From d4076ed6ae4c577a2bbf6caf408218ce754f2f7a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=9A=D0=B8=D1=80=D0=B8=D0=BB=D0=BB=20=D0=A0=D0=BE=D0=BC?= =?UTF-8?q?=D0=B0=D0=BD=D0=BE=D0=B2?= Date: Fri, 5 Jun 2026 13:03:23 +0000 Subject: [PATCH] Delete obsolete qdrant_store.py --- qdrant_store.py | 37 ------------------------------------- 1 file changed, 37 deletions(-) delete mode 100644 qdrant_store.py diff --git a/qdrant_store.py b/qdrant_store.py deleted file mode 100644 index 6120f7a..0000000 --- a/qdrant_store.py +++ /dev/null @@ -1,37 +0,0 @@ -"""Wrapper around QdrantVectorStore using Ollama embeddings. - -This module is intentionally lightweight and can be imported from any -context without requiring the caller to set up a package structure. -""" - -import os -import sys - -# Ensure the current directory is in sys.path so that relative imports work -sys.path.append(os.path.dirname(__file__)) - -from langchain_ollama import OllamaEmbeddings -from langchain_qdrant import QdrantVectorStore -from langchain_text_splitters import RecursiveCharacterTextSplitter -from typing import List, Dict - -class QdrantStore: - """Wrapper around QdrantVectorStore using Ollama embeddings.""" - - def __init__(self, host: str = "localhost", port: int = 6333, collection_name: str = "knowledge_base"): - self.embeddings = OllamaEmbeddings(model="nomic-embed-text") - self.store = QdrantVectorStore( - url=f"http://{host}:{port}", - collection_name=collection_name, - embeddings=self.embeddings, - ) - - def add_document(self, content: str, title: str) -> None: - splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50) - chunks = splitter.split_text(content) - metadatas = [{"title": title, "source": title} for _ in chunks] - self.store.add_texts(chunks, metadatas=metadatas) - - def search(self, query: str, k: int = 5) -> List[Dict]: - results = self.store.similarity_search(query, k=k) - return [{"content": doc.page_content, "metadata": doc.metadata} for doc in results] \ No newline at end of file