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<h1 id="future-roadmap-for-cortexgraph">Future Roadmap for CortexGraph<a class="headerlink" href="#future-roadmap-for-cortexgraph" title="Permanent link">¶</a></h1>
<p>This document outlines potential future improvements and implementation approaches for CortexGraph.</p>
<h2 id="1-spaced-repetition">1. Spaced Repetition<a class="headerlink" href="#1-spaced-repetition" title="Permanent link">¶</a></h2>
<p><strong>What it is:</strong> A learning technique where review intervals increase exponentially (e.g., SuperMemo, Anki algorithms).</p>
<p><strong>Current State in CortexGraph:</strong>
- You have <code>touch_memory()</code> which reinforces memories
- Decay algorithm reduces scores over time
- But there's no <strong>proactive suggestion</strong> of when to review</p>
<p><strong>Potential Implementation:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-0-1" name="__codelineno-0-1" href="#__codelineno-0-1"></a><span class="c1"># Calculate optimal review time based on current strength</span>
<a id="__codelineno-0-2" name="__codelineno-0-2" href="#__codelineno-0-2"></a><span class="n">next_review</span> <span class="o">=</span> <span class="n">calculate_next_review</span><span class="p">(</span><span class="n">memory</span><span class="p">)</span>
<a id="__codelineno-0-3" name="__codelineno-0-3" href="#__codelineno-0-3"></a> <span class="o">=</span> <span class="n">current_time</span> <span class="o">+</span> <span class="p">(</span><span class="n">strength</span> <span class="o">*</span> <span class="n">base_interval</span> <span class="o">*</span> <span class="p">(</span><span class="n">use_count</span> <span class="o">^</span> <span class="n">β</span><span class="p">))</span>
<a id="__codelineno-0-4" name="__codelineno-0-4" href="#__codelineno-0-4"></a>
<a id="__codelineno-0-5" name="__codelineno-0-5" href="#__codelineno-0-5"></a><span class="c1"># SM-2 inspired spacing</span>
<a id="__codelineno-0-6" name="__codelineno-0-6" href="#__codelineno-0-6"></a><span class="n">intervals</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span> <span class="n">day</span><span class="p">,</span> <span class="mi">3</span> <span class="n">days</span><span class="p">,</span> <span class="mi">7</span> <span class="n">days</span><span class="p">,</span> <span class="mi">14</span> <span class="n">days</span><span class="p">,</span> <span class="mi">30</span> <span class="n">days</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span>
</code></pre></div>
<p><strong>Features to add:</strong>
1. <strong>Review scheduling</strong> - Track <code>next_review_at</code> timestamp
2. <strong>Review queue tool</strong> - <code>get_review_queue()</code> returns memories due for review
3. <strong>Review outcome tracking</strong> - Easy/medium/hard adjusts next interval
4. <strong>Adaptive intervals</strong> - Learn from user's actual recall patterns</p>
<p><strong>Benefit:</strong> Memories you want to keep get reinforced just before they'd decay too much. More efficient than random touching.</p>
<hr />
<h2 id="2-adaptive-decay-parameters">2. Adaptive Decay Parameters<a class="headerlink" href="#2-adaptive-decay-parameters" title="Permanent link">¶</a></h2>
<p><strong>The Problem:</strong> Current λ (decay rate) and β (use weight) are fixed. But different memory types should decay differently:
- Preferences: slow decay
- Project context: medium decay
- Random facts: fast decay</p>
<p><strong>Approaches:</strong></p>
<h3 id="a-category-based-adaptation">A. Category-Based Adaptation<a class="headerlink" href="#a-category-based-adaptation" title="Permanent link">¶</a></h3>
<div class="highlight"><pre><span></span><code><a id="__codelineno-1-1" name="__codelineno-1-1" href="#__codelineno-1-1"></a><span class="n">DECAY_PROFILES</span> <span class="o">=</span> <span class="p">{</span>
<a id="__codelineno-1-2" name="__codelineno-1-2" href="#__codelineno-1-2"></a> <span class="s2">"preference"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"lambda"</span><span class="p">:</span> <span class="mf">5.7e-7</span><span class="p">,</span> <span class="s2">"beta"</span><span class="p">:</span> <span class="mf">0.3</span><span class="p">},</span> <span class="c1"># 14-day half-life</span>
<a id="__codelineno-1-3" name="__codelineno-1-3" href="#__codelineno-1-3"></a> <span class="s2">"decision"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"lambda"</span><span class="p">:</span> <span class="mf">1.15e-6</span><span class="p">,</span> <span class="s2">"beta"</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">},</span> <span class="c1"># 7-day half-life</span>
<a id="__codelineno-1-4" name="__codelineno-1-4" href="#__codelineno-1-4"></a> <span class="s2">"context"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"lambda"</span><span class="p">:</span> <span class="mf">2.67e-6</span><span class="p">,</span> <span class="s2">"beta"</span><span class="p">:</span> <span class="mf">0.6</span><span class="p">},</span> <span class="c1"># 3-day half-life (default)</span>
<a id="__codelineno-1-5" name="__codelineno-1-5" href="#__codelineno-1-5"></a> <span class="s2">"fact"</span><span class="p">:</span> <span class="p">{</span><span class="s2">"lambda"</span><span class="p">:</span> <span class="mf">8.02e-6</span><span class="p">,</span> <span class="s2">"beta"</span><span class="p">:</span> <span class="mf">0.8</span><span class="p">},</span> <span class="c1"># 1-day half-life</span>
