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title: Why I Needed Durable Execution to Read a Toy Manual
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# Why I Needed Durable Execution to Read a Toy Manual

**[Temporal](https://daily.dev/sources/temporal)** · 12 min read · 0 upvotes · 0 comments

## Summary

A developer built a Japanese toy manual translation pipeline using Temporal workflow orchestration to solve the real-world complexity of coordinating OCR, translation, AI cleanup, and static site generation. The pipeline uses Google Document AI for parallel OCR across all PDF pages simultaneously, Google Translate API with automatic retries, Gemini for context-aware LLM cleanup, and Pydantic for schema validation of LLM outputs. Temporal's durable execution model means if any step fails mid-pipeline, it resumes from that point rather than restarting entirely. The full pipeline processes a 20-page manual in ~50 seconds for about 43 cents. The resulting static site is version-controlled JSON/HTML served from a CDN, allowing community members to submit translation corrections via pull requests.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.youtube.com/watch?v=C_fE8T-DwiU>

## Similar posts on daily.dev

- [Why I needed Durable Execution to read a toy manual](https://daily.dev/posts/why-i-needed-durable-execution-to-read-a-toy-manual-zio5kepf6) · Temporal · 0 upvotes · 0 comments

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#workflow-orchestration](https://daily.dev/tags/workflow-orchestration)

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