app.py

import streamlit as st
import os
import re
from query_chat import GeminiQanA
from pathlib import Path

def extract_text_from_txt(file_path):
    # In a real scenario, handle FileNotFoundError
    try:
        with open(file_path, "r", encoding="utf-8") as file:
            return " ".join([line.strip() for line in file.readlines() if line.strip()])
    except FileNotFoundError:
        st.warning(f"File not found: {file_path}. Using placeholder text.")
        return f"Placeholder text for {os.path.basename(file_path)}"

def load_css(file_name):
    """Loads a CSS file and injects it into the Streamlit app."""
    try:
        css_path = Path(__file__).parent / file_name
        with open(css_path) as f:
            st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
        # st.info(f"Loaded CSS: {file_name}") # Optional: uncomment for debugging
    except FileNotFoundError:
        st.error(f"CSS file not found: {file_name}. Make sure it's in the same directory as app.py.")
    except Exception as e:
        st.error(f"Error loading CSS file {file_name}: {e}")
        
@st.cache_resource()
def load_chatbot():
    print("Attempting to load chatbot...") # Add print statement
    with st.spinner("Loading project information..."):
        # Use dummy paths if Files/ directory doesn't exist or is empty
        doc1_text = extract_text_from_txt("Files/brochure_1.txt")
        doc2_text = extract_text_from_txt("Files/brochure_2.txt")
        chatbot_instance = GeminiQanA(doc1_text, doc2_text)
        print("Chatbot loaded.") # Add print statement
        return chatbot_instance

# Streamlit App Configuration
st.set_page_config(page_title="Zega AI Sales Agent", page_icon="🤖", layout="centered")

st.markdown("""
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Inter+Tight:ital,wght@0,100..900;1,100..900&family=Space+Grotesk:wght@300..700&display=swap" rel="stylesheet">
""", unsafe_allow_html=True)
load_css("style.css")

st.sidebar.markdown("### Welcome to Zega AI Sales Agent!")
st.sidebar.markdown("Ask anything about our team's capabilities and projects.")

# Load API key safely (using dummy key for this example if not set)
if "GOOGLE_API_KEY" in st.secrets:
    os.environ["GOOGLE_API_KEY"] = st.secrets["GOOGLE_API_KEY"]
else:
    # For local testing without secrets, you might uncomment the next line
    # os.environ["GOOGLE_API_KEY"] = "YOUR_DUMMY_OR_REAL_API_KEY"
    st.sidebar.warning("Google API key not found in Streamlit secrets. Using demo mode.")

# --- Initialize Chatbot ---
# Ensure chatbot is loaded before defining callbacks that use it
try:
    chatbot = load_chatbot()
except Exception as e:
    st.error(f"Failed to load chatbot: {e}")
    st.stop() # Stop execution if chatbot fails to load

# --- Initialize Session State ---
if "messages" not in st.session_state:
    st.session_state.messages = []
# Initialize the input field state (important!)
if "question_input" not in st.session_state:
    st.session_state.question_input = ""

# --- Initialize session state if not already present ---
if "asked_ai" not in st.session_state:
    st.session_state.asked_ai = False

def handle_ask_ai():
    """Callback function for the 'Ask AI' button."""
    question = st.session_state.question_input  # Get question from state
    if question:

        st.session_state.messages.append({"role": "user", "content": question})

        try:
            answer = chatbot.answer_question(question)
            st.session_state.messages.append({"role": "assistant", "content": answer})
        except Exception as e:
            st.error(f"Error getting answer from chatbot: {e}")

        st.session_state.question_input = ""  # Clear input after processing



def handle_clear_chat():
    """Callback function for the 'Clear Chat' button."""
    st.session_state.messages = []
    chatbot.clear_conv_history()
    st.session_state.question_input = "" # Clear the input field state as well
    # No explicit st.rerun() needed here, on_click handles the rerun