<a id="__codelineno-1-6" name="__codelineno-1-6" href="#__codelineno-1-6"></a><span class="p">}</span>
</code></pre></div>
<p>Auto-detect category from tags or content analysis.</p>
<h3 id="b-usage-pattern-learning">B. Usage-Pattern Learning<a class="headerlink" href="#b-usage-pattern-learning" title="Permanent link">¶</a></h3>
<p>Track actual usage patterns and adjust:</p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-2-1" name="__codelineno-2-1" href="#__codelineno-2-1"></a><span class="k">if</span> <span class="n">memory</span><span class="o">.</span><span class="n">use_count</span> <span class="o">></span> <span class="mi">10</span> <span class="ow">and</span> <span class="n">time_since_last_use</span> <span class="o"><</span> <span class="mi">1</span><span class="n">_day</span><span class="p">:</span>
<a id="__codelineno-2-2" name="__codelineno-2-2" href="#__codelineno-2-2"></a> <span class="c1"># Frequently accessed → slow decay</span>
<a id="__codelineno-2-3" name="__codelineno-2-3" href="#__codelineno-2-3"></a> <span class="n">memory</span><span class="o">.</span><span class="n">custom_lambda</span> <span class="o">=</span> <span class="n">memory</span><span class="o">.</span><span class="n">custom_lambda</span> <span class="o">*</span> <span class="mf">0.8</span>
<a id="__codelineno-2-4" name="__codelineno-2-4" href="#__codelineno-2-4"></a><span class="k">elif</span> <span class="n">memory</span><span class="o">.</span><span class="n">use_count</span> <span class="o"><</span> <span class="mi">3</span> <span class="ow">and</span> <span class="n">time_since_last_use</span> <span class="o">></span> <span class="mi">7</span><span class="n">_days</span><span class="p">:</span>
<a id="__codelineno-2-5" name="__codelineno-2-5" href="#__codelineno-2-5"></a> <span class="c1"># Rarely accessed → fast decay</span>
<a id="__codelineno-2-6" name="__codelineno-2-6" href="#__codelineno-2-6"></a> <span class="n">memory</span><span class="o">.</span><span class="n">custom_lambda</span> <span class="o">=</span> <span class="n">memory</span><span class="o">.</span><span class="n">custom_lambda</span> <span class="o">*</span> <span class="mf">1.2</span>
</code></pre></div>
<h3 id="c-reinforcement-learning">C. Reinforcement Learning<a class="headerlink" href="#c-reinforcement-learning" title="Permanent link">¶</a></h3>
<ul>
<li>Track which memories get promoted vs forgotten</li>
<li>Learn optimal parameters per memory type</li>
<li>Requires more data but most powerful</li>
</ul>
<p><strong>Recommendation:</strong> Start with <strong>Category-Based</strong> (simple, immediate benefit), then add <strong>Usage-Pattern Learning</strong> (moderate complexity).</p>
<hr />
<h2 id="3-clustering-consolidation-llm-vs-algorithmic">3. Clustering & Consolidation: LLM vs Algorithmic?<a class="headerlink" href="#3-clustering-consolidation-llm-vs-algorithmic" title="Permanent link">¶</a></h2>
<p><strong>Current clustering (algorithmic):</strong>
- ✅ Embeddings-based similarity (cosine distance)
- ✅ Duplicate detection (high threshold like 0.88+)
- ✅ Cluster formation (medium threshold like 0.78-0.83)</p>
<p><strong>Consolidation Options:</strong></p>
<h3 id="option-a-pure-algorithmic-no-llm">Option A: Pure Algorithmic (No LLM)<a class="headerlink" href="#option-a-pure-algorithmic-no-llm" title="Permanent link">¶</a></h3>
<div class="highlight"><pre><span></span><code><a id="__codelineno-3-1" name="__codelineno-3-1" href="#__codelineno-3-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">consolidate_algorithmic</span><span class="p">(</span><span class="n">cluster</span><span class="p">):</span>
<a id="__codelineno-3-2" name="__codelineno-3-2" href="#__codelineno-3-2"></a> <span class="k">if</span> <span class="n">similarity</span> <span class="o">></span> <span class="mf">0.95</span><span class="p">:</span>
<a id="__codelineno-3-3" name="__codelineno-3-3" href="#__codelineno-3-3"></a> <span class="c1"># Near-duplicates: keep newer, delete older</span>
<a id="__codelineno-3-4" name="__codelineno-3-4" href="#__codelineno-3-4"></a> <span class="k">return</span> <span class="n">keep_newest</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
<a id="__codelineno-3-5" name="__codelineno-3-5" href="#__codelineno-3-5"></a>
<a id="__codelineno-3-6" name="__codelineno-3-6" href="#__codelineno-3-6"></a> <span class="k">if</span> <span class="n">similarity</span> <span class="o">></span> <span class="mf">0.85</span><span class="p">:</span>
<a id="__codelineno-3-7" name="__codelineno-3-7" href="#__codelineno-3-7"></a> <span class="c1"># High overlap: merge tags, combine entities</span>
<a id="__codelineno-3-8" name="__codelineno-3-8" href="#__codelineno-3-8"></a> <span class="k">return</span> <span class="n">merge_metadata</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
<a id="__codelineno-3-9" name="__codelineno-3-9" href="#__codelineno-3-9"></a>
<a id="__codelineno-3-10" name="__codelineno-3-10" href="#__codelineno-3-10"></a> <span class="k">if</span> <span class="n">similarity</span> <span class="o">></span> <span class="mf">0.75</span><span class="p">:</span>
<a id="__codelineno-3-11" name="__codelineno-3-11" href="#__codelineno-3-11"></a> <span class="c1"># Related: just create relations, don't merge</span>
