🌿 Fern Regeneration -- August 4, 2025 (#684)

* SDK regeneration

* Update ci

* Don't cd

* Enhance CI workflow to ignore changes in poetry.lock and pyproject.toml for clean working tree checks

* Update CI workflow to only fail on relevant changes, ignoring poetry.lock and pyproject.toml

* Remove unnecessary set -eu command from CI workflow

* Refactor CI workflow to reset poetry changes and improve clean working tree checks

* Remove unnecessary directory change in langchain-cohere CI workflow

---------

Co-authored-by: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
Co-authored-by: Billy Trend <billy@cohere.com>

Author: fern-api[bot]

.github/workflows/ci.yml

@@ -71,17 +71,18 @@ jobs:
           poetry install --with test,test_integration
 
           echo "Going to uninstall cohere package, and install the current version from the repo"
-          cd ../../../cohere-python && echo "Current dir $(pwd)"
-          echo "Current dir $(ls)"
-          pip uninstall cohere
-          pip install .
-          cd ../langchain-cohere/libs/cohere
 
-          echo "Current cohere installation: $(pip freeze | grep cohere)"
+          poetry remove cohere
+          poetry add ../../../cohere-python
+
+          echo "Current cohere installation: $(poetry show cohere)"
           make test
           make integration_test
           echo "tests passed"
 
+          # reset poetry changes
+          git checkout -- poetry.lock pyproject.toml
+
           set -eu
 
           STATUS="$(git status)"

poetry.lock

@@ -3,7 +3,7 @@ name = "cohere"
 
 [tool.poetry]
 name = "cohere"
-version = "5.16.1"
+version = "5.16.2"
 description = ""
 readme = "README.md"
 authors = []

pyproject.toml

@@ -27,6 +27,7 @@
     ChatContentStartEventDelta,
     ChatContentStartEventDeltaMessage,
     ChatContentStartEventDeltaMessageContent,
+    ChatContentStartEventDeltaMessageContentType,
     ChatDataMetrics,
     ChatDebugEvent,
     ChatDocument,
@@ -205,6 +206,7 @@
     TextResponseFormatV2,
     TextSystemMessageV2ContentItem,
     TextToolContent,
+    ThinkingAssistantMessageResponseContentItem,
     TokenizeResponse,
     Tool,
     ToolCall,
@@ -325,6 +327,7 @@
     "ChatContentStartEventDelta",
     "ChatContentStartEventDeltaMessage",
     "ChatContentStartEventDeltaMessageContent",
+    "ChatContentStartEventDeltaMessageContentType",
     "ChatDataMetrics",
     "ChatDebugEvent",
     "ChatDocument",
@@ -536,6 +539,7 @@
     "TextResponseFormatV2",
     "TextSystemMessageV2ContentItem",
     "TextToolContent",
+    "ThinkingAssistantMessageResponseContentItem",
     "TokenizeResponse",
     "TooManyRequestsError",
     "Tool",

src/cohere/__init__.py

@@ -146,6 +146,7 @@ def chat_stream(
         *,
         message: str,
         accepts: typing.Optional[typing.Literal["text/event-stream"]] = None,
+        raw_prompting: typing.Optional[bool] = OMIT,
         model: typing.Optional[str] = OMIT,
         preamble: typing.Optional[str] = OMIT,
         chat_history: typing.Optional[typing.Sequence[Message]] = OMIT,
@@ -186,6 +187,12 @@ def chat_stream(
         accepts : typing.Optional[typing.Literal["text/event-stream"]]
             Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
 
+        raw_prompting : typing.Optional[bool]
+            When enabled, the user's prompt will be sent to the model without
+            any pre-processing.
+
+            Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
+
         model : typing.Optional[str]
             The name of a compatible [Cohere model](https://docs.cohere.com/docs/models) or the ID of a [fine-tuned](https://docs.cohere.com/docs/chat-fine-tuning) model.
 
