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<li class="toctree-l1"><a class="reference internal" href="definition.html">🤔 What is this library for?</a></li>
<li class="toctree-l1"><a class="reference internal" href="install.html">⚙️ Installation and configuration</a></li>
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<li class="toctree-l1 current current-page"><a class="current reference internal" href="#">👻 Classes</a></li>
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<li class="toctree-l1"><a class="reference internal" href="notebooks/01_promptmeteo_usage.html">Promptmeteo Usage - Save and Load Model</a></li>
<li class="toctree-l1"><a class="reference internal" href="notebooks/03_sentiment_analysis.html">Sentiment Analysis</a></li>
<li class="toctree-l1"><a class="reference internal" href="notebooks/04_test_flant5_classification_prompts.html">Flan-t5-Small - Test Classification Prompts</a></li>
<li class="toctree-l1"><a class="reference internal" href="notebooks/05_test_openai_classification_prompts.html">OpenAI - Test Classification Prompts</a></li>
<li class="toctree-l1"><a class="reference internal" href="notebooks/06_test_openai_api-generation.html">OpenAI - Test API Generation</a></li>
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<section id="classes">
<h1>👻 Classes<a class="headerlink" href="#classes" title="Permalink to this heading">#</a></h1>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.APIGenerator">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">APIGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_provider_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_version</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_protocol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_style_instructions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.APIGenerator" title="Permalink to this definition">#</a></dt>
<dd><p>API Generator Task.</p>
<p>This class initializes the APIGenerator Task to create APIs based on descriptions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>language</strong> (<em>str</em>) – Language for the API descriptions.</p></li>
<li><p><strong>model_name</strong> (<em>str</em>) – Name of the model to be used for API generation.</p></li>
<li><p><strong>model_provider_name</strong> (<em>str</em>) – Name of the model provider.</p></li>
<li><p><strong>api_version</strong> (<em>str</em>) – Version of the API.</p></li>
<li><p><strong>api_protocol</strong> (<em>str</em>) – Protocol of the API.</p></li>
<li><p><strong>api_style_instructions</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>str</em><em>]</em><em>]</em>) – Instructions for API style.</p></li>
<li><p><strong>**kwargs</strong> (<em>dict</em>) – Additional keyword arguments.</p></li>
<li><p><strong>Raises</strong> – </p></li>
<li><p><strong>------</strong> – </p></li>
<li><p><strong>ValueError</strong> – If <cite>api_protocol</cite> is not in the allowed protocols or if <cite>api_version</cite>
is not in the correct format.</p></li>
<li><p><strong>Example</strong> – </p></li>
<li><p><strong>-------</strong> – </p></li>
<li><p><strong>APIGenerator</strong> (<em>>>> from promptmeteo import</em>) – </p></li>
<li><p><strong>APIGenerator</strong><strong>(</strong> (<em>>>> model =</em>) – </p></li>
<li><p><strong>language="en"</strong> (<em>...</em>) – </p></li>
</ul>
</dd>
</dl>
<p>:param :
:param … selector_k=5:
:param :
:param … api_version=”3.0.3”:
:param :
:param … api_protocol=”REST”:
:param :
:param … api_style_instructions=[“Use always camel case.”:
:param “Do not use acronyms.”]:
:param :
:param … model_provider_name=”openai”:
:param :
:param … model_name=”gpt-3.5-turbo-16k”:
:param :
:param … model_provider_token=model_token:
:param :
:param … ):
:param >>> model.train(api_description:
:param api_code):
:param >>> model.predict(“API for managing account access”):</p>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.APIGenerator.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">api_descriptions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_codes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.APIGenerator.train" title="Permalink to this definition">#</a></dt>
<dd><dl class="simple">
<dt>Trains the model given use cases and notes on behaviour. Check the</dt><dd><p>parameters and task behaviour in each specific model training docstring.</p>
</dd>
</dl>
<p>Train the APIGenerator from a list of APIs descriptions and contracts.</p>
