From ee4c2e78b5350e53375043d0d0f9d53c6c1e1206 Mon Sep 17 00:00:00 2001
From: fern-api <115122769+fern-api[bot]@users.noreply.github.com>
Date: Wed, 27 Nov 2024 14:52:53 +0000
Subject: [PATCH 1/4] SDK regeneration
---
.gitignore | 1 -
poetry.lock | 1946 ++---------------
pyproject.toml | 2 +-
reference.md | 71 +-
src/cohere/__init__.py | 4 +-
src/cohere/core/client_wrapper.py | 2 +-
src/cohere/finetuning/client.py | 4 +-
.../finetuning/types/finetuned_model.py | 2 +-
src/cohere/types/__init__.py | 10 +
src/cohere/types/streamed_chat_response_v2.py | 18 +
src/cohere/v2/__init__.py | 2 -
src/cohere/v2/client.py | 129 +-
src/cohere/v2/types/__init__.py | 2 -
.../types/v2rerank_request_documents_item.py | 6 -
14 files changed, 313 insertions(+), 1886 deletions(-)
delete mode 100644 src/cohere/v2/types/v2rerank_request_documents_item.py
diff --git a/.gitignore b/.gitignore
index 1c9940805..0da665fee 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,4 +3,3 @@ dist/
__pycache__/
poetry.toml
.ruff_cache/
-.venv/
diff --git a/poetry.lock b/poetry.lock
index 870dbba11..c3767a9db 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,26 +1,5 @@
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
-[[package]]
-name = "alembic"
-version = "1.14.0"
-description = "A database migration tool for SQLAlchemy."
-optional = true
-python-versions = ">=3.8"
-files = [
- {file = "alembic-1.14.0-py3-none-any.whl", hash = "sha256:99bd884ca390466db5e27ffccff1d179ec5c05c965cfefc0607e69f9e411cb25"},
- {file = "alembic-1.14.0.tar.gz", hash = "sha256:b00892b53b3642d0b8dbedba234dbf1924b69be83a9a769d5a624b01094e304b"},
-]
-
-[package.dependencies]
-importlib-metadata = {version = "*", markers = "python_version < \"3.9\""}
-importlib-resources = {version = "*", markers = "python_version < \"3.9\""}
-Mako = "*"
-SQLAlchemy = ">=1.3.0"
-typing-extensions = ">=4"
-
-[package.extras]
-tz = ["backports.zoneinfo"]
-
[[package]]
name = "annotated-types"
version = "0.7.0"
@@ -76,30 +55,19 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
-[[package]]
-name = "blinker"
-version = "1.8.2"
-description = "Fast, simple object-to-object and broadcast signaling"
-optional = true
-python-versions = ">=3.8"
-files = [
- {file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"},
- {file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"},
-]
-
[[package]]
name = "boto3"
-version = "1.35.63"
+version = "1.35.70"
description = "The AWS SDK for Python"
optional = true
python-versions = ">=3.8"
files = [
- {file = "boto3-1.35.63-py3-none-any.whl", hash = "sha256:d0f938d4f6f392b6ffc5e75fff14a42e5bbb5228675a0367c8af55398abadbec"},
- {file = "boto3-1.35.63.tar.gz", hash = "sha256:deb593d9a0fb240deb4c43e4da8e6626d7c36be7b2fd2fe28f49d44d395b7de0"},
+ {file = "boto3-1.35.70-py3-none-any.whl", hash = "sha256:ca385708f83f01b3f27d9d675880d2458cb3b40ed1e25da688f551454ed0c112"},
+ {file = "boto3-1.35.70.tar.gz", hash = "sha256:121dce8c7102eea6a6047d46bcd74e8a24dac793a4a3857de4f4bad9c12566fd"},
]
[package.dependencies]
-botocore = ">=1.35.63,<1.36.0"
+botocore = ">=1.35.70,<1.36.0"
jmespath = ">=0.7.1,<2.0.0"
s3transfer = ">=0.10.0,<0.11.0"
@@ -108,13 +76,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
[[package]]
name = "botocore"
-version = "1.35.63"
+version = "1.35.70"
description = "Low-level, data-driven core of boto 3."
