21–29 of 29 posts
It would be great to add location and role filters.
Thanks for the suggestion! It's on my todo list. For now, you at least can sort jobs by similarity to a selected job. It's the middle icon to the left of each entry (maybe not the most intuitive way how to do it, though).
I'm actually working on something similar, but specific to inbound job opportunities (Email and LinkedIn). The goal is to use GPT to parse unstructured, unstandardized jobs into a structured, standardized job format that makes it easy for candidates to search and review once they start their job search.
It's in it's early stages, but you can check it out here and let me know what you think: https://sharedrecruiting.co/
I'd love to chat about more about this if you up for it! You can reach me at team at sharedrecruiting.co
I've been playing around GPT information extraction, and I think your prompt can be simplified to save on token costs:
Instead of:
`The company name (field name: "companyName", field type: string)`
I use a prompt that looks like:
`... The JSON should consist of the following information, using the format : The company name `
I've also played around using JSON structure in the prompt, such as:
`Return a JSON object with following model, with the format { "companyName": , ... }`
In my experience, often the attribute name is enough and GPT can infer how to extract the information (i.e. { "companyName": string ... }
I wanted to share a little side project of mine that I created while tinkering around with GPT-3. The project uses the Algolia HN Search API [1] to retrieve the "Who is hiring?" posts from HN and then parses them with the help of GPT-3 / GPT-3.5 (I do not have API access to GPT-4, yet, but it already works quite well even with the older models). It then puts the job postings into a structured list that is hopefully e…
Thanks for your prompt. There are some pointers how to improve mine
This is cool! I am definitely going to use this A couple of small things. First a request, would you be able to add filtering by location other than the #remote? Say I wanted to see only jobs in US, there's no way of doing that. That would also mean that "Santa Monica, CA" should also show up in the US filter so that could get tricky. Same thing I see for Europe where "Munich, DE" should also show up in a filter for…
Thank you very much! Filtering by location (and role) is on my todo list, but it is trickier than it seems at first. And I totally agree that the buttons are confusing. Actually, the "sort" button does sort the jobs. It sorts by semantic similarity to the job you selected (using the GPT text embedding). As for the buttons (and probably other parts of the site) not being accessible: I apologize. This shouldn't be an a…
Looks great! I've been playing around GPT information extraction, and I think your prompt can be simplified to save on token costs: Instead of: `The company name (field name: "companyName", field type: string)` I use a prompt that looks like: `... The JSON should consist of the following information, using the format : The company name ` I've also played around using JSON structure in the prompt, such as: `Return a J…
I wanted to share a little side project of mine that I created while tinkering around with GPT-3. The project uses the Algolia HN Search API [1] to retrieve the "Who is hiring?" posts from HN and then parses them with the help of GPT-3 / GPT-3.5 (I do not have API access to GPT-4, yet, but it already works quite well even with the older models). It then puts the job postings into a structured list that is hopefully e…
I tried a similar thing today parsing unstructured text (client excel documents) and turn them into JSON. I ran into the problem that the output format changed and sometimes the JSON wants parsable. Thanks for your prompt. There are some pointers how to improve mine
I wanted to share a little side project of mine that I created while tinkering around with GPT-3. The project uses the Algolia HN Search API [1] to retrieve the "Who is hiring?" posts from HN and then parses them with the help of GPT-3 / GPT-3.5 (I do not have API access to GPT-4, yet, but it already works quite well even with the older models). It then puts the job postings into a structured list that is hopefully e…
You can make the intermediate step a bit more structured too via https://github.com/HackerNews/API For example, for the March one it is ID 34983767 (from the algolia search or a "there's only so many of them, here's a list that I'll add to each month"). You can then get a list of all the top level comments at https://hacker-news.firebaseio.com/v0/item/34983767.json?pri... And then pulling up a comment at https://hack…
Earlier quoted context omitted.
I tried a similar thing today parsing unstructured text (client excel documents) and turn them into JSON. I ran into the problem that the output format changed and sometimes the JSON wants parsable. Thanks for your prompt. There are some pointers how to improve mine
You're welcome! For the chat model, it definitely helps to let it know that you want valid, parsable JSON (and nothing else). Otherwise it tends to get chatty. ;-) Depending on your use case, you might even ask it to fix the JSON if it's not parsable.
In your first example, you told GPT what data structure you expected. I added this to my prompt, and now it produces the JSON Data consistently.