Added requirements.txt and history JSON file

chat_history.json

@@ -0,0 +1 @@
+["[2025-03-14 19:35:09] You: Hi", "[2025-03-14 19:35:09] Bot: Hey", "[2025-03-14 19:35:39] You: I need help.", "[2025-03-14 19:35:39] Bot: Sure, what do you need help with?", "[2025-03-14 19:37:41] You: How old are You ?", "[2025-03-14 19:37:41] Bot: Age is just a number for me.", "[2025-03-14 19:38:21] You: hi", "[2025-03-14 19:38:21] Bot: Nothing much", "[2025-03-14 19:38:46] You: Budget", "[2025-03-14 19:38:46] Bot: To make a budget, start by tracking your income and expenses. Then, allocate your income towards essential expenses like rent, food, and bills. Next, allocate some of your income towards savings and debt repayment. Finally, allocate the remainder of your income towards discretionary expenses like entertainment and hobbies.", "[2025-03-14 19:47:18] You: I need help.", "[2025-03-14 19:47:18] Bot: I'm here to help. What's the problem?", "[2025-03-14 19:51:35] You: Hi", "[2025-03-14 19:51:35] Bot: Nothing much", "[2025-03-14 19:54:12] You: Recommend some excercises.", "[2025-03-14 19:54:12] Bot: Setting boundaries with digital devices can improve sleep, productivity, and overall well-being."]

chatbot.py

@@ -2,6 +2,7 @@ import streamlit as st
 import torch
 from transformers import BertTokenizer, BertForSequenceClassification
 import json
+import os
 import time
 import datetime
 import random
@@ -21,8 +22,6 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 # Load model & tokenizer
 tokenizer = BertTokenizer.from_pretrained(MODEL_PATH)
 model = BertForSequenceClassification.from_pretrained(MODEL_PATH)
-
-# Move model to device
 model.to(device)
 model.eval()
 
@@ -30,10 +29,32 @@ model.eval()
 with open("intents.json", "r") as file:
     intents = json.load(file)
 
-# Create a mapping between index and intent tag
 intent_mapping = {i: intent['tag'] for i, intent in enumerate(intents)}
 
-DEBUG = False  # Set to True only when debugging
+# Chat history file
+CHAT_HISTORY_FILE = "chat_history.json"
+
+# Load Chat History (Ensuring Persistence)
+def load_chat_history():
+    if os.path.exists(CHAT_HISTORY_FILE):
+        with open(CHAT_HISTORY_FILE, "r") as file:
+            return json.load(file)
+    return []
+
+# Save Chat History
+def save_chat_history():
+    with open(CHAT_HISTORY_FILE, "w") as file:
+        json.dump(st.session_state.chat_history, file)
+
+# Initialize session state variables
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = load_chat_history()
+if "show_history" not in st.session_state:
+    st.session_state.show_history = False
+if "show_about" not in st.session_state:
+    st.session_state.show_about = False
+if "chat_input" not in st.session_state:
+    st.session_state.chat_input = ""
 
 def predict_intent(text):
     inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True).to(device)
@@ -41,95 +62,82 @@ def predict_intent(text):
         outputs = model(**inputs)
 
     predicted_index = torch.argmax(outputs.logits, dim=1).item()
-    predicted_tag = intent_mapping.get(predicted_index, "unknown")  # Convert index to tag
-
-    if DEBUG:  # Only print if debugging is enabled
-        print(f"Predicted Index: {predicted_index}, Mapped Intent: {predicted_tag}")
-
-    return predicted_tag
+    return intent_mapping.get(predicted_index, "unknown")
 
 def get_response(intent_label):
-    if DEBUG:
-        print(f"Intent Label: {intent_label}")
-
     for intent in intents:
-        if DEBUG:
-            print(f"Checking: {intent['tag']}")
         if intent_label == intent['tag']:
             return random.choice(intent['responses'])
-
     return "I'm not sure how to respond to that."
 
