updatation

app.py

@@ -1,19 +1,21 @@
-# app.py — from local backup
+# app.py
 
 import gradio as gr
 import os
 import tempfile
 import textwrap
 from datetime import datetime
-from pathlib import Path
 from typing import List, Dict, Any, Optional
+from reportlab.lib.pagesizes import A4
+from reportlab.pdfgen import canvas
 
 from src.model_loader import load_local_model
 from src.conversation import ConversationMemory
 from src.chatbot import LocalChatbot
 
-
-
+# -----------------------
+# Initialize
+# -----------------------
 llm = load_local_model()
 memory = ConversationMemory()
 bot = LocalChatbot(llm, memory)
@@ -30,34 +32,20 @@ def now_ts():
 
 
 # ----------------------
-# EXPORT TXT/PDF
+# Export TXT/PDF
 # ----------------------
-import os
-import tempfile
-import textwrap
-from datetime import datetime
-from typing import List, Dict, Optional
-from reportlab.lib.pagesizes import A4
-from reportlab.pdfgen import canvas
-
-def export_chat_files(history: List[Dict[str, any]]) -> Dict[str, Optional[str]]:
+def export_chat_files(history: List[Dict[str, Any]]) -> Dict[str, Optional[str]]:
     tmpdir = tempfile.gettempdir()
     timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
     txt_path = os.path.join(tmpdir, f"chat_history_{timestamp}.txt")
     pdf_path = os.path.join(tmpdir, f"chat_history_{timestamp}.pdf")
 
-
     def remove_last_closing_line(lines):
         closing_keywords = [
-            "let me know", "is there anything else",
-            "anything else i can help", "feel free to ask",
-            "hope this helps", "need further assistance",
-            "feel free", "happy to help",
-            "hello! how can i assist you today?",
-            "are there any specific industries or areas you'd like to explore in more detail?",
-            "how can i help you better?", "what did you like about our interaction?",
-            "do you have any feedback on your experience?", "would you like to explore",
-            "need clarification"
+            "let me know", "is there anything else", "anything else i can help",
+            "feel free to ask", "hope this helps", "need further assistance",
+            "feel free", "happy to help", "hello! how can i assist you today?",
+            "how can i help you better?", "would you like to explore", "need clarification"
         ]
         if not lines:
             return lines
@@ -66,22 +54,18 @@ def export_chat_files(history: List[Dict[str, any]]) -> Dict[str, Optional[str]]
             return lines[:-1]
         return lines
 
-    # ---------------- TXT FILE ----------------
+    # TXT
     with open(txt_path, "w", encoding="utf-8") as f:
         for msg in history:
-            content_data = msg.get("content", "")
-            if isinstance(content_data, dict):
-                content = content_data.get("text", "")
-            else:
-                content = str(content_data)
-
-            lines = content.splitlines()
-            clean = [l.strip() for l in lines if l.strip() and not l.strip().startswith("🕒")]
-            clean = remove_last_closing_line(clean)
-            f.write("\n".join(clean) + "\n\n")
+            content = msg.get("content", "")
+            if isinstance(content, dict):
+                content = content.get("text", "")
+            lines = [l.strip() for l in str(content).splitlines() if l.strip() and not l.strip().startswith("🕒")]
+            lines = remove_last_closing_line(lines)
+            f.write("\n".join(lines) + "\n\n")
             f.write("-" * 60 + "\n\n")
 
-    # ---------------- PDF FILE ----------------
+    # PDF
     try:
         c = canvas.Canvas(pdf_path, pagesize=A4)
         page_width, page_height = A4
@@ -89,41 +73,37 @@ def export_chat_files(history: List[Dict[str, any]]) -> Dict[str, Optional[str]]
         y = page_height - margin
         line_height = 14
         font_size = 10
-
         c.setFont("Helvetica", font_size)
 
         for msg in history:
             role = msg.get("role", "user").capitalize()
-            content_data = msg.get("content", "")
-            if isinstance(content_data, dict):
-                content = content_data.get("text", "")
-            else:
-                content = str(content_data) 
+            content = msg.get("content", "")
+            if isinstance(content, dict):
+                content = content.get("text", "")
 