@@ -407,6 +414,7 @@ def chat_stream(
         with self._raw_client.chat_stream(
             message=message,
             accepts=accepts,
+            raw_prompting=raw_prompting,
             model=model,
             preamble=preamble,
             chat_history=chat_history,
@@ -439,6 +447,7 @@ def chat(
         *,
         message: str,
         accepts: typing.Optional[typing.Literal["text/event-stream"]] = None,
+        raw_prompting: typing.Optional[bool] = OMIT,
         model: typing.Optional[str] = OMIT,
         preamble: typing.Optional[str] = OMIT,
         chat_history: typing.Optional[typing.Sequence[Message]] = OMIT,
@@ -478,6 +487,12 @@ def chat(
         accepts : typing.Optional[typing.Literal["text/event-stream"]]
             Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
 
+        raw_prompting : typing.Optional[bool]
+            When enabled, the user's prompt will be sent to the model without
+            any pre-processing.
+
+            Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
+
         model : typing.Optional[str]
             The name of a compatible [Cohere model](https://docs.cohere.com/docs/models) or the ID of a [fine-tuned](https://docs.cohere.com/docs/chat-fine-tuning) model.
 
@@ -710,6 +725,7 @@ def chat(
         _response = self._raw_client.chat(
             message=message,
             accepts=accepts,
+            raw_prompting=raw_prompting,
             model=model,
             preamble=preamble,
             chat_history=chat_history,
@@ -1586,6 +1602,7 @@ async def chat_stream(
         *,
         message: str,
         accepts: typing.Optional[typing.Literal["text/event-stream"]] = None,
+        raw_prompting: typing.Optional[bool] = OMIT,
         model: typing.Optional[str] = OMIT,
         preamble: typing.Optional[str] = OMIT,
         chat_history: typing.Optional[typing.Sequence[Message]] = OMIT,
@@ -1626,6 +1643,12 @@ async def chat_stream(
         accepts : typing.Optional[typing.Literal["text/event-stream"]]
             Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
 
+        raw_prompting : typing.Optional[bool]
+            When enabled, the user's prompt will be sent to the model without
+            any pre-processing.
+
+            Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
+
         model : typing.Optional[str]
             The name of a compatible [Cohere model](https://docs.cohere.com/docs/models) or the ID of a [fine-tuned](https://docs.cohere.com/docs/chat-fine-tuning) model.
 
@@ -1855,6 +1878,7 @@ async def main() -> None:
         async with self._raw_client.chat_stream(
             message=message,
             accepts=accepts,
+            raw_prompting=raw_prompting,
             model=model,
             preamble=preamble,
             chat_history=chat_history,
@@ -1888,6 +1912,7 @@ async def chat(
         *,
         message: str,
         accepts: typing.Optional[typing.Literal["text/event-stream"]] = None,
+        raw_prompting: typing.Optional[bool] = OMIT,
         model: typing.Optional[str] = OMIT,
         preamble: typing.Optional[str] = OMIT,
         chat_history: typing.Optional[typing.Sequence[Message]] = OMIT,
@@ -1927,6 +1952,12 @@ async def chat(
         accepts : typing.Optional[typing.Literal["text/event-stream"]]
             Pass text/event-stream to receive the streamed response as server-sent events. The default is `\n` delimited events.
 
+        raw_prompting : typing.Optional[bool]
+            When enabled, the user's prompt will be sent to the model without
+            any pre-processing.
+
+            Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments
+
         model : typing.Optional[str]
             The name of a compatible [Cohere model](https://docs.cohere.com/docs/models) or the ID of a [fine-tuned](https://docs.cohere.com/docs/chat-fine-tuning) model.
 
@@ -2167,6 +2198,7 @@ async def main() -> None:
         _response = await self._raw_client.chat(
             message=message,
             accepts=accepts,
+            raw_prompting=raw_prompting,
             model=model,
             preamble=preamble,
             chat_history=chat_history,

src/cohere/base_client.py

@@ -22,10 +22,10 @@ def __init__(
 
     def get_headers(self) -> typing.Dict[str, str]:
         headers: typing.Dict[str, str] = {
-            "User-Agent": "cohere/5.16.1",
+            "User-Agent": "cohere/5.16.2",
             "X-Fern-Language": "Python",
             "X-Fern-SDK-Name": "cohere",
-            "X-Fern-SDK-Version": "5.16.1",
+            "X-Fern-SDK-Version": "5.16.2",
         }
         if self._client_name is not None:
             headers["X-Client-Name"] = self._client_name

