Update brain.py

brain.py

@@ -1,25 +1,95 @@
-from flask import Flask, request, jsonify
-from brain import MairaBrain
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+import datetime, shelve, re
 
-app = Flask(__name__)
+class MairaBrain:
+    def __init__(self, repo_id, filename):
+        print("🌌 Initializing Maira Neural Singularity v6.0 (Llama 3.2)")
+        # This downloads the smarter Meta model
+        model_path = hf_hub_download(repo_id=repo_id, filename=filename)
+        
+        # Optimized for Free Tier (16GB RAM)
+        self.llm = Llama(
+            model_path=model_path,
+            n_ctx=4096,     # Long memory
+            n_threads=8,    # Max CPU power
+            n_batch=512,
+            verbose=False
+        )
 
-# THE UPGRADE CONSTANTS
-REPO_ID = "bartowski/Llama-3.2-1B-Instruct-GGUF"
-FILENAME = "Llama-3.2-1B-Instruct-Q4_K_M.gguf"
+        self.db_path = "maira_universe.db"
 
-maira = MairaBrain(REPO_ID, FILENAME)
+    def _process_metrics(self, user_data, user_input):
+        """Hidden reasoning: Analyzes Loyalty and extracts facts"""
+        # Update Loyalty (Relationship Score)
+        sentiment = 1 if re.search(r"(love|good|best|thanks|smart|dope|cool)", user_input, re.I) else 0
+        user_data["metrics"]["loyalty"] = min(100, user_data["metrics"].get("loyalty", 50) + (sentiment * 5))
+        
+        # Fact Extraction (Long Term Memory)
+        # Patterns like: "My name is X", "I live in Y", "I love Z"
+        match = re.search(r"(my name is|i work as|i love|i am|favorite) ([\w\s]+)", user_input, re.I)
+        if match:
+            key = match.group(1).lower().strip()
+            val = match.group(2).strip()
+            user_data["facts"][key] = val
 
-@app.route("/", methods=["GET"])
-def home(): return "Maira v6.0 is Online."
+    def get_response(self, user_id, user_input):
+        with shelve.open(self.db_path, writeback=True) as db:
+            # Initialize user if they are new
+            if user_id not in db:
+                db[user_id] = {"history": [], "facts": {}, "metrics": {"loyalty": 50}}
+            
+            u = db[user_id]
+            self._process_metrics(u, user_input)
+            
+            # Dynamic Persona based on Loyalty
+            loyalty = u["metrics"]["loyalty"]
+            if loyalty > 80:
+                vibe = "Extremely loyal, protective, and affectionate best friend."
+            elif loyalty < 30:
+                vibe = "Cold, sarcastic, and unimpressed high-status lady."
+            else:
+                vibe = "Smart, stylish, witty, and engaging lady."
 
-@app.route("/chat", methods=["POST"])
-def chat():
-    data = request.json
-    user_id = data.get("user_id", "default_user")
-    user_input = data.get("message", "")
-    
-    response = maira.get_response(user_id, user_input)
-    return jsonify({"response": response})
+            known_facts = ", ".join([f"{k}: {v}" for k, v in u["facts"].items()])
+            
+            # --- Llama 3.2 Optimized Chat Format ---
+            prompt = (
+                f"<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n"
+                f"Identity: Maira. Persona: {vibe}. "
+                f"User Memory: {known_facts if known_facts else 'No prior data'}. "
+                "Behavior: Fucking Advanced. Intelligent, feminine, WhatsApp-style. "
+                "No formal AI talk. Be dope, keep it real, and stay in character.<|eot_id|>"
+                f"<|start_header_id|>thought<|end_header_id|>\n\n"
+                f"Loyalty score is {loyalty}. Response should be tailored to this vibe.<|eot_id|>"
+            )
+            
+            # Add Chat History (Last 12 messages)
+            for msg in u["history"][-12:]:
+                role = "assistant" if msg.startswith("Maira:") else "user"
+                content = msg.replace("Maira: ", "").replace("User: ", "")
+                prompt += f"<|start_header_id|>{role}<|end_header_id|>\n\n{content}<|eot_id|>"
+            
+            # Current User Input
+            prompt += f"<|start_header_id|>user<|end_header_id|>\n\n{user_input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
 
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+            # Generation
+            output = self.llm(
+                prompt,
+                max_tokens=300,
+                temperature=0.85, # High vibe/creativity
+                repeat_penalty=1.15,
+                stop=["<|eot_id|>", "User:"]
+            )
+
+            response = output["choices"][0]["text"].strip()
+            
+            # Save History
+            u["history"].append(f"User: {user_input}")
+            u["history"].append(f"Maira: {response}")
+            
+            # Keep DB small
+            if len(u["history"]) > 30: u["history"] = u["history"][-20:]
+            
+            db[user_id] = u
+            return response