Copasetic Flow

 Debug notes from getting the AI help feature of the free ham radio exams to work today. Grabbing a text answer from OpenAI still works: That's from this method async function retrieveTextWithFileSearch ({ system , user }) {   const vsId = localStorage . getItem ( 'vector_store_id' );   if (! vsId ) throw new Error ( 'No vector_store_id found.' );   answText = answText + " " + user ;   const resp = await openai ( '/responses' , {     body : {       model : 'gpt-4.1-mini' ,       input : [         { role : 'system' , content : system },         { role : 'user' ,   content : answText }       ],       tools : [{ type : 'file_search' , vector_store_ids : [ vsId ] }]     }   }); With the agent  flow, it doesn't work async function retrieveTextWithAgent ({ system , user }) {   // 0) Make sure we have ...

 I'm using the new map in map feature I coded up this week to for a map that demonstrates that as the sun sets in Sweden, it's rising near Las Cruces, NM. A few minutes later, my QSO to Sweden from the Organ Mountains went through. The code is in a github repo . Here's the map: And here's a video demonstrating how to interact with the map above: For those who are curious, here's how Project TouCans was situated that day. Note that the dipole is only about five feet off the ground.

 I frequently find myself zooming in and out of QSO maps to see where the sun was with regard to my station's horizon  vs how far a given QSO propagated. I wanted a way to view maps without all the zooming. Now I have it! How I got It I've had Cesium maps on the blog for a while. Once I got the idea for a better way to view QSO maps, I deliberately executed on the habit I've been trying to build in myself:  I immediately asked GPT5 if it could augment my existing code. It turned out that it definitely could. In under half an hour, I had the new map view pictured above. You can steer around the maps at my POTA post .  The code for implementing map in map can be found in the csm-map-n-map repo.

 Project TouCans made it back on the HF airwaves last night! I had forgotten that urban POTAs are kind the epitome of luxury here in San Francisco. On my way to the bus stop for the MUNI 49, I noticed that it was happy hour, so I stepped in for a drink. Perched on a barstool at the joint's open front window, I contemplated the world outside and whether or not the radio would work. The power switch latching relay for the rig gave up on the last day of our Great Basin National Park camping trip. That'd been perfect timing, (if the thing was going to break at all), but also led to me not being on the air in the better part of two months. I wound up making the ten QSOs to activate the park in just over half an hour. My operating site was on the campus of City College San Francisco (CCSF.) The view across the city is kind of nice. I was there just into the night this time, and the city lights up after dark. I'm trying something new in the map below. I asked GTP5 to help me with...

 I've been looking for an excuse to try parallel processing with Python for a few months and yesterday, the FBI provided one. They released a collection of records related to the assassination of Reverend Dr. Martin Luthor King Jr. It's easy enough to get a count of the pdf files released from the announcement page . Information about the files released to the National Archives I was able to quickly read that there were 6,301 files. A brief internet search indicated that the files have not been released in any kind of compressed container, like a zip file yet. I also tested that the search box only searches the pdf file names, not their contents. The immediate next question was how many bytes of disc space do all the pdfs consume? I asked Chat GPT o4-mini-high to write a Python script to determine the size of the all the files combined. The script was unable to determine the size of each file by looking at the HEAD of the URL for each file, so it wound up having to use GET req...

 While doing some experiments about how someone might backup the Soldersmoke blog, I came across an interesting issue. I'd worked with ChatGPT to create a Python script that stored a post from the soldersmoke blog in a directory. The name of the directory was the date and time of the blog post concatentated with the the blog post title. In most cases, this wound up being a file name with more than 256 characters. I dont' remember where I tried my first prototypes a few months ago, but whatever system I was on, it wasn't Windows, because Windows doesn't support folder or file names longer than 256 characters. Google drive, however, does. As a result, when I tried to download the folders to a Windows machine, I got an error message indicating that the zipped directories from Google Drive could not be read. The simple fix, it turned out, was to change the naming scheme of the folders so that they contained only the timestamp of the post down to the second in UTC time. Wit...