flake8 cleanup

swarms/models/openai_embeddings.py

@@ -386,7 +386,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
             )
             for j in range(0, len(token), self.embedding_ctx_length):
                 tokens.append(
-                    token[j : j + self.embedding_ctx_length]
+                    token[j: j + self.embedding_ctx_length]
                 )
                 indices.append(i)
 
@@ -406,7 +406,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
         for i in _iter:
             response = embed_with_retry(
                 self,
-                input=tokens[i : i + _chunk_size],
+                input=tokens[i: i + _chunk_size],
                 **self._invocation_params,
             )
             batched_embeddings.extend(
@@ -486,7 +486,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
             )
             for j in range(0, len(token), self.embedding_ctx_length):
                 tokens.append(
-                    token[j : j + self.embedding_ctx_length]
+                    token[j: j + self.embedding_ctx_length]
                 )
                 indices.append(i)
 
@@ -495,7 +495,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
         for i in range(0, len(tokens), _chunk_size):
             response = await async_embed_with_retry(
                 self,
-                input=tokens[i : i + _chunk_size],
+                input=tokens[i: i + _chunk_size],
                 **self._invocation_params,
             )
             batched_embeddings.extend(

swarms/models/palm.py

@@ -41,15 +41,9 @@ def _create_retry_decorator() -> Callable[[Any], Any]:
             multiplier=multiplier, min=min_seconds, max=max_seconds
         ),
         retry=(
-            retry_if_exception_type(
-                google.api_core.exceptions.ResourceExhausted
-            )
-            | retry_if_exception_type(
-                google.api_core.exceptions.ServiceUnavailable
-            )
-            | retry_if_exception_type(
-                google.api_core.exceptions.GoogleAPIError
-            )
+            retry_if_exception_type(google.api_core.exceptions.ResourceExhausted)
+            | retry_if_exception_type(google.api_core.exceptions.ServiceUnavailable)
+            | retry_if_exception_type(google.api_core.exceptions.GoogleAPIError)
         ),
         before_sleep=before_sleep_log(logger, logging.WARNING),
     )
@@ -123,30 +117,17 @@ class GooglePalm(BaseLLM, BaseModel):
 
         values["client"] = genai
 
-        if (
-            values["temperature"] is not None
-            and not 0 <= values["temperature"] <= 1
-        ):
-            raise ValueError(
-                "temperature must be in the range [0.0, 1.0]"
-            )
+        if (values["temperature"] is not None and not 0 <= values["temperature"] <= 1):
+            raise ValueError("temperature must be in the range [0.0, 1.0]")
 
-        if (
-            values["top_p"] is not None
-            and not 0 <= values["top_p"] <= 1
-        ):
+        if (values["top_p"] is not None and not 0 <= values["top_p"] <= 1):
             raise ValueError("top_p must be in the range [0.0, 1.0]")
 
         if values["top_k"] is not None and values["top_k"] <= 0:
             raise ValueError("top_k must be positive")
 
-        if (
-            values["max_output_tokens"] is not None
-            and values["max_output_tokens"] <= 0
-        ):
-            raise ValueError(
-                "max_output_tokens must be greater than zero"
-            )
+        if (values["max_output_tokens"] is not None and values["max_output_tokens"] <= 0):
+            raise ValueError("max_output_tokens must be greater than zero")
 
         return values