From 57d748dde82b3ceaae0f16b9a1b1cdaf4e88e606 Mon Sep 17 00:00:00 2001
From: Ismail Ashraq <ismailashraq@Ismails-MacBook-Pro.local>
Date: Sun, 18 Aug 2024 16:14:17 +0500
Subject: [PATCH] linting
---
semantic_router/encoders/openai.py | 22 +++++++++++-----------
semantic_router/encoders/zure.py | 23 ++++++++++++-----------
2 files changed, 23 insertions(+), 22 deletions(-)
diff --git a/semantic_router/encoders/openai.py b/semantic_router/encoders/openai.py
index 0425d5df..8ba7ee5b 100644
--- a/semantic_router/encoders/openai.py
+++ b/semantic_router/encoders/openai.py
@@ -42,7 +42,7 @@ class OpenAIEncoder(BaseEncoder):
token_limit: int = 8192 # default value, should be replaced by config
_token_encoder: Any = PrivateAttr()
type: str = "openai"
- max_retries: int
+ max_retries: int = 3
def __init__(
self,
@@ -56,9 +56,6 @@ class OpenAIEncoder(BaseEncoder):
):
if name is None:
name = EncoderDefault.OPENAI.value["embedding_model"]
-
- max_retries = max_retries if max_retries is not None else 3
-
if score_threshold is None and name in model_configs:
set_score_threshold = model_configs[name].threshold
elif score_threshold is None:
@@ -71,13 +68,14 @@ class OpenAIEncoder(BaseEncoder):
super().__init__(
name=name,
score_threshold=set_score_threshold,
- max_retries=max_retries,
)
api_key = openai_api_key or os.getenv("OPENAI_API_KEY")
base_url = openai_base_url or os.getenv("OPENAI_BASE_URL")
openai_org_id = openai_org_id or os.getenv("OPENAI_ORG_ID")
if api_key is None:
raise ValueError("OpenAI API key cannot be 'None'.")
+ if max_retries is not None:
+ self.max_retries = max_retries
try:
self.client = openai.Client(
base_url=base_url, api_key=api_key, organization=openai_org_id
@@ -108,7 +106,6 @@ class OpenAIEncoder(BaseEncoder):
if self.client is None:
raise ValueError("OpenAI client is not initialized.")
embeds = None
- error_message = ""
if truncate:
# check if any document exceeds token limit and truncate if so
@@ -129,7 +126,9 @@ class OpenAIEncoder(BaseEncoder):
logger.error("Exception occurred", exc_info=True)
if self.max_retries != 0:
sleep(2**j)
- logger.warning(f"Retrying in {2**j} seconds due to OpenAIError: {e}")
+ logger.warning(
+ f"Retrying in {2**j} seconds due to OpenAIError: {e}"
+ )
except Exception as e:
logger.error(f"OpenAI API call failed. Error: {e}")
@@ -141,7 +140,7 @@ class OpenAIEncoder(BaseEncoder):
or not embeds.data
):
logger.info(f"Returned embeddings: {embeds}")
- raise ValueError(f"No embeddings returned.")
+ raise ValueError("No embeddings returned.")
embeddings = [embeds_obj.embedding for embeds_obj in embeds.data]
return embeddings
@@ -163,7 +162,6 @@ class OpenAIEncoder(BaseEncoder):
if self.async_client is None:
raise ValueError("OpenAI async client is not initialized.")
embeds = None
- error_message = ""
if truncate:
# check if any document exceeds token limit and truncate if so
@@ -184,7 +182,9 @@ class OpenAIEncoder(BaseEncoder):
logger.error("Exception occurred", exc_info=True)
if self.max_retries != 0:
await asleep(2**j)
- logger.warning(f"Retrying in {2**j} seconds due to OpenAIError: {e}")
+ logger.warning(
+ f"Retrying in {2**j} seconds due to OpenAIError: {e}"
+ )
except Exception as e:
logger.error(f"OpenAI API call failed. Error: {e}")
raise ValueError(f"OpenAI API call failed. Error: {e}") from e
@@ -195,7 +195,7 @@ class OpenAIEncoder(BaseEncoder):
or not embeds.data
):
logger.info(f"Returned embeddings: {embeds}")
- raise ValueError(f"No embeddings returned.")
