import os
import requests
import urllib.parse
from bs4 import BeautifulSoup
from flask import Flask, request, Response, stream_with_context, render_template_string

app = Flask(__name__)

# 🔐 100% सुरक्षित: सब कुछ केवल 'Secrets' से कॉल होगा, कोई हार्डकोडेड डेटा नहीं।
API_KEY = os.environ.get("YOUR_VEDIKA_API_KEY") 
BASE_URL = os.environ.get("BASE_URL")
MODEL_ID = os.environ.get("MODEL_ID")

# URL को सुरक्षित रूप से बनाना ताकि कोई डिफ़ॉल्ट लिंक न दिखे
INVOKE_URL = ""
if BASE_URL:
    if not BASE_URL.endswith("/chat/completions"):
        INVOKE_URL = f"{BASE_URL.rstrip('/')}/chat/completions"
    else:
        INVOKE_URL = BASE_URL


# 🌐 --- GOOGLE SEARCH SCRAPER ENGINE --- 🌐
def google_search_scraper(query, num_results=4):
    """
    यह फंक्शन Google सर्च से डेटा निकालता है और उसे AI के समझने लायक बनाता है।
    """
    # Google को धोखा देने के लिए असली ब्राउज़र का User-Agent
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
    }
    url = f"https://www.google.com/search?q={urllib.parse.quote(query)}&hl=en"
    
    try:
        response = requests.get(url, headers=headers, timeout=10)
        soup = BeautifulSoup(response.text, 'html.parser')
        results = []
        
        # Google के सर्च रिजल्ट्स 'div.g' के अंदर होते हैं
        for g in soup.find_all('div', class_='g'):
            title_elem = g.find('h3')
            link_elem = g.find('a')
            
            if title_elem and link_elem:
                title = title_elem.text
                link = link_elem.get('href', '')
                
                # Snippet (डिस्क्रिप्शन) निकालना
                snippet = ""
                snippet_box = g.find('div', class_='VwiC3b') 
                if snippet_box:
                    snippet = snippet_box.text
                
                results.append({
                    "title": title,
                    "link": link,
                    "snippet": snippet
                })
                
                if len(results) >= num_results:
                    break
                    
        return results
    except Exception as e:
        return [{"error": str(e)}]
# ---------------------------------------------


@app.route('/')
def home():
    try:
        with open('index.html', 'r', encoding='utf-8') as f:
            html_content = f.read()
        return render_template_string(html_content)
    except Exception as e:
        return f"index.html file missing! Error: {str(e)}"

@app.route('/api/chat', methods=['POST'])
def chat():
    # सुरक्षा जांच: अगर सीक्रेट्स सेट नहीं हैं, तो रिक्वेस्ट आगे नहीं जाएगी
    if not API_KEY or not INVOKE_URL or not MODEL_ID:
        return Response("Server Error: Configuration secrets are missing.", status=500)

    data = request.get_json() or {}
    user_message = data.get("message", "")
    attachments = data.get("attachments", []) 
    system_prompt = data.get("system_prompt", "")
    history = data.get("history", []) 
    max_tokens = data.get("max_tokens", 4096)
    temperature = data.get("temperature", 0.6)

    # 🚀 --- INTERCEPT & SEARCH LOGIC --- 🚀
    # अगर यूजर के मैसेज में /search या /google है, तो स्क्रैपर चालू करें
    if user_message.strip().lower().startswith("/search "):
        search_query = user_message[8:].strip()
        scraped_data = google_search_scraper(search_query)
        
        search_context = f"Real-time Google Search Results for '{search_query}':\n\n"
        for idx, res in enumerate(scraped_data):
            if "error" in res:
                search_context += f"Search Error: {res['error']}\n"
            else:
                search_context += f"{idx+1}. Title: {res['title']}\nSnippet: {res['snippet']}\nLink: {res['link']}\n\n"
        
        search_context += "\n[INSTRUCTION FOR AI: Formulate a comprehensive, professional response to the user's query using ONLY the real-time search data provided above. Cite sources if applicable.]"
        
        # एआई के लिए प्रॉम्प्ट को मॉडिफाई करना (यूजर को यह बैकग्राउंड डेटा नहीं दिखेगा)
        user_message = f"User Query: {search_query}\n\n[SYSTEM BACKGROUND CONTEXT]\n{search_context}"
    # ---------------------------------------

    messages = []

    # 1. सिस्टम प्रॉम्प्ट
    if system_prompt.strip():
        messages.append({"role": "system", "content": system_prompt})

    # 2. पुरानी हिस्ट्री को मॉडल के पेलोड में जोड़ना
    for msg in history:
        role = msg.get("role", "user")
        content = msg.get("content", "")
        if content:
            messages.append({"role": role, "content": content})

    # 3. मल्टीमोडल इनपुट (करेंट मैसेज)
    content_payload = []
    if user_message.strip():
        content_payload.append({"type": "text", "text": user_message})
        
    for att in attachments:
        att_type = att.get("type")
        b64_data = att.get("data")
        
        if att_type == "image":
            content_payload.append({"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{b64_data}"}})
        elif att_type in ["audio", "file"]:
            content_payload.append({"type": "input_audio", "input_audio": {"data": b64_data, "format": "wav"}})

    if not content_payload:
        content_payload.append({"type": "text", "text": "Hello"})

    # नया मैसेज सबसे आखिरी में जोड़ना
    messages.append({"role": "user", "content": content_payload})

    headers = {
        "Authorization": f"Bearer {API_KEY}",
        "Accept": "text/event-stream"
    }

    payload = {
        "model": MODEL_ID,
        "messages": messages,
        "max_tokens": int(max_tokens),
        "temperature": float(temperature),
        "top_p": 0.70,
        "stream": True
    }

    try:
        # सुरक्षित स्ट्रीमिंग रिक्वेस्ट
        response = requests.post(INVOKE_URL, headers=headers, json=payload, stream=True)
        
        def generate():
            for line in response.iter_lines():
                if line:
                    decoded_line = line.decode("utf-8")
                    if decoded_line.startswith("data: "):
                        yield decoded_line + "\n\n"
                        
        return Response(stream_with_context(generate()), mimetype='text/event-stream')
    except Exception as e:
        return Response("Internal Error: Unable to process request securely.", status=500)

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860)