-            lines = content.splitlines()
-            clean_lines = [l.strip() for l in lines if l.strip()]
-            clean_lines = remove_last_closing_line(clean_lines)
+            lines = [l.strip() for l in str(content).splitlines() if l.strip() and not l.strip().startswith("🕒")]
+            lines = remove_last_closing_line(lines)
 
-            for line in clean_lines:
+            for line in lines:
                 wrapped = textwrap.wrap(line, width=95)
                 for wline in wrapped:
                     if y < margin + line_height:
                         c.showPage()
                         c.setFont("Helvetica", font_size)
                         y = page_height - margin
-                    c.drawString(margin, y, f"{role}: {wline}" if role=="User" else wline)
+                    c.drawString(margin, y, f"{role}: {wline}")
                     y -= line_height
-
-            y -= line_height  # spacing between messages
+            y -= line_height
 
         c.showPage()
         c.save()
     except Exception as e:
         print("PDF export failed:", e)
         pdf_path = None
-    
+
     return {"txt": txt_path, "pdf": pdf_path}
 
+
 # ----------------------
 # Core chat function
 # ----------------------
@@ -134,6 +114,7 @@ def generate_reply(user_msg: str, history: Optional[List[Dict[str, Any]]]):
     if not user_msg.strip():
         return history
 
+    # Detect intent prefix from templates
     intent = None
     low = user_msg.lower()
     for key in INTENT_TEMPLATES:
@@ -142,19 +123,13 @@ def generate_reply(user_msg: str, history: Optional[List[Dict[str, Any]]]):
             user_msg = user_msg[len(key):].strip()
             break
 
-
-    system_prefix = INTENT_TEMPLATES.get(intent, None)
-    if system_prefix:
-        prompt = f"{system_prefix}\nUser: {user_msg}"
-    else:
-        prompt = f"User: {user_msg}"
-
-    bot_reply = bot.ask(prompt)
+    # Ask chatbot (pass intent)
+    bot_reply = bot.ask(user_msg, intent=intent)
     ts = now_ts()
     bot_reply_ts = f"{bot_reply}\n\n🕒 {ts}"
 
-    history.append({"role": "user", "content": user_msg})
-    history.append({"role": "assistant", "content": bot_reply_ts})
+    history.append({"role": "user", "content": str(user_msg)})
+    history.append({"role": "assistant", "content": str(bot_reply_ts)})
 
     try:
         memory.add(user_msg, bot_reply)
@@ -165,7 +140,7 @@ def generate_reply(user_msg: str, history: Optional[List[Dict[str, Any]]]):
 
 
 # ----------------------
-# CUSTOM CSS
+# UI / Gradio
 # ----------------------
 CUSTOM_CSS = """
 /* GLOBAL */
@@ -205,7 +180,6 @@ CUSTOM_CSS = """
     padding: 12px;
 }
 
-
 /* Input box */
 #message-box textarea {
     background: #e0e7ff !important;
@@ -219,9 +193,8 @@ CUSTOM_CSS = """
     color: white !important;
     transition: background 0.2s ease, transform 0.2s ease;
 }
-
 .send-btn:hover {
-    background: #4338ca !important; /* darker indigo */
+    background: #4338ca !important;
     transform: scale(1.05);
 }
 
@@ -230,18 +203,12 @@ CUSTOM_CSS = """
     background: #f1f5f9 !important;
     transition: background 0.2s ease, transform 0.2s ease;
 }
-
 .icon-btn:hover {
-    background: #e2e8f0 !important; /* slightly darker */
+    background: #e2e8f0 !important;
     transform: scale(1.05);
 }
-
 """
 
-#----------------------
-#JS (Voice only)
-#----------------------
-
 PAGE_JS = """
 <script>
 (function(){
@@ -260,8 +227,6 @@ PAGE_JS = """
 
     recog.onresult = function(e){
       textarea.value = e.results[0][0].transcript;
-
-      // Visual flash to confirm input
       textarea.style.background = "#e7f5ff";
       setTimeout(() => { textarea.style.background = ""; }, 400);
     };
@@ -272,33 +237,20 @@ PAGE_JS = """
 </script>
 """
 
-# ----------------------
-# UI
-# ----------------------
 with gr.Blocks(title="Tayyab — Chatbot") as demo:
-    gr.HTML(f"""
-    <style>{CUSTOM_CSS}</style>
-    <script>{PAGE_JS}</script>
-    """)
+    gr.HTML(f"<style>{CUSTOM_CSS}</style><script>{PAGE_JS}</script>")
 
     with gr.Row():
         with gr.Column(scale=1, min_width=220):
             gr.Markdown("### ⚡ Tools & Export")
-
             new_chat_btn = gr.Button("➕ New Chat")
             export_btn = gr.Button("📥 Export TXT/PDF")
 
         with gr.Column(scale=3, elem_id="main_card"):
             gr.Markdown("<h3>Smart Learning Assistant - Tayyab</h3>")
             chatbot = gr.Chatbot(height=480, elem_id="chatbot_box")
-
             with gr.Row():
-                msg = gr.Textbox(
-                    placeholder="Type a message or use the mic",
-                    elem_id="message-box",
-                    show_label=False,
-                    lines=3,
-                )
+                msg = gr.Textbox(placeholder="Type a message or use the mic", elem_id="message-box", show_label=False, lines=3)
                 send_btn = gr.Button("Send", elem_classes="send-btn")
                 mic_btn = gr.Button("🎤 Voice input", elem_classes="icon-btn")
                 mic_btn.click(None, None, None, js='startVoiceRecognition("message-box")')
@@ -315,19 +267,14 @@ with gr.Blocks(title="Tayyab — Chatbot") as demo:
 
     new_chat_btn.click(new_chat, outputs=[chatbot])
 
-
     def export_handler(history):
-        # history is already list of dicts: [{"role": "...", "content": "..."}]
         files = export_chat_files(history or [])
-
         return (
             gr.update(value=files.get("txt"), visible=True),
             gr.update(value=files.get("pdf"), visible=bool(files.get("pdf")))
         )
 
-
     export_btn.click(export_handler, inputs=[chatbot], outputs=[file_txt, file_pdf])
-    
-    
+
 if __name__ == "__main__":
     demo.launch()

src/chatbot.py

@@ -1,35 +1,33 @@
 # src/chatbot.py
 
 from typing import Dict, Any, Optional
-from src.intent import detect_intent
 from src.templates import TEMPLATES
+from src.intent import detect_intent
 
-# -------------------------------
-# DEFAULT GENERATION ARGUMENTS
-# -------------------------------
+MSG_SEPARATOR = "\n"
 
 DEFAULT_GEN_ARGS = {
-    "max_tokens": 350,     
-    "temperature": 0.6,    
-    "top_p": 0.9           
+    "max_tokens": 350,
+    "temperature": 0.6,
+    "top_p": 0.9
 }
 
-
-MSG_SEPARATOR = "\n"
-
-
 class LocalChatbot:
     def __init__(self, llm, memory, default_template: Optional[str] = "general"):
         self.llm = llm
         self.memory = memory
         self.default_template = default_template
 
+    # ------------------------------------------------
+    # Build system prompt based on intent
+    # ------------------------------------------------
     def _build_system_prompt(self, intent: str) -> str:
-        # get template for intent
         return TEMPLATES.get(intent, TEMPLATES.get(self.default_template, TEMPLATES["general"]))
 
+    # ------------------------------------------------
+    # Build full prompt with memory and user message
+    # ------------------------------------------------
     def _build_prompt(self, user_message: str, intent: str, max_pairs: int = 12) -> str:
-        # Trim memory to recent pairs before building prompt
         try:
             self.memory.trim_to_recent_pairs(max_pairs)
         except Exception:
@@ -37,44 +35,52 @@ class LocalChatbot:
 
         system_prompt = self._build_system_prompt(intent)
         history_text = self.memory.get_formatted(separator=MSG_SEPARATOR)
-     
-        parts = [
-                    f"System: {system_prompt}",
-                    history_text,
-                    f"User: {user_message}",
-                    "Assistant:"
-                ]
-                # join non-empty parts
-        return MSG_SEPARATOR.join([p for p in parts if p is not None and p != ""])
-
 
-    def ask(self, user_message: str, gen_args: Optional[Dict[str, Any]] = None) -> str:
-        if not user_message or not user_message.strip():
+        parts = [
+            f"System: {system_prompt}",
+            history_text,
+            f"User: {user_message}",
+            "Assistant:"
+        ]
+
+        return MSG_SEPARATOR.join([p for p in parts if p])
+
+    # ------------------------------------------------
+    # Main ask function
+    # ------------------------------------------------
+    def ask(self, user_message: Any, gen_args: Optional[Dict[str, Any]] = None, intent: Optional[str] = None) -> str:
+        # Extract text if passed from Gradio
+        if isinstance(user_message, list):
+            user_message = "\n".join([item.get("text", "") if isinstance(item, dict) else str(item) for item in user_message])
+        elif isinstance(user_message, dict) and "text" in user_message:
+            user_message = user_message["text"]
+
+        user_message = str(user_message).strip()
+        if not user_message:
             return "Please enter a message."
 
-        # Detect intent
-        intent = detect_intent(user_message)
+        # Use passed intent or detect
+        if intent is None:
+            intent = detect_intent(user_message)
 
         # Build prompt
         prompt = self._build_prompt(user_message, intent, max_pairs=12)
 
-
-   # Merge generation args
+        # Merge generation args
         gen = DEFAULT_GEN_ARGS.copy()
         if gen_args:
             gen.update(gen_args)
 
-        # Attempt to call the LLM (defensive: handle different API variants)
+        # Call LLM
         try:
             output = self.llm(prompt, **gen)
         except TypeError:
-            # fallback mapping: map max_tokens -> max_new_tokens
             alt_gen = gen.copy()
             if "max_tokens" in alt_gen:
                 alt_gen["max_new_tokens"] = alt_gen.pop("max_tokens")
             output = self.llm(prompt, **alt_gen)
 
-        # Parse the output robustly
+        # Parse output
         bot_reply = ""
         try:
             if isinstance(output, dict) and "choices" in output:
@@ -89,7 +95,7 @@ class LocalChatbot:
         if not bot_reply:
             bot_reply = "Sorry — I couldn't generate a response. Please try again."
 
-        # Add to memory
+        # Store memory
         try:
             self.memory.add(user_message, bot_reply)
         except Exception:
@@ -100,27 +106,3 @@ class LocalChatbot:
                 pass
 
         return bot_reply
-
-
-    
-    
-    # # Create the generation args HERE
-    #     gen = DEFAULT_GEN_ARGS.copy()
-    #     if gen_args:
-    #         gen.update(gen_args)
-            
-    #     response = self.llm(
-    #         prompt,
-    #         max_tokens=gen["max_tokens"],
-    #         temperature=gen["temperature"],
-    #         top_p=gen["top_p"],
-
-    #         stop=["</system>", "\nUser:", "\nUser says:", "\nSystem:", "\nAssistant:", "\nYou:"]
-
-
-    #     )
-
-    #     reply = response["choices"][0]["text"].strip()
-
-    #     self.memory.add(user_message, reply)
-    #     return reply