Update TLMOptions links (#56)

Co-authored-by: Hui Wen <[email protected]>

Author: mturk24

CHANGELOG.md

@@ -7,9 +7,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [1.1.1] - 2025-04-23
+
 ### Changed
 
-- Improved validation + error messages for TLM's `custom_eval_criteria`
+- Improved validation + error messages for TLM's `custom_eval_criteria`. 
+- Changed TLMOptions text in docs to have link to TLMOptions class
 
 ## [1.1.0] - 2025-04-21
 
@@ -138,7 +141,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Release of the Cleanlab TLM Python client.
 
-[Unreleased]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.0...HEAD
+[Unreleased]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.1...HEAD
+[1.1.1]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.1.0...v1.1.1
 [1.1.0]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.0.23...v1.1.0
 [1.0.23]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.0.22...v1.0.23
 [1.0.22]: https://github.com/cleanlab/cleanlab-tlm/compare/v1.0.21...v1.0.22

src/cleanlab_tlm/__about__.py

@@ -1,2 +1,2 @@
 # SPDX-License-Identifier: MIT
-__version__ = "1.1.0"
+__version__ = "1.1.1"

src/cleanlab_tlm/tlm.py

@@ -80,12 +80,12 @@ class TLM(BaseTLM):
                 When using this task type, `constrain_outputs` must be provided in the `prompt()` and `get_trustworthiness_score()` methods.
             - "code_generation": use for code generation tasks.
 
-        options (TLMOptions, optional): a typed dict of advanced configurations you can optionally specify.
+        options ([TLMOptions](#class-tlmoptions), optional): a typed dict of advanced configurations you can optionally specify.
         Available options (keys in this dict) include "model", "max_tokens", "num_candidate_responses", "num_consistency_samples", "use_self_reflection",
         "similarity_measure", "reasoning_effort", "log", "custom_eval_criteria".
         See detailed documentation under [TLMOptions](#class-tlmoptions).
         If specified, these override any settings from the choice of `quality_preset`
-        (each `quality_preset` is just a certain TLMOptions configuration).
+        (each `quality_preset` is just a certain [TLMOptions](#class-tlmoptions) configuration).
 
         timeout (float, optional): timeout (in seconds) to apply to each TLM prompt.
         If a batch of data is passed in, the timeout will be applied to each individual item in the batch.
@@ -557,7 +557,7 @@ class TLMResponse(TypedDict):
         trustworthiness_score (float, optional): score between 0-1 corresponding to the trustworthiness of the response.
         A higher score indicates a higher confidence that the response is correct/good.
 
-        log (dict, optional): additional logs and metadata returned from the LLM call, only if the `log` key was specified in TLMOptions.
+        log (dict, optional): additional logs and metadata returned from the LLM call, only if the `log` key was specified in [TLMOptions](#class-tlmoptions).
     """
 
     response: Optional[str]
@@ -572,7 +572,7 @@ class TLMScore(TypedDict):
         trustworthiness_score (float, optional): score between 0-1 corresponding to the trustworthiness of the response.
         A higher score indicates a higher confidence that the response is correct/good.
 
-        log (dict, optional): additional logs and metadata returned from the LLM call, only if the `log` key was specified in TLMOptions.
+        log (dict, optional): additional logs and metadata returned from the LLM call, only if the `log` key was specified in [TLMOptions](#class-tlmoptions).
     """
 
     trustworthiness_score: Optional[float]

src/cleanlab_tlm/utils/rag.py

@@ -73,7 +73,7 @@ class TrustworthyRAG(BaseTLM):
         api_key (str, optional): API key for accessing TLM. If not provided, this client will
             attempt to use the CLEANLAB_TLM_API_KEY environment variable.
 
-        options (TLMOptions, optional): a typed dict of advanced configurations you can optionally specify.
+        options ([TLMOptions](../tlm/#class-tlmoptions), optional): a typed dict of advanced configurations you can optionally specify.
             The "custom_eval_criteria" key for [TLM](../tlm/#class-tlm) is not supported for `TrustworthyRAG`, you can instead specify `evals`.
 
         timeout (float, optional): timeout (in seconds) to apply to each request.
@@ -706,7 +706,7 @@ class EvalMetric(TypedDict):
         score (float, optional): score between 0-1 corresponding to the evaluation metric.
         A higher score indicates a higher rating for the specific evaluation criteria being measured.
 
-        log (dict, optional): additional logs and metadata, reported only if the `log` key was specified in `TLMOptions`.
+        log (dict, optional): additional logs and metadata, reported only if the `log` key was specified in [TLMOptions](../tlm/#class-tlmoptions).
     """
 
     score: Optional[float]

src/cleanlab_tlm/utils/tlm_lite.py

@@ -34,14 +34,14 @@ class TLMLite:
     Args:
         response_model (str): LLM used to produce the response to the given prompt.
             Do not specify the model to use for scoring  trustworthiness here, instead specify that model in the `options` argument.
-            The list of supported model strings can be found in the TLMOptions documentation, by default, the model is "gpt-4o".
+            The list of supported model strings can be found in the [TLMOptions](../tlm/#class-tlmoptions) documentation, by default, the model is "gpt-4o".
 
         quality_preset (TLMQualityPreset, default = "medium"): preset configuration to control the quality of TLM trustworthiness scores vs. runtimes/costs.
             This preset only applies to the model computing the trustworthiness score.
             Supported options are only "medium" or "low", because TLMLite is not intended to improve response accuracy
             (use the regular [TLM](../tlm) for that).
 
-        options (TLMOptions, optional): a typed dict of advanced configuration options.
+        options ([TLMOptions](../tlm/#class-tlmoptions), optional): a typed dict of advanced configuration options.
             Most of these options only apply to the model scoring  trustworthiness, except for "max_tokens", which applies to the response model as well.
             Specify which model to use for scoring trustworthiness in these options.
             For more details about the options, see the documentation for [TLMOptions](../tlm/#class-tlmoptions).