import os
import gradio as gr
from huggingface_hub import InferenceClient
import itertools
import threading
import time
import json
import datetime

# ==========================================
# 1. HARD-CODED CONFIGURATION & PRESETS
# ==========================================
SECRET_API_KEY = os.getenv("APP_PASSWORD")

raw_tokens = [os.getenv(f"HF_TOKEN_{i}") for i in range(1, 11)]
raw_tokens.append(os.getenv("HF_TOKEN"))  
valid_tokens = [t for t in raw_tokens if t is not None and t.strip() != ""]

clients = [InferenceClient("stabilityai/stable-diffusion-xl-base-1.0", token=t) for t in valid_tokens]

if not clients:
    print("⚠️ WARNING: Space Settings में कोई HF_TOKEN नहीं मिला! ऐप काम नहीं करेगा।")

client_pool = itertools.cycle(clients) if clients else None
lock = threading.Lock()

# ✨✨✨ LOCKED PRESETS (हार्ड-कोडेड) ✨✨✨
LOCKED_SEED = 83492751 
STYLE_SUFFIX = ", a masterfully detailed oil painting, rich expressionist brushwork, visible oil textures, rich colors, cinematic lighting, masterpiece, 8k resolution, in the style of Rembrandt and Van Gogh"
DEFAULT_NEGATIVE_PROMPT = "blurry, text, watermark, bad anatomy, deformed, amateur, low quality, photorealistic, photography"

# ==========================================
# 2. CORE LOGIC (RATIO + STYLE LOCK + FAILOVER)
# ==========================================
def generate_image(prompt, user_negative_prompt, ratio, api_key):
    if api_key != SECRET_API_KEY:
        raise gr.Error("❌ Access Denied: Invalid API Password!")
    
    if not client_pool:
        raise gr.Error("❌ Server Error: API Tokens missing.")

    if ratio == "YouTube Video (16:9)":
        w, h = 1024, 576  
    else: 
        w, h = 576, 1024  

    # प्रॉम्प्ट को हार्ड-कोडेड स्टाइल के साथ बदलना
    cleaned_prompt = prompt.strip()
    if not cleaned_prompt:
        raise gr.Error("❌ Empty Prompt!")
    final_prompt = f"{cleaned_prompt}{STYLE_SUFFIX}"
    
    if user_negative_prompt.strip():
        final_negative_prompt = f"{DEFAULT_NEGATIVE_PROMPT}, {user_negative_prompt.strip()}"
    else:
        final_negative_prompt = DEFAULT_NEGATIVE_PROMPT

    attempts = len(clients)
    last_error = ""
    start_time = time.time()
    
    for attempt in range(attempts):
        with lock:
            current_client = next(client_pool)
            
        try:
            timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
            print(f"[{timestamp}] 🚀 Attempt {attempt + 1}/{attempts} - Generating image...")
            
            image = current_client.text_to_image(
                final_prompt,
                negative_prompt=final_negative_prompt,
                width=w,
                height=h,
                seed=LOCKED_SEED, # सीड लॉक है!
                guidance_scale=7.5,
                num_inference_steps=40
            )
            duration = round(time.time() - start_time, 2)
            
            log_data = {
                "timestamp": timestamp,
                "status": "Success",
                "ratio": ratio,
                "duration": duration,
                "token_index": valid_tokens.index(current_client.token),
                "prompt_snippet": cleaned_prompt[:30] + "..."
            }
            
            return image, log_data
            
        except Exception as e:
            last_error = str(e)
            print(f"⚠️ Token failed. Switching... Error: {last_error[:50]}")
            continue 
            
    raise gr.Error(f"⚠️ All tokens exhausted. Please try again later. Details: {last_error}")


# ==========================================
# 3. STUDIO UI & FULL API DOCUMENTATION
# ==========================================
with gr.Blocks(theme=gr.themes.Soft(primary_hue="amber"), title="Sparkling Gyan API Pro v3") as app:
    
    gr.Markdown("""
    <div style="text-align: center; margin-bottom: 25px; border-bottom: 2px solid #ffca28; padding-bottom: 15px;">
        <h1 style="color: #ffca28; font-size: 2.5rem; margin-bottom: 5px;">✨ Sparkling Gyan Image Studio Pro v3 ✨</h1>
        <p style="font-size: 1.1rem; color: #aaa;">Pro-Grade AI Generator with LOCKED Distributed Token Engine & MASTER Oil Painting Style</p>
    </div>
    """)
    
    with gr.Tabs():
        
        # -------- TAB 1: STUDIO APP --------
        with gr.TabItem("🎨 Studio App"):
            with gr.Row():
                with gr.Column(scale=2):
                    auth_key = gr.Textbox(label="🔑 API Password (Coded in secrets)", type="password", placeholder="अपना सीक्रेट पासवर्ड डालें...")
                    prompt_in = gr.Textbox(label="📝 Scene Prompt", lines=4, placeholder="Describe your cosmic/mythological scene here...")
                    neg_prompt_in = gr.Textbox(label="🚫 Negative Prompt (Optional)", value="photorealistic, 3d, realistic")
                    
                    ratio_choice = gr.Radio(
                        choices=["YouTube Video (16:9)", "YouTube Shorts (9:16)"], 
                        label="📐 Select Video Format / Ratio", 
                        value="YouTube Video (16:9)"
                    )
                    