optional = true
python-versions = ">=3.8"
files = [
- {file = "botocore-1.35.63-py3-none-any.whl", hash = "sha256:0ca1200694a4c0a3fa846795d8e8a08404c214e21195eb9e010c4b8a4ca78a4a"},
- {file = "botocore-1.35.63.tar.gz", hash = "sha256:2b8196bab0a997d206c3d490b52e779ef47dffb68c57c685443f77293aca1589"},
+ {file = "botocore-1.35.70-py3-none-any.whl", hash = "sha256:ba8a4797cf7c5d9c237e67a62692f5146e895613fd3e6a43b00b66f3a8c7fc73"},
+ {file = "botocore-1.35.70.tar.gz", hash = "sha256:18d1bb505722d9efd50c50719ed8de7284bfe6d3908a9e08756a7646e549da21"},
]
[package.dependencies]
@@ -128,17 +96,6 @@ urllib3 = [
[package.extras]
crt = ["awscrt (==0.22.0)"]
-[[package]]
-name = "cachetools"
-version = "5.5.0"
-description = "Extensible memoizing collections and decorators"
-optional = true
-python-versions = ">=3.7"
-files = [
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- {file = "cachetools-5.5.0.tar.gz", hash = "sha256:2cc24fb4cbe39633fb7badd9db9ca6295d766d9c2995f245725a46715d050f2a"},
-]
-
[[package]]
name = "certifi"
version = "2024.8.30"
@@ -264,20 +221,6 @@ files = [
{file = "charset_normalizer-3.4.0.tar.gz", hash = "sha256:223217c3d4f82c3ac5e29032b3f1c2eb0fb591b72161f86d93f5719079dae93e"},
]
-[[package]]
-name = "click"
-version = "8.1.7"
-description = "Composable command line interface toolkit"
-optional = true
-python-versions = ">=3.7"
-files = [
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- {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
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-
-[package.dependencies]
-colorama = {version = "*", markers = "platform_system == \"Windows\""}
-
[[package]]
name = "cloudpickle"
version = "2.2.1"
@@ -300,191 +243,6 @@ files = [
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]
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-name = "contourpy"
-version = "1.1.0"
-description = "Python library for calculating contours of 2D quadrilateral grids"
-optional = true
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- {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"},
-]
-
[[package]]
name = "zipp"
version = "3.20.2"
diff --git a/pyproject.toml b/pyproject.toml
index 7be4b6968..9f4308e69 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
[tool.poetry]
name = "cohere"
-version = "5.11.4"
+version = "5.12.0"
description = ""
readme = "README.md"
authors = []
diff --git a/reference.md b/reference.md
index 797a2fb2b..c1b7d5a60 100644
--- a/reference.md
+++ b/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.
+
+
+
+
+-
+
+**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.
+
+
@@ -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`.
-
-**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.
@@ -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.
+
+
+
+
+-
+
+**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.
+
+
@@ -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`.
-
-**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.
@@ -3057,7 +3086,15 @@ client.v2.rerank(
-
-**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`
@@ -3073,22 +3110,14 @@ client.v2.rerank(
-
-**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.
-
-
-
+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.
-
--
+**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.
@@ -3096,7 +3125,7 @@ We recommend a maximum of 1,000 documents for optimal endpoint performance.
-
-**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.
@@ -3115,7 +3144,7 @@ We recommend a maximum of 1,000 documents for optimal endpoint performance.
-
-**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.
@@ -5043,7 +5072,7 @@ client.finetuning.update_finetuned_model(
-
-**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.
diff --git a/src/cohere/__init__.py b/src/cohere/__init__.py
index 87f49bd4f..3a126e4f7 100644
--- a/src/cohere/__init__.py
+++ b/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",
diff --git a/src/cohere/core/client_wrapper.py b/src/cohere/core/client_wrapper.py
index 8e251265f..8213e6da3 100644
--- a/src/cohere/core/client_wrapper.py
+++ b/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
diff --git a/src/cohere/finetuning/client.py b/src/cohere/finetuning/client.py
index 60f0ce961..73c1e9b84 100644
--- a/src/cohere/finetuning/client.py
+++ b/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.
