Merge pull request #1186 from JohnSnowLabs/chore/final_website_updates

chakravarthik27 · web-flow · commit c528cbab5e09 · 2025-03-10T21:11:01.000+05:30
chore: update gem dependencies and enhance tutorial notebook links
diff --git a/docs/Gemfile.lock b/docs/Gemfile.lock
@@ -16,9 +16,10 @@ GEM
     coffee-script-source (1.11.1)
     colorator (1.1.0)
     commonmarker (0.23.11)
-    concurrent-ruby (1.3.4)
-    dnsruby (1.72.3)
+    concurrent-ruby (1.3.5)
+    dnsruby (1.72.4)
       base64 (~> 0.2.0)
+      logger (~> 1.6.5)
       simpleidn (~> 0.2.1)
     em-websocket (0.5.3)
       eventmachine (>= 0.12.9)
@@ -34,8 +35,6 @@ GEM
     faraday-net_http (3.4.0)
       net-http (>= 0.5.0)
     ffi (1.17.1)
-    ffi (1.17.1-arm64-darwin)
-    ffi (1.17.1-x86_64-darwin)
     forwardable-extended (2.6.0)
     gemoji (3.0.1)
     github-pages (226)
@@ -203,7 +202,7 @@ GEM
       gemoji (~> 3.0)
       html-pipeline (~> 2.2)
       jekyll (>= 3.0, < 5.0)
-    json (2.9.1)
+    json (2.10.1)
     kramdown (2.3.2)
       rexml
     kramdown-parser-gfm (1.1.0)
@@ -212,20 +211,18 @@ GEM
     listen (3.9.0)
       rb-fsevent (~> 0.10, >= 0.10.3)
       rb-inotify (~> 0.9, >= 0.9.10)
-    logger (1.6.4)
+    logger (1.6.6)
     mercenary (0.3.6)
+    mini_portile2 (2.8.8)
     minima (2.5.1)
       jekyll (>= 3.5, < 5.0)
       jekyll-feed (~> 0.9)
       jekyll-seo-tag (~> 2.1)
     minitest (5.25.4)
     net-http (0.6.0)
       uri
-    nokogiri (1.17.2-arm64-darwin)
-      racc (~> 1.4)
-    nokogiri (1.17.2-x86_64-darwin)
-      racc (~> 1.4)
-    nokogiri (1.17.2-x86_64-linux)
+    nokogiri (1.18.3)
+      mini_portile2 (~> 2.8.2)
       racc (~> 1.4)
     octokit (4.25.1)
       faraday (>= 1, < 3)
@@ -237,9 +234,9 @@ GEM
     rb-fsevent (0.11.2)
     rb-inotify (0.11.1)
       ffi (~> 1.0)
-    rexml (3.4.0)
+    rexml (3.4.1)
     rouge (3.26.0)
-    rubyzip (2.3.2)
+    rubyzip (2.4.1)
     safe_yaml (1.0.5)
     sass (3.7.4)
       sass-listen (~> 4.0.0)
@@ -258,18 +255,16 @@ GEM
     tzinfo (1.2.11)
       thread_safe (~> 0.1)
     unicode-display_width (1.8.0)
-    uri (1.0.2)
+    uri (1.0.3)
     webrick (1.9.1)
     zeitwerk (2.6.18)
 
 PLATFORMS
-  arm64-darwin
-  x86_64-darwin
   x86_64-linux
 
 DEPENDENCIES
   github-pages (= 226)
   webrick (~> 1.7)
 