                    gen_btn = gr.Button("🚀 Generate AI Image (with Locked Presets)", variant="primary")
                
                with gr.Column(scale=1):
                    # यहाँ f-string इस्तेमाल किया है क्योंकि यहाँ कोई JS का कोड नहीं है
                    gr.Markdown(f"""
                    <div style="background-color: #1a1a1a; padding: 15px; border-radius: 10px; border: 1px solid #333; margin-bottom: 15px;">
                        <h4 style="color: #ffca28; margin-top: 0; text-align: center;">🛡️ Locked Studio Presets 🛡️</h4>
                        <p style="margin: 5px 0;"><b>Style:</b> Masterful Oil Painting (Rembrandt/Van Gogh Style)</p>
                        <p style="margin: 5px 0;"><b>Seed:</b> <code style="color: #4caf50;">{LOCKED_SEED}</code> (Always Locked)</p>
                        <p style="margin: 5px 0;"><b>Quality:</b> Masterpiece, 8k Resolution</p>
                    </div>
                    """)
                    image_out = gr.Image(label="Generated Output (Auto-Ratio)")
            
            gen_btn.click(
                fn=generate_image, 
                inputs=[prompt_in, neg_prompt_in, ratio_choice, auth_key], 
                outputs=[image_out, gr.State()], 
                api_name="predict" 
            )

        # -------- TAB 2: SERVER LOGS --------
        with gr.TabItem("📋 Server Logs"):
            gr.Markdown("""
            ### 📋 Server Generation Logs
            यहाँ आपको जनरेट की गई इमेजेज की हिस्ट्री दिखेगी। यह जानकारी बैकएंड से आती है।
            """)
            logs_output = gr.JSON(label="Last Generation Log")
            gen_btn.click(fn=lambda x, y: y, inputs=[image_out, gr.State()], outputs=logs_output, queue=False)

        # -------- TAB 3: API DOCUMENTATION --------
        with gr.TabItem("📚 API Documentation"):
            # यहाँ मैंने f-string हटा दिया है ताकि JS के ब्रैकेट्स एरर न दें!
            gr.Markdown("""
            ### 🛠️ Developer API v3 Guide
            Hugging Face (Gradio 4) डायरेक्ट POST रिक्वेस्ट को ब्लॉक करता है। इसलिए API कॉल करने के लिए आधिकारिक **Gradio Client** का ही इस्तेमाल करें।
            
            **Space ID:** `Dws321/t2i`
            
            <div style="background-color: #1a1a1a; padding: 10px; border-radius: 5px; border: 1px solid #333;">
                <b>🚀 Locked Presets:</b> API बैकएंड में तेल चित्रकला (Oil Painting) स्टाइल और सीड `""" + str(LOCKED_SEED) + """` को अपने आप जोड़ती है। आपको इन्हें प्रॉम्प्ट में डालने की ज़रूरत नहीं है।
            </div>
            
            **API Parameters (Data Array Order):**
            1. `prompt` (String) - Describe your scene. Style will be auto-added.
            2. `negative_prompt` (String) - Things to avoid.
            3. `ratio` (String: "YouTube Video (16:9)" या "YouTube Shorts (9:16)")
            4. `api_key` (String: आपका सीक्रेट `APP_PASSWORD`)

            ---
            
            #### 1. Python Example (Using `gradio_client`)
            सबसे पहले इनस्टॉल करें: `pip install gradio_client`
            ```python
            from gradio_client import Client

            # अपने HF Space का लिंक यहाँ डालें
            client = Client("Dws321/t2i")
            
            try:
                result = client.predict(
                    prompt="A cosmic black hole swallowing a planet", 
                    negative_prompt="photorealistic, 3d, realistic", 
                    ratio="YouTube Shorts (9:16)", 
                    api_key="आपका_सीक्रेट_पासवर्ड",  
                    api_name="/predict"
                )
                print("✅ इमेज सफलतापूर्वक डाउनलोड हो गई:", result)
            except Exception as e:
                print("❌ एरर:", e)
            ```

            ---
            
            #### 2. JavaScript / HTML Example (Gradio JS Client)
            Gradio 4 के लिए आपको NPM या CDN से `@gradio/client` इम्पोर्ट करना होगा। रॉ (raw) `fetch` इस्तेमाल न करें।
            
            ```html
            <script type="module">
                import { client } from "[https://cdn.jsdelivr.net/npm/@gradio/client/dist/index.min.js](https://cdn.jsdelivr.net/npm/@gradio/client/dist/index.min.js)";

                async function generateMyImage() {
                    try {
                        const app = await client("Dws321/t2i");
                        const result = await app.predict("/predict", [
                            "Lord Shiva meditating, in cosmic space", 
                            "photorealistic, 3d",                                     
                            "YouTube Video (16:9)",                                   
                            "YOUR_SECRET_PASSWORD"                                   
                        ]);
                        
                        console.log("✅ Success! Image Link:", result.data[0].url);
                        document.getElementById('output').src = result.data[0].url;
                    } catch (error) {
                        console.error("❌ Error:", error);
                    }
                }
                
                generateMyImage();
            </script>
            <img id="output" src="">
            ```
            """)

# ==========================================
# 4. APP LAUNCH & QUEUE SYSTEM
# ==========================================
app.queue(default_concurrency_limit=1).launch()