Update app.py

app.py

@@ -1,10 +1,14 @@
-"""Gradio App for Veda Programming Assistant - Gradio 6.x compatible"""
+"""Gradio App for Veda Programming Assistant - Gradio 6.x compatible (with math solving)"""
 
 import gradio as gr
 import tensorflow as tf
 import os
 import json
 
+import re
+import ast
+import operator as op
+
 from model import VedaProgrammingLLM
 from tokenizer import VedaTokenizer
 from database import db
@@ -19,7 +23,7 @@ conversation_history = []  # used for building prompt context for the model
 current_conv_id = -1
 
 
-# --------- Helpers (IMPORTANT FIX) ----------
+# --------- Helpers (Gradio message parsing) ----------
 def extract_text(message):
     """
     Convert Gradio multimodal / messages objects -> plain string.
@@ -43,9 +47,8 @@ def extract_text(message):
     if isinstance(message, list):
         parts = []
         for part in message:
-            if isinstance(part, dict):
-                if part.get("type") == "text":
-                    parts.append(str(part.get("text", "")))
+            if isinstance(part, dict) and part.get("type") == "text":
+                parts.append(str(part.get("text", "")))
             elif isinstance(part, str):
                 parts.append(part)
         return "".join(parts).strip()
@@ -64,7 +67,12 @@ def ensure_messages_history(history):
         return []
 
     # Already messages format
-    if len(history) > 0 and isinstance(history[0], dict) and "role" in history[0] and "content" in history[0]:
+    if (
+        len(history) > 0
+        and isinstance(history[0], dict)
+        and "role" in history[0]
+        and "content" in history[0]
+    ):
         fixed = []
         for m in history:
             fixed.append({"role": m["role"], "content": extract_text(m["content"])})
@@ -79,6 +87,69 @@ def ensure_messages_history(history):
     return fixed
 
 
+# --------- Safe Math Solver ----------
+_ALLOWED_OPS = {
+    ast.Add: op.add,
+    ast.Sub: op.sub,
+    ast.Mult: op.mul,
+    ast.Div: op.truediv,
+    ast.Mod: op.mod,
+    ast.Pow: op.pow,
+    ast.USub: op.neg,
+    ast.UAdd: op.pos,
+}
+
+
+def safe_eval_math(expr: str):
+    """
+    Safely evaluate arithmetic expression (no variables, no function calls).
+    Supports: + - * / % ** and parentheses, integers/floats.
+    """
+    node = ast.parse(expr, mode="eval").body
+
+    def _eval(n):
+        if isinstance(n, ast.Constant) and isinstance(n.value, (int, float)):
+            return n.value
+        if isinstance(n, ast.BinOp) and type(n.op) in _ALLOWED_OPS:
+            return _ALLOWED_OPS[type(n.op)](_eval(n.left), _eval(n.right))
+        if isinstance(n, ast.UnaryOp) and type(n.op) in _ALLOWED_OPS:
+            return _ALLOWED_OPS[type(n.op)](_eval(n.operand))
+        raise ValueError("Unsupported expression")
+
+    return _eval(node)
+
+
+def try_math_answer(user_text: str):
+    """
+    If user text looks like a pure math expression, return computed answer as string.
+    Otherwise return None.
+    Examples:
+      "2+2=?" -> "4"
+      "2^5"   -> "32"
+      "(10+5)/3" -> "5"
+    """
+    if not user_text:
+        return None
+
+    # Normalize common decorations
+    s = user_text.strip()
+    s = s.replace("=", "").replace("?", "").strip()
+    s = s.replace("^", "**")  # allow ^ as power
+
+    # Only allow digits/operators/parentheses/dots/spaces
+    if not re.fullmatch(r"[0-9\.\s\+\-\*\/\(\)%]+", s):
+        return None
+
+    try:
+        val = safe_eval_math(s)
+        # pretty formatting: 4.0 -> 4
+        if isinstance(val, float) and val.is_integer():
+            val = int(val)
+        return str(val)
+    except Exception:
+        return None
+
+
 # --------- Model init ----------
 def initialize():
     """Initialize the assistant (load if exists, else train once)."""
@@ -145,18 +216,27 @@ def clean_response(text: str) -> str:
 
 
 def generate_response(user_input: str, temperature: float = 0.7, max_tokens: int = 200) -> str:
-    """Generate a response from the model."""
+    """Generate a response from the model OR solve math deterministically."""
     global current_conv_id, conversation_history
 
-    if model is None:
-        return "Model is loading, please wait..."
-
+    # Convert Gradio multimodal -> text
     user_input = extract_text(user_input).strip()
     if not user_input:
         return "Please type a message!"
 
