Python SDK Changelog
Updates to the Arize Python SDK
Version 7.11
7.11.1 (Mar 5, 2024)
🐛 Bug Fixes
Fix a bug that caused
ImportError
when importingClient
fromarize.api
7.11.0 (Feb 23, 2024)
🎁 New Features
Optional strict typing in pandas logger Schema
Optional strict typing in record-at-a-time logger
❗ Dependency Changes
Add optional extra dependencies if the Arize package is installed as
pip install arize[NLP_Metrics]
:nltk>=3.0.0, <4
sacrebleu>=2.3.1, <3
rouge-score>=0.1.2, <1
evaluate>=0.3, <1
Version 7.10
7.10.2 (Feb 14, 2024)
✅ Validation Changes
Check that space and API keys are of string type
🐛 Bug Fixes
Address backward compatibility issue for batch logging via Pandas for on-prem customers
7.10.1 (Feb 6, 2024)
❗Dependency Updates:
Our Tracing extra requirements now include
deprecated
, a dependency coming fromopentelemetry-semantic-conventions
, which absence produced anImportError
7.10.0 (Feb 1, 2024)
🎁 New Features:
New batch ingestion via Pandas DataFrames for
MULTICLASS
model typeNew
TRACING
environment. You can now log spans & traces for your LLM applications into Arize using batch ingestion via Pandas DataFramesRemoved size limitation on our Schema. You can now log wider models (more columns in your DataFrame)
✅ Validation Changes
Prediction ID and Ranking Group ID have an increased character limit from 128 to 512
❗Dependency Updates:
Our MimicExplainer extra requirements are now more relaxed.
We only require
interpret-community[mimic]>=0.22.0,<1
Version 7.9
7.9.0 (Dec 28, 2023)
🎁 New Features:
New
MULTICLASS
model type available for record-at-a-time ingestion
Version 7.8
7.8.1 (Dec 18, 2023)
🐛 Bug Fixes:
Fix a bug that caused missing columns validation feedback to have repeated columns in the message
Fix a bug that caused a
KeyError
whenllm_params
is not found in the dataframe. Improved feedback to the user was included.
7.8.0 (Dec 13, 2023)
🎁 New Features
Enable latent actuals for
GENERATIVE_LLM
models
💬 Feedback Enhancements
Enable feedback when files are too large for better user experience and troubleshooting
❗ Dependency Changes
Updated
pandas
requirement. We now accept pandas 2.x
Version 7.7
7.7.2 (Nov 9, 2023)
🐛 Bug Fixes:
Default prediction sent as string for
GENERATIVE_LLM
single-record-logger (before it was incorrectly set as an integer, resulting in it being categorized as prediction score instead of prediction label)
7.7.1 (Nov 8, 2023)
🐛 Bug Fixes:
Check the value of prompt/response raw_data only if not None
7.7.0 (Nov 2, 2023)
🎁 New Features
Add
CORPUS
supportAccept strings for prompt and response
Make prompt and response optional
Add support for a list of strings features in single-record-logger
🐛 Bug Fixes:
Avoid creating a view of a Pandas dataframe
Version 7.6
7.6.1 (Oct 24, 2023)
✅ Validation Changes
Add validation on embedding raw data for batch and record-at-a-time loggers
Raise validation string limits for string fields
Add truncation warnings for long string fields
7.6.0 (Oct 12, 2023)
🎁 New Features
New ability to send features with type
list[str]
New fields available to send token usage to Arize, both using our pandas batch logger and the single record logger
Version 7.5
7.5.1 (Oct 5, 2023)
✅ Validation Changes
Increase time interval validation from 2 years to 5 years
❗Dependency Changes
Require
python>=3.6
(as opposed topython>=3.8
) for our core SDK. Our extras still requirepython>=3.8
. See Python SDK for more details.Require
pyarrow>=0.15.0
(as opposed topyarrow>=5.0.0
)
7.5.0 (Sep 2, 2023)
🎁 New Features
Add prompt templates and LLM config fields to the single log and pandas batch ingestion. These fields are used in the Arize Prompt Template Playground
✅ Validation Changes
Add a validation check that fails if there are more than 30 embedding features sent
Version 7.4
7.4.0 (Aug 15, 2023)
🎁 New Features
Add filtering via the keyword
where
to the Exporter client
Version 7.3
7.3.0 (Aug 1, 2023)
🎁 New Features
AutoEmbeddings supports any model in the HuggingFace Hub, public or private.
