🌿 Fern Regeneration -- November 27, 2024

.gitignore

@@ -3,4 +3,3 @@ dist/
 __pycache__/
 poetry.toml
 .ruff_cache/
-.venv/

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cohere"
-version = "5.11.4"
+version = "5.12.0"
 description = ""
 readme = "README.md"
 authors = []

reference.md

@@ -2365,6 +2365,7 @@ response = client.v2.chat_stream(
             ),
         )
     ],
+    strict_tools=True,
     documents=["string"],
     citation_options=CitationOptions(
         mode="FAST",
@@ -2381,6 +2382,7 @@ response = client.v2.chat_stream(
     p=1.1,
     return_prompt=True,
     logprobs=True,
+    stream=True,
 )
 for chunk in response:
     yield chunk
@@ -2422,6 +2424,19 @@ A list of available tools (functions) that the model may suggest invoking before
 When `tools` is passed (without `tool_results`), the `text` content in the response will be empty and the `tool_calls` field in the response will be populated with a list of tool calls that need to be made. If no calls need to be made, the `tool_calls` array will be empty.
 
 
+</dd>
+</dl>
+
+<dl>
+<dd>
+
+**strict_tools:** `typing.Optional[bool]` 
+
+When set to `true`, tool calls in the Assistant message will be forced to follow the tool definition strictly. Learn more in the [Strict Tools guide](https://docs.cohere.com/docs/structured-outputs-json#structured-outputs-tools).
+
+**Note**: The first few requests with a new set of tools will take longer to process.
+
+
 </dd>
 </dl>
 
@@ -2546,7 +2561,7 @@ Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty
 
 **k:** `typing.Optional[float]` 
 
-Ensures that only the top `k` most likely tokens are considered for generation at each step. When `k` is set to `0`, k-sampling is disabled. 
+Ensures that only the top `k` most likely tokens are considered for generation at each step. When `k` is set to `0`, k-sampling is disabled.
 Defaults to `0`, min value of `0`, max value of `500`.
 
 
@@ -2576,7 +2591,7 @@ Defaults to `0.75`. min value of `0.01`, max value of `0.99`.
 <dl>
 <dd>
 
-**logprobs:** `typing.Optional[bool]` — Whether to return the log probabilities of the generated tokens. Defaults to false.
+**logprobs:** `typing.Optional[bool]` — Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
 
