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