Add a page for search_traces #14033
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Add a page for search_traces #14033
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Signed-off-by: TomuHirata <[email protected]>
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B-Step62
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Dec 10, 2024
| client = MlflowClient() | ||
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| client.search_traces(experiment_ids=[morning_experiment.experiment_id]) | ||
| # Returns Trace #1 |
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Instead of "Trace #1", can we actually show the screenshot (or equivalent ascii) for the retuned object of each API? This might be a bit confusing because it looks like they return the same object.
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Sure, I guess putting screenshots every time is probably noisy, let me add some ascii to make it different.
| request_id ... morning_greeting.inputs morning_greeting.outputs | ||
| 0 053adf2f5f5e4ad68d432e06e254c8a4 ... {'name': 'Tom'} 'Good morning Tom.' | ||
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| Lastly, you can convert the pandas DataFrame to the MLflow LLM evaluation dataset format and evaluate your language model. |
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Thank you for adding this example!
Signed-off-by: TomuHirata <[email protected]>
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@B-Step62 Thank you for the review. I've addressed your comments, can you take another look? |
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Signed-off-by: TomuHirata <[email protected]>
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Signed-off-by: TomuHirata <[email protected]> Signed-off-by: k99kurella <[email protected]>
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Signed-off-by: TomuHirata <[email protected]> Signed-off-by: k99kurella <[email protected]>
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Related Issues/PRs
N/A
What changes are proposed in this pull request?
This PR create a new page for the usage of the mlflow.search_traces and MlflowClient.search_traces API.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
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.