# --- Chat UI ---
st.title("📄 Zega AI Sales Agent")

# Function to display messages and replace image tags with actual images
def display_message(role, content):
     with st.chat_message(role):
        # Find all image tags in the response (Corrected regex)
        image_tags = re.findall(r"\[(.*?\.png)\]", content) # Find content inside brackets ending with .png

        # Split response by image tags and process separately
        parts = re.split(r"(\[.*?\.png\])", content) # Keep the delimiters

        for part in parts:
            if not part: # Skip empty strings from split
                continue
            match = re.match(r"\[(.*?\.png)\]", part) # Check if the part IS an image tag
            if match:
                image_filename = match.group(1)
                # Assuming images are in a subfolder relative to the script
                # Make sure the ZegaPos folder exists or handle the error
                image_folder = "ZegaPos"
                if not os.path.isdir(image_folder):
                     st.warning(f"Image folder '{image_folder}' not found.")
                     st.markdown(f"_{image_filename}_") # Display filename as text fallback
                     continue # Skip trying to display the image

                image_path = os.path.join(image_folder, image_filename)
                if os.path.exists(image_path):
                    st.image(image_path, use_container_width=True)
                else:
                    st.markdown(f"⚠️ Image `{image_filename}` not found at `{image_path}`.")
            else:
                # Otherwise, display text
                st.markdown(part)


# --- Display Chat History ---
# This loop runs on every rerun, displaying the current state of messages
for message in st.session_state.messages:
    display_message(message["role"], message["content"])

# --- Chat Input using st.chat_input (Handles Enter automatically) ---
prompt = st.chat_input("Ask a question about Zega AI:")
if prompt:
    # 1. Add user message to chat history immediately
    st.session_state.messages.append({"role": "user", "content": prompt})

    # 2. Display the user message (using your existing function)
    display_message("user", prompt)

    # 3. Get and display AI response
    try:
        with st.spinner("Thinking..."): # Optional: Add spinner for feedback
            answer = chatbot.answer_question(prompt)
        st.session_state.messages.append({"role": "assistant", "content": answer})
        # Display the assistant message immediately after getting it
        display_message("assistant", answer)
    except Exception as e:
        st.error(f"Error getting answer from chatbot: {e}")
        # Optionally add an error message to the chat history
        # st.session_state.messages.append({"role": "assistant", "content": f"Sorry, an error occurred: {e}"})
        # display_message("assistant", f"Sorry, an error occurred: {e}")

    # No need to manually clear st.session_state.question_input
    # st.chat_input handles its state internally upon submission.
    # Streamlit automatically reruns after processing the input block.

# --- Clear Chat Button (Keep this separate) ---
# Place it where you want it, maybe in the sidebar or below the chat input
st.markdown("""
    <style>
    .stButton > button {
        color: white !important;
        background-color: #ff4b4b; /* optional: red background for the trash button */
    }
    </style>
    """, unsafe_allow_html=True)
if st.sidebar.button("🗑️ Clear Chat"):
    st.session_state.messages = []
    if 'chatbot' in globals() and hasattr(chatbot, 'clear_conv_history'):
        chatbot.clear_conv_history()
    # st.session_state.question_input is no longer used, so no need to clear it
    st.rerun() # Rerun to reflect the cleared chat visually
    
import streamlit.components.v1 as components
components.html(
    """
    <script>
      function sendHeightWhenReady() {
        const el = window.parent.document.getElementsByClassName('stMain')[0];
        if (el) {
          const height = el.scrollHeight;
          console.log("Sending height to parent:", height);
          window.parent.parent.postMessage({ type: 'setHeight', height: height }, '*');
        } else {
          // Retry in 100ms until the element appears
          setTimeout(sendHeightWhenReady, 1000);
        }
      }

      window.onload = sendHeightWhenReady;
      window.addEventListener('resize', sendHeightWhenReady);
      setInterval(sendHeightWhenReady, 1000);
    </script>
    """
)