diff --git a/src/cohere/finetuning/finetuning/types/finetuned_model.py b/src/cohere/finetuning/finetuning/types/finetuned_model.py
index 861c2c2fd..786ad6eca 100644
--- a/src/cohere/finetuning/finetuning/types/finetuned_model.py
+++ b/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:
diff --git a/src/cohere/types/__init__.py b/src/cohere/types/__init__.py
index e1b8dca33..84c5d74c0 100644
--- a/src/cohere/types/__init__.py
+++ b/src/cohere/types/__init__.py
@@ -111,6 +111,7 @@
from .detokenize_response import DetokenizeResponse
from .document import Document
from .document_content import DocumentContent
+from .document_source import DocumentSource
from .embed_by_type_response import EmbedByTypeResponse
from .embed_by_type_response_embeddings import EmbedByTypeResponseEmbeddings
from .embed_floats_response import EmbedFloatsResponse
@@ -188,6 +189,7 @@
ContentDeltaStreamedChatResponseV2,
ContentEndStreamedChatResponseV2,
ContentStartStreamedChatResponseV2,
+ DebugStreamedChatResponseV2,
MessageEndStreamedChatResponseV2,
MessageStartStreamedChatResponseV2,
StreamedChatResponseV2,
@@ -200,8 +202,12 @@
from .summarize_request_format import SummarizeRequestFormat
from .summarize_request_length import SummarizeRequestLength
from .summarize_response import SummarizeResponse
+from .system_message import SystemMessage
from .system_message_content import SystemMessageContent
from .system_message_content_item import SystemMessageContentItem, TextSystemMessageContentItem
+from .text_content import TextContent
+from .text_response_format import TextResponseFormat
+from .text_response_format_v2 import TextResponseFormatV2
from .tokenize_response import TokenizeResponse
from .too_many_requests_error_body import TooManyRequestsErrorBody
from .tool import Tool
@@ -210,10 +216,12 @@
from .tool_call_v2 import ToolCallV2
from .tool_call_v2function import ToolCallV2Function
from .tool_content import DocumentToolContent, TextToolContent, ToolContent
+from .tool_message import ToolMessage
from .tool_message_v2 import ToolMessageV2
from .tool_message_v2content import ToolMessageV2Content
from .tool_parameter_definitions_value import ToolParameterDefinitionsValue
from .tool_result import ToolResult
+from .tool_source import ToolSource
from .tool_v2 import ToolV2
from .tool_v2function import ToolV2Function
from .unprocessable_entity_error_body import UnprocessableEntityErrorBody
@@ -221,6 +229,7 @@
from .usage import Usage
from .usage_billed_units import UsageBilledUnits
from .usage_tokens import UsageTokens
+from .user_message import UserMessage
from .user_message_content import UserMessageContent
__all__ = [
@@ -329,6 +338,7 @@
"DatasetType",
"DatasetValidationStatus",
"DebugStreamedChatResponse",
+ "DebugStreamedChatResponseV2",
"DeleteConnectorResponse",
"DetokenizeResponse",
"Document",
diff --git a/src/cohere/types/streamed_chat_response_v2.py b/src/cohere/types/streamed_chat_response_v2.py
index 6c1e111b8..f5eb2f7be 100644
--- a/src/cohere/types/streamed_chat_response_v2.py
+++ b/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"),
]
diff --git a/src/cohere/v2/__init__.py b/src/cohere/v2/__init__.py
index f84be0915..e0cd560eb 100644
--- a/src/cohere/v2/__init__.py
+++ b/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",
diff --git a/src/cohere/v2/client.py b/src/cohere/v2/client.py
index 58059a61d..a6abbebb8 100644
--- a/src/cohere/v2/client.py
+++ b/src/cohere/v2/client.py
@@ -39,7 +39,6 @@
from ..types.embedding_type import EmbeddingType
from .types.v2embed_request_truncate import V2EmbedRequestTruncate
from ..types.embed_by_type_response import EmbedByTypeResponse
-from .types.v2rerank_request_documents_item import V2RerankRequestDocumentsItem
from .types.v2rerank_response import V2RerankResponse
from ..core.client_wrapper import AsyncClientWrapper
@@ -57,6 +56,7 @@ def chat_stream(
model: str,
messages: ChatMessages,
tools: typing.Optional[typing.Sequence[ToolV2]] = OMIT,
+ strict_tools: typing.Optional[bool] = OMIT,
documents: typing.Optional[typing.Sequence[V2ChatStreamRequestDocumentsItem]] = OMIT,
citation_options: typing.Optional[CitationOptions] = OMIT,
response_format: typing.Optional[ResponseFormatV2] = OMIT,
@@ -91,6 +91,12 @@ def chat_stream(
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.
+ 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.
+
+
documents : typing.Optional[typing.Sequence[V2ChatStreamRequestDocumentsItem]]
A list of relevant documents that the model can cite to generate a more accurate reply. Each document is either a string or document object with content and metadata.