 
 </dd>
@@ -2640,6 +2655,7 @@ client.v2.chat(
             content="messages",
         )
     ],
+    stream=False,
 )
 
 ```
@@ -2679,6 +2695,19 @@ A list of available tools (functions) that the model may suggest invoking before
 When `tools` is passed (without `tool_results`), the `text` content in the response will be empty and the `tool_calls` field in the response will be populated with a list of tool calls that need to be made. If no calls need to be made, the `tool_calls` array will be empty.
 
 
+</dd>
+</dl>
+
+<dl>
+<dd>
+
+**strict_tools:** `typing.Optional[bool]` 
+
+When set to `true`, tool calls in the Assistant message will be forced to follow the tool definition strictly. Learn more in the [Strict Tools guide](https://docs.cohere.com/docs/structured-outputs-json#structured-outputs-tools).
+
+**Note**: The first few requests with a new set of tools will take longer to process.
+
+
 </dd>
 </dl>
 
@@ -2803,7 +2832,7 @@ Used to reduce repetitiveness of generated tokens. Similar to `frequency_penalty
 
 **k:** `typing.Optional[float]` 
 
-Ensures that only the top `k` most likely tokens are considered for generation at each step. When `k` is set to `0`, k-sampling is disabled. 
+Ensures that only the top `k` most likely tokens are considered for generation at each step. When `k` is set to `0`, k-sampling is disabled.
 Defaults to `0`, min value of `0`, max value of `500`.
 
 
@@ -2833,7 +2862,7 @@ Defaults to `0.75`. min value of `0.01`, max value of `0.99`.
 <dl>
 <dd>
 
-**logprobs:** `typing.Optional[bool]` — Whether to return the log probabilities of the generated tokens. Defaults to false.
+**logprobs:** `typing.Optional[bool]` — Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
 
 
 </dd>
@@ -3057,7 +3086,15 @@ client.v2.rerank(
 <dl>
 <dd>
 
-**model:** `str` — The identifier of the model to use, one of : `rerank-english-v3.0`, `rerank-multilingual-v3.0`, `rerank-english-v2.0`, `rerank-multilingual-v2.0`
+**model:** `str` 
+
+The identifier of the model to use.
+
+Supported models:
+  - `rerank-english-v3.0`
+  - `rerank-multilingual-v3.0`
+  - `rerank-english-v2.0`
+  - `rerank-multilingual-v2.0`
 
 </dd>
 </dl>
@@ -3073,30 +3110,22 @@ client.v2.rerank(
 <dl>
 <dd>
 
-**documents:** `typing.Sequence[V2RerankRequestDocumentsItem]` 
-
-A list of document objects or strings to rerank.
-If a document is provided the text fields is required and all other fields will be preserved in the response.
-
-The total max chunks (length of documents * max_chunks_per_doc) must be less than 10000.
+**documents:** `typing.Sequence[str]` 
 
-We recommend a maximum of 1,000 documents for optimal endpoint performance.
-
-</dd>
-</dl>
+A list of texts that will be compared to the `query`.
+For optimal performance we recommend against sending more than 1,000 documents in a single request.
 
-<dl>
-<dd>
+**Note**: long documents will automatically be truncated to the value of `max_tokens_per_doc`.
 
-**top_n:** `typing.Optional[int]` — The number of most relevant documents or indices to return, defaults to the length of the documents
+**Note**: structured data should be formatted as YAML strings for best performance.  
 
 </dd>
 </dl>
 
 <dl>
 <dd>
 
-**rank_fields:** `typing.Optional[typing.Sequence[str]]` — If a JSON object is provided, you can specify which keys you would like to have considered for reranking. The model will rerank based on order of the fields passed in (i.e. rank_fields=['title','author','text'] will rerank using the values in title, author, text  sequentially. If the length of title, author, and text exceeds the context length of the model, the chunking will not re-consider earlier fields). If not provided, the model will use the default text field for ranking.
+**top_n:** `typing.Optional[int]` — Limits the number of returned rerank results to the specified value. If not passed, all the rerank results will be returned.
 
 </dd>
 </dl>
@@ -3115,7 +3144,7 @@ We recommend a maximum of 1,000 documents for optimal endpoint performance.
 <dl>
 <dd>
 
-**max_chunks_per_doc:** `typing.Optional[int]` — The maximum number of chunks to produce internally from a document
+**max_tokens_per_doc:** `typing.Optional[int]` — Defaults to `4096`. Long documents will be automatically truncated to the specified number of tokens.
 
 </dd>
 </dl>
@@ -5043,7 +5072,7 @@ client.finetuning.update_finetuned_model(
 <dl>
 <dd>
 
-**last_used:** `typing.Optional[dt.datetime]` — Timestamp for the latest request to this fine-tuned model.
+**last_used:** `typing.Optional[dt.datetime]` — Deprecated: Timestamp for the latest request to this fine-tuned model.
 