<a id="__codelineno-3-12" name="__codelineno-3-12" href="#__codelineno-3-12"></a> <span class="k">return</span> <span class="n">link_memories</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
</code></pre></div>
<p><strong>Pros:</strong> Fast, deterministic, no external dependencies
<strong>Cons:</strong> Can't understand semantic nuance, might lose information</p>
<h3 id="option-b-llm-assisted-hybrid">Option B: LLM-Assisted (Hybrid)<a class="headerlink" href="#option-b-llm-assisted-hybrid" title="Permanent link">¶</a></h3>
<div class="highlight"><pre><span></span><code><a id="__codelineno-4-1" name="__codelineno-4-1" href="#__codelineno-4-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">consolidate_with_llm</span><span class="p">(</span><span class="n">cluster</span><span class="p">):</span>
<a id="__codelineno-4-2" name="__codelineno-4-2" href="#__codelineno-4-2"></a> <span class="c1"># 1. Algorithmic pre-filter</span>
<a id="__codelineno-4-3" name="__codelineno-4-3" href="#__codelineno-4-3"></a> <span class="k">if</span> <span class="n">similarity</span> <span class="o"><</span> <span class="mf">0.75</span><span class="p">:</span>
<a id="__codelineno-4-4" name="__codelineno-4-4" href="#__codelineno-4-4"></a> <span class="k">return</span> <span class="s2">"no_action"</span>
<a id="__codelineno-4-5" name="__codelineno-4-5" href="#__codelineno-4-5"></a>
<a id="__codelineno-4-6" name="__codelineno-4-6" href="#__codelineno-4-6"></a> <span class="c1"># 2. LLM decides merge strategy</span>
<a id="__codelineno-4-7" name="__codelineno-4-7" href="#__codelineno-4-7"></a> <span class="n">prompt</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">"""</span>
<a id="__codelineno-4-8" name="__codelineno-4-8" href="#__codelineno-4-8"></a><span class="s2"> These memories are similar. Should they be:</span>
<a id="__codelineno-4-9" name="__codelineno-4-9" href="#__codelineno-4-9"></a><span class="s2"> 1. Merged (duplicates/redundant)</span>
<a id="__codelineno-4-10" name="__codelineno-4-10" href="#__codelineno-4-10"></a><span class="s2"> 2. Linked (related but distinct)</span>
<a id="__codelineno-4-11" name="__codelineno-4-11" href="#__codelineno-4-11"></a><span class="s2"> 3. Kept separate</span>
<a id="__codelineno-4-12" name="__codelineno-4-12" href="#__codelineno-4-12"></a>
<a id="__codelineno-4-13" name="__codelineno-4-13" href="#__codelineno-4-13"></a><span class="s2"> Memory 1: </span><span class="si">{</span><span class="n">mem1</span><span class="o">.</span><span class="n">content</span><span class="si">}</span>
<a id="__codelineno-4-14" name="__codelineno-4-14" href="#__codelineno-4-14"></a><span class="s2"> Memory 2: </span><span class="si">{</span><span class="n">mem2</span><span class="o">.</span><span class="n">content</span><span class="si">}</span>
<a id="__codelineno-4-15" name="__codelineno-4-15" href="#__codelineno-4-15"></a><span class="s2"> """</span>
<a id="__codelineno-4-16" name="__codelineno-4-16" href="#__codelineno-4-16"></a>
<a id="__codelineno-4-17" name="__codelineno-4-17" href="#__codelineno-4-17"></a> <span class="n">decision</span> <span class="o">=</span> <span class="n">llm_call</span><span class="p">(</span><span class="n">prompt</span><span class="p">)</span>
<a id="__codelineno-4-18" name="__codelineno-4-18" href="#__codelineno-4-18"></a>
<a id="__codelineno-4-19" name="__codelineno-4-19" href="#__codelineno-4-19"></a> <span class="c1"># 3. If merge, LLM writes consolidated version</span>
<a id="__codelineno-4-20" name="__codelineno-4-20" href="#__codelineno-4-20"></a> <span class="k">if</span> <span class="n">decision</span> <span class="o">==</span> <span class="s2">"merge"</span><span class="p">:</span>
<a id="__codelineno-4-21" name="__codelineno-4-21" href="#__codelineno-4-21"></a> <span class="n">merged_content</span> <span class="o">=</span> <span class="n">llm_call</span><span class="p">(</span><span class="sa">f</span><span class="s2">"Merge these: </span><span class="si">{</span><span class="n">memories</span><span class="si">}</span><span class="s2">"</span><span class="p">)</span>
<a id="__codelineno-4-22" name="__codelineno-4-22" href="#__codelineno-4-22"></a> <span class="k">return</span> <span class="n">create_consolidated_memory</span><span class="p">(</span><span class="n">merged_content</span><span class="p">)</span>
</code></pre></div>
<p><strong>Pros:</strong> Smart decisions, preserves semantic meaning
<strong>Cons:</strong> Slower, requires MCP client support, not deterministic</p>
<h3 id="option-c-algorithmic-with-human-review">Option C: Algorithmic with Human Review<a class="headerlink" href="#option-c-algorithmic-with-human-review" title="Permanent link">¶</a></h3>
<div class="highlight"><pre><span></span><code><a id="__codelineno-5-1" name="__codelineno-5-1" href="#__codelineno-5-1"></a><span class="k">def</span><span class="w"> </span><span class="nf">consolidate_interactive</span><span class="p">(</span><span class="n">cluster</span><span class="p">):</span>
<a id="__codelineno-5-2" name="__codelineno-5-2" href="#__codelineno-5-2"></a> <span class="c1"># Show side-by-side comparison</span>
<a id="__codelineno-5-3" name="__codelineno-5-3" href="#__codelineno-5-3"></a> <span class="n">preview</span> <span class="o">=</span> <span class="n">generate_merge_preview</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
<a id="__codelineno-5-4" name="__codelineno-5-4" href="#__codelineno-5-4"></a>