@@ -157,7 +163,7 @@ def chat_stream(
Whether to return the prompt in the response.
logprobs : typing.Optional[bool]
- Whether to return the log probabilities of the generated tokens. Defaults to false.
+ Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
request_options : typing.Optional[RequestOptions]
@@ -199,6 +205,7 @@ def chat_stream(
),
)
],
+ strict_tools=True,
documents=["string"],
citation_options=CitationOptions(
mode="FAST",
@@ -215,6 +222,7 @@ def chat_stream(
p=1.1,
return_prompt=True,
logprobs=True,
+ stream=True,
)
for chunk in response:
yield chunk
@@ -230,6 +238,7 @@ def chat_stream(
"tools": convert_and_respect_annotation_metadata(
object_=tools, annotation=typing.Sequence[ToolV2], direction="write"
),
+ "strict_tools": strict_tools,
"documents": convert_and_respect_annotation_metadata(
object_=documents, annotation=typing.Sequence[V2ChatStreamRequestDocumentsItem], direction="write"
),
@@ -250,7 +259,6 @@ def chat_stream(
"p": p,
"return_prompt": return_prompt,
"logprobs": logprobs,
- "stream": True,
},
request_options=request_options,
omit=OMIT,
@@ -392,6 +400,7 @@ def chat(
model: str,
messages: ChatMessages,
tools: typing.Optional[typing.Sequence[ToolV2]] = OMIT,
+ strict_tools: typing.Optional[bool] = OMIT,
documents: typing.Optional[typing.Sequence[V2ChatRequestDocumentsItem]] = OMIT,
citation_options: typing.Optional[CitationOptions] = OMIT,
response_format: typing.Optional[ResponseFormatV2] = OMIT,
@@ -426,6 +435,12 @@ def chat(
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.
+ 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.
+
+
documents : typing.Optional[typing.Sequence[V2ChatRequestDocumentsItem]]
A list of relevant documents that the model can cite to generate a more accurate reply. Each document is either a string or document object with content and metadata.
@@ -492,7 +507,7 @@ def chat(
Whether to return the prompt in the response.
logprobs : typing.Optional[bool]
- Whether to return the log probabilities of the generated tokens. Defaults to false.
+ Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
request_options : typing.Optional[RequestOptions]
@@ -519,6 +534,7 @@ def chat(
content="messages",
)
],
+ stream=False,
)
"""
_response = self._client_wrapper.httpx_client.request(
@@ -532,6 +548,7 @@ def chat(
"tools": convert_and_respect_annotation_metadata(
object_=tools, annotation=typing.Sequence[ToolV2], direction="write"
),
+ "strict_tools": strict_tools,
"documents": convert_and_respect_annotation_metadata(
object_=documents, annotation=typing.Sequence[V2ChatRequestDocumentsItem], direction="write"
),
@@ -552,7 +569,6 @@ def chat(
"p": p,
"return_prompt": return_prompt,
"logprobs": logprobs,
- "stream": False,
},
request_options=request_options,
omit=OMIT,
@@ -908,11 +924,10 @@ def rerank(
*,
model: str,
query: str,
- documents: typing.Sequence[V2RerankRequestDocumentsItem],
+ documents: typing.Sequence[str],
top_n: typing.Optional[int] = OMIT,
- rank_fields: typing.Optional[typing.Sequence[str]] = OMIT,
return_documents: typing.Optional[bool] = OMIT,
- max_chunks_per_doc: typing.Optional[int] = OMIT,
+ max_tokens_per_doc: typing.Optional[int] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> V2RerankResponse:
"""
@@ -921,31 +936,34 @@ def rerank(
Parameters
----------
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`
+ 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`
query : str
The search query
- 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.
+ documents : typing.Sequence[str]
+ 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.
- The total max chunks (length of documents * max_chunks_per_doc) must be less than 10000.
+ **Note**: long documents will automatically be truncated to the value of `max_tokens_per_doc`.
- We recommend a maximum of 1,000 documents for optimal endpoint performance.
+ **Note**: structured data should be formatted as YAML strings for best performance.
top_n : typing.Optional[int]
- The number of most relevant documents or indices to return, defaults to the length of the documents
-
- 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.
+ Limits the number of returned rerank results to the specified value. If not passed, all the rerank results will be returned.
return_documents : typing.Optional[bool]
- If false, returns results without the doc text - the api will return a list of {index, relevance score} where index is inferred from the list passed into the request.
