MCP Agentic RAG

#from llama_index.embeddings.huggingface import HuggingFaceEmbedding #import llama_index #print(llama_index.__version__) #embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2") from rag_code import QdrantVDB, EmbedData, Retriever retriever = Retriever(QdrantVDB("ml_faq_collection"), EmbedData()) print(retriever.search("Como evitar overfitting em modelos de machine learning?"))