SDK regeneration

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cohere"
-version = "5.0.0a7"
+version = "5.0.0a8"
 description = ""
 readme = "README.md"
 authors = []

src/cohere/__init__.py

@@ -109,10 +109,8 @@
  SummarizeResponse,
  TokenizeResponse,
  Tool,
- ToolDefinition,
- ToolDefinitionInputsItem,
- ToolDefinitionOutputsItem,
  ToolInput,
+ ToolParameterDefinitionsValue,
  UpdateConnectorResponse,
 )
 from .errors import BadRequestError, ForbiddenError, InternalServerError, NotFoundError, TooManyRequestsError
@@ -252,10 +250,8 @@
  "TokenizeResponse",
  "TooManyRequestsError",
  "Tool",
- "ToolDefinition",
- "ToolDefinitionInputsItem",
- "ToolDefinitionOutputsItem",
  "ToolInput",
+ "ToolParameterDefinitionsValue",
  "UpdateConnectorResponse",
  "connectors",
  "datasets",

src/cohere/base_client.py

@@ -127,6 +127,7 @@ def chat_stream(
  p: typing.Optional[float] = OMIT,
  frequency_penalty: typing.Optional[float] = OMIT,
  presence_penalty: typing.Optional[float] = OMIT,
+ raw_prompting: typing.Optional[bool] = OMIT,
  request_options: typing.Optional[RequestOptions] = None,
  ) -> typing.Iterator[StreamedChatResponse]:
  """
@@ -204,6 +205,8 @@ def chat_stream(
 
  Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty`, except that this penalty is applied equally to all tokens that have already appeared, regardless of their exact frequencies.
 
+ - raw_prompting: typing.Optional[bool]. When enabled, the user's prompt will be sent to the model without any pre-processing.
+
  - request_options: typing.Optional[RequestOptions]. Request-specific configuration.
  """
  _request: typing.Dict[str, typing.Any] = {"message": message, "stream": True}
@@ -235,6 +238,8 @@ def chat_stream(
  _request["frequency_penalty"] = frequency_penalty
  if presence_penalty is not OMIT:
  _request["presence_penalty"] = presence_penalty
+ if raw_prompting is not OMIT:
+ _request["raw_prompting"] = raw_prompting
  with self._client_wrapper.httpx_client.stream(
  "POST",
  urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "chat"),
@@ -292,6 +297,7 @@ def chat(
  p: typing.Optional[float] = OMIT,
  frequency_penalty: typing.Optional[float] = OMIT,
  presence_penalty: typing.Optional[float] = OMIT,
+ raw_prompting: typing.Optional[bool] = OMIT,
  request_options: typing.Optional[RequestOptions] = None,
  ) -> NonStreamedChatResponse:
  """
@@ -369,6 +375,8 @@ def chat(
 
  Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty`, except that this penalty is applied equally to all tokens that have already appeared, regardless of their exact frequencies.
 
+ - raw_prompting: typing.Optional[bool]. When enabled, the user's prompt will be sent to the model without any pre-processing.
+
  - request_options: typing.Optional[RequestOptions]. Request-specific configuration.
  ---
  from cohere import ChatMessage, ChatMessageRole, ChatRequestPromptTruncation
@@ -427,6 +435,8 @@ def chat(
  _request["frequency_penalty"] = frequency_penalty
  if presence_penalty is not OMIT:
  _request["presence_penalty"] = presence_penalty
+ if raw_prompting is not OMIT:
+ _request["raw_prompting"] = raw_prompting
  _response = self._client_wrapper.httpx_client.request(
  "POST",
  urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "chat"),
@@ -1368,6 +1378,7 @@ async def chat_stream(
  p: typing.Optional[float] = OMIT,
  frequency_penalty: typing.Optional[float] = OMIT,
  presence_penalty: typing.Optional[float] = OMIT,
+ raw_prompting: typing.Optional[bool] = OMIT,
  request_options: typing.Optional[RequestOptions] = None,
  ) -> typing.AsyncIterator[StreamedChatResponse]:
  """
@@ -1445,6 +1456,8 @@ async def chat_stream(
 
  Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty`, except that this penalty is applied equally to all tokens that have already appeared, regardless of their exact frequencies.
 