- If true, returns results with the doc text passed in - the api will return an ordered list of {index, text, relevance score} where index + text refers to the list passed into the request.
- 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.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
@@ -975,13 +993,10 @@ def rerank(
json={
"model": model,
"query": query,
- "documents": convert_and_respect_annotation_metadata(
- object_=documents, annotation=typing.Sequence[V2RerankRequestDocumentsItem], direction="write"
- ),
+ "documents": documents,
"top_n": top_n,
- "rank_fields": rank_fields,
"return_documents": return_documents,
- "max_chunks_per_doc": max_chunks_per_doc,
+ "max_tokens_per_doc": max_tokens_per_doc,
},
request_options=request_options,
omit=OMIT,
@@ -1121,6 +1136,7 @@ async def chat_stream(
model: str,
messages: ChatMessages,
tools: typing.Optional[typing.Sequence[ToolV2]] = OMIT,
+ strict_tools: typing.Optional[bool] = OMIT,
documents: typing.Optional[typing.Sequence[V2ChatStreamRequestDocumentsItem]] = OMIT,
citation_options: typing.Optional[CitationOptions] = OMIT,
response_format: typing.Optional[ResponseFormatV2] = OMIT,
@@ -1155,6 +1171,12 @@ async def chat_stream(
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.
+ 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.
+
+
documents : typing.Optional[typing.Sequence[V2ChatStreamRequestDocumentsItem]]
A list of relevant documents that the model can cite to generate a more accurate reply. Each document is either a string or document object with content and metadata.
@@ -1221,7 +1243,7 @@ async def chat_stream(
Whether to return the prompt in the response.
logprobs : typing.Optional[bool]
- Whether to return the log probabilities of the generated tokens. Defaults to false.
+ Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
request_options : typing.Optional[RequestOptions]
@@ -1268,6 +1290,7 @@ async def main() -> None:
),
)
],
+ strict_tools=True,
documents=["string"],
citation_options=CitationOptions(
mode="FAST",
@@ -1284,6 +1307,7 @@ async def main() -> None:
p=1.1,
return_prompt=True,
logprobs=True,
+ stream=True,
)
async for chunk in response:
yield chunk
@@ -1302,6 +1326,7 @@ async def main() -> None:
"tools": convert_and_respect_annotation_metadata(
object_=tools, annotation=typing.Sequence[ToolV2], direction="write"
),
+ "strict_tools": strict_tools,
"documents": convert_and_respect_annotation_metadata(
object_=documents, annotation=typing.Sequence[V2ChatStreamRequestDocumentsItem], direction="write"
),
@@ -1322,7 +1347,6 @@ async def main() -> None:
"p": p,
"return_prompt": return_prompt,
"logprobs": logprobs,
- "stream": True,
},
request_options=request_options,
omit=OMIT,
@@ -1464,6 +1488,7 @@ async def chat(
model: str,
messages: ChatMessages,
tools: typing.Optional[typing.Sequence[ToolV2]] = OMIT,
+ strict_tools: typing.Optional[bool] = OMIT,
documents: typing.Optional[typing.Sequence[V2ChatRequestDocumentsItem]] = OMIT,
citation_options: typing.Optional[CitationOptions] = OMIT,
response_format: typing.Optional[ResponseFormatV2] = OMIT,
@@ -1498,6 +1523,12 @@ async def chat(
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.
+ 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.
+
+
documents : typing.Optional[typing.Sequence[V2ChatRequestDocumentsItem]]
A list of relevant documents that the model can cite to generate a more accurate reply. Each document is either a string or document object with content and metadata.
@@ -1564,7 +1595,7 @@ async def chat(
Whether to return the prompt in the response.
logprobs : typing.Optional[bool]
- Whether to return the log probabilities of the generated tokens. Defaults to false.