-# Initialize session state for chat history
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
-if "chat_input" not in st.session_state:
-    st.session_state.chat_input = ""
-
 # Sidebar menu
 with st.sidebar:
+    st.image("Images/Bot Image.jpeg", use_container_width=True)
     st.title("💬 Chatbot Menu")
     add_vertical_space(1)
+
     if st.button("🆕 New Chat"):
-        st.session_state.chat_history = []
         st.session_state.chat_input = ""
-        st.rerun()
+        save_chat_history()
+
     if st.button("📜 Chat History"):
         st.session_state.show_history = True
+
     if st.button("ℹ️ About"):
         st.session_state.show_about = True
 
-# Modals for Chat History and About
+# Modal Windows (Chat History & About)
 history_modal = Modal("Chat History", key="history_modal")
 about_modal = Modal("About", key="about_modal")
 
-if "show_history" in st.session_state and st.session_state.show_history:
+# Display chat history without affecting the chat window
+if st.session_state.show_history:
     with history_modal.container():
         st.subheader("🕰 Chat History")
-        for chat in st.session_state.chat_history:
+        for chat in st.session_state.chat_history[-10:]:  # Show last 10 messages
             st.write(chat)
         if st.button("Close", key="close_history"):
-            st.session_state.show_history = False
+            st.session_state.show_history = False  # Close modal without resetting UI
             st.rerun()
 
-if "show_about" in st.session_state and st.session_state.show_about:
+if st.session_state.show_about:
     with about_modal.container():
         st.subheader("ℹ️ About")
-        st.info("This is an intent-based chatbot powered by BERT, built using Streamlit with an elegant UI.")
+        st.info("This is an intent-based chatbot powered by BERT, built using Streamlit.")
         if st.button("Close", key="close_about"):
-            st.session_state.show_about = False
+            st.session_state.show_about = False  # Close modal without resetting UI
             st.rerun()
 
 # Chat UI
 st.title("🤖 AI Chatbot")
 st.markdown("### Talk to me, I'm listening...")
 
-rain(
-    emoji="💬",
-    font_size=10,
-    falling_speed=5,
-    animation_length="infinite",
-)
-
-# User input
-st.session_state.chat_input = st.text_input("You:", st.session_state.chat_input, key="input")
-if st.session_state.chat_input:
-    intent_label = predict_intent(st.session_state.chat_input)
+rain(emoji="💬", font_size=10, falling_speed=5, animation_length="infinite")
+
+# Chat Input with Enter Button
+with st.form("chat_form", clear_on_submit=True):
+    chat_input = st.text_input("You:", key="chat_input")
+    submit_button = st.form_submit_button("Enter")
+
+if submit_button and chat_input:
+    intent_label = predict_intent(chat_input)
     response = get_response(intent_label)
     chat_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    st.session_state.chat_history.append(f"[{chat_time}] You: {st.session_state.chat_input}")
+
+    # Append messages to chat history (User & Bot)
+    st.session_state.chat_history.append(f"[{chat_time}] You: {chat_input}")
     st.session_state.chat_history.append(f"[{chat_time}] Bot: {response}")
 
-    # Display conversation
+    # Save chat history persistently
+    save_chat_history()
+
+    # Display conversation immediately
     with st.chat_message("user"):
-        st.markdown(f"**You:** {st.session_state.chat_input}")
+        st.markdown(f"**You:** {chat_input}")
         time.sleep(0.5)
     with st.chat_message("assistant"):
         st.markdown(f"**Bot:** {response}")
 
-    # Clear input box after sending
-    st.session_state.chat_input = ""
-
 # Style customization
 st.markdown("""
 <style>

requirements.txt

@@ -0,0 +1,12 @@
+streamlit
+torch
+transformers
+json
+os
+time
+datetime
+random
+streamlit_extras
+streamlit_extras.add_vertical_space
+streamlit_extras.let_it_rain
+streamlit_modal