+ - raw_prompting: typing.Optional[bool]. When enabled, the user's prompt will be sent to the model without any pre-processing.
+
  - request_options: typing.Optional[RequestOptions]. Request-specific configuration.
  """
  _request: typing.Dict[str, typing.Any] = {"message": message, "stream": True}
@@ -1476,6 +1489,8 @@ async def chat_stream(
  _request["frequency_penalty"] = frequency_penalty
  if presence_penalty is not OMIT:
  _request["presence_penalty"] = presence_penalty
+ if raw_prompting is not OMIT:
+ _request["raw_prompting"] = raw_prompting
  async with self._client_wrapper.httpx_client.stream(
  "POST",
  urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "chat"),
@@ -1533,6 +1548,7 @@ async def chat(
  p: typing.Optional[float] = OMIT,
  frequency_penalty: typing.Optional[float] = OMIT,
  presence_penalty: typing.Optional[float] = OMIT,
+ raw_prompting: typing.Optional[bool] = OMIT,
  request_options: typing.Optional[RequestOptions] = None,
  ) -> NonStreamedChatResponse:
  """
@@ -1610,6 +1626,8 @@ async def chat(
 
  Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty`, except that this penalty is applied equally to all tokens that have already appeared, regardless of their exact frequencies.
 
+ - raw_prompting: typing.Optional[bool]. When enabled, the user's prompt will be sent to the model without any pre-processing.
+
  - request_options: typing.Optional[RequestOptions]. Request-specific configuration.
  ---
  from cohere import ChatMessage, ChatMessageRole, ChatRequestPromptTruncation
@@ -1668,6 +1686,8 @@ async def chat(
  _request["frequency_penalty"] = frequency_penalty
  if presence_penalty is not OMIT:
  _request["presence_penalty"] = presence_penalty
+ if raw_prompting is not OMIT:
+ _request["raw_prompting"] = raw_prompting
  _response = await self._client_wrapper.httpx_client.request(
  "POST",
  urllib.parse.urljoin(f"{self._client_wrapper.get_base_url()}/", "chat"),

src/cohere/core/client_wrapper.py

@@ -21,7 +21,7 @@ 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": "5.0.0a7",
+ "X-Fern-SDK-Version": "5.0.0a8",
  }
  if self._client_name is not None:
  headers["X-Client-Name"] = self._client_name

src/cohere/types/__init__.py

@@ -112,10 +112,8 @@
 from .summarize_response import SummarizeResponse
 from .tokenize_response import TokenizeResponse
 from .tool import Tool
-from .tool_definition import ToolDefinition
-from .tool_definition_inputs_item import ToolDefinitionInputsItem
-from .tool_definition_outputs_item import ToolDefinitionOutputsItem
 from .tool_input import ToolInput
+from .tool_parameter_definitions_value import ToolParameterDefinitionsValue
 from .update_connector_response import UpdateConnectorResponse
 
 __all__ = [
@@ -227,9 +225,7 @@
  "SummarizeResponse",
  "TokenizeResponse",
  "Tool",
- "ToolDefinition",
- "ToolDefinitionInputsItem",
- "ToolDefinitionOutputsItem",
  "ToolInput",
+ "ToolParameterDefinitionsValue",
  "UpdateConnectorResponse",
 ]

src/cohere/types/tool.py

@@ -4,7 +4,7 @@
 import typing
 
 from ..core.datetime_utils import serialize_datetime
-from .tool_definition import ToolDefinition
+from .tool_parameter_definitions_value import ToolParameterDefinitionsValue
 
 try:
  import pydantic.v1 as pydantic # type: ignore
@@ -14,7 +14,8 @@
 
 class Tool(pydantic.BaseModel):
  name: str
- definition: typing.Optional[ToolDefinition] = None
+ description: str
+ parameter_definitions: typing.Optional[typing.Dict[str, ToolParameterDefinitionsValue]] = None
 
  def json(self, **kwargs: typing.Any) -> str:
  kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs}

src/cohere/types/tool_definition_inputs_item.py → src/cohere/types/tool_parameter_definitions_value.py

@@ -11,8 +11,7 @@
  import pydantic # type: ignore
 
 
-class ToolDefinitionInputsItem(pydantic.BaseModel):
- name: str
+class ToolParameterDefinitionsValue(pydantic.BaseModel):
  description: str
  type: str
  required: typing.Optional[bool] = None