[MLflow] Updating langchain databricks_dependency to use resources and format #11834
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Documentation preview for 8cea2ff will be available when this CircleCI job More info
|
github-actions
bot
added
area/tracking
sunishsheth2009
force-pushed
the
sunish-langchain-update
branch
3 times, most recently
from
52ea50e
to
903f906
Compare
…d format Signed-off-by: Sunish Sheth <sunishsheth2009@gmail.com>
sunishsheth2009
force-pushed
the
sunish-langchain-update
branch
from
903f906
to
8cea2ff
Compare
aakrati
reviewed
Apr 30, 2024
There was a problem hiding this comment.
@sunishsheth2009 - These changes are breaking changes to the existing API.
Can we either:
- Make the Serving side changes first before we update the mlflow and support both new / old MLModel formats
- Or make this change backwards compatible
Discussed with @sunishsheth2009 since this change needs to make in first, he will support backwards compatible change.
| "databricks_llm_endpoint_name": ["llm_endpoint"], | ||
| "databricks_chat_endpoint_name": ["chat_endpoint"], | ||
| } | ||
| "resources": { |
There was a problem hiding this comment.
Lets ensure Serving side changes are supported and released before mlflow release is finished
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
🛠 DevTools 🛠
Install mlflow from this PR
Checkout with GitHub CLI
What changes are proposed in this pull request?
[MLflow] Updating langchain databricks_dependency to use resources and format
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
[MLflow] Updating langchain databricks_dependency to use resources and format
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrationsarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notesShould this PR be included in the next patch release?
Yesshould be selected for bug fixes, documentation updates, and other small changes.Noshould be selected for new features and larger changes. If you're unsure about the release classification of this PR, leave this unchecked to let the maintainers decide.What is a minor/patch release?
Bug fixes, doc updates and new features usually go into minor releases.
Bug fixes and doc updates usually go into patch releases.