Remove quality_preset arg and cleanup validate docstring (#93)

* Remove quality_preset arg and cleanup validate docstring

* bump version 1.022

Author: LukeMainwaring

CHANGELOG.md

@@ -7,6 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [1.0.22] 2025-06-23
+
+- Remove quality_preset arg
+
 ## [1.0.21] 2025-06-22
 
 - Support adding remediations to a project
@@ -104,7 +108,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Initial release of the `cleanlab-codex` client library.
 
-[Unreleased]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.21...HEAD
+[Unreleased]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.22...HEAD
+[1.0.22]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.21...v1.0.22
 [1.0.21]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.20...v1.0.21
 [1.0.20]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.19...v1.0.20
 [1.0.19]: https://github.com/cleanlab/cleanlab-codex/compare/v1.0.18...v1.0.19

src/cleanlab_codex/__about__.py

@@ -1,2 +1,2 @@
 # SPDX-License-Identifier: MIT
-__version__ = "1.0.21"
+__version__ = "1.0.22"

src/cleanlab_codex/project.py

@@ -4,7 +4,7 @@
 
 from datetime import datetime
 from typing import TYPE_CHECKING as _TYPE_CHECKING
-from typing import Dict, Literal, Optional
+from typing import Dict, Optional
 
 from codex import AuthenticationError
 
@@ -153,7 +153,6 @@ def validate(
         custom_metadata: Optional[object] = None,
         eval_scores: Optional[Dict[str, float]] = None,
         eval_thresholds: Optional[Dict[str, float]] = None,
-        quality_preset: Literal["best", "high", "medium", "low", "base"] = "medium",
     ) -> ProjectValidateResponse:
         """Run validation on a query to an AI system.
 
@@ -165,7 +164,6 @@ def validate(
             custom_metadata (object, optional): Custom metadata to log in Codex for the query.
             eval_scores (Dict[str, float], optional): Optional scores to use for the query. When provided, Codex will skip running TrustworthyRAG evaluations on the query and use the provided scores instead.
             eval_thresholds (Dict[str, float], optional): Optional thresholds to use for evaluating the query. We recommend configuring thresholds on the Project instead and using the same thresholds for all queries.
-            quality_preset (Literal["best", "high", "medium", "low", "base"], optional): The quality preset to use for the query.
 
         Returns:
             ProjectValidateResponse: The response from the validation.
@@ -179,7 +177,6 @@ def validate(
             custom_eval_thresholds=eval_thresholds,
             custom_metadata=custom_metadata,
             eval_scores=eval_scores,
-            quality_preset=quality_preset,
         )
 
     def add_remediation(self, question: str, answer: str | None = None) -> None:

src/cleanlab_codex/validator.py

@@ -5,7 +5,7 @@
 from __future__ import annotations
 
 from typing import TYPE_CHECKING as _TYPE_CHECKING
-from typing import Any, Callable, Literal, Optional
+from typing import Any, Callable, Optional
 
 from cleanlab_tlm import TrustworthyRAG
 
@@ -59,7 +59,6 @@ def validate(
         form_prompt: Optional[Callable[[str, str], str]] = None,
         metadata: Optional[dict[str, Any]] = None,
         eval_scores: Optional[dict[str, float]] = None,
-        quality_preset: Literal["best", "high", "medium", "low", "base"] = "medium",
     ) -> ProjectValidateResponse:
         """Evaluate whether the AI-generated response is bad, and if so, request an alternate expert answer.
         If no expert answer is available, this query is still logged for SMEs to answer.
@@ -72,8 +71,6 @@ def validate(
             form_prompt (Callable[[str, str], str], optional): Optional function to format the prompt based on query and context. Cannot be provided together with prompt, provide one or the other. This function should take query and context as parameters and return a formatted prompt string. If not provided, a default prompt formatter will be used. To include a system prompt or any other special instructions for your LLM, incorporate them directly in your custom form_prompt() function definition.
             metadata (dict, optional): Additional custom metadata to associate with the query logged in the Codex Project.
             eval_scores (dict[str, float], optional): Scores assessing different aspects of the RAG system. If provided, TLM Trustworthy RAG will not be used to generate scores.
-            options (ProjectValidateOptions, optional): Typed dict of advanced TLM configuration options. See [TLMOptions](/tlm/api/python/tlm/#class-tlmoptions)
-            quality_preset (Literal["best", "high", "medium", "low", "base"], optional): The quality preset to use for the TLM or Trustworthy RAG API.
 
         Returns:
             ProjectValidateResponse: A response object containing:
@@ -103,5 +100,4 @@ def validate(
             custom_metadata=metadata,
             eval_scores=eval_scores,
             eval_thresholds=self._eval_thresholds,
-            quality_preset=quality_preset,
         )