fix: rag_store.py — Агент с RAG-памятью

rag_store.py

@@ -0,0 +1,23 @@
+import os
+from langchain_openai import OpenAIEmbeddings
+from langchain_qdrant import Qdrant
+from langchain_core.documents import Document
+
+class KnowledgeBase:
+    def __init__(self, collection_name: str = "knowledge", host: str = "localhost", port: int = 6333):
+        self.embeddings = OpenAIEmbeddings(
+            model="text-embedding-3-small",
+            base_url="https://openrouter.ai/api/v1",
+            api_key=os.getenv("OPENAI_API_KEY"),
+        )
+        self.vector_store = Qdrant(
+            collection_name=collection_name,
+            url=f"http://{host}:{port}",
+            embedding_function=self.embeddings,
+        )
+
+    def add_documents(self, documents):
+        self.vector_store.add_documents(documents)
+
+    def similarity_search(self, query: str, k: int = 3):
+        return self.vector_store.similarity_search(query, k=k)