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I built a local Elixir/Python pipeline to curate 14,000 RAW photos

Details

External ID
47829271
Source
HN
Company
—
Product
I built a local Elixir/Python pipeline to curate 14,000 RAW photos
Website domain
qwelian.com
Launched
April 20, 2026
Cohort
—
Upvotes
5
Upvotes percentile
0.11182519280205655
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

I had 14,000 photos sitting on a drive and wanted an excuse to play with local vision models and Elixir/Phoenix. I originally tried to get LLaVA to tell me if a photo was 'good' or matched my style, but quickly learned that LLMs have terrible taste. I ended up demoting the LLM to just extract metadata, and built a custom CLIP/Ridge Regression pipeline to actually learn my preferences based on how I rate things.The stack is Phoenix/Oban on the orchestrator side, and Python/FastAPI/Instructor for the AI workers. Happy to answer any questions about the architecture, fighting with local RAW file ingestion, or the pains of Pydantic validation with open weights.

Enrichment

Theme
lightweight and on-device AI runtimes
Vertical
Horizontal
Function
Workflow automation
Audience
Prosumer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
local photo curation pipeline
Manually corrected
False

Could you build this?

Yes The project is a personal local script pipeline combining an Elixir/Phoenix gallery with a Python worker script running local CLIP and LLaVA models via Ollama or PyTorch.

Discussion

2 comments analyzed.

Concerns raised: Network latency impact, RAM constraints for metadata extraction, RAW file processing overhead

Feature requests: Native RAW file conversion in Elixir

Competitors

Other products that read as similar to this one — 118 launches clear the similarity bar, closest 8 shown.

Attention rank: #107 of 119 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 171 days after the earliest competitor.

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