Initial commit: LangChain evolution tutorial deck (132 slides)

- Cover, TOC, 5 dividers, 3 recap slides
- 5 sections (chains, langgraph, deepagents, openswe, ecosystem)
- design-system.js with theme tokens + 9 helper functions
- research/: timeline + sources + per-tech notes
- final-compile.js + merge.js for rebuild pipeline
- output/: langchain-evolution.pptx (2.3 MB) + langchain-evolution.pdf (1.1 MB) + 7 sample previews

slides/section1-chains/slide-22.js

@@ -0,0 +1,58 @@
+// Slide 22: Long-term memory -- InMemoryStore + namespace
+// Code slide: cross-thread memory, semantic search over stored facts.
+
+const ds = require('./design-system');
+
+function createSlide(pres, theme) {
+  const slide = pres.addSlide();
+  ds.helpers.slideBase(slide, pres, theme);
+
+  ds.helpers.addHeader(slide, pres, theme, {
+    eyebrow: 'STAGE 1: CHAINS',
+    section: 'Memory',
+    title: 'Долгосрочная память: store + namespace',
+    sectionNumber: 1,
+  });
+
+  ds.helpers.addCodeBlock(slide, pres, theme, {
+    x: 0.5, y: 1.5, w: 9.0, h: 3.25,
+    language: 'python',
+    filePath: 'examples/memory_long.py',
+    code: [
+      'from langgraph.store.memory import InMemoryStore',
+      'from langchain.agents import create_agent',
+      'from langchain.embeddings import init_embeddings',
+      '',
+      '# Store может быть in-memory (dev) или Postgres (prod)',
+      'store = InMemoryStore(',
+      '    index={"embed": init_embeddings("openai:text-embedding-3-small"),',
+      '           "dims": 1536},',
+      ')',
+      '',
+      'agent = create_agent(',
+      '    model="openai:gpt-4.1-mini",',
+      '    tools=[...],',
+      '    store=store,',
+      ')',
+      '',
+      '# Namespace = ("user-id", "facts") -- разделение по пользователям',
+      'ns = ("user-42", "facts")',
+      'store.put(ns, "pref-1", {"text": "User prefers concise answers."})',
+      '',
+      '# В новой сессии store.search(ns, query="preferences") вернёт факты',
+    ].join('\n'),
+  });
+
+  ds.helpers.addCallout(slide, pres, theme, {
+    x: 0.5, y: 4.85, w: 9.0, h: 0.3,
+    kind: 'info',
+    text: 'Long-term memory переживает thread. Идеальна для user preferences, summary прошлых сессий, learned facts.',
+  });
+
+  ds.helpers.addSourceLine(slide, pres, theme, {
+    source: 'docs.langchain.com/oss/python/langgraph/memory',
+  });
+  ds.helpers.addPageNumber(slide, pres, theme, 22);
+}
+
+module.exports = { createSlide };