 </dd>
 </dl>

src/cohere/__init__.py

@@ -106,6 +106,7 @@
     DatasetType,
     DatasetValidationStatus,
     DebugStreamedChatResponse,
+    DebugStreamedChatResponseV2,
     DeleteConnectorResponse,
     DetokenizeResponse,
     Document,
@@ -263,7 +264,6 @@
     V2ChatStreamRequestDocumentsItem,
     V2ChatStreamRequestSafetyMode,
     V2EmbedRequestTruncate,
-    V2RerankRequestDocumentsItem,
     V2RerankResponse,
     V2RerankResponseResultsItem,
     V2RerankResponseResultsItemDocument,
@@ -391,6 +391,7 @@
     "DatasetsGetUsageResponse",
     "DatasetsListResponse",
     "DebugStreamedChatResponse",
+    "DebugStreamedChatResponseV2",
     "DeleteConnectorResponse",
     "DetokenizeResponse",
     "Document",
@@ -528,7 +529,6 @@
     "V2ChatStreamRequestDocumentsItem",
     "V2ChatStreamRequestSafetyMode",
     "V2EmbedRequestTruncate",
-    "V2RerankRequestDocumentsItem",
     "V2RerankResponse",
     "V2RerankResponseResultsItem",
     "V2RerankResponseResultsItemDocument",

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": "5.11.4",
+            "X-Fern-SDK-Version": "5.12.0",
         }
         if self._client_name is not None:
             headers["X-Client-Name"] = self._client_name

src/cohere/finetuning/client.py

@@ -543,7 +543,7 @@ def update_finetuned_model(
             Timestamp for the completed fine-tuning.
 
         last_used : typing.Optional[dt.datetime]
-            Timestamp for the latest request to this fine-tuned model.
+            Deprecated: Timestamp for the latest request to this fine-tuned model.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.
@@ -1468,7 +1468,7 @@ async def update_finetuned_model(
             Timestamp for the completed fine-tuning.
 
         last_used : typing.Optional[dt.datetime]
-            Timestamp for the latest request to this fine-tuned model.
+            Deprecated: Timestamp for the latest request to this fine-tuned model.
 
         request_options : typing.Optional[RequestOptions]
             Request-specific configuration.

src/cohere/finetuning/finetuning/types/finetuned_model.py

@@ -61,7 +61,7 @@ class FinetunedModel(UncheckedBaseModel):
 
     last_used: typing.Optional[dt.datetime] = pydantic.Field(default=None)
     """
-    read-only. Timestamp for the latest request to this fine-tuned model.
+    read-only. Deprecated: Timestamp for the latest request to this fine-tuned model.
     """
 
     if IS_PYDANTIC_V2:

src/cohere/types/__init__.py

@@ -188,6 +188,7 @@
     ContentDeltaStreamedChatResponseV2,
     ContentEndStreamedChatResponseV2,
     ContentStartStreamedChatResponseV2,
+    DebugStreamedChatResponseV2,
     MessageEndStreamedChatResponseV2,
     MessageStartStreamedChatResponseV2,
     StreamedChatResponseV2,
@@ -329,6 +330,7 @@
     "DatasetType",
     "DatasetValidationStatus",
     "DebugStreamedChatResponse",
+    "DebugStreamedChatResponseV2",
     "DeleteConnectorResponse",
     "DetokenizeResponse",
     "Document",

src/cohere/types/streamed_chat_response_v2.py

@@ -213,6 +213,23 @@ class Config:
             extra = pydantic.Extra.allow
 
 
+class DebugStreamedChatResponseV2(UncheckedBaseModel):
+    """
+    StreamedChatResponse is returned in streaming mode (specified with `stream=True` in the request).
+    """
+
+    type: typing.Literal["debug"] = "debug"
+    prompt: typing.Optional[str] = None
+
+    if IS_PYDANTIC_V2:
+        model_config: typing.ClassVar[pydantic.ConfigDict] = pydantic.ConfigDict(extra="allow")  # type: ignore # Pydantic v2
+    else:
+
+        class Config:
+            smart_union = True
+            extra = pydantic.Extra.allow
+
+
 StreamedChatResponseV2 = typing_extensions.Annotated[
     typing.Union[
         MessageStartStreamedChatResponseV2,
@@ -226,6 +243,7 @@ class Config:
         CitationStartStreamedChatResponseV2,
         CitationEndStreamedChatResponseV2,
         MessageEndStreamedChatResponseV2,
+        DebugStreamedChatResponseV2,
     ],
     UnionMetadata(discriminant="type"),
 ]

src/cohere/v2/__init__.py

@@ -6,7 +6,6 @@
     V2ChatStreamRequestDocumentsItem,
     V2ChatStreamRequestSafetyMode,
     V2EmbedRequestTruncate,
-    V2RerankRequestDocumentsItem,
     V2RerankResponse,
     V2RerankResponseResultsItem,
     V2RerankResponseResultsItemDocument,
@@ -18,7 +17,6 @@
     "V2ChatStreamRequestDocumentsItem",
     "V2ChatStreamRequestSafetyMode",
     "V2EmbedRequestTruncate",
-    "V2RerankRequestDocumentsItem",
     "V2RerankResponse",
     "V2RerankResponseResultsItem",
     "V2RerankResponseResultsItemDocument",