fix: change exception type

lightrag/llm.py

@@ -15,7 +15,7 @@ from openai import (
     AsyncOpenAI,
     APIConnectionError,
     RateLimitError,
-    Timeout,
+    APITimeoutError,
     AsyncAzureOpenAI,
 )
 from pydantic import BaseModel, Field
@@ -47,7 +47,7 @@ os.environ["TOKENIZERS_PARALLELISM"] = "false"
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def openai_complete_if_cache(
     model,
@@ -108,7 +108,7 @@ async def openai_complete_if_cache(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APIConnectionError)),
 )
 async def azure_openai_complete_if_cache(
     model,
@@ -259,7 +259,7 @@ def initialize_hf_model(model_name):
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def hf_model_if_cache(
     model,
@@ -326,7 +326,7 @@ async def hf_model_if_cache(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def ollama_model_if_cache(
     model,
@@ -444,7 +444,7 @@ def initialize_lmdeploy_pipeline(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def lmdeploy_model_if_cache(
     model,
@@ -704,7 +704,7 @@ async def lollms_model_complete(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def zhipu_complete_if_cache(
     prompt: Union[str, List[Dict[str, str]]],
@@ -834,7 +834,7 @@ async def zhipu_complete(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=60),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def zhipu_embedding(
     texts: list[str], model: str = "embedding-3", api_key: str = None, **kwargs
@@ -870,7 +870,7 @@ async def zhipu_embedding(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=60),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def openai_embedding(
     texts: list[str],
@@ -928,7 +928,7 @@ async def jina_embedding(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=60),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def nvidia_openai_embedding(
     texts: list[str],
@@ -959,7 +959,7 @@ async def nvidia_openai_embedding(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=10),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def azure_openai_embedding(
     texts: list[str],
@@ -990,7 +990,7 @@ async def azure_openai_embedding(
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=4, max=60),
-    retry=retry_if_exception_type((RateLimitError, APIConnectionError, Timeout)),
+    retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
 )
 async def siliconcloud_embedding(
     texts: list[str],