Upload jairvis.py

models/jairvis.py

@@ -0,0 +1,47 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+from utils.self_awareness import SelfAwareness
+from config import MODEL_NAME, DEVICE
+
+class JAIRVISMKV:
+    def __init__(self):
+        self.model = AutoModelForCausalLM.from_pretrained(MODEL_NAME).to(DEVICE)
+        self.tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+        self.self_awareness = SelfAwareness(self)
+        self.conversation_context = []
+        self.max_context_length = 1024
+
+    def generate_response(self, prompt):
+        self.conversation_context.append(f"Human: {prompt}")
+        context = "\n".join(self.conversation_context[-5:])
+        
+        inputs = self.tokenizer.encode(context + "\nAI:", return_tensors="pt").to(DEVICE)
+        attention_mask = torch.ones(inputs.shape, dtype=torch.long, device=DEVICE)
+        
+        outputs = self.model.generate(
+            inputs,
+            attention_mask=attention_mask,
+            max_length=self.max_context_length,
+            num_return_sequences=1,
+            no_repeat_ngram_size=2,
+            top_k=50,
+            top_p=0.95,
+            temperature=0.7
+        )
+        
+        response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        ai_response = response.split("AI:")[-1].strip()
+        
+        self.conversation_context.append(f"AI: {ai_response}")
+        self.self_awareness.update_self_model()
+        
+        return ai_response
+
+    def introspect(self):
+        return self.self_awareness.generate_insights(str(self))
+
+    def implement_improvement(self, suggestion):
+        return self.self_awareness.implement_improvement(suggestion)
+
+    def __str__(self):
+        return f"JAIRVISMKV Model: {MODEL_NAME}, Device: {DEVICE}"