<a id="__codelineno-5-5" name="__codelineno-5-5" href="#__codelineno-5-5"></a> <span class="c1"># User approves/rejects/edits</span>
<a id="__codelineno-5-6" name="__codelineno-5-6" href="#__codelineno-5-6"></a> <span class="k">return</span> <span class="p">{</span>
<a id="__codelineno-5-7" name="__codelineno-5-7" href="#__codelineno-5-7"></a> <span class="s2">"action"</span><span class="p">:</span> <span class="s2">"preview"</span><span class="p">,</span>
<a id="__codelineno-5-8" name="__codelineno-5-8" href="#__codelineno-5-8"></a> <span class="s2">"original_memories"</span><span class="p">:</span> <span class="n">cluster</span><span class="p">,</span>
<a id="__codelineno-5-9" name="__codelineno-5-9" href="#__codelineno-5-9"></a> <span class="s2">"suggested_merge"</span><span class="p">:</span> <span class="n">algorithmic_merge</span><span class="p">(</span><span class="n">cluster</span><span class="p">),</span>
<a id="__codelineno-5-10" name="__codelineno-5-10" href="#__codelineno-5-10"></a> <span class="s2">"user_can_edit"</span><span class="p">:</span> <span class="kc">True</span>
<a id="__codelineno-5-11" name="__codelineno-5-11" href="#__codelineno-5-11"></a> <span class="p">}</span>
</code></pre></div>
<p><strong>Pros:</strong> User control, no LLM needed, no data loss
<strong>Cons:</strong> Manual work required</p>
<h3 id="recommendation"><strong>Recommendation:</strong><a class="headerlink" href="#recommendation" title="Permanent link">¶</a></h3>
<p>Start with <strong>Option C (Algorithmic + Human Review)</strong> because:
1. <strong>Safe</strong> - No automatic deletions, user confirms
2. <strong>Fast</strong> - No LLM calls needed
3. <strong>Flexible</strong> - User can edit merged content
4. <strong>MCP-friendly</strong> - Returns preview, client handles approval</p>
<p>Later, add <strong>Option B (LLM-assisted)</strong> as an opt-in feature for power users.</p>
<p><strong>Implementation:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-6-1" name="__codelineno-6-1" href="#__codelineno-6-1"></a><span class="nd">@mcp</span><span class="o">.</span><span class="n">tool</span><span class="p">()</span>
<a id="__codelineno-6-2" name="__codelineno-6-2" href="#__codelineno-6-2"></a><span class="k">def</span><span class="w"> </span><span class="nf">consolidate_memories</span><span class="p">(</span><span class="n">cluster_id</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">mode</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">"preview"</span><span class="p">):</span>
<a id="__codelineno-6-3" name="__codelineno-6-3" href="#__codelineno-6-3"></a> <span class="n">cluster</span> <span class="o">=</span> <span class="n">get_cluster</span><span class="p">(</span><span class="n">cluster_id</span><span class="p">)</span>
<a id="__codelineno-6-4" name="__codelineno-6-4" href="#__codelineno-6-4"></a>
<a id="__codelineno-6-5" name="__codelineno-6-5" href="#__codelineno-6-5"></a> <span class="k">if</span> <span class="n">mode</span> <span class="o">==</span> <span class="s2">"preview"</span><span class="p">:</span>
<a id="__codelineno-6-6" name="__codelineno-6-6" href="#__codelineno-6-6"></a> <span class="c1"># Algorithmic merge</span>
<a id="__codelineno-6-7" name="__codelineno-6-7" href="#__codelineno-6-7"></a> <span class="n">merged</span> <span class="o">=</span> <span class="p">{</span>
<a id="__codelineno-6-8" name="__codelineno-6-8" href="#__codelineno-6-8"></a> <span class="s2">"content"</span><span class="p">:</span> <span class="n">merge_content_smart</span><span class="p">(</span><span class="n">cluster</span><span class="p">),</span>
<a id="__codelineno-6-9" name="__codelineno-6-9" href="#__codelineno-6-9"></a> <span class="s2">"tags"</span><span class="p">:</span> <span class="n">union</span><span class="p">(</span><span class="n">tags</span><span class="p">),</span>
<a id="__codelineno-6-10" name="__codelineno-6-10" href="#__codelineno-6-10"></a> <span class="s2">"entities"</span><span class="p">:</span> <span class="n">union</span><span class="p">(</span><span class="n">entities</span><span class="p">),</span>
<a id="__codelineno-6-11" name="__codelineno-6-11" href="#__codelineno-6-11"></a> <span class="s2">"strength"</span><span class="p">:</span> <span class="nb">max</span><span class="p">(</span><span class="n">strengths</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.1</span><span class="p">,</span>
<a id="__codelineno-6-12" name="__codelineno-6-12" href="#__codelineno-6-12"></a> <span class="s2">"original_ids"</span><span class="p">:</span> <span class="p">[</span><span class="n">m</span><span class="o">.</span><span class="n">id</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">cluster</span><span class="p">]</span>
<a id="__codelineno-6-13" name="__codelineno-6-13" href="#__codelineno-6-13"></a> <span class="p">}</span>
<a id="__codelineno-6-14" name="__codelineno-6-14" href="#__codelineno-6-14"></a> <span class="k">return</span> <span class="p">{</span><span class="s2">"preview"</span><span class="p">:</span> <span class="n">merged</span><span class="p">,</span> <span class="s2">"action"</span><span class="p">:</span> <span class="s2">"awaiting_approval"</span><span class="p">}</span>
<a id="__codelineno-6-15" name="__codelineno-6-15" href="#__codelineno-6-15"></a>
<a id="__codelineno-6-16" name="__codelineno-6-16" href="#__codelineno-6-16"></a> <span class="k">if</span> <span class="n">mode</span> <span class="o">==</span> <span class="s2">"apply"</span><span class="p">:</span>
