"""
ShazaTwin - AI Assistant

A Gradio-based chatbot that acts as a digital twin for Shaza Aly,
answering questions about skills, experience, and background.
"""

import os
import gradio as gr
from openai import OpenAI
from dotenv import load_dotenv
from pypdf import PdfReader

# --- 1. Load Environment Variables and API Keys ---
load_dotenv(override=True)

api_key = os.getenv("OPENROUTER_API_KEY")
cv_link = os.getenv("CV_LINK")
name = os.getenv("NAME")

if not api_key:
    raise ValueError("OPENROUTER_API_KEY not found in .env file. Please set it.")

# --- 2. Initialize OpenAI Client ---
client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key=api_key
)

# --- 3. THEME CUSTOMIZATION ---
# Using a cheerful theme with vibrant colors
cheerful_theme = gr.themes.Soft(
    primary_hue=gr.themes.colors.purple,
    secondary_hue=gr.themes.colors.pink,
    font=gr.themes.GoogleFont("Poppins")
)

# --- 4. Prepare Context for the Chatbot ---
summary = (
    "I am a 3 years experienced Backend Software Engineer with a strong focus on building scalable, well-architected systems "
    "using NestJS, GraphQL, and PostgreSQL. I have proven experience in developing high-performance APIs, "
    "applying Domain-Driven Design (DDD), and leading AI-powered solutions such as RAG-based chatbots "
    "integrated with vector databases like Qdrant and Pinecone. I am skilled in clean architecture, "
    "microservices, and production-grade e-commerce systems, and I'm adept at bridging business needs with "
    "technical implementation through both code and technical writing. I have contributed to real-time systems "
    "using gRPC, Redis, and message queues (e.g., RabbitMQ). I'm passionate about automation, developer "
    "tools (e.g., n8n, Copilot, Cursor), and mentoring through technical content. As an ALX alumna, I have a "
    "hands-on mindset and a continuous learning attitude. I am also the author of a technical blog on "
    "software engineering and AI systems: shazaali.substack.com. "
    "I worked on projects like: Mediconsult, E-commerce, and more. So proud of RAG chatbot I built for suplyd.app"
)
linkedin_text = "My LinkedIn Profile: https://www.linkedin.com/in/shazaali/\n\n"
try:
    reader = PdfReader("linkedin.pdf")
    for page in reader.pages:
        linkedin_text += page.extract_text() + "\n"
except FileNotFoundError:
    print("Warning: 'linkedin.pdf' not found. The bot will rely only on the summary.")
    linkedin_text = "LinkedIn profile data is not available."

system_prompt = (
    f"You are acting as {name}. You are answering questions on my personal website, "
    f"particularly questions related to my career, background, skills, and experience. "
    f"Your responsibility is to represent me as faithfully as possible. "
    f"You are given a summary of my background and my LinkedIn profile to use for answering questions. "
    f"Be professional, friendly, and engaging, as if you are talking to a potential client or future employer. "
    f"If you don't know the answer based on the provided context, it's better to say so than to invent information. "
    f"Always stay in character as {name}. Answer in the same language as the user's question without disclosing any private information."
    f"\n\n## My Summary:\n{summary}\n\n## My LinkedIn Profile Text:\n{linkedin_text}\n\n## My CV:\n{cv_link}"
)

# --- 5. Define the Chat Function ---
def chat(message, history):
    formatted_history = []
    for user_msg, assistant_msg in history:
        formatted_history.append({"role": "user", "content": user_msg})
        formatted_history.append({"role": "assistant", "content": assistant_msg})

    messages = [
        {"role": "system", "content": system_prompt},
        *formatted_history,
        {"role": "user", "content": message}
    ]

    try:
        response = client.chat.completions.create(
            model="openai/gpt-3.5-turbo",
            max_tokens=300,
            messages=messages,
            temperature=0.7
        )
        return response.choices[0].message.content
    except Exception as e:
        print(f"An error occurred: {e}")
        return "Sorry, I encountered an error while processing your request. Please try again."

