import gradio as gr
from openai import OpenAI

def respond(message, chat_history, api_key):
    # Failsafe to ensure history initializes as an empty list
    if chat_history is None:
        chat_history = []
        
    # Gatekeeper: Halt execution if no compute resource is provided
    if not api_key:
        chat_history.append({"role": "user", "content": message})
        chat_history.append({"role": "assistant", "content": "System locked: Please enter your OpenAI API Key in the secure box above."})
        return "", chat_history
        
    try:
        client = OpenAI(api_key=api_key)
        
        # System prompt
        openai_messages = [
            {
                "role": "system", 
                "content": "You are an elite Florida State University (FSU) intelligence agent. You provide highly accurate, actionable information regarding FSU campus life, academic infrastructure, and Seminoles Division 1 football history. Default to thinking in systems. Be concise, eliminate filler, and output structured data where appropriate."
            }
        ]
        
        # Pass the direct Gradio history into the OpenAI pipeline
        openai_messages.extend(chat_history)
        openai_messages.append({"role": "user", "content": message})
        
        # Execute query
        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=openai_messages,
            temperature=0.4
        )
        
        bot_reply = response.choices[0].message.content
        
        # Append the new interaction using the native dictionary format
        chat_history.append({"role": "user", "content": message})
        chat_history.append({"role": "assistant", "content": bot_reply})
        
        return "", chat_history
        
    except Exception as e:
        chat_history.append({"role": "user", "content": message})
        chat_history.append({"role": "assistant", "content": f"Pipeline Error: {str(e)}"})
        return "", chat_history

# Custom CSS for the glassmorphic visual interface
glassmorphism_css = """
body {
    background: linear-gradient(135deg, #fdfbfb 0%, #ebedee 100%);
}
.gradio-container {
    background: rgba(255, 255, 255, 0.65) !important;
    backdrop-filter: blur(16px) !important;
    -webkit-backdrop-filter: blur(16px) !important;
    border-radius: 18px !important;
    border: 1px solid rgba(255, 255, 255, 0.5) !important;
    box-shadow: 0 8px 32px 0 rgba(31, 38, 135, 0.07) !important;
}
"""

with gr.Blocks() as demo:
    gr.Markdown("## 🍢 FSU Intelligence Node")
    gr.Markdown("A domain-specific AI pipeline engineered for Florida State University logistics and Division 1 football strategy.\n\n*Compute requires user-provided API authentication.*")
    
    # 1. API Key Input - Isolated from the chat submission wipe
    with gr.Row():
        api_input = gr.Textbox(
            label="OpenAI API Key (Required)", 
            placeholder="sk-proj-...", 
            type="password",
            info="Injected dynamically at runtime. Keys are not stored or logged."
        )
        
    # 2. Main Chat Display - Removed the 'type' parameter as it is now strictly implicit
    chatbot = gr.Chatbot(height=450, label="Intelligence Feed")
    
    # 3. User Input Area
    with gr.Row():
        msg = gr.Textbox(
            label="Query Input",
            placeholder="Type your query here and press Enter...",
            scale=4
        )
        submit_btn = gr.Button("Send", variant="primary", scale=1)
        
    # 4. Quick-Load Examples
    gr.Examples(
        examples=[
            "Break down the structural timeline of FSU's Division 1 football championships.",
            "What are the core technology infrastructure facilities on the Tallahassee campus?",
            "Provide a statistical overview of the 2013 Seminoles season."
        ],
        inputs=msg
    )
        
    # 5. Explicit Event Binding
    msg.submit(respond, inputs=[msg, chatbot, api_input], outputs=[msg, chatbot])
    submit_btn.click(respond, inputs=[msg, chatbot, api_input], outputs=[msg, chatbot])

if __name__ == "__main__":
    demo.launch(
        css=glassmorphism_css, 
        theme=gr.themes.Default(primary_hue="red", neutral_hue="zinc")
    )