Parsing Uploaded Resumes into Form Fields with Google Gemini

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As I’ve recently become somewhat familiar with job application sites (sigh, thanks Adobe), I’ve noticed an interesting feature some sites use. After selecting your resume to upload, they will parse the resume and either offer to, or automatically, fill in some of the form fields of the application for you. I thought it would be interesting to try this myself making use of Google’s Gemini APIs. Here’s what I discovered. The Test Script As always, I began with a script that would take a hard-coded resume and attempt to parse it. For the most part, this is basic "upload a file and ask the AI to talk about", but in my case, I wanted a very particular set of data... more →
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Generative AI Images with Gemini and Imagen – an Introduction

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I’ve been waiting for this to launch for a few days now, and while technically this isn’t quite yet available in Gemini, only Vertex, it should be testable in Gemini in the very short term. You can now use Google’s APIs to generate really high quality images via their Imagen 3 technology. I’ve got a few blog posts planned that will demonstrate these features (and from what I’ve been told, even more powerful stuff is coming), but I thought I’d start off today with a simple short example. To begin, and remember this may not available just yet, take a look at the docs, Imagen 3 in the Gemini API. First, let’s consider the sample code, that I’m going... more →
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Automating Object Detection with Google Gemini GenAI and Pipedream

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For my last technical post of the year (although I can’t promise I’ll stop blogging!), I wanted to share an interesting workflow I built using Google Gemini and Pipedream. The idea was somewhat simple – how difficult would it be to build a "general purpose" workflow to look for objects in images and trigger an alert if certain things were found. Here’s what I was able to build. Step One – Image Input In my mind, I imagined this workflow would be tied to some service that was either streaming in video or generating still images. You could image a security camera posting new pictures every 30 seconds or so, or some other system that takes a picture at a regular... more →
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Adding AI Insights to Data with Google Gemini

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Yesterday, Elizabeth Siegle, a developer advocate for CLoudflare, showed off a really freaking cool demo making use of Cloudflare’s Workers AI support. Her demo made use of WNBA stats to create a beautiful dashboard that’s then enhanced with AI. You can find the demo here: https://wnba-analytics-ai-insights.streamlit.app/ I found this incredibly exciting. I last looked at Cloudflare’s AI stuff almost an entire year ago ("Using Cloudflare’s AI Workers to Add Translations to PDFs"), and I haven’t quite had a chance to try it again, mostly because I’ve been focused on Google Gemini for my Generative AI work. From an API/usage perspective, Cloudflare’s... more →
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ColdFusion Component for Google Gemini

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This week I had the pleasure to present on Google Gemini at the ColdFusion Summit. If you weren’t able to make it, I do plan on giving the talk again on the ColdFusion Meetup sometime later this year. After the presentation, I took my ‘rough and ugly’ code that called Gemini and decided to wrap it up in a nice ColdFusion component. This allows for (hopefully) easier use. For example: gemini = new gemini(key="your key", model="gemini-1.5-pro");result = gemini.prompt('why is the sky blue?'); And that’s it. The result variable will contain two keys, a raw value that is exactly what Gemini returned, and a text value that narrows down into the text response. Multimodal... more →
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Using PDF Content with Google Gemini – An Update

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Way back in March of this year, I took a look at using Google’s Gemini APIs to analyze PDF documents ("Using PDF Content with Google Gemini"). At the time, the Gemini API didn’t support PDF documents, so I made use of our (Adobe) PDF Extract service to get the text content out from the document. This "worked" but was possibly less than ideal as my "glom all the text together" approach didn’t really represent the PDF well. The PDF Extract API returns information about text context (like if it is a header for example), but my method ignored that. I’m happy to share that Gemini now supports PDF files natively. Let’s take a look at how this... more →
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Caching Input with Google Gemini

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A little over a month ago, Google announced multiple updates to their GenAI platform. I made a note of it for research later and finally got time to look at one aspect – context caching. When you send prompts to a GenAI system, your input is tokenized for analysis. While not a "one token per word" relation, basically the bigger the input (context) the more the cost (tokens). The process of converting your input into tokens takes time, especially when dealing with large media, for example, a video. Google introduced a "Context caching" system that helps improve the performance of your queries. As the docs suggest, this is really suited for cases where you’ve got... more →
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Creating a Generic Generative Template Language in Google Gemini

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I’ve been a fan of ‘random text’ for some time. "Random text" is a bit vague, but to me the idea of using code to generate random stories, or even snippets, is fascinating. Back in April, I blogged about how I created short dragon-based stories. It took a generic string: A #adjective# dragon lives #place#. She #verb# her hoard, which consists of a #number# of #thing#, #number# of #thing#, and #number# of #thing#. She feels #feeling#. And created a story by replacing the pound-wrapped tokens with real words. I used a couple of different tools to build this, but the core one was a cool little Node library named random-word-slugs. It’s a powerful random word library... more →
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