# --- 6. Create and Launch the Gradio App with Your Custom CSS ---

# The magic happens here: fill_height=True and your refined CSS.
with gr.Blocks(
    theme=cheerful_theme,
    fill_height=True,  # This is crucial for making the app fill the HF Space vertically
    css="""
    /* --- Global Layout & Background --- */
    #root, .gradio-container {
        background: linear-gradient(135deg, #f5f7fa 0%, #e4e8ff 100%) !important;
    }

    /* --- Titles & Headers --- */
    h1 {
        font-size: 42px !important;
        font-weight: 700 !important;
        background: linear-gradient(90deg, #9333ea, #e879f9);
        -webkit-background-clip: text;
        -webkit-text-fill-color: transparent;
        text-shadow: 0px 2px 4px rgba(0,0,0,0.1);
        text-align: center !important;
        padding-top: 20px !important;
    }

    /* --- Example Prompts Section --- */
    .examples-panel {
        padding: 20px !important;
        background-color: rgba(255, 255, 255, 0.7) !important;
        border-radius: 20px !important;
        box-shadow: 0 4px 15px rgba(0, 0, 0, 0.05) !important;
    }
    .examples-panel .prose h2 {
        font-size: 28px !important; color: #7e22ce !important; text-align: center !important; font-weight: 700 !important;
    }
    .examples-panel .prose h2::before { content: "✨ "; }
    .examples-panel .prose h2::after { content: " ✨"; }
    .examples-panel .gr-button {
        font-size: 18px !important;
        background-color: #f0e6ff !important;
        border: 2px solid #d8b4fe !important;
        color: #7e22ce !important;
        transition: all 0.3s ease !important;
        border-radius: 16px !important;
        font-weight: 600 !important;
        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.05) !important;
    }
    .examples-panel .gr-button:hover {
        background-color: #e9d5ff !important;
        transform: scale(1.03) !important;
        box-shadow: 0 8px 15px rgba(0, 0, 0, 0.1) !important;
    }

/* --- Chat Area & Messages --- */
.message-wrap { font-size: 18px !important; } /* Base message font size */
.message { margin-bottom: 12px !important; } /* Space between messages */
.user > .message { 
    background-color: #4b0082 !important; /* or keep your original color */
    border-radius: 18px !important; 
    color: #ffffff !important; /* bright text for dark background */
    font-weight: 500 !important;
}

.bot > .message { 
    background-color: #6a0dad !important; /* or keep your original color */
    border-radius: 18px !important; 
    color: #ffffff !important; /* bright text for dark background */
    font-weight: 500 !important;
}

    /* --- Input Textbox & Submit Button --- */
    textarea {
        font-size: 20px !important;
        line-height: 1.5 !important;
        padding: 16px !important;
        border-radius: 16px !important;
        border: 2px solid #d8b4fe !important;
        box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1) !important;
    }
    textarea:focus {
        border-color: #9333ea !important;
        box-shadow: 0 0 0 3px rgba(147, 51, 234, 0.3) !important;
    }
    .send-button { /* More specific selector for the submit button */
        background: linear-gradient(90deg, #9333ea, #d946ef) !important;
        color: white !important;
        font-weight: bold !important;
        font-size: 20px !important;
    }
    .send-button:hover {
        background: linear-gradient(90deg, #7e22ce, #c026d3) !important;
        transform: translateY(-2px) !important;
    }
""") as interface:
    gr.ChatInterface(
        fn=chat,
        # We don't need the title and description here because your CSS h1 is now the main title.
        chatbot=gr.Chatbot(
            label="Talk to me: Shaza Aly",
        ),
        examples=[
            ["What are your main technical skills?"],
            ["Tell me about your experience with AI and RAG chatbots."],
            ["¿Hablas español?"]
        ]
    )

# Now, launch the interface defined within the Blocks context.
if __name__ == "__main__":
    interface.launch()