griptape-ai / griptape

Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.
https://www.griptape.ai
Apache License 2.0
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Bump the dependencies group with 11 updates #1192

Closed dependabot[bot] closed 5 days ago

dependabot[bot] commented 5 days ago

Bumps the dependencies group with 11 updates:

Package From To
openai 1.45.1 1.47.1
cohere 5.9.2 5.9.4
huggingface-hub 0.24.7 0.25.1
boto3 1.35.19 1.35.24
pymongo 4.8.0 4.9.1
marqo 3.8.0 3.8.1
elevenlabs 1.8.1 1.9.0
qdrant-client 1.11.1 1.11.2
astrapy 1.4.2 1.5.0
sqlalchemy 2.0.34 2.0.35
diffusers 0.30.2 0.30.3

Updates openai from 1.45.1 to 1.47.1

Release notes

Sourced from openai's releases.

v1.47.1

1.47.1 (2024-09-23)

Full Changelog: v1.47.0...v1.47.1

Bug Fixes

  • pydantic v1: avoid warnings error (1e8e7d1)

v1.47.0

1.47.0 (2024-09-20)

Full Changelog: v1.46.1...v1.47.0

Features

  • client: send retry count header (21b0c00)

Chores

  • types: improve type name for embedding models (#1730) (4b4eb2b)

v1.46.1

1.46.1 (2024-09-19)

Full Changelog: v1.46.0...v1.46.1

Bug Fixes

Chores

  • streaming: silence pydantic model_dump warnings (#1722) (30f84b9)

v1.46.0

1.46.0 (2024-09-17)

Full Changelog: v1.45.1...v1.46.0

Features

  • client: add ._request_id property to object responses (#1707) (8b3da05)

Documentation

  • readme: add examples for chat with image content (#1703) (192b8f2)
Changelog

Sourced from openai's changelog.

1.47.1 (2024-09-23)

Full Changelog: v1.47.0...v1.47.1

Bug Fixes

  • pydantic v1: avoid warnings error (1e8e7d1)

1.47.0 (2024-09-20)

Full Changelog: v1.46.1...v1.47.0

Features

  • client: send retry count header (21b0c00)

Chores

  • types: improve type name for embedding models (#1730) (4b4eb2b)

1.46.1 (2024-09-19)

Full Changelog: v1.46.0...v1.46.1

Bug Fixes

Chores

  • streaming: silence pydantic model_dump warnings (#1722) (30f84b9)

1.46.0 (2024-09-17)

Full Changelog: v1.45.1...v1.46.0

Features

  • client: add ._request_id property to object responses (#1707) (8b3da05)

Documentation

  • readme: add examples for chat with image content (#1703) (192b8f2)
Commits
  • 89e5a01 release: 1.47.1
  • 5b2dbcd fix(pydantic v1): avoid warnings error
  • 45315a7 release: 1.47.0
  • eab2e5a chore(types): improve type name for embedding models (#1730)
  • 3765cc2 feat(client): send retry count header
  • 6172976 release: 1.46.1
  • bd1e9e2 fix(client): handle domains with underscores (#1726)
  • 349b7f6 chore(streaming): silence pydantic model_dump warnings (#1722)
  • bcf9fcc release: 1.46.0
  • 4b30234 feat(client): add ._request_id property to object responses (#1707)
  • Additional commits viewable in compare view


Updates cohere from 5.9.2 to 5.9.4

Updates huggingface-hub from 0.24.7 to 0.25.1

Release notes

Sourced from huggingface-hub's releases.

[v0.25.1]: Raise error if encountered in chat completion SSE stream

Full Changelog : v0.25.0...v0.25.1 For more details, refer to the related PR #2558

v0.25.0: Large uploads made simple + quality of life improvements

📂 Upload large folders

Uploading large models or datasets is challenging. We've already written some tips and tricks to facilitate the process but something was still missing. We are now glad to release the huggingface-cli upload-large-folder command. Consider it as a "please upload this no matter what, and be quick" command. Contrarily to huggingface-cli download, this new command is more opinionated and will split the upload into several commits. Multiple workers are started locally to hash, pre-upload and commit the files in a way that is resumable, resilient to connection errors, and optimized against rate limits. This feature has already been stress tested by the community over the last months to make it as easy and convenient to use as possible.

