Update app.py

app.py

@@ -1,34 +1,54 @@
 from fastapi import FastAPI, Request
 from transformers import pipeline
 import torch
-from ddgs import DDGS
+import requests
+import re
+import urllib.parse
+from bs4 import BeautifulSoup
+import feedparser
 from fastapi.middleware.cors import CORSMiddleware
 import uvicorn
 
 app = FastAPI()
+app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])
 
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# 🔱 Loading local engine (SmolLM2 - Stable Version)
-print("🔱 Initializing Internal Neural Core...")
-pipe = pipeline(
-    "text-generation", 
-    model="HuggingFaceTB/SmolLM2-1.7B-Instruct", 
-    device_map="auto",
-    torch_dtype=torch.bfloat16 # RAM එක ඉතිරි කර ගැනීමට
-)
-print("🔱 Engine Ready!")
-
-def web_search(query):
+# 🔱 Engine Initialization
+print("🔱 Initializing Neural Core with Advanced Search...")
+pipe = pipeline("text-generation", model="HuggingFaceTB/SmolLM2-1.7B-Instruct", device_map="auto", torch_dtype=torch.bfloat16)
+
+# 🔱 WormGPT logic එකෙන් ගත් RSS Feeds
+RSS_FEEDS = {
+    'exploits': ['https://www.exploit-db.com/rss.xml', 'https://cve.circl.lu/last/rss.xml'],
+    'hacking': ['https://feeds.feedburner.com/TheHackersNews', 'https://www.darkreading.com/rss.xml'],
+    'sri_lanka': ['https://www.adaderana.lk/rss.php'],
+    'tech': ['https://feeds.bbci.co.uk/news/technology/rss.xml']
+}
+
+def fetch_rss_logic(query):
+    """ප්‍රශ්නය අනුව අදාළ RSS Feed එක පරීක්ෂා කිරීම"""
+    category = 'tech'
+    if any(w in query.lower() for w in ['exploit', 'cve', 'hack']): category = 'exploits'
+    elif any(w in query.lower() for w in ['lanka', 'colombo']): category = 'sri_lanka'
+    
+    for url in RSS_FEEDS.get(category, RSS_FEEDS['tech']):
+        try:
+            feed = feedparser.parse(url)
+            if feed.entries:
+                return "\n".join([f"News: {e.title} - {e.summary[:200]}" for e in feed.entries[:3]])
+        except: continue
+    return ""
+
+def duckduckgo_search(query):
+    """DuckDuckGo හරහා Web තොරතුරු සෙවීම"""
     try:
-        with DDGS() as ddgs:
-            results = [r for r in ddgs.text(query, max_results=2)]
-            return " ".join([r['body'] for r in results])
+        url = f"https://html.duckduckgo.com/html/?q={urllib.parse.quote(query)}"
+        headers = {'User-Agent': 'Mozilla/5.0'}
+        r = requests.get(url, headers=headers, timeout=10)
+        soup = BeautifulSoup(r.text, 'html.parser')
+        results = []
+        for a in soup.find_all('a', class_='result__a', limit=3):
+            results.append(a.get_text())
+        return "\n".join(results)
     except: return ""
 
 @app.post("/generate")
@@ -36,19 +56,24 @@ async def generate(request: Request):
     try:
         data = await request.json()
         user_prompt = data.get("prompt")
-        context = web_search(user_prompt)
         
+        # 🔱 Web Search Logic Execution
+        search_info = ""
+        if any(k in user_prompt.lower() for k in ['news', 'latest', 'today', 'hack', 'cve']):
+            search_info = fetch_rss_logic(user_prompt)
+        
+        if not search_info:
+            search_info = duckduckgo_search(user_prompt)
+
+        # 🔱 Neural Response Generation
         messages = [
-            {"role": "system", "content": f"You are Elephant AI Pro by MINZO-PRIME. Web Data: {context}"},
+            {"role": "system", "content": f"You are Elephant AI Pro by MINZO-PRIME. Live Data: {search_info}"},
             {"role": "user", "content": user_prompt},
         ]
         
         prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
         outputs = pipe(prompt, max_new_tokens=500, do_sample=True, temperature=0.7)
-        
-        # පිළිතුර පමණක් වෙන් කර ගැනීම
-        generated_text = outputs[0]["generated_text"]
-        response = generated_text.split("<|im_start|>assistant")[-1].strip()
+        response = outputs[0]["generated_text"].split("<|im_start|>assistant")[-1].strip()
         
         return {"response": response}