🌿 Fern Regeneration -- December 2, 2024

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cohere"
-version = "5.12.0"
+version = "5.13.0"
 description = ""
 readme = "README.md"
 authors = []

reference.md

@@ -2382,7 +2382,6 @@ response = client.v2.chat_stream(
     p=1.1,
     return_prompt=True,
     logprobs=True,
-    stream=True,
 )
 for chunk in response:
     yield chunk
@@ -2655,7 +2654,6 @@ client.v2.chat(
             content="messages",
         )
     ],
-    stream=False,
 )
 
 ```
@@ -2973,7 +2971,7 @@ Available models and corresponding embedding dimensions:
 
 **embedding_types:** `typing.Sequence[EmbeddingType]` 
 
-Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types.
+Specifies the types of embeddings you want to get back. Can be one or more of the following types.
 
 * `"float"`: Use this when you want to get back the default float embeddings. Valid for all models.
 * `"int8"`: Use this when you want to get back signed int8 embeddings. Valid for only v3 models.

src/cohere/__init__.py

@@ -245,7 +245,7 @@
 )
 from . import connectors, datasets, embed_jobs, finetuning, models, v2
 from .aws_client import AwsClient
-from .bedrock_client import BedrockClient
+from .bedrock_client import BedrockClient, BedrockClientV2
 from .client import AsyncClient, Client
 from .client_v2 import AsyncClientV2, ClientV2
 from .datasets import (
@@ -257,7 +257,7 @@
 )
 from .embed_jobs import CreateEmbedJobRequestTruncate
 from .environment import ClientEnvironment
-from .sagemaker_client import SagemakerClient
+from .sagemaker_client import SagemakerClient, SagemakerClientV2
 from .v2 import (
     V2ChatRequestDocumentsItem,
     V2ChatRequestSafetyMode,
@@ -287,6 +287,7 @@
     "AwsClient",
     "BadRequestError",
     "BedrockClient",
+    "BedrockClientV2",
     "ChatCitation",
     "ChatCitationGenerationEvent",
     "ChatConnector",
@@ -460,6 +461,7 @@
     "ResponseFormat",
     "ResponseFormatV2",
     "SagemakerClient",
+    "SagemakerClientV2",
     "SearchQueriesGenerationStreamedChatResponse",
     "SearchResultsStreamedChatResponse",
     "ServiceUnavailableError",

src/cohere/core/client_wrapper.py

@@ -24,7 +24,7 @@ def get_headers(self) -> typing.Dict[str, str]:
         headers: typing.Dict[str, str] = {
             "X-Fern-Language": "Python",
             "X-Fern-SDK-Name": "cohere",
-            "X-Fern-SDK-Version": "5.12.0",
+            "X-Fern-SDK-Version": "5.13.0",
         }
         if self._client_name is not None:
             headers["X-Client-Name"] = self._client_name

src/cohere/v2/client.py

@@ -222,7 +222,6 @@ def chat_stream(
             p=1.1,
             return_prompt=True,
             logprobs=True,
-            stream=True,
         )
         for chunk in response:
             yield chunk
@@ -535,7 +534,6 @@ def chat(
                     content="messages",
                 )
             ],
-            stream=False,
         )
         """
         _response = self._client_wrapper.httpx_client.request(
@@ -570,6 +568,7 @@ def chat(
                 "p": p,
                 "return_prompt": return_prompt,
                 "logprobs": logprobs,
+                "stream": False,
             },
             request_options=request_options,
             omit=OMIT,
@@ -737,7 +736,7 @@ def embed(
         input_type : EmbedInputType
 
         embedding_types : typing.Sequence[EmbeddingType]
-            Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types.
+            Specifies the types of embeddings you want to get back. Can be one or more of the following types.
 
             * `"float"`: Use this when you want to get back the default float embeddings. Valid for all models.
             * `"int8"`: Use this when you want to get back signed int8 embeddings. Valid for only v3 models.
@@ -1308,7 +1307,6 @@ async def main() -> None:
                 p=1.1,
                 return_prompt=True,
                 logprobs=True,
-                stream=True,
             )
             async for chunk in response:
                 yield chunk
@@ -1348,6 +1346,7 @@ async def main() -> None:
                 "p": p,
                 "return_prompt": return_prompt,
                 "logprobs": logprobs,
+                "stream": True,
             },
             request_options=request_options,
             omit=OMIT,
@@ -1628,7 +1627,6 @@ async def main() -> None:
                         content="messages",
                     )
                 ],
-                stream=False,
             )
 
 
@@ -1666,6 +1664,7 @@ async def main() -> None:
                 "p": p,
                 "return_prompt": return_prompt,
                 "logprobs": logprobs,
+                "stream": False,
             },
             request_options=request_options,
             omit=OMIT,
@@ -1833,7 +1832,7 @@ async def embed(
         input_type : EmbedInputType
 
         embedding_types : typing.Sequence[EmbeddingType]
-            Specifies the types of embeddings you want to get back. Not required and default is None, which returns the Embed Floats response type. Can be one or more of the following types.
+            Specifies the types of embeddings you want to get back. Can be one or more of the following types.
 
             * `"float"`: Use this when you want to get back the default float embeddings. Valid for all models.
             * `"int8"`: Use this when you want to get back signed int8 embeddings. Valid for only v3 models.