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<div class="section" id="texts">
<h1>Texts<a class="headerlink" href="#texts" title="Permalink to this headline">¶</a></h1>
<div class="section" id="id1">
<h2>Texts<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h2>
<p>Texts</p>
<span class="target" id="module-vectorai.api.text"></span><dl class="py class">
<dt class="sig sig-object py" id="vectorai.api.text.ViTextClient">
<em class="property"><span class="pre">class</span> </em><span class="sig-prename descclassname"><span class="pre">vectorai.api.text.</span></span><span class="sig-name descname"><span class="pre">ViTextClient</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">username</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">api_key</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">url</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#vectorai.api.text.ViTextClient" title="Permalink to this definition">¶</a></dt>
<dd><p>Search and Encoding of Texts</p>
<dl class="py method">
<dt class="sig sig-object py" id="vectorai.api.text.ViTextClient.search_text">
<span class="sig-name descname"><span class="pre">search_text</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">collection_name</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">text</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fields</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">List</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metric</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">'cosine'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_score</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">page</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">page_size</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">int</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_vector</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_count</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">asc</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_curl</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</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="#vectorai.api.text.ViTextClient.search_text" title="Permalink to this definition">¶</a></dt>
<dd><p>Search a text field with text using Vector Search with text directly.</p>
<p>For example: “product_description” represents the description of a product:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="s2">"AirPods deliver effortless, all-day audio on the go. And AirPods Pro bring Active Noise Cancellation to an in-ear headphone — with a customisable fit"</span>
<span class="o">-></span> <span class="o"><</span><span class="n">Encode</span> <span class="n">the</span> <span class="n">text</span> <span class="n">to</span> <span class="n">vector</span><span class="o">></span> <span class="o">-></span>
<span class="n">i</span><span class="o">.</span><span class="n">e</span><span class="o">.</span> <span class="n">text</span> <span class="n">vector</span><span class="p">,</span> <span class="s2">"product_description_vector_"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.794617772102356</span><span class="p">,</span> <span class="mf">0.3581121861934662</span><span class="p">,</span> <span class="mf">0.21113917231559753</span><span class="p">,</span> <span class="mf">0.24878688156604767</span><span class="p">,</span> <span class="mf">0.9741804003715515</span> <span class="o">...</span><span class="p">]</span>
<span class="o">-></span> <span class="o"><</span><span class="n">Vector</span> <span class="n">Search</span><span class="o">></span> <span class="o">-></span>
<span class="n">Search</span> <span class="n">Results</span><span class="p">:</span> <span class="p">{</span><span class="o">...</span><span class="p">}</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>text</strong> – Text to encode into vector and vector search with</p></li>
<li><p><strong>collection_name</strong> – Name of Collection</p></li>
<li><p><strong>search_fields</strong> – Vector fields to search through</p></li>
<li><p><strong>approx</strong> – Used for approximate search</p></li>
<li><p><strong>sum_fields</strong> – Whether to sum the multiple vectors similarity search score as 1 or seperate</p></li>
<li><p><strong>page_size</strong> – Size of each page of results</p></li>
<li><p><strong>page</strong> – Page of the results</p></li>
<li><p><strong>metric</strong> – Similarity Metric, choose from [‘cosine’, ‘l1’, ‘l2’, ‘dp’]</p></li>
<li><p><strong>min_score</strong> – Minimum score for similarity metric</p></li>
<li><p><strong>include_vector</strong> – Include vectors in the search results</p></li>
<li><p><strong>include_count</strong> – Include count in the search results</p></li>
<li><p><strong>hundred_scale</strong> – <p>Whether to scale up the metric by 100</p>
<dl class="simple">
<dt>asc:</dt><dd><p>Whether to sort the score by ascending order (default is false, for getting most similar results)</p>
</dd>
</dl>
</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="vectorai.api.text.ViTextClient.encode_text_job">
<span class="sig-name descname"><span class="pre">encode_text_job</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">collection_name</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">text_field</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">refresh</span></span><span class="p"><span class="pre">:</span></span> <span class="n"><span class="pre">bool</span></span> <span class="o"><span class="pre">=</span></span> <span class="default_value"><span class="pre">False</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="#vectorai.api.text.ViTextClient.encode_text_job" title="Permalink to this definition">¶</a></dt>
<dd><p>Encode all texts in a field into vectors</p>
<p>Within a collection encode the specified text field in every document into vectors.</p>
<p>For example, a text field “product_description” represents the description of a product:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">document</span> <span class="mi">1</span> <span class="n">text</span> <span class="n">field</span><span class="p">:</span> <span class="p">{</span><span class="s2">"product_description"</span> <span class="p">:</span> <span class="s2">"AirPods deliver effortless, all-day audio on the go. And AirPods Pro bring Active Noise Cancellation to an in-ear headphone — with a customisable fit."</span>
<span class="n">document</span> <span class="mi">2</span> <span class="n">text</span> <span class="n">field</span><span class="p">:</span> <span class="p">{</span><span class="s2">"product_description"</span> <span class="p">:</span> <span class="s2">"MacBook Pro elevates the notebook to a whole new level of performance and portability. Wherever your ideas take you, you’ll get there faster than ever with high‑performance processors and memory, advanced graphics, blazing‑fast storage and more — all in a compact package."</span>
<span class="o">-></span> <span class="o"><</span><span class="n">Encode</span> <span class="n">the</span> <span class="n">texts</span> <span class="n">to</span> <span class="n">vectors</span><span class="o">></span> <span class="o">-></span>
<span class="n">document</span> <span class="mi">1</span> <span class="n">text</span> <span class="n">vector</span><span class="p">:</span> <span class="p">{</span><span class="s2">"product_description_vector_"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.794617772102356</span><span class="p">,</span> <span class="mf">0.3581121861934662</span><span class="p">,</span> <span class="mf">0.21113917231559753</span><span class="p">,</span> <span class="mf">0.24878688156604767</span><span class="p">,</span> <span class="mf">0.9741804003715515</span> <span class="o">...</span><span class="p">]}</span>
<span class="n">document</span> <span class="mi">2</span> <span class="n">text</span> <span class="n">vector</span><span class="p">:</span> <span class="p">{</span><span class="s2">"product_description_vector_"</span><span class="p">:</span> <span class="p">[</span><span class="mf">0.8364648222923279</span><span class="p">,</span> <span class="mf">0.6280597448348999</span><span class="p">,</span> <span class="mf">0.8112713694572449</span><span class="p">,</span> <span class="mf">0.36105549335479736</span><span class="p">,</span> <span class="mf">0.005313870031386614</span> <span class="o">...</span><span class="p">]}</span>
</pre></div>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>text_field</strong> – The text field to encode into vectors</p></li>
<li><p><strong>refresh</strong> – Whether to refresh the whole collection and re-encode all to vectors</p></li>
<li><p><strong>collection_name</strong> – Name of Collection</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</dd></dl>
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