src/cohere/core/client_wrapper.py

@@ -44,6 +44,8 @@ def list_finetuned_models(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListFinetunedModelsResponse:
         """
+        Returns a list of fine-tuned models that the user has access to.
+
         Parameters
         ----------
         page_size : typing.Optional[int]
@@ -88,6 +90,8 @@ def create_finetuned_model(
         self, *, request: FinetunedModel, request_options: typing.Optional[RequestOptions] = None
     ) -> CreateFinetunedModelResponse:
         """
+        Creates a new fine-tuned model. The model will be trained on the dataset specified in the request body. The training process may take some time, and the model will be available once the training is complete.
+
         Parameters
         ----------
         request : FinetunedModel
@@ -128,6 +132,8 @@ def get_finetuned_model(
         self, id: str, *, request_options: typing.Optional[RequestOptions] = None
     ) -> GetFinetunedModelResponse:
         """
+        Retrieve a fine-tuned model by its ID.
+
         Parameters
         ----------
         id : str
@@ -160,6 +166,9 @@ def delete_finetuned_model(
         self, id: str, *, request_options: typing.Optional[RequestOptions] = None
     ) -> DeleteFinetunedModelResponse:
         """
+        Deletes a fine-tuned model. The model will be removed from the system and will no longer be available for use.
+        This operation is irreversible.
+
         Parameters
         ----------
         id : str
@@ -198,6 +207,8 @@ def update_finetuned_model(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> UpdateFinetunedModelResponse:
         """
+        Updates the fine-tuned model with the given ID. The model will be updated with the new settings and name provided in the request body.
+
         Parameters
         ----------
         id : str
@@ -255,6 +266,10 @@ def list_events(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListEventsResponse:
         """
+        Returns a list of events that occurred during the life-cycle of the fine-tuned model.
+        The events are ordered by creation time, with the most recent event first.
+        The list can be paginated using `page_size` and `page_token` parameters.
+
         Parameters
         ----------
         finetuned_model_id : str
@@ -313,6 +328,10 @@ def list_training_step_metrics(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListTrainingStepMetricsResponse:
         """
+        Returns a list of metrics measured during the training of a fine-tuned model.
+        The metrics are ordered by step number, with the most recent step first.
+        The list can be paginated using `page_size` and `page_token` parameters.
+
         Parameters
         ----------
         finetuned_model_id : str
@@ -375,6 +394,8 @@ async def list_finetuned_models(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListFinetunedModelsResponse:
         """
+        Returns a list of fine-tuned models that the user has access to.
+
         Parameters
         ----------
         page_size : typing.Optional[int]
@@ -427,6 +448,8 @@ async def create_finetuned_model(
         self, *, request: FinetunedModel, request_options: typing.Optional[RequestOptions] = None
     ) -> CreateFinetunedModelResponse:
         """
+        Creates a new fine-tuned model. The model will be trained on the dataset specified in the request body. The training process may take some time, and the model will be available once the training is complete.
+
         Parameters
         ----------
         request : FinetunedModel
@@ -475,6 +498,8 @@ async def get_finetuned_model(
         self, id: str, *, request_options: typing.Optional[RequestOptions] = None
     ) -> GetFinetunedModelResponse:
         """
+        Retrieve a fine-tuned model by its ID.
+
         Parameters
         ----------
         id : str
@@ -515,6 +540,9 @@ async def delete_finetuned_model(
         self, id: str, *, request_options: typing.Optional[RequestOptions] = None
     ) -> DeleteFinetunedModelResponse:
         """
+        Deletes a fine-tuned model. The model will be removed from the system and will no longer be available for use.
+        This operation is irreversible.
+
         Parameters
         ----------
         id : str
@@ -561,6 +589,8 @@ async def update_finetuned_model(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> UpdateFinetunedModelResponse:
         """
+        Updates the fine-tuned model with the given ID. The model will be updated with the new settings and name provided in the request body.
+
         Parameters
         ----------
         id : str
@@ -626,6 +656,10 @@ async def list_events(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListEventsResponse:
         """
+        Returns a list of events that occurred during the life-cycle of the fine-tuned model.
+        The events are ordered by creation time, with the most recent event first.
+        The list can be paginated using `page_size` and `page_token` parameters.
+
         Parameters
         ----------
         finetuned_model_id : str
@@ -692,6 +726,10 @@ async def list_training_step_metrics(
         request_options: typing.Optional[RequestOptions] = None,
     ) -> ListTrainingStepMetricsResponse:
         """
+        Returns a list of metrics measured during the training of a fine-tuned model.
+        The metrics are ordered by step number, with the most recent step first.
+        The list can be paginated using `page_size` and `page_token` parameters.
+
         Parameters
         ----------
         finetuned_model_id : str