Upload app.py

app.py

@@ -0,0 +1,122 @@
+# -*- 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
+
+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 the updated chat history
+    save_chat(updated_history)
+
+    # Return the updated history for the chatbot display and an empty string for the textbox
+    return updated_history, "", updated_history # Also return updated history for the state
+
+with gr.Blocks() as demo:
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(placeholder="Type your message here...")
+    state = gr.State([]) # This state variable holds the chat history
+
+    # Update the submit action to call the new function
+    # Add 'msg' to the outputs so its value can be updated
+    msg.submit(process_input, inputs=[msg, state], outputs=[chatbot, msg, state])
+
+demo.launch()
+
+with open("my_data.txt", "w", encoding="utf-8") as f:
+    f.write("Hello! This is my nino bot  text file.\nYou can use this as a data source.")