<a id="__codelineno-6-17" name="__codelineno-6-17" href="#__codelineno-6-17"></a> <span class="c1"># User approved, do the merge</span>
<a id="__codelineno-6-18" name="__codelineno-6-18" href="#__codelineno-6-18"></a> <span class="n">new_mem</span> <span class="o">=</span> <span class="n">create_memory</span><span class="p">(</span><span class="n">merged</span><span class="p">)</span>
<a id="__codelineno-6-19" name="__codelineno-6-19" href="#__codelineno-6-19"></a> <span class="k">for</span> <span class="n">old_mem</span> <span class="ow">in</span> <span class="n">cluster</span><span class="p">:</span>
<a id="__codelineno-6-20" name="__codelineno-6-20" href="#__codelineno-6-20"></a> <span class="n">mark_as_consolidated</span><span class="p">(</span><span class="n">old_mem</span><span class="p">,</span> <span class="n">new_mem</span><span class="o">.</span><span class="n">id</span><span class="p">)</span>
<a id="__codelineno-6-21" name="__codelineno-6-21" href="#__codelineno-6-21"></a> <span class="k">return</span> <span class="p">{</span><span class="s2">"success"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"new_id"</span><span class="p">:</span> <span class="n">new_mem</span><span class="o">.</span><span class="n">id</span><span class="p">}</span>
</code></pre></div>
<hr />
<h2 id="4-performance-improvements">4. Performance Improvements<a class="headerlink" href="#4-performance-improvements" title="Permanent link">¶</a></h2>
<p><strong>Current Bottlenecks:</strong></p>
<h3 id="a-in-memory-search-jsonl-files">A. In-Memory Search (JSONL files)<a class="headerlink" href="#a-in-memory-search-jsonl-files" title="Permanent link">¶</a></h3>
<ul>
<li>Every search reads entire file</li>
<li>O(n) for every query</li>
<li>Gets slow at 10K+ memories</li>
</ul>
<p><strong>Solution:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-7-1" name="__codelineno-7-1" href="#__codelineno-7-1"></a><span class="c1"># Option 1: Index by tags/entities</span>
<a id="__codelineno-7-2" name="__codelineno-7-2" href="#__codelineno-7-2"></a><span class="n">tag_index</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"typescript"</span><span class="p">:</span> <span class="p">[</span><span class="n">mem_id1</span><span class="p">,</span> <span class="n">mem_id2</span><span class="p">,</span> <span class="o">...</span><span class="p">]}</span>
<a id="__codelineno-7-3" name="__codelineno-7-3" href="#__codelineno-7-3"></a><span class="n">entity_index</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"Claude"</span><span class="p">:</span> <span class="p">[</span><span class="n">mem_id3</span><span class="p">,</span> <span class="n">mem_id4</span><span class="p">,</span> <span class="o">...</span><span class="p">]}</span>
<a id="__codelineno-7-4" name="__codelineno-7-4" href="#__codelineno-7-4"></a>
<a id="__codelineno-7-5" name="__codelineno-7-5" href="#__codelineno-7-5"></a><span class="c1"># Option 2: Bloom filter for quick "not found"</span>
<a id="__codelineno-7-6" name="__codelineno-7-6" href="#__codelineno-7-6"></a><span class="k">if</span> <span class="ow">not</span> <span class="n">bloom_filter</span><span class="o">.</span><span class="n">might_contain</span><span class="p">(</span><span class="n">query</span><span class="p">):</span>
<a id="__codelineno-7-7" name="__codelineno-7-7" href="#__codelineno-7-7"></a> <span class="k">return</span> <span class="p">[]</span> <span class="c1"># Fast path</span>
<a id="__codelineno-7-8" name="__codelineno-7-8" href="#__codelineno-7-8"></a>
<a id="__codelineno-7-9" name="__codelineno-7-9" href="#__codelineno-7-9"></a><span class="c1"># Option 3: Incremental compaction</span>
<a id="__codelineno-7-10" name="__codelineno-7-10" href="#__codelineno-7-10"></a><span class="n">compact_if</span><span class="p">(</span><span class="n">num_tombstones</span> <span class="o">></span> <span class="mi">1000</span> <span class="ow">or</span> <span class="n">file_size</span> <span class="o">></span> <span class="mi">10</span><span class="n">MB</span><span class="p">)</span>
</code></pre></div>
<h3 id="b-embedding-generation">B. Embedding Generation<a class="headerlink" href="#b-embedding-generation" title="Permanent link">¶</a></h3>
<ul>
<li>Slow for large batches</li>
<li>Re-computes for duplicates</li>
</ul>
<p><strong>Solution:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-8-1" name="__codelineno-8-1" href="#__codelineno-8-1"></a><span class="c1"># Cache embeddings by content hash</span>
<a id="__codelineno-8-2" name="__codelineno-8-2" href="#__codelineno-8-2"></a><span class="n">embedding_cache</span><span class="p">[</span><span class="nb">hash</span><span class="p">(</span><span class="n">content</span><span class="p">)]</span> <span class="o">=</span> <span class="n">embedding</span>
</code></pre></div>
<h3 id="c-decay-calculation">C. Decay Calculation<a class="headerlink" href="#c-decay-calculation" title="Permanent link">¶</a></h3>
<ul>
<li>Calculates score for every memory on every search</li>
</ul>
<p><strong>Solution:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-9-1" name="__codelineno-9-1" href="#__codelineno-9-1"></a><span class="c1"># Pre-compute scores periodically</span>
<a id="__codelineno-9-2" name="__codelineno-9-2" href="#__codelineno-9-2"></a><span class="n">background_task</span><span class="p">:</span>
