state])
-demo.launch()