[4/4] Documentation for DeepEval scorers#19409
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Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
| "mlflow-test-plugin", | ||
| ] | ||
| constraints = [{ name = "xgboost", specifier = "<3.1.0" }] | ||
| excludes = ["databricks-connect"] |
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Why is this change included in this PR? Ditto fro the other databricks-connect changes in the uv.lock
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Should be resolved!
B-Step62
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LGTM, with one suggestion to handle multiple 3p integrations.
| { | ||
| type: 'doc', | ||
| id: 'eval-monitor/scorers/third-party', | ||
| label: 'Third-party Scorers', | ||
| }, |
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Since we will introduce more integrations in the same release, does it make sense to have tree structure?
Third-party Scorers
|- Deepeval
|- Ragas
...
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I was actually thinking of using tabs - see #19451 - WDYT? I don't have a strong preference
| }, | ||
| { | ||
| type: 'category', | ||
| label: 'Supported Scorers', |
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[not scope of this PR] @AveshCSingh @smoorjani I think it is a part of documentation organization, but please feel free to adjust the structure of judge documentation drastically. Admittedly as an original author the current structure is not clearly describe which one to use when and also draws incorrect boundary e.g., most of "Predefined Scorers" are actually "LLM-as-a-Judge", also there is overlap between Agentic judge and template-based (make_judge). My sense is we should eliminate all jargons and call everything either of "LLM-as-a-Judge" or "Code scorer"🙂
| tensorflow-cpu<=2.12.0; platform_system!="Darwin" or platform_machine!="arm64" | ||
| tensorflow-macos<=2.12.0; platform_system=="Darwin" and platform_machine=="arm64" | ||
| pyspark | ||
| pyspark<4.1.0 |
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note to reviewer: had to change this to get CI to pass
pyproject.toml
Outdated
| "tensorflow", | ||
| "keras", | ||
| "pyspark", | ||
| "pyspark<4.1.0", |
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we can move this in constraint-dependencies
harupy
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LGTM once #19409 (comment) is addressed
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
Signed-off-by: Samraj Moorjani <samraj.moorjani@databricks.com>
🛠 DevTools 🛠
Install mlflow from this PR
For Databricks, use the following command:
Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Introduces documentation for the DeepEval scorers
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/tracking: Tracking Service, tracking client APIs, autologgingarea/models: MLmodel format, model serialization/deserialization, flavorsarea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflowsarea/gateway: MLflow AI Gateway client APIs, server, and third-party integrationsarea/prompts: MLflow prompt engineering features, prompt templates, and prompt managementarea/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionalityarea/projects: MLproject format, project running backendsarea/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesHow 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.