from langchain_qdrant import QdrantStore
from langchain_ollama import OllamaEmbeddings

class QdrantStore:
    def __init__(self, url="http://localhost:6333", collection_name="rag_collection"):
        self.client = QdrantStore(url=url, collection_name=collection_name)
        self.embeddings = OllamaEmbeddings(model="nomic-embed-text")

    def add_documents(self, docs):
        self.client.add_documents(docs, embeddings=self.embeddings)

    def search(self, query, limit=5):
        return self.client.search(query, limit=limit, embeddings=self.embeddings)