+ raise ValueError("No embeddings returned.")
embeddings = [embeds_obj.embedding for embeds_obj in embeds.data]
return embeddings
diff --git a/semantic_router/encoders/zure.py b/semantic_router/encoders/zure.py
index 3c199692..e04b55bf 100644
--- a/semantic_router/encoders/zure.py
+++ b/semantic_router/encoders/zure.py
@@ -23,7 +23,7 @@ class AzureOpenAIEncoder(BaseEncoder):
azure_endpoint: Optional[str] = None
api_version: Optional[str] = None
model: Optional[str] = None
- max_retries: int
+ max_retries: int = 3
def __init__(
self,
@@ -39,10 +39,7 @@ class AzureOpenAIEncoder(BaseEncoder):
name = deployment_name
if name is None:
name = EncoderDefault.AZURE.value["embedding_model"]
-
- max_retries = max_retries if max_retries is not None else 3
-
- super().__init__(name=name, score_threshold=score_threshold, max_retries=max_retries)
+ super().__init__(name=name, score_threshold=score_threshold)
self.api_key = api_key
self.deployment_name = deployment_name
self.azure_endpoint = azure_endpoint
@@ -54,6 +51,8 @@ class AzureOpenAIEncoder(BaseEncoder):
self.api_key = os.getenv("AZURE_OPENAI_API_KEY")
if self.api_key is None:
raise ValueError("No Azure OpenAI API key provided.")
+ if max_retries is not None:
+ self.max_retries = max_retries
if self.deployment_name is None:
self.deployment_name = EncoderDefault.AZURE.value["deployment_name"]
# deployment_name may still be None, but it is optional in the API
@@ -102,7 +101,6 @@ class AzureOpenAIEncoder(BaseEncoder):
if self.client is None:
raise ValueError("Azure OpenAI client is not initialized.")
embeds = None
- error_message = ""
# Exponential backoff
for j in range(self.max_retries + 1):
@@ -119,7 +117,9 @@ class AzureOpenAIEncoder(BaseEncoder):
logger.error("Exception occurred", exc_info=True)
if self.max_retries != 0:
sleep(2**j)
- logger.warning(f"Retrying in {2**j} seconds due to OpenAIError: {e}")
+ logger.warning(
+ f"Retrying in {2**j} seconds due to OpenAIError: {e}"
+ )
except Exception as e:
logger.error(f"Azure OpenAI API call failed. Error: {e}")
raise ValueError(f"Azure OpenAI API call failed. Error: {e}") from e
@@ -129,7 +129,7 @@ class AzureOpenAIEncoder(BaseEncoder):
or not isinstance(embeds, CreateEmbeddingResponse)
or not embeds.data
):
- raise ValueError(f"No embeddings returned.")
+ raise ValueError("No embeddings returned.")
embeddings = [embeds_obj.embedding for embeds_obj in embeds.data]
return embeddings
@@ -138,7 +138,6 @@ class AzureOpenAIEncoder(BaseEncoder):
if self.async_client is None:
raise ValueError("Azure OpenAI async client is not initialized.")
embeds = None
- error_message = ""
# Exponential backoff
for j in range(self.max_retries + 1):
@@ -156,7 +155,9 @@ class AzureOpenAIEncoder(BaseEncoder):
logger.error("Exception occurred", exc_info=True)
if self.max_retries != 0:
await asleep(2**j)
- logger.warning(f"Retrying in {2**j} seconds due to OpenAIError: {e}")
+ logger.warning(
+ f"Retrying in {2**j} seconds due to OpenAIError: {e}"
+ )
except Exception as e:
logger.error(f"Azure OpenAI API call failed. Error: {e}")
raise ValueError(f"Azure OpenAI API call failed. Error: {e}") from e
@@ -166,7 +167,7 @@ class AzureOpenAIEncoder(BaseEncoder):
or not isinstance(embeds, CreateEmbeddingResponse)
or not embeds.data
):
- raise ValueError(f"No embeddings returned.")
+ raise ValueError("No embeddings returned.")
embeddings = [embeds_obj.embedding for embeds_obj in embeds.data]
return embeddings
--
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