<blockquote>
<div><dl class="simple">
<dt>api_descriptions<span class="classifier">List[str]</span></dt><dd><p>List of API descriptions.</p>
</dd>
<dt>api_codes<span class="classifier">List[str]</span></dt><dd><p>List of API codes - contracts.</p>
</dd>
</dl>
<dl class="simple">
<dt>APIGenerator</dt><dd><p>Returns the trained APIGenerator object.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.APIFormatter">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">APIFormatter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">language</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model_provider_name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_version</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_protocol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_style_instructions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.APIFormatter" title="Permalink to this definition">#</a></dt>
<dd><p>API Formatter Task.</p>
<p>This class initializes the API Formatter Task to correct and format APIs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>language</strong> (<em>str</em>) – Language for the API descriptions.</p></li>
<li><p><strong>model_name</strong> (<em>str</em>) – Name of the model to be used for API generation.</p></li>
<li><p><strong>model_provider_name</strong> (<em>str</em>) – Name of the model provider.</p></li>
<li><p><strong>api_version</strong> (<em>str</em>) – Version of the API.</p></li>
<li><p><strong>api_protocol</strong> (<em>str</em>) – Protocol of the API.</p></li>
<li><p><strong>api_style_instructions</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>str</em><em>]</em><em>]</em>) – Instructions for API style.</p></li>
<li><p><strong>**kwargs</strong> (<em>dict</em>) – Additional keyword arguments.</p></li>
<li><p><strong>Raises</strong> – </p></li>
<li><p><strong>------</strong> – </p></li>
<li><p><strong>ValueError</strong> – If <cite>api_protocol</cite> is not in the allowed protocols or if <cite>api_version</cite>
is not in the correct format.</p></li>
<li><p><strong>Example</strong> – </p></li>
<li><p><strong>-------</strong> – </p></li>
<li><p><strong>APIFormatter</strong> (<em>>>> from promptmeteo import</em>) – </p></li>
<li><p><strong>APIFormatter</strong><strong>(</strong> (<em>>>> model =</em>) – </p></li>
<li><p><strong>language="en"</strong> (<em>...</em>) – </p></li>
</ul>
</dd>
</dl>
<p>:param :
:param … api_version=”3.0.3”:
:param :
:param … api_protocol=”REST”:
:param :
:param … api_style_instructions=[“Use always camel case.”:
:param “Do not use acronyms.”]:
:param :
:param … model_provider_name=”openai”:
:param :
:param … model_name=”gpt-3.5-turbo-16k”:
:param :
:param … model_provider_token=model_token:
:param :
:param … external_info={:
:param … “servers”:
:type … “servers”: [
:param … {:
:param … “url”:
:type … “url”: “<a class="reference external" href="http://localhost:8080/">http://localhost:8080/</a>”,
:param … “description”:
:type … “description”: “Local environment”,
:param … }:
:param … ]:
:param :
:param … }:
:param :
:param … ):
:param >>> model.train(api_code):
:param >>> model.predict(api):</p>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.APIFormatter.load_model">
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.APIFormatter.load_model" title="Permalink to this definition">#</a></dt>
<dd><p>Load a saved model from disk.</p>
<blockquote>
<div><dl class="simple">
<dt>model_path<span class="classifier">str</span></dt><dd><p>Path from where the model will be loaded.</p>
</dd>
</dl>
<dl class="simple">
<dt>Base</dt><dd><p>Loaded model instance.</p>
</dd>
</dl>
</div></blockquote>
<p>Loads a model artifact to make new predictions.</p>
<blockquote>
<div><dl class="simple">
<dt>model_path<span class="classifier">str</span></dt><dd><p>Path to the model artifact.</p>
</dd>
</dl>
<dl class="simple">
<dt>APIFormatter</dt><dd><p>Returns the loaded APIFormatter object.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.APIFormatter.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">api_codes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">external_info</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#promptmeteo.APIFormatter.predict" title="Permalink to this definition">#</a></dt>
<dd><p>Predict over new text samples.</p>
<blockquote>
<div><dl class="simple">
<dt>examples<span class="classifier">List[str]</span></dt><dd><p>List of text samples to predict.</p>
</dd>
</dl>
<dl class="simple">
<dt>List[str]</dt><dd><p>List of predictions.</p>
</dd>
</dl>
</div></blockquote>
<p>Receive a list of API codes and return a list with the corrected APIs.</p>
<blockquote>
<div><dl class="simple">
<dt>api_codes<span class="classifier">List[str]</span></dt><dd><p>List of API codes.</p>
</dd>
<dt>external_info<span class="classifier">dict</span></dt><dd><p>External information to be added to the APIs.</p>
</dd>
</dl>
<dl class="simple">
<dt>List[str]</dt><dd><p>List of corrected APIs.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.APIFormatter.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">api_codes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.APIFormatter.train" title="Permalink to this definition">#</a></dt>
<dd><dl class="simple">
<dt>Trains the model given use cases and notes on behaviour. Check the</dt><dd><p>parameters and task behaviour in each specific model training docstring.</p>
</dd>
</dl>
<p>Train the APIFormatter to extract entities and parameters.</p>
<blockquote>
<div><dl class="simple">
<dt>api_codes<span class="classifier">List[str]</span></dt><dd><p>List of API codes.</p>
</dd>
</dl>
<dl class="simple">
<dt>APIFormatter</dt><dd><p>Returns the trained APIFormatter object.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.CodeGenerator">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">CodeGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.CodeGenerator" title="Permalink to this definition">#</a></dt>
<dd><p>Code Generator Task.</p>
<p>This class represents a model for generating code based on natural language descriptions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>**kwargs</strong> (<em>dict</em>) – Additional keyword arguments.</p></li>
<li><p><strong>Example</strong> – </p></li>
<li><p><strong>-------</strong> – </p></li>
<li><p><strong>CodeGenerator</strong> (<em>>>> from promptmeteo import</em>) – </p></li>
<li><p><strong>CodeGenerator</strong><strong>(</strong> (<em>>>> model =</em>) – </p></li>
<li><p><strong>language="en"</strong> (<em>...</em>) – </p></li>
</ul>
</dd>
</dl>
<p>:param :
:param … prompt_domain=”python”:
:param :
:param … model_provider_name=”openai”:
:param :
:param … model_name=”text-davinci-003”:
:param :
:param … model_provider_token=model_token:
:param :
:param … prompt_detail=[:
:param … “add docstring in function definitions”:
:param :
:param … “add argument typing annotations”:
:param :
:param … ]:
:param :
:param … ):
:param >>> pred = model.predict(:
:param … [“A function that receives the argument <cite>foo</cite> and prints it.”]:
:param … ):
:param Returns:
:param ——-:
:param None:</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.DocumentClassifier">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">DocumentClassifier</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.DocumentClassifier" title="Permalink to this definition">#</a></dt>
<dd><p>DocumentClassifier Task</p>
<p>This class represents a model for classifying documents into predefined categories.</p>
<section id="example">
<h2>Example:<a class="headerlink" href="#example" title="Permalink to this heading">#</a></h2>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">promptmeteo</span> <span class="kn">import</span> <span class="n">DocumentClassifier</span>
<span class="gp">>>> </span><span class="n">clf</span> <span class="o">=</span> <span class="n">DocumentClassifier</span><span class="p">(</span>
<span class="gp">... </span> <span class="n">model_provider_name</span><span class="o">=</span><span class="s2">"hf_pipeline"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">model_name</span><span class="o">=</span><span class="s2">"google/flan-t5-small"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">prompt_labels</span><span class="o">=</span><span class="p">[</span><span class="s2">"positive"</span><span class="p">,</span> <span class="s2">"negative"</span><span class="p">,</span> <span class="s2">"neutral"</span><span class="p">],</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">clf</span><span class="o">.</span><span class="n">train</span><span class="p">(</span>
<span class="gp">... </span> <span class="n">examples</span><span class="o">=</span><span class="p">[</span><span class="s2">"estoy feliz"</span><span class="p">,</span> <span class="s2">"me da igual"</span><span class="p">,</span> <span class="s2">"no me gusta"</span><span class="p">],</span>
