I carried my stories From Python to Node and found Apple's hidden city of Metal
The article discusses the author's journey of creating a local AI model using Python and Node.js. It describes the development of a general-purpose AI experiment runner and the functionalities it offers. Additionally, it provides insights into the setup process and customization options available for users.
- ▪The author initially wrote weird fiction set in Portland and aimed to create an AI model that mimics their voice.
- ▪The project began with a Python notebook and evolved into a general-purpose AI experiment runner that can be set up quickly.
- ▪Users can customize the UI and modify the project files freely, allowing for a personalized experience.
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Story provenance
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/jahbini/pipeline-demo |
| Publication time | Tue, 19 May 2026 21:50:13 +0000 |
| Retrieval time | 2026-05-19T22:04:58.349Z |
| Last seen | 2026-05-19T22:04:58.349Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | YzPj4_55LGOR |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
pipeline-demo I wrote weird fiction set in Portland, Oregon. I wanted a local AI model that could write in my voice. I started with a Python notebook, and by the time I was done I'd accidentally built a general-purpose AI experiment runner. Here's a paragraph it generated: Right now, the sun is hanging low, and the treetops are weeping golden liquid into the crows' nests... That's not cherry-picked. The voice holds because of how retrieval works — keywords instead of embeddings... Clone, install, run — and in under a minute you'll see the shipped test pipeline execute end-to-end and print a friendly hand-off message telling you where to go next. This repo is intentionally small.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.