AOT: Finalize RAG-integrated Space deployment

app.py

@@ -1,49 +1,20 @@
-#!/usr/bin/env python3
-import os
-import sys
-from pathlib import Path
+import gradio as gr
+from src.core.memory_engine import MemoryEngine
 
-BASE_DIR = Path(__file__).parent.absolute()
-if str(BASE_DIR) not in sys.path:
-    sys.path.insert(0, str(BASE_DIR))
+# Initialize the Sovereign Brain
+brain = MemoryEngine()
+brain.ingest_knowledge('storage/knowledge')
 
-from core.brain import VitalisBrain
-from extensions.dreamer import Dreamer
-from extensions.temp_scheduler import TemperatureScheduler
-from src.energy.free_energy import FreeEnergyEngine
+def vitalis_chat(user_message, history):
+    # Retrieve relevant protocol from local vector store
+    response = brain.query(user_message)
+    return f"[VITALIS_CORE_UI]: {response}"
 
-def main():
-    print("[*] Launching Vitalis Bio-AI Engine with Active Inference (FEP)...")
-    brain = VitalisBrain()
-    temp_scheduler = TemperatureScheduler(brain)
-    fe_engine = FreeEnergyEngine(alpha=0.85)
-    
-    dreamer = Dreamer(brain, interval_sec=600)
-    dreamer.start()
-    
-    print("[+] Engine operational. Free-Energy optimization loops tracking live telemetry.")
-    print("Telemetry In > ", end="")
-    
-    while True:
-        try:
-            user_input = input().strip()
-            if not user_input:
-                print("Telemetry In > ", end="")
-                continue
-            if user_input.lower() in ["exit", "quit"]:
-                dreamer.stop()
-                break
-            
-            tokens = brain._tokenize(user_input)
-            logprob = brain.calculate_last_logprob(tokens)
-            fe_engine.ingest_observation(logprob)
-            brain.current_temperature = fe_engine.temperature_factor(base_temp=0.8)
-            temp_scheduler.tick()
-            response = brain.process(user_input)
-            print(f"Metrics Out > {response} [FE: {fe_engine.free_energy:.4f} | Temp: {brain.current_temperature:.4f}]\nTelemetry In > ", end="")
-        except (KeyboardInterrupt, EOFError):
-            dreamer.stop()
-            break
+demo = gr.ChatInterface(
+    fn=vitalis_chat,
+    title="Vitalis Synthetic Intelligence | Sovereign Core",
+    theme="soft"
+)
 
 if __name__ == "__main__":
-    main()
+    demo.launch()

requirements.txt

@@ -1,6 +1,4 @@
-numpy
-pyyaml
-click
-faiss-cpu
+gradio==4.26.0
 sentence-transformers
-huggingface_hub
+faiss-cpu
+numpy

src/core/memory_engine.py

@@ -0,0 +1,25 @@
+from sentence_transformers import SentenceTransformer
+import faiss
+import numpy as np
+import os
+
+class MemoryEngine:
+    def __init__(self):
+        self.model = SentenceTransformer('all-MiniLM-L6-v2')
+        self.index = None
+        self.documents = []
+
+    def ingest_knowledge(self, directory):
+        for filename in os.listdir(directory):
+            with open(os.path.join(directory, filename), 'r') as f:
+                content = f.read()
+                self.documents.append(content)
+        embeddings = self.model.encode(self.documents)
+        dimension = embeddings.shape[1]
+        self.index = faiss.IndexFlatL2(dimension)
+        self.index.add(np.array(embeddings).astype('float32'))
+
+    def query(self, user_input):
+        query_vector = self.model.encode([user_input])
+        D, I = self.index.search(np.array(query_vector).astype('float32'), k=1)
+        return self.documents[I[0][0]]