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fix: Fix potential mutable default parameter issue

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This commit is contained in:
yangdx
2025-02-06 14:46:07 +08:00
parent a49ee2ce71
commit eb5f57e989
2 changed files with 21 additions and 7 deletions
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8
lightrag/api/lightrag_server.py
View File

@@ -752,10 +752,12 @@ def create_app(args):
async def openai_alike_model_complete( async def openai_alike_model_complete(
prompt, prompt,
system_prompt=None, system_prompt=None,
history_messages=[], history_messages=None,
keyword_extraction=False, keyword_extraction=False,
**kwargs, **kwargs,
) -> str: ) -> str:
if history_messages is None:
history_messages = []
return await openai_complete_if_cache( return await openai_complete_if_cache(
args.llm_model, args.llm_model,
prompt, prompt,
@@ -769,10 +771,12 @@ def create_app(args):
async def azure_openai_model_complete( async def azure_openai_model_complete(
prompt, prompt,
system_prompt=None, system_prompt=None,
history_messages=[], history_messages=None,
keyword_extraction=False, keyword_extraction=False,
**kwargs, **kwargs,
) -> str: ) -> str:
if history_messages is None:
history_messages = []
return await azure_openai_complete_if_cache( return await azure_openai_complete_if_cache(
args.llm_model, args.llm_model,
prompt, prompt,

20
lightrag/llm/openai.py
View File

@@ -89,11 +89,13 @@ async def openai_complete_if_cache(
model, model,
prompt, prompt,
system_prompt=None, system_prompt=None,
history_messages=[], history_messages=None,
base_url=None, base_url=None,
api_key=None, api_key=None,
**kwargs, **kwargs,
) -> str: ) -> str:
if history_messages is None:
history_messages = []
if api_key: if api_key:
os.environ["OPENAI_API_KEY"] = api_key os.environ["OPENAI_API_KEY"] = api_key
@@ -146,8 +148,10 @@ async def openai_complete_if_cache(
async def openai_complete( async def openai_complete(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs prompt, system_prompt=None, history_messages=None, keyword_extraction=False, **kwargs
) -> Union[str, AsyncIterator[str]]: ) -> Union[str, AsyncIterator[str]]:
if history_messages is None:
history_messages = []
keyword_extraction = kwargs.pop("keyword_extraction", None) keyword_extraction = kwargs.pop("keyword_extraction", None)
if keyword_extraction: if keyword_extraction:
kwargs["response_format"] = "json" kwargs["response_format"] = "json"
@@ -162,8 +166,10 @@ async def openai_complete(
async def gpt_4o_complete( async def gpt_4o_complete(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs prompt, system_prompt=None, history_messages=None, keyword_extraction=False, **kwargs
) -> str: ) -> str:
if history_messages is None:
history_messages = []
keyword_extraction = kwargs.pop("keyword_extraction", None) keyword_extraction = kwargs.pop("keyword_extraction", None)
if keyword_extraction: if keyword_extraction:
kwargs["response_format"] = GPTKeywordExtractionFormat kwargs["response_format"] = GPTKeywordExtractionFormat
@@ -177,8 +183,10 @@ async def gpt_4o_complete(
async def gpt_4o_mini_complete( async def gpt_4o_mini_complete(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs prompt, system_prompt=None, history_messages=None, keyword_extraction=False, **kwargs
) -> str: ) -> str:
if history_messages is None:
history_messages = []
keyword_extraction = kwargs.pop("keyword_extraction", None) keyword_extraction = kwargs.pop("keyword_extraction", None)
if keyword_extraction: if keyword_extraction:
kwargs["response_format"] = GPTKeywordExtractionFormat kwargs["response_format"] = GPTKeywordExtractionFormat
@@ -192,8 +200,10 @@ async def gpt_4o_mini_complete(
async def nvidia_openai_complete( async def nvidia_openai_complete(
prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs prompt, system_prompt=None, history_messages=None, keyword_extraction=False, **kwargs
) -> str: ) -> str:
if history_messages is None:
history_messages = []
keyword_extraction = kwargs.pop("keyword_extraction", None) keyword_extraction = kwargs.pop("keyword_extraction", None)
result = await openai_complete_if_cache( result = await openai_complete_if_cache(
"nvidia/llama-3.1-nemotron-70b-instruct", # context length 128k "nvidia/llama-3.1-nemotron-70b-instruct", # context length 128k