<a id="__codelineno-9-3" name="__codelineno-9-3" href="#__codelineno-9-3"></a> <span class="n">update_all_scores_cached</span><span class="p">()</span>
<a id="__codelineno-9-4" name="__codelineno-9-4" href="#__codelineno-9-4"></a> <span class="n">sleep</span><span class="p">(</span><span class="mi">60</span><span class="p">)</span> <span class="c1"># Refresh every minute</span>
<a id="__codelineno-9-5" name="__codelineno-9-5" href="#__codelineno-9-5"></a>
<a id="__codelineno-9-6" name="__codelineno-9-6" href="#__codelineno-9-6"></a><span class="c1"># Search uses cached scores</span>
<a id="__codelineno-9-7" name="__codelineno-9-7" href="#__codelineno-9-7"></a><span class="k">def</span><span class="w"> </span><span class="nf">search</span><span class="p">(</span><span class="n">query</span><span class="p">):</span>
<a id="__codelineno-9-8" name="__codelineno-9-8" href="#__codelineno-9-8"></a> <span class="n">candidates</span> <span class="o">=</span> <span class="n">filter_by_tags</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
<a id="__codelineno-9-9" name="__codelineno-9-9" href="#__codelineno-9-9"></a> <span class="c1"># Use pre-computed scores, don't recalc</span>
<a id="__codelineno-9-10" name="__codelineno-9-10" href="#__codelineno-9-10"></a> <span class="k">return</span> <span class="n">sort_by</span><span class="p">(</span><span class="n">candidates</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">m</span><span class="p">:</span> <span class="n">m</span><span class="o">.</span><span class="n">cached_score</span><span class="p">)</span>
</code></pre></div>
<p><strong>Benchmarking Plan:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-10-1" name="__codelineno-10-1" href="#__codelineno-10-1"></a><span class="c1"># tests/performance/test_benchmarks.py</span>
<a id="__codelineno-10-2" name="__codelineno-10-2" href="#__codelineno-10-2"></a><span class="k">def</span><span class="w"> </span><span class="nf">benchmark_search</span><span class="p">():</span>
<a id="__codelineno-10-3" name="__codelineno-10-3" href="#__codelineno-10-3"></a> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">1000</span><span class="p">,</span> <span class="mi">10000</span><span class="p">,</span> <span class="mi">100000</span><span class="p">]:</span>
<a id="__codelineno-10-4" name="__codelineno-10-4" href="#__codelineno-10-4"></a> <span class="n">memories</span> <span class="o">=</span> <span class="n">generate_test_memories</span><span class="p">(</span><span class="n">n</span><span class="p">)</span>
<a id="__codelineno-10-5" name="__codelineno-10-5" href="#__codelineno-10-5"></a> <span class="n">start</span> <span class="o">=</span> <span class="n">time</span><span class="p">()</span>
<a id="__codelineno-10-6" name="__codelineno-10-6" href="#__codelineno-10-6"></a> <span class="n">search</span><span class="p">(</span><span class="n">query</span><span class="p">)</span>
<a id="__codelineno-10-7" name="__codelineno-10-7" href="#__codelineno-10-7"></a> <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">"n=</span><span class="si">{</span><span class="n">n</span><span class="si">}</span><span class="s2">: </span><span class="si">{</span><span class="n">time</span><span class="p">()</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="n">start</span><span class="si">}</span><span class="s2">s"</span><span class="p">)</span>
<a id="__codelineno-10-8" name="__codelineno-10-8" href="#__codelineno-10-8"></a>
<a id="__codelineno-10-9" name="__codelineno-10-9" href="#__codelineno-10-9"></a><span class="k">def</span><span class="w"> </span><span class="nf">benchmark_decay</span><span class="p">():</span>
<a id="__codelineno-10-10" name="__codelineno-10-10" href="#__codelineno-10-10"></a> <span class="c1"># Measure score calculation speed</span>
<a id="__codelineno-10-11" name="__codelineno-10-11" href="#__codelineno-10-11"></a>
<a id="__codelineno-10-12" name="__codelineno-10-12" href="#__codelineno-10-12"></a><span class="k">def</span><span class="w"> </span><span class="nf">benchmark_compaction</span><span class="p">():</span>
<a id="__codelineno-10-13" name="__codelineno-10-13" href="#__codelineno-10-13"></a> <span class="c1"># Measure JSONL rewrite performance</span>
</code></pre></div>
<hr />
<h2 id="5-other-improvements">5. Other Improvements<a class="headerlink" href="#5-other-improvements" title="Permanent link">¶</a></h2>
<h3 id="a-testing-coverage">A. Testing Coverage<a class="headerlink" href="#a-testing-coverage" title="Permanent link">¶</a></h3>
<p>Current gaps (likely):
- Edge cases in decay models
- LTM index updates
- Git backup failures
- Concurrent access</p>
<p><strong>Plan:</strong></p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-11-1" name="__codelineno-11-1" href="#__codelineno-11-1"></a><span class="c1"># Generate coverage report</span>
<a id="__codelineno-11-2" name="__codelineno-11-2" href="#__codelineno-11-2"></a>pytest<span class="w"> </span>--cov<span class="o">=</span>cortexgraph<span class="w"> </span>--cov-report<span class="o">=</span>html
<a id="__codelineno-11-3" name="__codelineno-11-3" href="#__codelineno-11-3"></a>open<span class="w"> </span>htmlcov/index.html
<a id="__codelineno-11-4" name="__codelineno-11-4" href="#__codelineno-11-4"></a>
<a id="__codelineno-11-5" name="__codelineno-11-5" href="#__codelineno-11-5"></a><span class="c1"># Focus on <80% coverage modules</span>
<a id="__codelineno-11-6" name="__codelineno-11-6" href="#__codelineno-11-6"></a><span class="c1"># Add integration tests for CLI tools</span>