Here is how to use it:

huggingface-cli upload-large-folder <repo-id> <local-path> --repo-type=dataset

Every minute, a report is logged with the current status of the files and workers:

---------- 2024-04-26 16:24:25 (0:00:00) ----------
Files:   hashed 104/104 (22.5G/22.5G) | pre-uploaded: 0/42 (0.0/22.5G) | committed: 58/104 (24.9M/22.5G) | ignored: 0
Workers: hashing: 0 | get upload mode: 0 | pre-uploading: 6 | committing: 0 | waiting: 0
---------------------------------------------------

You can also run it from a script:

>>> from huggingface_hub import HfApi
>>> api = HfApi()
>>> api.upload_large_folder(
...     repo_id="HuggingFaceM4/Docmatix",
...     repo_type="dataset",
...     folder_path="/path/to/local/docmatix",
... )

For more details about the command options, run:

huggingface-cli upload-large-folder --help

or visit the upload guide.

✨ HfApi & CLI improvements

... (truncated)

Commits
  • f7dc3fd Release: v0.25.1
  • efafba2 Raise error if encountered in chat completion SSE stream (#2558)
  • 10e403d Release: v0.25.0
  • e331a05 Release: v0.25.0.rc1
  • 1b4bfe7 Merge branch 'main' into v0.25-release
  • f1a7ed4 Suggest using upload_large_folder when appropriate (#2547)
  • 796eb5a Fixed the issue #2535 Added user followers and following in class User and ad...
  • a06e246 Reduce number of commits in upload large folder (#2546)
  • 6f49af5 Release: v0.25.0.rc0
  • a9adf8f Add GGUF as supported expand[] parameter (#2545)
  • Additional commits viewable in compare view


Updates boto3 from 1.35.19 to 1.35.24

Commits
  • 0902ce1 Merge branch 'release-1.35.24'
  • 03cb1ed Bumping version to 1.35.24
  • 08b0363 Add changelog entries from botocore
  • 746a999 Merge branch 'release-1.35.23'
  • bf912c6 Merge branch 'release-1.35.23' into develop
  • dc7b107 Bumping version to 1.35.23
  • 1edd472 Add changelog entries from botocore
  • dd54fe9 Merge branch 'release-1.35.22'
  • 9acc473 Merge branch 'release-1.35.22' into develop
  • fe83dce Bumping version to 1.35.22
  • Additional commits viewable in compare view


Updates pymongo from 4.8.0 to 4.9.1

Release notes

Sourced from pymongo's releases.

PyMongo 4.9.1

Community notes: https://www.mongodb.com/community/forums/t/pymongo-4-9-released/297833

Changelog

Sourced from pymongo's changelog.

Changelog

Changes in Version 4.9.0

.. warning:: Driver support for MongoDB 3.6 reached end of life in April 2024. PyMongo 4.9 will be the last release to support MongoDB 3.6.

.. warning:: PyMongo 4.9 refactors a large portion of internal APIs to support the new asynchronous API beta. As a result, versions of Motor older than 3.6 are not compatible with PyMongo 4.9. Existing users of these versions must either upgrade to Motor 3.6 and PyMongo 4.9, or cap their PyMongo version to < 4.9. Any applications that use private APIs may also break as a result of these internal changes.

PyMongo 4.9 brings a number of improvements including:

  • Added support for MongoDB 8.0.
  • Added support for Python 3.13.
  • A new beta asynchronous API with full asyncio support. This new asynchronous API is a work-in-progress that may change during the beta period before the full release.
  • Added support for In-Use Encryption range queries with MongoDB 8.0. Added :attr:~pymongo.encryption.Algorithm.RANGE. sparsity and trim_factor are now optional in :class:~pymongo.encryption_options.RangeOpts.
  • Added support for the "delegated" option for the KMIP master_key in :meth:~pymongo.encryption.ClientEncryption.create_data_key.
  • pymongocrypt>=1.10 is now required for :ref:In-Use Encryption support.
  • Added :meth:~pymongo.cursor.Cursor.to_list to :class:~pymongo.cursor.Cursor, :class:~pymongo.command_cursor.CommandCursor, :class:~pymongo.asynchronous.cursor.AsyncCursor, and :class:~pymongo.asynchronous.command_cursor.AsyncCommandCursor as an asynchronous-friendly alternative to list(cursor).
  • Added :meth:~pymongo.mongo_client.MongoClient.bulk_write to :class:~pymongo.mongo_client.MongoClient and :class:~pymongo.asynchronous.mongo_client.AsyncMongoClient, enabling users to perform insert, update, and delete operations against mixed namespaces in a minimized number of round trips. Please see :doc:examples/client_bulk for more information.
  • Added support for the namespace parameter to the :class:~pymongo.operations.InsertOne, :class:~pymongo.operations.ReplaceOne, :class:~pymongo.operations.UpdateOne, :class:~pymongo.operations.UpdateMany, :class:~pymongo.operations.DeleteOne, and :class:~pymongo.operations.DeleteMany operations, so they can be used in the new :meth:~pymongo.mongo_client.MongoClient.bulk_write.
  • Added :func:repr support to :class:bson.tz_util.FixedOffset.
  • Fixed a bug where PyMongo would raise InvalidBSON: unhashable type: 'tzfile' when using :attr:~bson.codec_options.DatetimeConversion.DATETIME_CLAMP or :attr:~bson.codec_options.DatetimeConversion.DATETIME_AUTO with a timezone from dateutil.
  • Fixed a bug where PyMongo would raise InvalidBSON: date value out of range