 BUNDLED WITH
-   2.5.16
+   2.3.7
diff --git a/docs/pages/tutorials/LLM_testing_Notebooks/llm_testing_notebooks.md b/docs/pages/tutorials/LLM_testing_Notebooks/llm_testing_notebooks.md
@@ -43,5 +43,5 @@ The following table gives an overview of the different tutorial notebooks to tes
 | **Fewshot Model Evaluation**: This notebook provides a demo on Optimize and evaluate your models using few-shot prompt techniques  |  OpenAI         | Question-Answering                          | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/llm_notebooks/Fewshot_QA_Notebook.ipynb) |
 | **Evaluating NER in LLMs**:In this tutorial, we assess the support for Named Entity Recognition (NER) tasks specifically for Large Language Models (LLMs) |  OpenAI         | Question-Answering                           | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/llm_notebooks/NER%20Casual%20LLM.ipynb) |
 | **Swapping Drug Names Test**:In this notebook, we discussed implementing tests that facilitate the swapping of generic drug names with brand names and vice versa. This feature ensures accurate evaluations in medical and pharmaceutical contexts. |  OpenAI         | Question-Answering                           | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/llm_notebooks/Swapping_Drug_Names_Test.ipynb) |
-| **Evaluation with Structured Outputs**:In this notebook, we discussed implementing evalution with structured output APIs for OpenAI, Ollama, and Azure-OpenAI, offering greater flexibility and precision when processing model responses. |  OpenAI         | Question-Answering                           | https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Evaluation_with_Structured_Outputs.ipynb |
-| **Med Halt Tests**:In this notebook, we discussed about insights into your LLMs’ robustness and reliability under diverse conditions with our upgraded Med Halt tests.  |  OpenAI         | Question-Answering                           | https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/llm_notebooks/Med_Halt_Tests.ipynb |
+| **Evaluation with Structured Outputs**:In this notebook, we discussed implementing evalution with structured output APIs for OpenAI, Ollama, and Azure-OpenAI, offering greater flexibility and precision when processing model responses. |  OpenAI         | Question-Answering                           | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Evaluation_with_Structured_Outputs.ipynb) |
+| **Med Halt Tests**:In this notebook, we discussed about insights into your LLMs’ robustness and reliability under diverse conditions with our upgraded Med Halt tests.  |  OpenAI         | Question-Answering                           | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/llm_notebooks/Med_Halt_Tests.ipynb) |
diff --git a/docs/pages/tutorials/miscellaneous_notebooks/miscellaneous_notebooks.md b/docs/pages/tutorials/miscellaneous_notebooks/miscellaneous_notebooks.md
@@ -47,4 +47,4 @@ The following table gives an overview of the different tutorial notebooks. In th
 | **Visual_QA**: In this Notebook, we discussed about the visual question answering tests to evaluate how models handle both visual and textual inputs, offering a deeper understanding of their versatility.   | OpenAI                    | Visual-Question-Answering (visualqa)                                | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Misuse_Test_with_Prometheus_evaluation.ipynb) |
 | **Add_New_Lines_and_Tabs_Tests**: In this Notebook, we discussed about new tests like inserting new lines and tab characters into text inputs, challenging your models to handle structural changes without compromising accuracy.   | Hugging Face/John Snow Labs/Spacy	                    |Text-Classification/Question-Answering/Summarization                            | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Add_New_Lines_and_Tabs_Tests.ipynb) |
 | **Safety_Tests_With_PromptGuard**: In this Notebook, we discussed about evaluating prompts before they are sent to large language models (LLMs), ensuring harmful or unethical outputs are avoided with PromptGuard.   | Hugging Face/John Snow Labs/Spacy                    | Text-Classification/Question-Answering/Summarization                               | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Safety_Tests_With_PromptGuard.ipynb) |
-| **De-biasing Data Augmentation**: In this Notebook, We’ve integrated de-biasing techniques into our data augmentation process, ensuring more equitable and representative model assessments.   | Hugging Face/John Snow Labs/Spacy                    | Text-Classification/Question-Answering                               | https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Dataset_Debiasing.ipynb |
+| **De-biasing Data Augmentation**: In this Notebook, We’ve integrated de-biasing techniques into our data augmentation process, ensuring more equitable and representative model assessments.   | Hugging Face/John Snow Labs/Spacy                    | Text-Classification/Question-Answering                               | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/JohnSnowLabs/langtest/blob/main/demo/tutorials/misc/Dataset_Debiasing.ipynb) |