</code></pre></div>
<h3 id="b-production-hardening">B. Production Hardening<a class="headerlink" href="#b-production-hardening" title="Permanent link">¶</a></h3>
<ul>
<li>Error handling for corrupted JSONL</li>
<li>Graceful degradation if embeddings fail</li>
<li>File locking for concurrent access</li>
<li>Backup before destructive operations</li>
</ul>
<h3 id="c-github-release-v100">C. GitHub Release (v1.0.0)<a class="headerlink" href="#c-github-release-v100" title="Permanent link">¶</a></h3>
<ul>
<li>Tag the current commit</li>
<li>Generate changelog</li>
<li>Build wheel</li>
<li>Publish to PyPI (optional)</li>
</ul>
<h3 id="d-more-examples">D. More Examples<a class="headerlink" href="#d-more-examples" title="Permanent link">¶</a></h3>
<ul>
<li>Claude prompt templates for auto-save</li>
<li>Different use cases (personal assistant, dev env, research)</li>
<li>Integration with other tools (Raycast, Alfred, etc.)</li>
</ul>
<hr />
<h2 id="completed-uv-tool-install-migration">Completed: UV Tool Install Migration ✅<a class="headerlink" href="#completed-uv-tool-install-migration" title="Permanent link">¶</a></h2>
<h3 id="changes-made">Changes Made<a class="headerlink" href="#changes-made" title="Permanent link">¶</a></h3>
<p><strong>Installation Simplified:</strong></p>
<p>Before:
<div class="highlight"><pre><span></span><code><a id="__codelineno-12-1" name="__codelineno-12-1" href="#__codelineno-12-1"></a>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/simplemindedbot/cortexgraph.git
<a id="__codelineno-12-2" name="__codelineno-12-2" href="#__codelineno-12-2"></a><span class="nb">cd</span><span class="w"> </span>cortexgraph
<a id="__codelineno-12-3" name="__codelineno-12-3" href="#__codelineno-12-3"></a>uv<span class="w"> </span>pip<span class="w"> </span>install<span class="w"> </span>-e<span class="w"> </span>.
<a id="__codelineno-12-4" name="__codelineno-12-4" href="#__codelineno-12-4"></a><span class="c1"># Complex MCP config with paths and PYTHONPATH</span>
</code></pre></div></p>
<p>After:
<div class="highlight"><pre><span></span><code><a id="__codelineno-13-1" name="__codelineno-13-1" href="#__codelineno-13-1"></a>uv<span class="w"> </span>tool<span class="w"> </span>install<span class="w"> </span>git+https://github.com/simplemindedbot/cortexgraph.git
<a id="__codelineno-13-2" name="__codelineno-13-2" href="#__codelineno-13-2"></a><span class="c1"># Simple MCP config: {"command": "cortexgraph"}</span>
</code></pre></div></p>
<h3 id="mcp-config-updates">MCP Config Updates<a class="headerlink" href="#mcp-config-updates" title="Permanent link">¶</a></h3>
<p><strong>Before:</strong>
<div class="highlight"><pre><span></span><code><a id="__codelineno-14-1" name="__codelineno-14-1" href="#__codelineno-14-1"></a><span class="p">{</span>
<a id="__codelineno-14-2" name="__codelineno-14-2" href="#__codelineno-14-2"></a><span class="w"> </span><span class="nt">"mcpServers"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
<a id="__codelineno-14-3" name="__codelineno-14-3" href="#__codelineno-14-3"></a><span class="w"> </span><span class="nt">"cortexgraph"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
<a id="__codelineno-14-4" name="__codelineno-14-4" href="#__codelineno-14-4"></a><span class="w"> </span><span class="nt">"command"</span><span class="p">:</span><span class="w"> </span><span class="s2">"uv"</span><span class="p">,</span>
<a id="__codelineno-14-5" name="__codelineno-14-5" href="#__codelineno-14-5"></a><span class="w"> </span><span class="nt">"args"</span><span class="p">:</span><span class="w"> </span><span class="p">[</span><span class="s2">"--directory"</span><span class="p">,</span><span class="w"> </span><span class="s2">"/path/to/cortexgraph"</span><span class="p">,</span><span class="w"> </span><span class="s2">"run"</span><span class="p">,</span><span class="w"> </span><span class="s2">"cortexgraph"</span><span class="p">],</span>
<a id="__codelineno-14-6" name="__codelineno-14-6" href="#__codelineno-14-6"></a><span class="w"> </span><span class="nt">"env"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span><span class="nt">"PYTHONPATH"</span><span class="p">:</span><span class="w"> </span><span class="s2">"/path/to/cortexgraph/src"</span><span class="p">}</span>
<a id="__codelineno-14-7" name="__codelineno-14-7" href="#__codelineno-14-7"></a><span class="w"> </span><span class="p">}</span>
<a id="__codelineno-14-8" name="__codelineno-14-8" href="#__codelineno-14-8"></a><span class="w"> </span><span class="p">}</span>
<a id="__codelineno-14-9" name="__codelineno-14-9" href="#__codelineno-14-9"></a><span class="p">}</span>
</code></pre></div></p>
<p><strong>After:</strong>
<div class="highlight"><pre><span></span><code><a id="__codelineno-15-1" name="__codelineno-15-1" href="#__codelineno-15-1"></a><span class="p">{</span>
<a id="__codelineno-15-2" name="__codelineno-15-2" href="#__codelineno-15-2"></a><span class="w"> </span><span class="nt">"mcpServers"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
<a id="__codelineno-15-3" name="__codelineno-15-3" href="#__codelineno-15-3"></a><span class="w"> </span><span class="nt">"cortexgraph"</span><span class="p">:</span><span class="w"> </span><span class="p">{</span>
<a id="__codelineno-15-4" name="__codelineno-15-4" href="#__codelineno-15-4"></a><span class="w"> </span><span class="nt">"command"</span><span class="p">:</span><span class="w"> </span><span class="s2">"cortexgraph"</span>
