update to langchain-core >= 0.3 (#379)

backend/embeddings.py

@@ -0,0 +1,6 @@
+from langchain_core.embeddings import Embeddings
+from langchain_openai import OpenAIEmbeddings
+
+
+def get_embeddings_model() -> Embeddings:
+    return OpenAIEmbeddings(model="text-embedding-3-small", chunk_size=200)

backend/graph.py

@@ -31,7 +31,7 @@
 from langsmith import Client as LangsmithClient
 
 from backend.constants import WEAVIATE_DOCS_INDEX_NAME
-from backend.ingest import get_embeddings_model
+from backend.embeddings import get_embeddings_model
 
 RESPONSE_TEMPLATE = """\
 You are an expert programmer and problem-solver, tasked with answering any question \

backend/ingest.py

@@ -8,23 +8,18 @@
 from bs4 import BeautifulSoup, SoupStrainer
 from langchain.document_loaders import RecursiveUrlLoader, SitemapLoader
 from langchain.indexes import SQLRecordManager, index
-from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.utils.html import PREFIXES_TO_IGNORE_REGEX, SUFFIXES_TO_IGNORE_REGEX
-from langchain_core.embeddings import Embeddings
-from langchain_openai import OpenAIEmbeddings
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_weaviate import WeaviateVectorStore
 
 from backend.constants import WEAVIATE_DOCS_INDEX_NAME
+from backend.embeddings import get_embeddings_model
 from backend.parser import langchain_docs_extractor
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 
-def get_embeddings_model() -> Embeddings:
-    return OpenAIEmbeddings(model="text-embedding-3-small", chunk_size=200)
-
-
 def metadata_extractor(
     meta: dict, soup: BeautifulSoup, title_suffix: Optional[str] = None
 ) -> dict: