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Merged
mkozakov merged 2 commits into from
Oct 16, 2025
Merged

🌿 Fern Regeneration -- October 15, 2025 #703

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87b7eac
SDK regeneration
fern-api[bot] Oct 15, 2025
ee8d312
Add back usage.tokens
mkozakov Oct 16, 2025
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820 changes: 456 additions & 364 deletions poetry.lock
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Large diffs are not rendered by default.

2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@ name = "cohere"

[tool.poetry]
name = "cohere"
version = "5.18.0"
version = "5.19.0"
description = ""
readme = "README.md"
authors = []
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10 changes: 9 additions & 1 deletion src/cohere/__init__.py
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Expand Up @@ -251,7 +251,7 @@
UnauthorizedError,
UnprocessableEntityError,
)
from . import connectors, datasets, embed_jobs, finetuning, models, v2
from . import batches, connectors, datasets, embed_jobs, finetuning, models, v2
from .aliases import (
ChatResponse,
ContentDeltaStreamedChatResponseV2,
Expand All @@ -265,6 +265,7 @@
ToolCallStartStreamedChatResponseV2,
)
from .aws_client import AwsClient
from .batches import Batch, BatchStatus, CancelBatchResponse, CreateBatchResponse, GetBatchResponse, ListBatchesResponse
from .bedrock_client import BedrockClient, BedrockClientV2
from .client import AsyncClient, Client
from .client_v2 import AsyncClientV2, ClientV2
Expand Down Expand Up @@ -315,8 +316,11 @@
"AuthTokenType",
"AwsClient",
"BadRequestError",
"Batch",
"BatchStatus",
"BedrockClient",
"BedrockClientV2",
"CancelBatchResponse",
"ChatCitation",
"ChatCitationGenerationEvent",
"ChatCitationType",
Expand Down Expand Up @@ -417,6 +421,7 @@
"ContentEndV2ChatStreamResponse",
"ContentStartStreamedChatResponseV2",
"ContentStartV2ChatStreamResponse",
"CreateBatchResponse",
"CreateConnectorOAuth",
"CreateConnectorResponse",
"CreateConnectorServiceAuth",
Expand Down Expand Up @@ -470,6 +475,7 @@
"GenerateStreamText",
"GenerateStreamedResponse",
"Generation",
"GetBatchResponse",
"GetConnectorResponse",
"GetModelResponse",
"Image",
Expand All @@ -485,6 +491,7 @@
"JsonResponseFormat",
"JsonResponseFormatV2",
"LabelMetric",
"ListBatchesResponse",
"ListConnectorsResponse",
"ListEmbedJobResponse",
"ListModelsResponse",
Expand Down Expand Up @@ -594,6 +601,7 @@
"V2RerankResponse",
"V2RerankResponseResultsItem",
"__version__",
"batches",
"connectors",
"datasets",
"embed_jobs",
Expand Down
69 changes: 23 additions & 46 deletions src/cohere/base_client.py
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Expand Up @@ -4,6 +4,7 @@
import typing

import httpx
from .batches.client import AsyncBatchesClient, BatchesClient
from .connectors.client import AsyncConnectorsClient, ConnectorsClient
from .core.api_error import ApiError
from .core.client_wrapper import AsyncClientWrapper, SyncClientWrapper
Expand Down Expand Up @@ -124,6 +125,7 @@ def __init__(
)
self._raw_client = RawBaseCohere(client_wrapper=self._client_wrapper)
self.v2 = V2Client(client_wrapper=self._client_wrapper)
self.batches = BatchesClient(client_wrapper=self._client_wrapper)
self.embed_jobs = EmbedJobsClient(client_wrapper=self._client_wrapper)
self.datasets = DatasetsClient(client_wrapper=self._client_wrapper)
self.connectors = ConnectorsClient(client_wrapper=self._client_wrapper)
Expand Down Expand Up @@ -268,9 +270,8 @@ def chat_stream(
Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

citation_quality : typing.Optional[ChatStreamRequestCitationQuality]
Defaults to `"accurate"`.

Dictates the approach taken to generating citations as part of the RAG flow by allowing the user to specify whether they want `"accurate"` results, `"fast"` results or no results.
Defaults to `"enabled"`.
Citations are enabled by default for models that support it, but can be turned off by setting `"type": "disabled"`.

Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

Expand Down Expand Up @@ -406,7 +407,8 @@ def chat_stream(
token="YOUR_TOKEN",
)
response = client.chat_stream(
message="hello world!",
model="command-a-03-2025",
message="hello!",
)
for chunk in response:
yield chunk
Expand Down Expand Up @@ -568,9 +570,8 @@ def chat(
Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

citation_quality : typing.Optional[ChatRequestCitationQuality]
Defaults to `"accurate"`.

Dictates the approach taken to generating citations as part of the RAG flow by allowing the user to specify whether they want `"accurate"` results, `"fast"` results or no results.
Defaults to `"enabled"`.
Citations are enabled by default for models that support it, but can be turned off by setting `"type": "disabled"`.

Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

Expand Down Expand Up @@ -699,27 +700,15 @@ def chat(

Examples
--------
from cohere import ChatbotMessage, ChatConnector, Client, UserMessage
from cohere import Client

client = Client(
client_name="YOUR_CLIENT_NAME",
token="YOUR_TOKEN",
)
client.chat(
chat_history=[
UserMessage(
message="Who discovered gravity?",
),
ChatbotMessage(
message="The man who is widely credited with discovering gravity is Sir Isaac Newton",
),
],
message="What year was he born?",
connectors=[
ChatConnector(
id="web-search",
)
],
model="command-a-03-2025",
message="Tell me about LLMs",
)
"""
_response = self._raw_client.chat(
Expand Down Expand Up @@ -1073,7 +1062,7 @@ def embed(
images : typing.Optional[typing.Sequence[str]]
An array of image data URIs for the model to embed. Maximum number of images per call is `1`.

The image must be a valid [data URI](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data). The image must be in either `image/jpeg` or `image/png` format and has a maximum size of 5MB.
The image must be a valid [data URI](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data). The image must be in either `image/jpeg`, `image/png`, `image/webp`, or `image/gif` format and has a maximum size of 5MB.

Images are only supported with Embed v3.0 and newer models.

Expand Down Expand Up @@ -1580,6 +1569,7 @@ def __init__(
)
self._raw_client = AsyncRawBaseCohere(client_wrapper=self._client_wrapper)
self.v2 = AsyncV2Client(client_wrapper=self._client_wrapper)
self.batches = AsyncBatchesClient(client_wrapper=self._client_wrapper)
self.embed_jobs = AsyncEmbedJobsClient(client_wrapper=self._client_wrapper)
self.datasets = AsyncDatasetsClient(client_wrapper=self._client_wrapper)
self.connectors = AsyncConnectorsClient(client_wrapper=self._client_wrapper)
Expand Down Expand Up @@ -1724,9 +1714,8 @@ async def chat_stream(
Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

citation_quality : typing.Optional[ChatStreamRequestCitationQuality]
Defaults to `"accurate"`.

Dictates the approach taken to generating citations as part of the RAG flow by allowing the user to specify whether they want `"accurate"` results, `"fast"` results or no results.
Defaults to `"enabled"`.
Citations are enabled by default for models that support it, but can be turned off by setting `"type": "disabled"`.

Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

Expand Down Expand Up @@ -1867,7 +1856,8 @@ async def chat_stream(

async def main() -> None:
response = await client.chat_stream(
message="hello world!",
model="command-a-03-2025",
message="hello!",
)
async for chunk in response:
yield chunk
Expand Down Expand Up @@ -2033,9 +2023,8 @@ async def chat(
Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

citation_quality : typing.Optional[ChatRequestCitationQuality]
Defaults to `"accurate"`.

Dictates the approach taken to generating citations as part of the RAG flow by allowing the user to specify whether they want `"accurate"` results, `"fast"` results or no results.
Defaults to `"enabled"`.
Citations are enabled by default for models that support it, but can be turned off by setting `"type": "disabled"`.

Compatible Deployments: Cohere Platform, Azure, AWS Sagemaker/Bedrock, Private Deployments

Expand Down Expand Up @@ -2166,7 +2155,7 @@ async def chat(
--------
import asyncio

from cohere import AsyncClient, ChatbotMessage, ChatConnector, UserMessage
from cohere import AsyncClient

client = AsyncClient(
client_name="YOUR_CLIENT_NAME",
Expand All @@ -2176,20 +2165,8 @@ async def chat(

async def main() -> None:
await client.chat(
chat_history=[
UserMessage(
message="Who discovered gravity?",
),
ChatbotMessage(
message="The man who is widely credited with discovering gravity is Sir Isaac Newton",
),
],
message="What year was he born?",
connectors=[
ChatConnector(
id="web-search",
)
],
model="command-a-03-2025",
message="Tell me about LLMs",
)


Expand Down Expand Up @@ -2563,7 +2540,7 @@ async def embed(
images : typing.Optional[typing.Sequence[str]]
An array of image data URIs for the model to embed. Maximum number of images per call is `1`.

The image must be a valid [data URI](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data). The image must be in either `image/jpeg` or `image/png` format and has a maximum size of 5MB.
The image must be a valid [data URI](https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data). The image must be in either `image/jpeg`, `image/png`, `image/webp`, or `image/gif` format and has a maximum size of 5MB.

Images are only supported with Embed v3.0 and newer models.

Expand Down
14 changes: 14 additions & 0 deletions src/cohere/batches/__init__.py
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@@ -0,0 +1,14 @@
# This file was auto-generated by Fern from our API Definition.

# isort: skip_file

from .types import Batch, BatchStatus, CancelBatchResponse, CreateBatchResponse, GetBatchResponse, ListBatchesResponse

__all__ = [
"Batch",
"BatchStatus",
"CancelBatchResponse",
"CreateBatchResponse",
"GetBatchResponse",
"ListBatchesResponse",
]
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