add safety case study

pyproject.toml

@@ -7,15 +7,15 @@ license = "Attribution-NonCommercial-ShareAlike 4.0 International"
 readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.11"
+python = ">=3.11,<3.13"
 jupyter-book = "^1.0.3"
 pandas = "^2.2.3"
 openai = "^1.54.4"
 ipykernel = "^6.29.5"
 python-dotenv = "^1.0.1"
 requests = "^2.32.3"
 beautifulsoup4 = "^4.12.3"
-tiktoken = "^0.8.0"
+tiktoken = ">=0.5,<0.8"
 litellm = "^1.52.9"
 pydata-sphinx-theme = "^0.16.0"
 sphinx-multitoc-numbering = "^0.1.3"
@@ -38,6 +38,10 @@ ollama = "^0.4.3"
 langsmith = "0.2.0"
 sphinxcontrib-mermaid = "^1.0.0"
 seaborn = "^0.13.2"
+ipywidgets = "^8.1.5"
+mistralai = "^1.2.5"
+llm-guard = "^0.3.15"
+pygments = "^2.18.0"
 
 
 [build-system]

tamingllms/_build/html/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 0674df45a82890a4968a11e155ae506b
+config: 188f476ff603503d272f0faa368442ae
 tags: 645f666f9bcd5a90fca523b33c5a78b7

tamingllms/_build/html/markdown/preface.html

@@ -214,7 +214,7 @@ <h1><span class="section-number">1. </span>Preface<a class="headerlink" href="#p
 <div><p>Models tell you merely what something is like, not what something is.</p>
 <p class="attribution">—Emanuel Derman</p>
 </div></blockquote>
-<p>An alternative title of this book could have been “Language Models Behaving Badly”. If you are coming from a background in financial modeling, you may have noticed the parallel with Emanuel Derman’s seminal work “Models.Behaving.Badly” <span id="id1">[<a class="reference internal" href="#id116" title="E. Derman. Models.Behaving.Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life. Free Press, 2011. ISBN 9781439165010. URL: https://books.google.co.uk/books?id=lke_cwM4wm8C.">Derman, 2011</a>]</span>. This parallel is not coincidental. Just as Derman cautioned against treating financial models as perfect representations of reality, this book aims to highlight the limitations and pitfalls of Large Language Models (LLMs) in practical applications (of course baring the fact Derman is an actual physicist and legendary author, professor and quant; I am not).</p>
+<p>An alternative title of this book could have been “Language Models Behaving Badly”. If you are coming from a background in financial modeling, you may have noticed the parallel with Emanuel Derman’s seminal work “Models.Behaving.Badly” <span id="id1">[<a class="reference internal" href="#id117" title="E. Derman. Models.Behaving.Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life. Free Press, 2011. ISBN 9781439165010. URL: https://books.google.co.uk/books?id=lke_cwM4wm8C.">Derman, 2011</a>]</span>. This parallel is not coincidental. Just as Derman cautioned against treating financial models as perfect representations of reality, this book aims to highlight the limitations and pitfalls of Large Language Models (LLMs) in practical applications (of course baring the fact Derman is an actual physicist and legendary author, professor and quant; I am not).</p>
 <p>The book “Models.Behaving.Badly” by Emanuel Derman, a former physicist and Goldman Sachs quant, explores how financial and scientific models can fail when we mistake them for reality rather than treating them as approximations full of assumptions.
 The core premise of his work is that while models can be useful tools for understanding aspects of the world, they inherently involve simplification and assumptions. Derman argues that many financial crises, including the 2008 crash, occurred partly because people put too much faith in mathematical models without recognizing their limitations.</p>
 <p>Like financial models that failed to capture the complexity of human behavior and market dynamics, LLMs have inherent constraints. They can hallucinate facts, struggle with logical reasoning, and fail to maintain consistency across long outputs. Their responses, while often convincing, are probabilistic approximations based on training data rather than true understanding even though humans insist on treating them as “machines that can reason”.</p>
@@ -224,7 +224,7 @@ <h1><span class="section-number">1. </span>Preface<a class="headerlink" href="#p
 <section id="references">
 <h2><span class="section-number">1.1. </span>References<a class="headerlink" href="#references" title="Permalink to this heading">¶</a></h2>
 <div class="docutils container" id="id2">
-<div class="citation" id="id116" role="doc-biblioentry">
+<div class="citation" id="id117" role="doc-biblioentry">
 <span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id1">Der11</a><span class="fn-bracket">]</span></span>
 <p>E. Derman. <em>Models.Behaving.Badly.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life</em>. Free Press, 2011. ISBN 9781439165010. URL: <a class="reference external" href="https://books.google.co.uk/books?id=lke_cwM4wm8C">https://books.google.co.uk/books?id=lke_cwM4wm8C</a>.</p>
 </div>