For the technical audience, the tool runs on Cloudflare Worker with D1 for data and R2 for photos. It's one hand-rolled HTML file and is only ~1.1MB. I built in an HEIC decoder utilizing libheif in a Web Worker. It also has an android and apple version with watch, widgets, and Live Activity native capabilities.
Sonnet 4.5 does the extraction with numerous logic variations built in from trial and error, on many different file types. I am challenging all to try and stump it (PDF, .eml, .csv, .tsv, JPG, .ics).
Thanks for the comment and suggestion! Petrel, in its current state, is deliberately in the post-planning phase of travel, but definitely great ideas on planning portion.
We are agnostic on which LLM does the parsing because the rules and structure built around it is the real magic.
Out of curiosity, how do you currently save ideas you get from Reels?
The extraction setup was actually the easy part. The magic in the tool is from the deterministic rules I put in place over months of iteration using it myself.
Inconsistent date formats, multi-lingual reservations, logic around when a new trip starts and your previous trip ends, parsing both an expense and a confirmation from the same email, duplication rules for when someone accidentally adds the same booking but from a different source, etc. These were all causes of actual parsing errors found from people testing it out.
I built 68 modules within the tool itself from testing.
The logic of the output will only improve over time with more usage. Building the right logic and ruleset into every conceivable scenario is the end goal.
For the technical audience, the tool runs on Cloudflare Worker with D1 for data and R2 for photos. It's one hand-rolled HTML file and is only ~1.1MB. I built in an HEIC decoder utilizing libheif in a Web Worker. It also has an android and apple version with watch, widgets, and Live Activity native capabilities.
Sonnet 4.5 does the extraction with numerous logic variations built in from trial and error, on many different file types. I am challenging all to try and stump it (PDF, .eml, .csv, .tsv, JPG, .ics).
Use Meta muse, freaking insane
Also, pull information from instagram reels to make the best plan for you
Thanks for the comment and suggestion! Petrel, in its current state, is deliberately in the post-planning phase of travel, but definitely great ideas on planning portion.
We are agnostic on which LLM does the parsing because the rules and structure built around it is the real magic.
Out of curiosity, how do you currently save ideas you get from Reels?
Isn't this just an LLM call? What's the moat?
Very fair callout and question.
The extraction setup was actually the easy part. The magic in the tool is from the deterministic rules I put in place over months of iteration using it myself.
Inconsistent date formats, multi-lingual reservations, logic around when a new trip starts and your previous trip ends, parsing both an expense and a confirmation from the same email, duplication rules for when someone accidentally adds the same booking but from a different source, etc. These were all causes of actual parsing errors found from people testing it out.
I built 68 modules within the tool itself from testing.
The logic of the output will only improve over time with more usage. Building the right logic and ruleset into every conceivable scenario is the end goal.
Looks clean great work
Thank you! I had a lot of fun branding it around the bird. Do you have any unique booking confirmations to test the tool with?
I don't but this was interesting to see as I have not seen this put together like this. I just appreciate the creativity.
No worries and I appreciate the feedback!
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