+ Defaults to `false`. When set to `true`, the log probabilities of the generated tokens will be included in the response.
request_options : typing.Optional[RequestOptions]
@@ -1596,6 +1627,7 @@ async def main() -> None:
content="messages",
)
],
+ stream=False,
)
@@ -1612,6 +1644,7 @@ async def main() -> None:
"tools": convert_and_respect_annotation_metadata(
object_=tools, annotation=typing.Sequence[ToolV2], direction="write"
),
+ "strict_tools": strict_tools,
"documents": convert_and_respect_annotation_metadata(
object_=documents, annotation=typing.Sequence[V2ChatRequestDocumentsItem], direction="write"
),
@@ -1632,7 +1665,6 @@ async def main() -> None:
"p": p,
"return_prompt": return_prompt,
"logprobs": logprobs,
- "stream": False,
},
request_options=request_options,
omit=OMIT,
@@ -1996,11 +2028,10 @@ async def rerank(
*,
model: str,
query: str,
- documents: typing.Sequence[V2RerankRequestDocumentsItem],
+ documents: typing.Sequence[str],
top_n: typing.Optional[int] = OMIT,
- rank_fields: typing.Optional[typing.Sequence[str]] = OMIT,
return_documents: typing.Optional[bool] = OMIT,
- max_chunks_per_doc: typing.Optional[int] = OMIT,
+ max_tokens_per_doc: typing.Optional[int] = OMIT,
request_options: typing.Optional[RequestOptions] = None,
) -> V2RerankResponse:
"""
@@ -2009,31 +2040,34 @@ async def rerank(
Parameters
----------
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`
+ 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`
query : str
The search query
- 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.
+ documents : typing.Sequence[str]
+ 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.
- The total max chunks (length of documents * max_chunks_per_doc) must be less than 10000.
+ **Note**: long documents will automatically be truncated to the value of `max_tokens_per_doc`.
- We recommend a maximum of 1,000 documents for optimal endpoint performance.
+ **Note**: structured data should be formatted as YAML strings for best performance.
top_n : typing.Optional[int]
- The number of most relevant documents or indices to return, defaults to the length of the documents
-
- 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.
+ Limits the number of returned rerank results to the specified value. If not passed, all the rerank results will be returned.
return_documents : typing.Optional[bool]
- If false, returns results without the doc text - the api will return a list of {index, relevance score} where index is inferred from the list passed into the request.
- If true, returns results with the doc text passed in - the api will return an ordered list of {index, text, relevance score} where index + text refers to the list passed into the request.
- 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.
request_options : typing.Optional[RequestOptions]
Request-specific configuration.
@@ -2071,13 +2105,10 @@ async def main() -> None:
json={
"model": model,
"query": query,
- "documents": convert_and_respect_annotation_metadata(
- object_=documents, annotation=typing.Sequence[V2RerankRequestDocumentsItem], direction="write"
- ),
+ "documents": documents,
"top_n": top_n,
- "rank_fields": rank_fields,
"return_documents": return_documents,
- "max_chunks_per_doc": max_chunks_per_doc,
+ "max_tokens_per_doc": max_tokens_per_doc,
},
request_options=request_options,
omit=OMIT,
diff --git a/src/cohere/v2/types/__init__.py b/src/cohere/v2/types/__init__.py
index fff15903b..47b0a3911 100644
--- a/src/cohere/v2/types/__init__.py
+++ b/src/cohere/v2/types/__init__.py
@@ -5,7 +5,6 @@
from .v2chat_stream_request_documents_item import V2ChatStreamRequestDocumentsItem
from .v2chat_stream_request_safety_mode import V2ChatStreamRequestSafetyMode
from .v2embed_request_truncate import V2EmbedRequestTruncate
-from .v2rerank_request_documents_item import V2RerankRequestDocumentsItem
from .v2rerank_response import V2RerankResponse
from .v2rerank_response_results_item import V2RerankResponseResultsItem
from .v2rerank_response_results_item_document import V2RerankResponseResultsItemDocument
@@ -16,7 +15,6 @@
"V2ChatStreamRequestDocumentsItem",
"V2ChatStreamRequestSafetyMode",
"V2EmbedRequestTruncate",
- "V2RerankRequestDocumentsItem",
"V2RerankResponse",
"V2RerankResponseResultsItem",
"V2RerankResponseResultsItemDocument",
diff --git a/src/cohere/v2/types/v2rerank_request_documents_item.py b/src/cohere/v2/types/v2rerank_request_documents_item.py
deleted file mode 100644
index d66b77dc4..000000000
--- a/src/cohere/v2/types/v2rerank_request_documents_item.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# This file was auto-generated by Fern from our API Definition.