Add AutoEmbeddings
UseCase
for Object DetectionAdd
EmbeddingGenerator.list_default_models()
method
💀 Deprecations
Computer Vision AutoEmbeddings switched from using
FeatureExtractor
(deprecated from HuggingFace) toImageProcessor
class
Version 7.2
7.2.0 (Jul 22, 2023)
🎁 New Features
Authenticating Arize Client using environment variables
🐛 Bug Fixes
A bug causing permission errors for pandas logging using Windows machines
A bug forcing tags to be strings
Version 7.1
7.1.0 (Jun 26, 2023)
🎁 New Features
Add Generative LLM model-type support for single-record logging
Version 7.0
7.0.6 (Jun 24, 2023)
❗Dependency Changes
Removed dependency on
interpret
for the MimicExplainer
7.0.5 (Jun 23, 2023)
➕ Enhancements
Add a progress bar to the Exporter client
Sort exported dataframe by time
Update reserved headers
✅ Validation Changes
Add validation check to Exporter client that will fail if
start_time > end_time
🐛 Bug Fixes
Add bug causing to return an error when a query returns no data. Instead, return an empty response
A bug causing the Exporter client to return empty columns in the dataframe if there was no data in them
A bug causing incorrect parsing of
GENERATIVE_LLM
model fields:prompt
&response
❗ Dependency Changes
Add missing dependency for Exporter:
tqdm>=4.60.0,<5
7.0.4 (Jun 13, 2023)
❗ Dependency Changes
Relax protobuf requirements from
protobuf~=3.12
toprotobuf>=3.12, <5
7.0.3 (Jun 2, 2023)
🎁 New Features
Python Export Client, you can now export data from Arize using the Python SDK
🐛 Bug Fixes
A bug preventing
REGRESSION
models from using the MimicExplainer
✅ Validation Changes
Remove null value validation for
prediction_label
andactual_label
from single-record loggingAdd model mapping rules validation for
OBJECT_DETECTION
models
7.0.2 (May 12, 2023)
💬 Feedback Enhancements
Improve error messages around prediction ID, prediction labels, and tags
🐛 Bug Fixes
A bug causing predictions to be sent as scores instead of labels for
NUMERIC
model types
✅ Validation Changes
Add a validation check that will fail if the character limit on tags (1000 max) is exceeded
Add a validation check that will fail if actuals are sent without prediction ID information (for single-record logging). This would result in a delayed record being sent without a prediction ID, which is necessary for the latent join
Add a validation check that will fail if the
Schema
, without prediction columns, does not contain a prediction ID column (for pandas logging). This would result in a delayed record being sent without a prediction ID, which is necessary for the latent joinAdd a validation check that will fail if the
Schema
points to an empty string as a column nameAdd check for invalid index in AutoEmbeddings: DataFrames must have a sorted, continuous index starting at 0
Remove label requirements & accept null values on
SCORE_CATEGORICAL
,NUMERIC
, andRANKING
modelsAllow feature and tag columns to contain null values for pandas logging
Allow to send delayed actuals for
RANKING
models, it is no longer enforced the presence ofrank
andprediction_group_id
columns in theSchema
. However, if the columns are sent, they must not have nulls, since we cannot construct predictions with either value null
❗ Dependency Changes
Change optional dependency for
MimicExplainer
, raise the version ceiling oflightgbm
from 3.3.4 to 4
7.0.1 (Apr 25, 2023)
🐛 Bug Fixes
A bug causing
GENERATIVE_LLM
models to be sent asSCORE_CATEGORICAL
models
7.0.0 (Apr 13, 2023)
🎁 New Features
Add Object Detection model-type support
Add Generative LLM model-type support for pandas logging
Add evaluation metrics generation for Generative LLM models
Make prediction IDs optional
Add summarization
UseCase
to AutoEmbeddingsAdd optional, additional custom headers to
Client
instantiation
💬 Feedback Enhancements
Add a warning message when only actuals are sent
Add a descriptive error message when embedding features are sent without a vector
Add warning when prediction label or prediction ID will be defaulted
🐛 Bug Fixes
A bug causing skipped validation checks when the new REGRESSION and CATEGORICAL model types are selected
✅ Validation Changes
Add a validation check that will fail if the character limit on prediction ID (128 max) is exceeded
Add a validation check that will fail if there are duplicated columns in the dataframe
Changed time range requirements to -2/+1 (two years in the past, and 1 future year)
❗ Dependency Changes
Require
Python >= 3.8
Add optional extra dependencies if the Arize package is installed as
pip install arize[LLM_Evaluation]
:nltk>=3.0.0, <4
sacrebleu>=2.3.1, <3
rouge-score>=0.1.2, <1
evaluate>=0.3, <1
💀 Deprecations
Remove
numeric_sequence
support
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