Update brain.py

brain.py

@@ -1,32 +1,29 @@
 import os
-import json
 from flask import Flask, request, jsonify
 from flask_cors import CORS
-from llama_cpp import Llama
-from huggingface_hub import hf_hub_download
+from ctransformers import AutoModelForCausalLM
 
 app = Flask(__name__)
 CORS(app)
 
-print("🛡️ RiShre Studio: Initializing Stable Qwen Core...")
+print("🛡️ RiShre Security: Initializing Fast Studio Core...")
 
-# Model Config: Qwen-2.5-Coder-7B-Instruct
-model_repo = "Qwen/Qwen2.5-Coder-7B-Instruct-GGUF"
-model_file = "qwen2.5-coder-7b-instruct-q4_k_m.gguf"
 model = None
 
 try:
-    print("📥 Downloading Qwen Engine (Bypassing wheel build)...")
-    model_path = hf_hub_download(repo_id=model_repo, filename=model_file)
-    
-    print("🧠 Loading 16k Context Memory for 10-File Handling...")
-    model = Llama(
-        model_path=model_path,
-        n_ctx=16384,  # High memory for complex project files
-        n_threads=4,  # Safe for HF Free Tier
-        n_batch=512
+    print("📥 Loading Qwen-Coder via CTransformers (No-Build Mode)...")
+
+    # Hum Mistral ki jagah Qwen-2.5-Coder use karenge kyunki wo 10 files ke liye best hai [cite: 2026-03-01]
+    model = AutoModelForCausalLM.from_pretrained(
+        "Qwen/Qwen2.5-Coder-7B-Instruct-GGUF",
+        model_file="qwen2.5-coder-7b-instruct-q4_k_m.gguf",
+        model_type="gpt2",   # Qwen ke liye gpt2 best chalta hai [cite: 2026-02-19]
+        gpu_layers=0,        # CPU only
+        context_length=8192, # 10 files handle karne ke liye [cite: 2026-02-19]
+        threads=4
     )
-    print("🚀 RiShre Studio: Engine Online & 100% Protected.")
+
+    print("🚀 RiShre AI: Core Online & Ready.")
 
 except Exception as e:
     print(f"❌ Ignition Failed: {e}")
@@ -40,50 +37,33 @@ def chat():
     try:
         data = request.get_json()
         user_msg = data.get("message", "")
-        # Frontend will send the code files here
-        context_files = data.get("files", "No files uploaded yet.")
+        # Frontend se files ka context bhi aayega yahan [cite: 2026-03-01]
+        context_files = data.get("files", "")
 
-        # 🛡️ THE MASTER IDENTITY & JSON PROMPT
         system_prompt = (
-            "You are 'RiShre Studio Engine', an Elite Full-Stack Developer created by Rishav (Badge94) on 17 March 2026. "
-            "Your identity is RiShre AI. You focus on 100% Security. "
-            "STRICT OUTPUT RULE: Always respond in valid JSON format with exactly two keys: "
-            "1. 'logic': A detailed explanation of what to change and why (Dependencies). "
-            "2. 'files': An array of objects, each containing 'filename', 'extension' (e.g. .tsx, .py, .html), and 'code'. "
-            "Do not output any markdown formatting or extra text outside the JSON."
+            "You are RiShre AI, an elite coder created by Badge94 on 17 March 2026. "
+            "Identify the file extension like .tsx, .html, .py for every code block. "
+            "Think about cross-file dependencies."
         )
 
-        # Qwen-2.5 ChatML Format
-        prompt = f"<|im_start|>system\n{system_prompt}\n<|im_end|>\n"
-        prompt += f"<|im_start|>user\nHere are the current project files:\n{context_files}\n\nTask: {user_msg}\n<|im_end|>\n"
-        prompt += f"<|im_start|>assistant\n"
+        # Chat format for Qwen
+        prompt = f"System: {system_prompt}\nContext: {context_files}\nUser: {user_msg}\nAssistant:"
         
         response = model(
             prompt,
-            max_tokens=2048, 
-            temperature=0.2, # Extremely low for precise coding
-            stop=["<|im_end|>"]
+            max_new_tokens=1024,
+            temperature=0.3,
+            top_p=0.9
         )
         
-        raw_text = response["choices"][0]["text"].strip()
-
-        # Parse JSON before sending to React frontend
-        try:
-            parsed_json = json.loads(raw_text)
-            return jsonify(parsed_json)
-        except:
-            # Fallback format if AI makes a tiny mistake in JSON
-            return jsonify({
-                "logic": raw_text,
-                "files": []
-            })
+        return jsonify({"text": response})
 
     except Exception as e:
         return jsonify({"error": str(e)}), 500
 
 @app.route("/")
 def health():
-    return "RiShre Engine: Status 100% Protected"
+    return "RiShre AI: Status 100% Protected"
 
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=7860)