... (truncated)

Commits
  • 8b26d4b BUMP 4.9.1
  • d0772f2 PYTHON-4773 - Async PyMongo Beta docs update (#1868)
  • 2ddd16d BUMP 4.10.0.dev0
  • 699d962 BUMP 4.9
  • 2c432b5 PYTHON-4768 - Fix atlas connection tests and cleanup uses of raw MongoClients...
  • 6d472a1 PYTHON-4738 Skip encryption test_fork on PyPy (#1865)
  • 9a71be1 PYTHON-4740 Convert asyncio.TimeoutError to socket.timeout for compat (#1864)
  • c136684 PYTHON-4585 Cursor.to_list does not apply client's timeoutMS setting (#1860)
  • 40ebc16 PYTHON-4764 Update to use current supported EVG hosts (#1858)
  • 163e3d4 PYTHON-4738 - Make test_encryption.TestClientSimple.test_fork sync-only (#1862)
  • Additional commits viewable in compare view


Updates marqo from 3.8.0 to 3.8.1

Commits


Updates elevenlabs from 1.8.1 to 1.9.0

Release notes

Sourced from elevenlabs's releases.

1.9.0

What's Changed

Full Changelog: https://github.com/elevenlabs/elevenlabs-python/compare/v1.8.2...1.9.0

v1.8.2

What's Changed

Full Changelog: https://github.com/elevenlabs/elevenlabs-python/compare/v1.8.1...v1.8.2

Commits


Updates qdrant-client from 1.11.1 to 1.11.2

Release notes

Sourced from qdrant-client's releases.

v1.11.2

Change Log

Bug Fixes 🪰

Thanks to everyone, who've contributed to this release! @​paul2302 @​hh-space-invader @​joein

Commits


Updates astrapy from 1.4.2 to 1.5.0

Release notes

Sourced from astrapy's releases.

Release v1.5.0

v. 1.5.0

Deprecation of "namespace-" terminology, replaced by "keyspace-" (removal in 2.0)

  • deprecation of all namespace method names
  • deprecation of the namespace= named argument to all methods
  • deprecation of the update_db_namespace parameter to create_*space

Deprecation of collection bulk_write method (removal in 2.0) APICommander logs warnings received from the Data API Full removal of "core library" from the current API:

  • DevOps API accessed through APICommander everywhere
  • Admin objects use APICommander consistently
  • [Async]Database and [Async]Collection directly use APICommander
  • Cursor library uses APICommander directly
  • Core library imports triggers a submodule-wide deprecation warning
  • (simplification of the vector/vectorize deprecator utility)

Widened exception hierarchy with:

  • DevOpsAPIHttpException
  • DevOpsAPITimeoutException
  • DevOpsAPIFaultyResponseException

Rearrangement into separate modules for:

  • constants, strings, magic numbers and settings
  • request low-level tools
  • payload/response transformations
  • (sometimes with temporary duplication to avoid depending on 'core')

Testing:

  • testing on HCD targets Data API v 1.0.16
  • added tests for APICommander
  • improved tests for admin classes

Logging of API requests made more uniform and easier to read Replaced collections.abc.Iterator => typing.Iterator for python3.8 compatibility

Changelog

Sourced from astrapy's changelog.

