import gradio as gr
import os
import json
from Pdf_utils import extract_text_from_pdf
from ocr_utils import extract_text_from_image
from Prompt_Builder import build_prompt
from openai import OpenAI

# ----------------------------
# CONFIG & SECRETS
# ----------------------------
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
OCR_API_KEY = os.environ.get("OCR_API_KEY")

client = OpenAI(
    api_key=GROQ_API_KEY,
    base_url="https://api.groq.com/openai/v1",
)

# ----------------------------
# UI CUSTOMIZATION (Vanta.js + Glassmorphism)
# ----------------------------
css = """
footer {visibility: hidden}
.gradio-container {
    background: rgba(10, 25, 47, 0.7) !important;
    backdrop-filter: blur(15px) !important;
    border: 1px solid rgba(255, 255, 255, 0.1) !important;
    border-radius: 20px !important;
    color: white !important;
}
#vanta-canvas {
    position: fixed;
    top: 0; left: 0; width: 100vw; height: 100vh;
    z-index: -1;
}
#output-box {
    background: rgba(0, 0, 0, 0.3) !important;
    padding: 20px;
    border-radius: 10px;
}
"""

vanta_head = """
<div id="vanta-canvas"></div>
<script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r134/three.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/vanta@latest/dist/vanta.net.min.js"></script>
<script>
    document.addEventListener('DOMContentLoaded', function() {
        VANTA.NET({
          el: "#vanta-canvas",
          mouseControls: true,
          touchControls: true,
          gyroControls: false,
          minHeight: 200.00,
          minWidth: 200.00,
          scale: 1.00,
          scaleMobile: 1.00,
          color: 0x3fbbee,
          backgroundColor: 0x0a192f,
          points: 15.00,
          maxDistance: 20.00,
          spacing: 16.00
        })
    });
</script>
"""

# ----------------------------
# CORE LOGIC WITH UX ALERTS
# ----------------------------
def generate_nexus_post(file, user_text, url, url_desc, hashtags, custom_p, suggestions, model_name):
    # Validation Check
    if not file and not user_text.strip():
        raise gr.Error("Bhai, kam az kam kuch text ya file toh do! Input empty hai.")

    # User Feedback Notification
    gr.Info("🚀 Processing your request... Sit tight!")
    
    file_text = ""
    if file:
        try:
            if file.name.lower().endswith(".pdf"):
                gr.Info("📄 Reading PDF...")
                file_text = extract_text_from_pdf(file.name)
            else:
                gr.Info("🖼️ Running OCR on Image...")
                file_text = extract_text_from_image(file.name, OCR_API_KEY)
        except Exception as e:
            raise gr.Error(f"File processing error: {str(e)}")

    # Prompt Building
    final_prompt = build_prompt(user_text, file_text, {"url": url, "description": url_desc}, [], hashtags.split(","), custom_p, suggestions)

    try:
        gr.Info("🤖 AI is ghostwriting your post...")
        completion = client.chat.completions.create(
            model=model_name,
            messages=[{"role": "user", "content": final_prompt}],
            temperature=0.7,
            timeout=45.0 # Pre-emptively stop if API is stuck
        )
        gr.Info("✅ Done! Post generated.")
        return completion.choices[0].message.content
    except Exception as e:
        raise gr.Error(f"API Error: {str(e)}")

# ----------------------------
# GRADIO INTERFACE
# ----------------------------
with gr.Blocks(theme=gr.themes.Default(), css=css) as demo:
    gr.HTML(vanta_head)
    
    with gr.Column():
        gr.Markdown("# 🚀 Nexus Post AI\n### Professional LinkedIn Ghostwriter")
        
        with gr.Row():
            with gr.Column(scale=1):
                file_input = gr.File(label="Upload Context (PDF/Image)")
                user_msg = gr.Textbox(label="Core Idea", placeholder="What's this post about?", lines=3)
                
                with gr.Accordion("🔗 Links & Tags", open=False):
                    link_url = gr.Textbox(label="Reference URL")
                    link_d = gr.Textbox(label="Link Description")
                    tags = gr.Textbox(label="Hashtags (comma separated)")
            
            with gr.Column(scale=1):
                model_drop = gr.Dropdown(
                    choices=["llama-3.3-70b-versatile", "mixtral-8x7b-32768"],
                    value="llama-3.3-70b-versatile",
                    label="AI Model"
                )
                ai_adds = gr.CheckboxGroup(
                    label="Enhancements",
                    choices=["Strong Hook", "Storytelling", "Bullet Points", "Emojis", "Call-to-Action"]
                )
                custom_inst = gr.Textbox(label="Custom Instructions", placeholder="e.g. 'Make it professional'")

        # Button with explicit loading
        submit_btn = gr.Button("🔥 GENERATE POST", variant="primary")
        
        output_display = gr.Markdown(label="Generated Drafts", elem_id="output-box")

    # The Logic Trigger
    submit_btn.click(
        fn=generate_nexus_post,
        inputs=[file_input, user_msg, link_url, link_d, tags, custom_inst, ai_adds, model_drop],
        outputs=output_display,
        show_progress="full", # Full screen overlay for clear status
        scroll_to_output=True
    )

demo.launch()