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enh: tiktoken/token splitter support

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This commit is contained in:
Timothy J. Baek
2024-10-13 02:07:50 -07:00
parent 8ae605ec4b
commit dff3732fcd
4 changed files with 49 additions and 7 deletions
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28
backend/open_webui/apps/retrieval/main.py
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@@ -47,6 +47,8 @@ from open_webui.apps.retrieval.utils import (
from open_webui.apps.webui.models.files import Files
from open_webui.config import (
BRAVE_SEARCH_API_KEY,
TIKTOKEN_ENCODING_NAME,
RAG_TEXT_SPLITTER,
CHUNK_OVERLAP,
CHUNK_SIZE,
CONTENT_EXTRACTION_ENGINE,
@@ -102,7 +104,7 @@ from open_webui.utils.misc import (
)
from open_webui.utils.utils import get_admin_user, get_verified_user
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.text_splitter import RecursiveCharacterTextSplitter, TokenTextSplitter
from langchain_community.document_loaders import (
YoutubeLoader,
)
@@ -129,6 +131,9 @@ app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION = (
app.state.config.CONTENT_EXTRACTION_ENGINE = CONTENT_EXTRACTION_ENGINE
app.state.config.TIKA_SERVER_URL = TIKA_SERVER_URL
app.state.config.TEXT_SPLITTER = RAG_TEXT_SPLITTER
app.state.config.TIKTOKEN_ENCODING_NAME = TIKTOKEN_ENCODING_NAME
app.state.config.CHUNK_SIZE = CHUNK_SIZE
app.state.config.CHUNK_OVERLAP = CHUNK_OVERLAP
@@ -648,11 +653,22 @@ def save_docs_to_vector_db(
raise ValueError(ERROR_MESSAGES.DUPLICATE_CONTENT)
if split:
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=app.state.config.CHUNK_SIZE,
chunk_overlap=app.state.config.CHUNK_OVERLAP,
add_start_index=True,
)
if app.state.config.TEXT_SPLITTER in ["", "character"]:
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=app.state.config.CHUNK_SIZE,
chunk_overlap=app.state.config.CHUNK_OVERLAP,
add_start_index=True,
)
elif app.state.config.TEXT_SPLITTER == "token":
text_splitter = TokenTextSplitter(
encoding_name=app.state.config.TIKTOKEN_ENCODING_NAME,
chunk_size=app.state.config.CHUNK_SIZE,
chunk_overlap=app.state.config.CHUNK_OVERLAP,
add_start_index=True,
)
else:
raise ValueError(ERROR_MESSAGES.DEFAULT("Invalid text splitter"))
docs = text_splitter.split_documents(docs)
if len(docs) == 0: