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  508. <a href="https://github.com/princeton-nlp/SWE-agent/edit/main/docs/config/summarizers.md" title="Edit this page" class="md-content__button md-icon">
  509. <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M10 20H6V4h7v5h5v3.1l2-2V8l-6-6H6c-1.1 0-2 .9-2 2v16c0 1.1.9 2 2 2h4zm10.2-7c.1 0 .3.1.4.2l1.3 1.3c.2.2.2.6 0 .8l-1 1-2.1-2.1 1-1c.1-.1.2-.2.4-.2m0 3.9L14.1 23H12v-2.1l6.1-6.1z"/></svg>
  510. </a>
  511. <h1 id="summarizers-configuration">Summarizers Configuration</h1>
  512. <p>LMs perform best if given concise inputs; superfluous context can degrade performance while increasing costs. Because agents require LMs to process entire trajectories, compressing context is of particular importance.</p>
  513. <p>We designed two summarizers to handle long output commands. The first, a <strong><em>simple summarizer</em></strong>, saves the command output to a file if it exceeds a certain configurable line count. We show an indicative warning to the agent and tell it to open the saved command output using the built-in SWE-agent utility <code>open</code>.</p>
  514. <p>The second, an <strong><em>LM summarizer</em></strong>, integrates with the main agent to enhance its problem-solving efficacy and avoid exceeding input length limitations. It employs the same model (though can be configured differently) as the main agent; it receives a configurable prompt containing some context about the problem, the most recent action taken by the main agent, and any observations from that action exceeding a configurable line count threshold. The LM summarizer then generates a concise summary of the observation that is directly relevant to the ongoing problem. This summary is sent to the main agent, accompanied by a warning message indicating that the command output was summarized due to exceeding the line count limit.</p>
  515. <p>The summarizer configuration is defined within the main <a href="../config/">configuration</a> <code>.yaml</code> file, and has the following structure:</p>
  516. <div class="highlight"><pre><span></span><code><span class="nt">summarizer_config</span><span class="p">:</span>
  517. <span class="w"> </span><span class="nt">function</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Reference to functionality of the summarizer. Can be one of SimpleSummarizer, LMSummarizer or Identity</span>
  518. <span class="w"> </span><span class="nt">window_length</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Threshold of the line count limit. Observation output exceeding these number, will be summarized.</span>
  519. <span class="w"> </span><span class="nt">system_template</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">|-</span>
  520. <span class="w"> </span><span class="no">First `system` message shown to the LMSummarizer.</span>
  521. <span class="w"> </span><span class="no">This has no effect in other summarizer functionalities.</span>
  522. <span class="w"> </span><span class="nt">instance_template</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">|-</span>
  523. <span class="w"> </span><span class="no">Instance prompt, contains task instance-specific content,</span>
  524. <span class="w"> </span><span class="no">the most recent action taken by the main agent,</span>
  525. <span class="w"> </span><span class="no">and any observations from that action exceeding the line count threshold.</span>
  526. <span class="w"> </span><span class="no">This has effect only for the LM Summarizer functionality.</span>
  527. <span class="w"> </span><span class="nt">model</span><span class="p">:</span><span class="w"> </span><span class="p p-Indicator">[</span><span class="nv">Optional configuration of a different model</span><span class="p p-Indicator">,</span>
  528. <span class="w"> </span><span class="nv">if not configured the same model as the main agent model will be used.</span>
  529. <span class="w"> </span><span class="nv">This has effect only for the LM Summarizer functionality.</span><span class="p p-Indicator">]</span>
  530. <span class="w"> </span><span class="nt">model_name</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Name of the model to use</span>
  531. <span class="w"> </span><span class="nt">per_instance_cost_limit</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Cost limit for every instance (task)</span>
  532. <span class="w"> </span><span class="nt">total_cost_limit</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Total cost limit for summarizer only</span>
  533. <span class="w"> </span><span class="nt">temperature</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Sampling temperature</span>
  534. <span class="w"> </span><span class="nt">top_p</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Sampling top-p</span>
  535. <span class="w"> </span><span class="nt">host_url</span><span class="p">:</span><span class="w"> </span><span class="l l-Scalar l-Scalar-Plain">Host URL when using Ollama model</span>
  536. </code></pre></div>
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