+    # 1) Try math solver first
+    math_ans = try_math_answer(user_input)
+    if math_ans is not None:
+        # Save conversation too (optional)
+        conversation_history.append({"user": user_input, "assistant": math_ans})
+        current_conv_id = db.save_conversation(user_input, math_ans)
+        return math_ans
+
+    # 2) Otherwise use model
+    if model is None:
+        return "Model is loading, please wait..."
+
     try:
-        # Build context from last few turns (stored as plain strings)
         context = ""
         for msg in conversation_history[-3:]:
             context += f"<USER> {msg['user']}\n<ASSISTANT> {msg['assistant']}\n"
@@ -165,7 +245,6 @@ def generate_response(user_input: str, temperature: float = 0.7, max_tokens: int
 
         tokens = tokenizer.encode(prompt)
 
-        # Truncate to leave room for generation
         if len(tokens) > model.max_length - max_tokens:
             tokens = tokens[-(model.max_length - max_tokens):]
 
@@ -180,7 +259,6 @@ def generate_response(user_input: str, temperature: float = 0.7, max_tokens: int
 
         response = tokenizer.decode(generated)
 
-        # Extract assistant portion only
         if "<ASSISTANT>" in response:
             response = response.split("<ASSISTANT>")[-1].strip()
         if "<USER>" in response:
@@ -191,10 +269,7 @@ def generate_response(user_input: str, temperature: float = 0.7, max_tokens: int
         if not response:
             response = "I'm not sure how to respond to that. Could you try rephrasing?"
 
-        # Save for future context
         conversation_history.append({"user": user_input, "assistant": response})
-
-        # Save in DB
         current_conv_id = db.save_conversation(user_input, response)
 
         return response
@@ -207,10 +282,7 @@ def generate_response(user_input: str, temperature: float = 0.7, max_tokens: int
 
 # --------- Gradio handlers ----------
 def respond(message, history, temperature, max_tokens):
-    """
-    Chat function for Gradio Chatbot.
-    IMPORTANT: Always return messages-format history.
-    """
+    """Always return messages-format history."""
     history = ensure_messages_history(history)
 
     user_text = extract_text(message).strip()
@@ -252,7 +324,6 @@ def retrain(epochs):
     global model, tokenizer
 
     good_convs = db.get_good_conversations()
-
     if not good_convs:
         return "No approved conversations yet. Rate some responses as 'Good' first!"
 
@@ -295,22 +366,18 @@ with gr.Blocks(title="Veda Programming Assistant") as demo:
         """
 # 🕉️ Veda Programming Assistant
 
-I can **chat**, **write code**, **explain concepts**, and **answer questions**!
+Now supports **math** (e.g., `2+2=?`, `(10+5)/3`, `2^5`) plus coding/chatting.
 """
     )
 
     with gr.Tabs():
         with gr.TabItem("💬 Chat"):
-            chatbot = gr.Chatbot(
-                label="Conversation",
-                height=400,
-                value=[],
-            )
+            chatbot = gr.Chatbot(label="Conversation", height=400, value=[])
 
             with gr.Row():
                 msg = gr.Textbox(
                     label="Your message",
-                    placeholder="Ask me anything about programming...",
+                    placeholder="Ask me anything about programming... or type math like 2+2=?",
                     lines=2,
                     scale=4,
                 )
@@ -327,31 +394,22 @@ I can **chat**, **write code**, **explain concepts**, and **answer questions**!
 
             feedback_msg = gr.Textbox(label="Status", lines=1, interactive=False)
 
-            send_btn.click(
-                respond,
-                inputs=[msg, chatbot, temperature, max_tokens],
-                outputs=[msg, chatbot],
-            )
-            msg.submit(
-                respond,
-                inputs=[msg, chatbot, temperature, max_tokens],
-                outputs=[msg, chatbot],
-            )
+            send_btn.click(respond, inputs=[msg, chatbot, temperature, max_tokens], outputs=[msg, chatbot])
+            msg.submit(respond, inputs=[msg, chatbot, temperature, max_tokens], outputs=[msg, chatbot])
 
             good_btn.click(feedback_good, outputs=feedback_msg)
             bad_btn.click(feedback_bad, outputs=feedback_msg)
             clear_btn.click(clear_chat, outputs=[chatbot, feedback_msg])
 
-            gr.Markdown("### 💡 Try these examples:")
+            gr.Markdown("### 💡 Examples")
             gr.Examples(
                 examples=[
                     ["2+2=?"],
-                    ["Hello! What can you do?"],
+                    ["(10+5)/3"],
+                    ["2^8"],
                     ["What is Python?"],
                     ["Write a function to calculate factorial"],
-                    ["Explain what recursion is"],
-                    ["How do I read a file in Python?"],
-                    ["Write a bubble sort algorithm"],
+                    ["Explain recursion"],
                 ],
                 inputs=msg,
             )
@@ -377,7 +435,7 @@ I can **chat**, **write code**, **explain concepts**, and **answer questions**!
             refresh_btn = gr.Button("🔄 Refresh Statistics")
             refresh_btn.click(get_stats, outputs=stats_out)
 
-    gr.Markdown("---\n**Veda Programming Assistant** - Learning from every conversation!")
+    gr.Markdown("---\n**Veda Programming Assistant**")
 
 
 if __name__ == "__main__":