Raymond Camden

For the past few months or so, I've started tracking my movie watching with Letterboxd. I'm not doing a lot of reviews, mostly just logging, but I find it neat to look back and remind myself of what I've watched recently. You can see my profile if you're curious, or check out my "Now" page as well. I thought it might be interesting to see if I could use my Letterboxd data along with Google Gemini as a way to suggest the next movie I should watch. I was able to build a quick workflow using the incredible Pipedream in a few minutes. Let me share with you how I did that.

development generative ai

Forgive the somewhat alliterative title there, but today's post covers something that's been on my mind since I started playing with Google Gemini, specifically, how to get the results of your API calls in JSON. To be clear, the REST API returns a result in JSON, but I'm talking about the content of the result itself. Before I continue, a quick shot out to Allen Firstenberg who has been helping me off and on with Google Gemini stuff. Anything I get wrong though is entirely my fault. 😜

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Good day my fabulous readers and I hope all is well with you. I just got back from speaking at the excellent Devnexus event and despite some travel issues (thank you storms, really), I had a great time. I got to see not one, not two, but three very old friends of mine and attended some good sessions as well. I'm home for a week and then on the road again to the Adobe ColdFusion Summit in the DC area. Don't forget, this Tuesday I've got another episode of <Code><Br> coming up. I'll be building, or attempting to, build a PWA live. Surely it will go perfectly, right?

misc links4you

A few weeks back I wrote up my experience with generative AI as a dungeon master. That post ended up being really popular and got me thinking about other ways I could integrate D & D, or other games, with Generative AI. With Gemini 1.5 now available via API, I thought it would be good to find an excuse to hit the API in a demo. So with that in mind, I'd like to introduce you to the Class Suggester.

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For some time now, I've relied on my Netlify Analytics report to keep track of how well my site is doing, what content is popular, and so forth. I was a Google Analytics user for over ten years, but when they updated the UI, I saw red every time I tried to use it. Netlify Analytics is super simple and quick. (My only real complaint is that it's limited to 30 days, but I've got free access to the feature so I'm happy to not care about that.) I complement Netlify Analytics with GoatCounter as well. Netify's analytics show much more traffic than Goat, and I figure the truth is somewhere in the middle, and again, I'm fine with that.

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My regular readers (hello, yall rock!) know I've been playing with generative AI the past few months. I'm still a bit skeptical about the amount of hype involved around the space, but I'm slowly getting more excited as I see some of the interesting possibilities available with these tools. Most of my recent exploration has been on the Google Gemini side, but after hearing my buddy Todd Sharp talk about Amazon Bedrock on his stream yesterday, I figured it was time to check it out. (FYI, you should absolutely check out his weekly Twitch show on the AWS Twitch channel called "Streaming on Streaming" - Wednesdays at 3PM CST.)

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Forgive the somewhat silly title, but it's not like I haven't been silly here before. Almost four years ago I wrote a little post about a random text-generated app called the "Queen Maker": Let's Make Everyone a Queen!. The idea for that app (which lives on at queenof.netlify.app) was to use a random text library called Tracery to generate random short "queen-based" stories. Yeah, that may not make much sense, but read the earlier post or play with the app to see.

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