v. 1.5.0

Deprecation of "namespace-" terminology, replaced by "keyspace-" (removal in 2.0) - deprecation of all namespace method names - deprecation of the namespace= named argument to all methods - deprecation of the update_db_namespace parameter to create_*space Deprecation of collection bulk_write method (removal in 2.0) APICommander logs warnings received from the Data API Full removal of "core library" from the current API: - DevOps API accessed through APICommander everywhere - Admin objects use APICommander consistently - [Async]Database and [Async]Collection directly use APICommander - Cursor library uses APICommander directly - Core library imports triggers a submodule-wide deprecation warning - (simplification of the vector/vectorize deprecator utility) Widened exception hierarchy with: - DevOpsAPIHttpException - DevOpsAPITimeoutException - DevOpsAPIFaultyResponseException Rearrangement into separate modules for: - constants, strings, magic numbers and settings - request low-level tools - payload/response transformations - (sometimes with temporary duplication to avoid depending on 'core') Testing: - testing on HCD targets Data API v 1.0.16 - added tests for APICommander - improved tests for admin classes Logging of API requests made more uniform and easier to read Replaced collections.abc.Iterator => typing.Iterator for python3.8 compatibility

Commits


Updates sqlalchemy from 2.0.34 to 2.0.35

Release notes

Sourced from sqlalchemy's releases.

2.0.35

Released: September 16, 2024

orm

  • [orm] [bug] [typing] Fixed issue where it was not possible to use typing.Literal with Mapped[] on Python 3.8 and 3.9. Pull request courtesy Frazer McLean.

    References: #11820

  • [orm] [bug] Fixed issue in ORM evaluator where two datatypes being evaluated with the SQL concatenator operator would not be checked for UnevaluatableError based on their datatype; this missed the case of _postgresql.JSONB values being used in a concatenate operation which is supported by PostgreSQL as well as how SQLAlchemy renders the SQL for this operation, but does not work at the Python level. By implementing UnevaluatableError for this combination, ORM update statements will now fall back to "expire" when a concatenated JSON value used in a SET clause is to be synchronized to a Python object.

    References: #11849

  • [orm] [bug] An warning is emitted if _orm.joinedload() or _orm.subqueryload() are used as a top level option against a statement that is not a SELECT statement, such as with an insert().returning(). There are no JOINs in INSERT statements nor is there a "subquery" that can be repurposed for subquery eager loading, and for UPDATE/DELETE joinedload does not support these either, so it is never appropriate for this use to pass silently.

    References: #11853

  • [orm] [bug] Fixed issue where using loader options such as _orm.selectinload() with additional criteria in combination with ORM DML such as _sql.insert() with RETURNING would not correctly set up internal contexts required for caching to work correctly, leading to incorrect results.

    References: #11855

mysql

  • [mysql] [bug] Fixed issue in mariadbconnector dialect where query string arguments that weren't checked integer or boolean arguments would be ignored, such as string arguments like unix_socket, etc. As part of this change, the argument parsing for particular elements such as client_flags, compress, local_infile has been made more consistent across all

... (truncated)

Commits


Updates diffusers from 0.30.2 to 0.30.3

Release notes

Sourced from diffusers's releases.

v0.30.3: CogVideoX Image-to-Video and Video-to-Video

This patch release adds Diffusers support for the upcoming CogVideoX-5B-I2V release (an Image-to-Video generation model)! The model weights will be available by end of the week on the HF Hub at THUDM/CogVideoX-5b-I2V (Link). Stay tuned for the release!

This release features two new pipelines:

  • CogVideoXImageToVideoPipeline
  • CogVideoXVideoToVideoPipeline

Additionally, we now have support for tiled encoding in the CogVideoX VAE. This can be enabled by calling the vae.enable_tiling() method, and it is used in the new Video-to-Video pipeline to encode sample videos to latents in a memory-efficient manner.

CogVideoXImageToVideoPipeline

The code below demonstrates how to use the new image-to-video pipeline:

import torch
from diffusers import CogVideoXImageToVideoPipeline
from diffusers.utils import export_to_video, load_image

pipe = CogVideoXImageToVideoPipeline.from_pretrained("THUDM/CogVideoX-5b-I2V", torch_dtype=torch.bfloat16) pipe.to("cuda")

Optionally, enable memory optimizations.

If enabling CPU offloading, remember to remove pipe.to(&quot;cuda&quot;) above

pipe.enable_model_cpu_offload() pipe.vae.enable_tiling()

prompt = "An astronaut hatching from an egg, on the surface of the moon, the darkness and depth of space realised in the background. High quality, ultrarealistic detail and breath-taking movie-like camera shot." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg" ) video = pipe(image, prompt, use_dynamic_cfg=True) export_to_video(video.frames[0], "output.mp4", fps=8)

CogVideoXVideoToVideoPipeline

The code below demonstrates how to use the new video-to-video pipeline:

import torch
from diffusers import CogVideoXDPMScheduler, CogVideoXVideoToVideoPipeline
from diffusers.utils import export_to_video, load_video
</tr></table> 

... (truncated)

Commits


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