-
-import typing
-from ...types.rerank_document import RerankDocument
-
-V2RerankRequestDocumentsItem = typing.Union[str, RerankDocument]
From 1fb46ce312c73c90308fb17e2f1590b8877fcfec Mon Sep 17 00:00:00 2001
From: Billy Trend
Date: Thu, 19 Sep 2024 17:00:18 +0100
Subject: [PATCH 2/4] Fixes
---
src/cohere/types/__init__.py | 8 --------
1 file changed, 8 deletions(-)
diff --git a/src/cohere/types/__init__.py b/src/cohere/types/__init__.py
index 84c5d74c0..28d9dc8dc 100644
--- a/src/cohere/types/__init__.py
+++ b/src/cohere/types/__init__.py
@@ -111,7 +111,6 @@
from .detokenize_response import DetokenizeResponse
from .document import Document
from .document_content import DocumentContent
-from .document_source import DocumentSource
from .embed_by_type_response import EmbedByTypeResponse
from .embed_by_type_response_embeddings import EmbedByTypeResponseEmbeddings
from .embed_floats_response import EmbedFloatsResponse
@@ -202,12 +201,8 @@
from .summarize_request_format import SummarizeRequestFormat
from .summarize_request_length import SummarizeRequestLength
from .summarize_response import SummarizeResponse
-from .system_message import SystemMessage
from .system_message_content import SystemMessageContent
from .system_message_content_item import SystemMessageContentItem, TextSystemMessageContentItem
-from .text_content import TextContent
-from .text_response_format import TextResponseFormat
-from .text_response_format_v2 import TextResponseFormatV2
from .tokenize_response import TokenizeResponse
from .too_many_requests_error_body import TooManyRequestsErrorBody
from .tool import Tool
@@ -216,12 +211,10 @@
from .tool_call_v2 import ToolCallV2
from .tool_call_v2function import ToolCallV2Function
from .tool_content import DocumentToolContent, TextToolContent, ToolContent
-from .tool_message import ToolMessage
from .tool_message_v2 import ToolMessageV2
from .tool_message_v2content import ToolMessageV2Content
from .tool_parameter_definitions_value import ToolParameterDefinitionsValue
from .tool_result import ToolResult
-from .tool_source import ToolSource
from .tool_v2 import ToolV2
from .tool_v2function import ToolV2Function
from .unprocessable_entity_error_body import UnprocessableEntityErrorBody
@@ -229,7 +222,6 @@
from .usage import Usage
from .usage_billed_units import UsageBilledUnits
from .usage_tokens import UsageTokens
-from .user_message import UserMessage
from .user_message_content import UserMessageContent
__all__ = [
From 97c297c5a6ed467f8384caa8c935d60e74bc0da8 Mon Sep 17 00:00:00 2001
From: Billy Trend
Date: Wed, 27 Nov 2024 14:57:16 +0000
Subject: [PATCH 3/4] reset lock
---
poetry.lock | 1946 +++++++++++++++++++++++++++++++++++++++++++++++----
1 file changed, 1798 insertions(+), 148 deletions(-)
diff --git a/poetry.lock b/poetry.lock
index c3767a9db..870dbba11 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,26 @@
# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+[[package]]
+name = "alembic"
+version = "1.14.0"
+description = "A database migration tool for SQLAlchemy."
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "alembic-1.14.0-py3-none-any.whl", hash = "sha256:99bd884ca390466db5e27ffccff1d179ec5c05c965cfefc0607e69f9e411cb25"},
+ {file = "alembic-1.14.0.tar.gz", hash = "sha256:b00892b53b3642d0b8dbedba234dbf1924b69be83a9a769d5a624b01094e304b"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.9\""}
+importlib-resources = {version = "*", markers = "python_version < \"3.9\""}
+Mako = "*"
+SQLAlchemy = ">=1.3.0"
+typing-extensions = ">=4"
+
+[package.extras]
+tz = ["backports.zoneinfo"]
+
[[package]]
name = "annotated-types"
version = "0.7.0"
@@ -55,19 +76,30 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
+[[package]]
+name = "blinker"
+version = "1.8.2"
+description = "Fast, simple object-to-object and broadcast signaling"
+optional = true
+python-versions = ">=3.8"
+files = [
+ {file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"},
+ {file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"},
+]
+
[[package]]
name = "boto3"
-version = "1.35.70"
+version = "1.35.63"
description = "The AWS SDK for Python"
optional = true
python-versions = ">=3.8"
files = [
- {file = "boto3-1.35.70-py3-none-any.whl", hash = "sha256:ca385708f83f01b3f27d9d675880d2458cb3b40ed1e25da688f551454ed0c112"},
- {file = "boto3-1.35.70.tar.gz", hash = "sha256:121dce8c7102eea6a6047d46bcd74e8a24dac793a4a3857de4f4bad9c12566fd"},
+ {file = "boto3-1.35.63-py3-none-any.whl", hash = "sha256:d0f938d4f6f392b6ffc5e75fff14a42e5bbb5228675a0367c8af55398abadbec"},
+ {file = "boto3-1.35.63.tar.gz", hash = "sha256:deb593d9a0fb240deb4c43e4da8e6626d7c36be7b2fd2fe28f49d44d395b7de0"},
]
[package.dependencies]
-botocore = ">=1.35.70,<1.36.0"
+botocore = ">=1.35.63,<1.36.0"
jmespath = ">=0.7.1,<2.0.0"
s3transfer = ">=0.10.0,<0.11.0"
@@ -76,13 +108,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
[[package]]
name = "botocore"
-version = "1.35.70"
+version = "1.35.63"
description = "Low-level, data-driven core of boto 3."
