gardel/lightrag
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fix linting error

Browse Source
This commit is contained in:
zrguo
2025-02-11 13:32:24 +08:00
parent 2d2ed19095
commit 5ffbb548ad
2 changed files with 7 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
lightrag/kg/jsondocstatus_impl.py
View File

@@ -116,7 +116,7 @@ class JsonDocStatusStorage(DocStatusStorage):
for k, v in self._data.items() for k, v in self._data.items()
if v["status"] == DocStatus.PROCESSED if v["status"] == DocStatus.PROCESSED
} }
async def get_processing_docs(self) -> dict[str, DocProcessingStatus]: async def get_processing_docs(self) -> dict[str, DocProcessingStatus]:
"""Get all processing documents""" """Get all processing documents"""
return { return {

8
lightrag/llm/openai.py
View File

@@ -113,7 +113,9 @@ async def openai_complete_if_cache(
openai_async_client = ( openai_async_client = (
AsyncOpenAI(default_headers=default_headers, api_key=api_key) AsyncOpenAI(default_headers=default_headers, api_key=api_key)
if base_url is None if base_url is None
else AsyncOpenAI(base_url=base_url, default_headers=default_headers, api_key=api_key) else AsyncOpenAI(
base_url=base_url, default_headers=default_headers, api_key=api_key
)
) )
kwargs.pop("hashing_kv", None) kwargs.pop("hashing_kv", None)
kwargs.pop("keyword_extraction", None) kwargs.pop("keyword_extraction", None)
@@ -304,7 +306,9 @@ async def openai_embed(
openai_async_client = ( openai_async_client = (
AsyncOpenAI(default_headers=default_headers, api_key=api_key) AsyncOpenAI(default_headers=default_headers, api_key=api_key)
if base_url is None if base_url is None
else AsyncOpenAI(base_url=base_url, default_headers=default_headers, api_key=api_key) else AsyncOpenAI(
base_url=base_url, default_headers=default_headers, api_key=api_key
)
) )
response = await openai_async_client.embeddings.create( response = await openai_async_client.embeddings.create(
model=model, input=texts, encoding_format="float" model=model, input=texts, encoding_format="float"