app.py

# app.py — from local backup

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 src.model_loader import load_local_model
from src.conversation import ConversationMemory
from src.chatbot import LocalChatbot



llm = load_local_model()
memory = ConversationMemory()
bot = LocalChatbot(llm, memory)

INTENT_TEMPLATES = {
    "math": "You are a math solver. Solve step-by-step only.",
    "code": "You are a coding expert. Provide clean, working code.",
    "civics": "Explain clearly like a Class 10 SST teacher.",
    "exam": "Prepare concise exam-focused notes and important questions."
}

def now_ts():
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")


# ----------------------
# EXPORT TXT/PDF
# ----------------------
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")

    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"
        ]
        if not lines:
            return lines
        last = lines[-1].lower().strip()
        if any(k in last for k in closing_keywords):
            return lines[:-1]
        return lines

    with open(txt_path, "w", encoding="utf-8") as f:
        for msg in history:
            content = msg.get("content", "")
            lines = content.splitlines()

            clean = [l for l in lines if not l.strip().startswith("🕒")]
            if clean and clean[0].startswith("**"):
                clean = clean[1:]
            clean = [l for l in clean if not set(l) == {"-"}]
            clean = [l.replace("USER:", "").replace("ASSISTANT:", "").strip() for l in clean]

            clean = remove_last_closing_line(clean)
            f.write("\n".join(clean).strip() + "\n")
            f.write("-" * 60 + "\n")

    pdf_path = None
    try:
        from reportlab.lib.pagesizes import A4
        from reportlab.pdfgen import canvas

        pdf_path = os.path.join(tmpdir, f"chat_history_{timestamp}.pdf")
        c = canvas.Canvas(pdf_path, pagesize=A4)
        width, height = A4
        margin = 40
        textobject = c.beginText(margin, height - margin)
        textobject.setFont("Helvetica", 10)
        with open(txt_path, "r", encoding="utf-8") as fh:
            for line in fh:
                for wrapped in textwrap.wrap(line.rstrip(), 100):
                    textobject.textLine(wrapped)
        c.drawText(textobject)
        c.showPage()
        c.save()
    except:
        pdf_path = None

    return {"txt": txt_path, "pdf": pdf_path}


# ----------------------
# Core chat function
# ----------------------
def generate_reply(user_msg: str, history: Optional[List[Dict[str, Any]]]):
    if history is None:
        history = []

    if not user_msg.strip():
        return history

    intent = None
    low = user_msg.lower()
    for key in INTENT_TEMPLATES:
        if low.startswith(key):
            intent = key
            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)
    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})

    try:
        memory.add(user_msg, bot_reply)
    except:
        pass

    return history


# ----------------------
# CUSTOM CSS
# ----------------------
CUSTOM_CSS = """
/* GLOBAL */
.gradio-container { 
    background: linear-gradient(135deg, #f6f7f9 0%, #e9ecf1 100%);
    font-family: Inter, system-ui;
}
#main_card h3 {
    font-size: 28px !important;
    font-weight: 700 !important;
    background: linear-gradient(90deg, #0ea5e9, #06b6d4);
    -webkit-background-clip: text;
    -webkit-text-fill-color: transparent;
    text-align: center;
    border-bottom: 2px solid rgba(0,0,0,0.15);
}

/* MAIN CARD */
#main_card { 
    background: #ffffff;
    border: 1px solid #e3e8ef;
    border-radius: 16px;
    padding: 16px;
    box-shadow: 0 4px 16px rgba(0,0,0,0.05);
}

/* Chat UI */
.gradio-chatbot .assistant {
    background: #4f46e5 !important;
    color: white !important;
    border-radius: 14px;
    padding: 12px;
}
.gradio-chatbot .user {
    background: #f1f5f9 !important;
    border-radius: 14px;
    padding: 12px;
}


/* Input box */
#message-box textarea {
    background: #e0e7ff !important;
    border-radius: 12px !important;
    font-size: 24px !important;
}

/* Send button */
.send-btn {
    background: #4f46e5 !important;
    color: white !important;
    transition: background 0.2s ease, transform 0.2s ease;
}

.send-btn:hover {
    background: #4338ca !important; /* darker indigo */
    transform: scale(1.05);
}

/* Mic / Voice input button */
.icon-btn {
    background: #f1f5f9 !important;
    transition: background 0.2s ease, transform 0.2s ease;
}

.icon-btn:hover {
    background: #e2e8f0 !important; /* slightly darker */
    transform: scale(1.05);
}

"""

#----------------------
#JS (Voice only)
#----------------------

PAGE_JS = """
<script>
(function(){
  window.startVoiceRecognition = function(elem_id){
    const wrapper = document.getElementById(elem_id);
    if(!wrapper) return;
    const textarea = wrapper.querySelector('textarea');
    if(!textarea) return;

    const SR = window.SpeechRecognition || window.webkitSpeechRecognition;
    if(!SR) return alert('Speech recognition not supported');

    const recog = new SR();
    recog.lang = 'en-US';
    recog.interimResults = false;

    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);
    };

    recog.start();
  };
})();
</script>
"""

# ----------------------
# UI
# ----------------------
with gr.Blocks(css=CUSTOM_CSS, title="Tayyab — Chatbot") as demo:
    gr.HTML(PAGE_JS)

    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, type="messages", 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,
                )
                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")')

    file_txt = gr.File(visible=False)
    file_pdf = gr.File(visible=False)

    send_btn.click(generate_reply, inputs=[msg, chatbot], outputs=[chatbot])
    msg.submit(generate_reply, inputs=[msg, chatbot], outputs=[chatbot])

    def new_chat():
        memory.clear()
        return []

    new_chat_btn.click(new_chat, outputs=[chatbot])

    def export_handler(history):
        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()