<span class="gp">... </span> <span class="n">annotations</span><span class="o">=</span><span class="p">[</span><span class="s2">"positive"</span><span class="p">,</span> <span class="s2">"neutral"</span><span class="p">,</span> <span class="s2">"negative"</span><span class="p">],</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="s2">"que guay!!"</span><span class="p">])</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="p">[[</span><span class="s2">"positive"</span><span class="p">]]</span>
</pre></div>
</div>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.DocumentClassifier.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">examples</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">annotations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.DocumentClassifier.train" title="Permalink to this definition">#</a></dt>
<dd><dl class="simple">
<dt>Trains the model given use cases and notes on behaviour. Check the</dt><dd><p>parameters and task behaviour in each specific model training docstring.</p>
</dd>
</dl>
<p>Trains the DocumentClassifier model.</p>
<blockquote>
<div><dl class="simple">
<dt>examples<span class="classifier">List[str]</span></dt><dd><p>List of document examples.</p>
</dd>
<dt>annotations<span class="classifier">List[str]</span></dt><dd><p>List of corresponding annotations.</p>
</dd>
</dl>
<p>Self</p>
</div></blockquote>
</dd></dl>
</section>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.DocumentQA">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">DocumentQA</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.DocumentQA" title="Permalink to this definition">#</a></dt>
<dd><p>Question Answering over Documents Task</p>
<p>This class represents a model for answering questions based on documents.</p>
<section id="id1">
<h2>Example:<a class="headerlink" href="#id1" title="Permalink to this heading">#</a></h2>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">promptmeteo</span> <span class="kn">import</span> <span class="n">DocumentQA</span>
<span class="gp">>>> </span><span class="n">clf</span> <span class="o">=</span> <span class="n">DocumentQA</span><span class="p">(</span>
<span class="gp">... </span> <span class="n">language</span><span class="o">=</span><span class="s2">"en"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">model_provider_name</span><span class="o">=</span><span class="s2">"hf_pipeline"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">model_name</span><span class="o">=</span><span class="s2">"google/flan-t5-small"</span><span class="p">,</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">clf</span><span class="o">.</span><span class="n">train</span><span class="p">(</span>
<span class="gp">... </span> <span class="n">examples</span><span class="o">=</span><span class="p">[</span>
<span class="gp">... </span> <span class="s2">"The rain in spain is always in plain"</span><span class="p">,</span>
<span class="gp">... </span> <span class="s2">"The logarithm's limit is the limit's logarithm"</span><span class="p">,</span>
<span class="gp">... </span> <span class="s2">"To punish oppresors is clementy. To forgive them is cruelty"</span><span class="p">,</span>
<span class="gp">... </span> <span class="p">],</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="s2">"How is the rain in spain?"</span><span class="p">])</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="p">[[</span><span class="s2">"in plain"</span><span class="p">]]</span>
</pre></div>
</div>
</section>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="promptmeteo.Summarizer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">promptmeteo.</span></span><span class="sig-name descname"><span class="pre">Summarizer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#promptmeteo.Summarizer" title="Permalink to this definition">#</a></dt>
<dd><p>Class for text summarization</p>
<p>This class represents a model for text summarization.</p>
<section id="id2">
<h2>Example:<a class="headerlink" href="#id2" title="Permalink to this heading">#</a></h2>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">from</span> <span class="nn">promptmeteo</span> <span class="kn">import</span> <span class="n">Summarizer</span>
<span class="gp">>>> </span><span class="n">model</span> <span class="o">=</span> <span class="n">Summarizer</span><span class="p">(</span>