<a id="__codelineno-15-5" name="__codelineno-15-5" href="#__codelineno-15-5"></a><span class="w"> </span><span class="p">}</span>
<a id="__codelineno-15-6" name="__codelineno-15-6" href="#__codelineno-15-6"></a><span class="w"> </span><span class="p">}</span>
<a id="__codelineno-15-7" name="__codelineno-15-7" href="#__codelineno-15-7"></a><span class="p">}</span>
</code></pre></div></p>
<h3 id="migration-guide-for-users">Migration Guide for Users<a class="headerlink" href="#migration-guide-for-users" title="Permanent link">¶</a></h3>
<p>For existing users switching from editable install:</p>
<div class="highlight"><pre><span></span><code><a id="__codelineno-16-1" name="__codelineno-16-1" href="#__codelineno-16-1"></a><span class="c1"># 1. Uninstall editable version</span>
<a id="__codelineno-16-2" name="__codelineno-16-2" href="#__codelineno-16-2"></a>uv<span class="w"> </span>pip<span class="w"> </span>uninstall<span class="w"> </span>cortexgraph
<a id="__codelineno-16-3" name="__codelineno-16-3" href="#__codelineno-16-3"></a>
<a id="__codelineno-16-4" name="__codelineno-16-4" href="#__codelineno-16-4"></a><span class="c1"># 2. Install as tool</span>
<a id="__codelineno-16-5" name="__codelineno-16-5" href="#__codelineno-16-5"></a>uv<span class="w"> </span>tool<span class="w"> </span>install<span class="w"> </span>git+https://github.com/simplemindedbot/cortexgraph.git
<a id="__codelineno-16-6" name="__codelineno-16-6" href="#__codelineno-16-6"></a>
<a id="__codelineno-16-7" name="__codelineno-16-7" href="#__codelineno-16-7"></a><span class="c1"># 3. Update Claude config to just: {"command": "cortexgraph"}</span>
<a id="__codelineno-16-8" name="__codelineno-16-8" href="#__codelineno-16-8"></a><span class="c1"># Remove the --directory, run, and PYTHONPATH settings</span>
</code></pre></div>
<p><strong>Your data is safe!</strong> This only changes how the command is installed. Your memories in <code>~/.config/cortexgraph/</code> are untouched.</p>
<hr />
<h2 id="completed-consolidation-tool">Completed: Consolidation Tool ✅<a class="headerlink" href="#completed-consolidation-tool" title="Permanent link">¶</a></h2>
<h3 id="implementation-summary">Implementation Summary<a class="headerlink" href="#implementation-summary" title="Permanent link">¶</a></h3>
<p><strong>Completed:</strong> Algorithmic consolidation with preview/apply modes</p>
<p><strong>Files Added:</strong>
- <code>src/cortexgraph/core/consolidation.py</code> - Core merging logic
- <code>tests/test_consolidation.py</code> - Comprehensive test suite (15 tests, 100% coverage)</p>
<p><strong>Features:</strong>
- Smart content merging (preserves unique information, detects duplicates)
- Tag and entity merging (union of all values)
- Strength calculation based on cluster cohesion
- Timestamp preservation (earliest created_at, latest last_used)
- Relation tracking (consolidated_from relations)
- Auto-detect mode (finds high-cohesion clusters automatically)
- Preview mode (dry-run to inspect before applying)</p>
<p><strong>Usage:</strong>
<div class="highlight"><pre><span></span><code><a id="__codelineno-17-1" name="__codelineno-17-1" href="#__codelineno-17-1"></a><span class="c1"># Auto-detect and preview</span>
<a id="__codelineno-17-2" name="__codelineno-17-2" href="#__codelineno-17-2"></a><span class="n">consolidate_memories</span><span class="p">(</span><span class="n">auto_detect</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"preview"</span><span class="p">,</span> <span class="n">cohesion_threshold</span><span class="o">=</span><span class="mf">0.75</span><span class="p">)</span>
<a id="__codelineno-17-3" name="__codelineno-17-3" href="#__codelineno-17-3"></a>
<a id="__codelineno-17-4" name="__codelineno-17-4" href="#__codelineno-17-4"></a><span class="c1"># Apply consolidation</span>
<a id="__codelineno-17-5" name="__codelineno-17-5" href="#__codelineno-17-5"></a><span class="n">consolidate_memories</span><span class="p">(</span><span class="n">auto_detect</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">"apply"</span><span class="p">,</span> <span class="n">cohesion_threshold</span><span class="o">=</span><span class="mf">0.80</span><span class="p">)</span>
</code></pre></div></p>
<p><strong>Test Results:</strong>
All 15 tests passing:
- <code>test_merge_tags</code>, <code>test_merge_entities</code>, <code>test_merge_metadata</code>
- <code>test_merge_content_duplicates</code>, <code>test_merge_content_distinct</code>
- <code>test_calculate_merged_strength</code>
- <code>test_generate_consolidation_preview</code>
- <code>test_execute_consolidation</code>
- <code>test_consolidation_preserves_timestamps</code></p>
<hr />
<h2 id="priority-order">Priority Order<a class="headerlink" href="#priority-order" title="Permanent link">¶</a></h2>
<ol>
<li>~~<strong>Consolidation Tool</strong> (1-2 days) - Implement algorithmic merge with preview~~ ✅ <strong>DONE</strong></li>
<li><strong>Spaced Repetition</strong> (2-3 days) - Add review queue and scheduling</li>
<li><strong>Adaptive Decay</strong> (3-4 days) - Category-based decay profiles</li>
<li><strong>Performance</strong> (1-2 days) - Benchmarking and optimization</li>
<li><strong>Production Hardening</strong> (ongoing) - Testing and error handling</li>
</ol>
</article>
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