optional = true
python-versions = ">=3.8"
files = [
- {file = "botocore-1.35.70-py3-none-any.whl", hash = "sha256:ba8a4797cf7c5d9c237e67a62692f5146e895613fd3e6a43b00b66f3a8c7fc73"},
- {file = "botocore-1.35.70.tar.gz", hash = "sha256:18d1bb505722d9efd50c50719ed8de7284bfe6d3908a9e08756a7646e549da21"},
+ {file = "botocore-1.35.63-py3-none-any.whl", hash = "sha256:0ca1200694a4c0a3fa846795d8e8a08404c214e21195eb9e010c4b8a4ca78a4a"},
+ {file = "botocore-1.35.63.tar.gz", hash = "sha256:2b8196bab0a997d206c3d490b52e779ef47dffb68c57c685443f77293aca1589"},
]
[package.dependencies]
@@ -96,6 +128,17 @@ urllib3 = [
[package.extras]
crt = ["awscrt (==0.22.0)"]
+[[package]]
+name = "cachetools"
+version = "5.5.0"
+description = "Extensible memoizing collections and decorators"
+optional = true
+python-versions = ">=3.7"
+files = [
+ {file = "cachetools-5.5.0-py3-none-any.whl", hash = "sha256:02134e8439cdc2ffb62023ce1debca2944c3f289d66bb17ead3ab3dede74b292"},
+ {file = "cachetools-5.5.0.tar.gz", hash = "sha256:2cc24fb4cbe39633fb7badd9db9ca6295d766d9c2995f245725a46715d050f2a"},
+]
+
[[package]]
name = "certifi"
version = "2024.8.30"
@@ -221,6 +264,20 @@ files = [
{file = "charset_normalizer-3.4.0.tar.gz", hash = "sha256:223217c3d4f82c3ac5e29032b3f1c2eb0fb591b72161f86d93f5719079dae93e"},
]
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six = "*"
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notebook = ["ipywidgets (>=6)"]
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+ {file = "wrapt-1.16.0-cp39-cp39-win_amd64.whl", hash = "sha256:eb1b046be06b0fce7249f1d025cd359b4b80fc1c3e24ad9eca33e0dcdb2e4a35"},
+ {file = "wrapt-1.16.0-py3-none-any.whl", hash = "sha256:6906c4100a8fcbf2fa735f6059214bb13b97f75b1a61777fcf6432121ef12ef1"},
+ {file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"},
+]
+
[[package]]
name = "zipp"
version = "3.20.2"
From 96751184e74cedd8a755aa5bc0ff4b37977046d6 Mon Sep 17 00:00:00 2001
From: billytrend-cohere <144115527+billytrend-cohere@users.noreply.github.com>
Date: Wed, 27 Nov 2024 10:36:59 -0500
Subject: [PATCH 4/4] Update src/cohere/v2/client.py
---
src/cohere/v2/client.py | 1 +
1 file changed, 1 insertion(+)
diff --git a/src/cohere/v2/client.py b/src/cohere/v2/client.py
index a6abbebb8..a4e465e79 100644
--- a/src/cohere/v2/client.py
+++ b/src/cohere/v2/client.py
@@ -259,6 +259,7 @@ def chat_stream(
"p": p,
"return_prompt": return_prompt,
"logprobs": logprobs,
+ "stream": True,
},
request_options=request_options,
omit=OMIT,