fix: fix formatting issues
This commit is contained in:
@@ -47,7 +47,9 @@ os.environ["TOKENIZERS_PARALLELISM"] = "false"
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def openai_complete_if_cache(
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model,
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@@ -108,7 +110,9 @@ async def openai_complete_if_cache(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APIConnectionError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APIConnectionError)
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),
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)
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async def azure_openai_complete_if_cache(
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model,
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@@ -259,7 +263,9 @@ def initialize_hf_model(model_name):
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def hf_model_if_cache(
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model,
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@@ -326,7 +332,9 @@ async def hf_model_if_cache(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def ollama_model_if_cache(
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model,
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@@ -444,7 +452,9 @@ def initialize_lmdeploy_pipeline(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def lmdeploy_model_if_cache(
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model,
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@@ -704,7 +714,9 @@ async def lollms_model_complete(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def zhipu_complete_if_cache(
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prompt: Union[str, List[Dict[str, str]]],
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@@ -834,7 +846,9 @@ async def zhipu_complete(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=60),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def zhipu_embedding(
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texts: list[str], model: str = "embedding-3", api_key: str = None, **kwargs
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@@ -870,7 +884,9 @@ async def zhipu_embedding(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=60),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def openai_embedding(
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texts: list[str],
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@@ -928,7 +944,9 @@ async def jina_embedding(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=60),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def nvidia_openai_embedding(
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texts: list[str],
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@@ -959,7 +977,9 @@ async def nvidia_openai_embedding(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=10),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def azure_openai_embedding(
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texts: list[str],
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@@ -990,7 +1010,9 @@ async def azure_openai_embedding(
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@retry(
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=4, max=60),
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retry=retry_if_exception_type((RateLimitError, APIConnectionError, APITimeoutError)),
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retry=retry_if_exception_type(
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(RateLimitError, APIConnectionError, APITimeoutError)
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),
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)
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async def siliconcloud_embedding(
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texts: list[str],
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