fix: vectorstore.py — Экзамен: RAG-агент с ChromaDB и веб-поиском

vectorstore.py

@@ -0,0 +1,34 @@
+import os
+from langchain_community.embeddings import OllamaEmbeddings
+from langchain_chroma import Chroma
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_core.documents import Document
+
+def create_vectorstore(persist_directory: str = "./chroma_db") -> Chroma:
+    embeddings = OllamaEmbeddings(model="nomic-embed-text")
+    return Chroma(
+        collection_name="knowledge",
+        embedding_function=embeddings,
+        persist_directory=persist_directory,
+    )
+
+def load_documents(directory: str, vectorstore: Chroma) -> None:
+    splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
+    documents = []
+    for root, _, files in os.walk(directory):
+        for file in files:
+            if file.endswith((".txt", ".md")):
+                path = os.path.join(root, file)
+                with open(path, "r", encoding="utf-8") as f:
+                    content = f.read()
+                docs = splitter.split_text(content)
+                for i, chunk in enumerate(docs):
+                    documents.append(
+                        Document(
+                            page_content=chunk,
+                            metadata={"source": path, "chunk": i},
+                        )
+                    )
+    if documents:
+        vectorstore.add_documents(documents)
+        vectorstore.persist()