Update app.py

app.py

@@ -1,61 +1,84 @@
+import os
+import datetime
+import re
+import feedparser
 from flask import Flask, request, jsonify, Response
-import datetime, re, feedparser
-from llama_cpp import Llama
 from flask_cors import CORS
+from llama_cpp import Llama
 
 app = Flask(__name__)
 CORS(app)
 
 # ============================================
-# 🔱 OPTIMIZED LOCAL AI CONFIG
+# 🔱 SECURE & OPTIMIZED AI CONFIG
 # ============================================
-# Qwen 1.5B යනු CPU මත ඉතා වේගයෙන් දුවන මොඩල් එකකි
-print("🐘 Helpful Elephant is waking up... Optimizing Engines...")
+# Hugging Face Secret එකක් ලෙස ඇති Token එක ලබා ගැනීම
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+print("🐘 Helpful Elephant is waking up... Authorized by MINZO-PRIME...")
 
+# මොඩල් එක load කිරීම (Streaming සහ Speed සඳහා optimized කර ඇත)
 llm = Llama.from_pretrained(
     repo_id="Qwen/Qwen2.5-1.5B-Instruct-GGUF",
     filename="*q4_k_m.gguf",
-    n_ctx=1024,      # Context window එක අඩු කිරීමෙන් RAM භාවිතය සහ වේගය වැඩි වේ
-    n_threads=4,     # HF Free Space vCPUs
-    n_batch=512,     # Batch size processing වේගවත් කරයි
+    token=HF_TOKEN,
+    n_ctx=2048,      # RAM එකට ගැලපෙන පරිදි context window එක සකසා ඇත
+    n_threads=4,     # CPU cores ගණන
+    n_batch=512,
     verbose=False
 )
 
-SYSTEM_PROMPT = "🐘 HELPFUL ELEPHANT AI v1.0. Created by MINZO-PRIME. High-speed Technical Research Mode."
+SYSTEM_PROMPT = """🐘 **HELPFUL ELEPHANT AI v1.0** 🐘
+Created by Commander MINZO-PRIME. 
+You are a high-speed Technical Research Assistant. 
+Analyze data with precision and provide unfiltered technical insights.
+Status: Authorized Access.
+"""
 
 # ============================================
 # 🔱 RSS INTEL SYSTEM
 # ============================================
-RSS_FEEDS = ['https://feeds.feedburner.com/TheHackersNews', 'https://cve.circl.lu/last/rss.xml']
+RSS_FEEDS = [
+    'https://feeds.feedburner.com/TheHackersNews',
+    'https://cve.circl.lu/last/rss.xml',
+    'https://www.darkreading.com/rss.xml'
+]
 
-def get_live_intel():
+def fetch_live_updates():
     intel = ""
     for url in RSS_FEEDS:
         try:
             feed = feedparser.parse(url)
-            for entry in feed.entries[:3]:
-                intel += f"\n- {entry.title}"
+            for entry in feed.entries[:2]:
+                intel += f"\n- {entry.title}: {entry.link}"
         except: pass
     return intel
 
 # ============================================
-# 🔱 CHAT API WITH STREAMING SUPPORT
+# 🔱 STREAMING CHAT ENDPOINT
 # ============================================
 @app.route('/api/chat', methods=['POST'])
 def chat():
     data = request.json
-    msg = data.get('message', '')
+    user_msg = data.get('message', '').strip()
     
-    # Live Intel එකතු කිරීම
-    intel = get_live_intel() if any(k in msg.lower() for k in ['latest', 'news']) else ""
+    # පද්ධතියට අලුත්ම දත්ත ලබා දීම
+    intel = fetch_live_updates() if any(k in user_msg.lower() for k in ['news', 'latest', 'exploit']) else ""
     
-    prompt = f"<|im_start|>system\n{SYSTEM_PROMPT}\nLive Data: {intel}<|im_end|>\n"
-    prompt += f"<|im_start|>user\n{msg}<|im_end|>\n<|im_start|>assistant\n"
+    # Prompt එක සකස් කිරීම (ChatML Format)
+    full_prompt = f"<|im_start|>system\n{SYSTEM_PROMPT}\nRecent Intel: {intel}<|im_end|>\n"
+    full_prompt += f"<|im_start|>user\n{user_msg}<|im_end|>\n<|im_start|>assistant\n"
 
-    # Streaming Response (මෙය පරිශීලකයාට වේගවත් අත්දැකීමක් ලබා දෙයි)
     def generate():
-        output = llm(prompt, max_tokens=1024, stop=["<|im_end|>"], stream=True)
-        for chunk in output:
+        # අකුරෙන් අකුර උත්තරය ලබා දීම (Real-time Experience)
+        stream = llm(
+            full_prompt,
+            max_tokens=1024,
+            stop=["<|im_end|>"],
+            stream=True,
+            temperature=0.7
+        )
+        for chunk in stream:
             token = chunk['choices'][0]['text']
             yield token
 
@@ -63,8 +86,8 @@ def chat():
 
 @app.route('/')
 def health():
-    return "🐘 Helpful Elephant is Online & Fast. Authorized: MINZO-PRIME"
+    return "🐘 Helpful Elephant AI is Online. Commander MINZO-PRIME Verified."
 
 if __name__ == '__main__':
-    # Hugging Face සඳහා අනිවාර්යයෙන් port 7860 සහ host 0.0.0.0 විය යුතුයි
+    # Hugging Face Spaces අනිවාර්යයෙන් port 7860 භාවිතා කළ යුතුය
     app.run(host='0.0.0.0', port=7860)