<span class="gp">... </span> <span class="n">language</span><span class="o">=</span><span class="s2">"es"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">prompt_domain</span><span class="o">=</span><span class="s2">"A partir del siguiente texto:"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">model_name</span><span class="o">=</span><span class="s2">"anthropic.claude-v2"</span><span class="p">,</span>
<span class="gp">... </span> <span class="n">model_provider_name</span><span class="o">=</span><span class="s2">"bedrock"</span><span class="p">,</span>
<span class="gp">... </span><span class="p">)</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">([</span><span class="n">text</span><span class="p">])</span>
</pre></div>
</div>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.Summarizer.load_model">
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.Summarizer.load_model" title="Permalink to this definition">#</a></dt>
<dd><p>Load a saved model from disk.</p>
<blockquote>
<div><dl class="simple">
<dt>model_path<span class="classifier">str</span></dt><dd><p>Path from where the model will be loaded.</p>
</dd>
</dl>
<dl class="simple">
<dt>Base</dt><dd><p>Loaded model instance.</p>
</dd>
</dl>
</div></blockquote>
<p>Loads a model artifact to make new predictions.</p>
<blockquote>
<div><dl class="simple">
<dt>model_path<span class="classifier">str</span></dt><dd><p>The path to the saved model artifact.</p>
</dd>
</dl>
<dl class="simple">
<dt>self<span class="classifier">Summarizer</span></dt><dd><p>The loaded Summarizer model.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="promptmeteo.Summarizer.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="headerlink" href="#promptmeteo.Summarizer.train" title="Permalink to this definition">#</a></dt>
<dd><dl class="simple">
<dt>Trains the model given use cases and notes on behaviour. Check the</dt><dd><p>parameters and task behaviour in each specific model training docstring.</p>
</dd>
</dl>
<p>Train the Summarizer model.</p>
<blockquote>
<div><dl class="simple">
<dt>self<span class="classifier">Summarizer</span></dt><dd><p>The trained Summarizer model.</p>
</dd>
</dl>
</div></blockquote>
</dd></dl>
</section>
</dd></dl>
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<ul>
<li><a class="reference internal" href="#">👻 Classes</a><ul>
<li><a class="reference internal" href="#promptmeteo.APIGenerator"><code class="docutils literal notranslate"><span class="pre">APIGenerator</span></code></a><ul>
<li><a class="reference internal" href="#promptmeteo.APIGenerator.train"><code class="docutils literal notranslate"><span class="pre">APIGenerator.train()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#promptmeteo.APIFormatter"><code class="docutils literal notranslate"><span class="pre">APIFormatter</span></code></a><ul>
<li><a class="reference internal" href="#promptmeteo.APIFormatter.load_model"><code class="docutils literal notranslate"><span class="pre">APIFormatter.load_model()</span></code></a></li>
<li><a class="reference internal" href="#promptmeteo.APIFormatter.predict"><code class="docutils literal notranslate"><span class="pre">APIFormatter.predict()</span></code></a></li>
<li><a class="reference internal" href="#promptmeteo.APIFormatter.train"><code class="docutils literal notranslate"><span class="pre">APIFormatter.train()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#promptmeteo.CodeGenerator"><code class="docutils literal notranslate"><span class="pre">CodeGenerator</span></code></a></li>
<li><a class="reference internal" href="#promptmeteo.DocumentClassifier"><code class="docutils literal notranslate"><span class="pre">DocumentClassifier</span></code></a><ul>
<li><a class="reference internal" href="#promptmeteo.DocumentClassifier.train"><code class="docutils literal notranslate"><span class="pre">DocumentClassifier.train()</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#promptmeteo.DocumentQA"><code class="docutils literal notranslate"><span class="pre">DocumentQA</span></code></a></li>
<li><a class="reference internal" href="#promptmeteo.Summarizer"><code class="docutils literal notranslate"><span class="pre">Summarizer</span></code></a><ul>
<li><a class="reference internal" href="#promptmeteo.Summarizer.load_model"><code class="docutils literal notranslate"><span class="pre">Summarizer.load_model()</span></code></a></li>
<li><a class="reference internal" href="#promptmeteo.Summarizer.train"><code class="docutils literal notranslate"><span class="pre">Summarizer.train()</span></code></a></li>
</ul>
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