75601988c2
- 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
54 lines
1.9 KiB
JavaScript
54 lines
1.9 KiB
JavaScript
// Slide 07: Streaming -- .stream() yields chunks progressively
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// Code slide: how to consume the model output as a stream.
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const ds = require('./design-system');
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function createSlide(pres, theme) {
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const slide = pres.addSlide();
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ds.helpers.slideBase(slide, pres, theme);
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ds.helpers.addHeader(slide, pres, theme, {
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eyebrow: 'STAGE 1: CHAINS',
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section: 'Streaming',
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title: 'Потоковый вывод -- token за токеном',
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sectionNumber: 1,
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});
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ds.helpers.addCodeBlock(slide, pres, theme, {
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x: 0.5, y: 1.5, w: 9.0, h: 3.25,
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language: 'python',
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filePath: 'examples/streaming.py',
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code: [
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'from langchain.chat_models import init_chat_model',
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'',
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'model = init_chat_model("openai:gpt-4.1-mini")',
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'',
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'# .stream() -> итератор по AIMessageChunk',
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'for chunk in model.stream("Write a haiku about Python"):',
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' # У каждого chunk-а есть .content (текст) и .response_metadata',
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' print(chunk.content, end="", flush=True)',
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'',
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'print() # перевод строки после потока',
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'',
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'# Async-вариант: model.astream() -- то же самое в async-контексте',
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'import asyncio',
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'',
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'async def main():',
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' async for chunk in model.astream("Write a haiku about async"):',
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' print(chunk.content, end="", flush=True)',
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].join('\n'),
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});
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ds.helpers.addCallout(slide, pres, theme, {
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x: 0.5, y: 4.85, w: 9.0, h: 0.3,
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kind: 'success',
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text: 'AIMessageChunk можно складывать через оператор + -- для буферизации и метрик.',
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});
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ds.helpers.addSourceLine(slide, pres, theme, {
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source: 'python.langchain.com/docs/how_to/streaming/',
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});
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ds.helpers.addPageNumber(slide, pres, theme, 7);
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}
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module.exports = { createSlide }; |