IamNA.me (해석 인터페이스 계층)

import ollama
from vector_db import ChromaConnector
from data_ingestor import SessionStream
  
class DigitalTwinAgent(object):
    # Initializes the individual cognitive RAG agent
    def __init__(self, user_id, model_name="qwen2.5-coder"):
        self.db = ChromaConnector(collection_name=f"twin_{user_id}")
        self.model = model_name
        self.stream_monitor = SessionStream(anchor="localhost")
        
    def query_cognitive_context(self, prompt):
        # 1. Fetch relevant vector history from ChromaDB
        context_nodes = self.db.similarity_search(query= prompt, limit= 5)
        
        # 2. Augment prompt with spatial/temporal context
        augmented_prompt = self.stream_monitor.inject_context(prompt, context_nodes)
        
        # 3. Generate response using local Ollama model
        response = ollama.generate(model= self.model, prompt= augmented_prompt)
        return response['response']
 
# Instance initialization (Host: Local Mac Mini Cluster)
agent = DigitalTwinAgent(user_id="moogyung")