# Simon Willison 实测用 GPT-6 Astra 和 ChatGPT Work 生成跑步路线 - 来源：Simon Willison 博客 - 发布时间：2026-09-13 07:56 - AIHOT 分数：53 - AIHOT 链接：https://aihot.news/items/cmtz3xjif0sroroupt3ox806y - 原文链接：https://simonwillison.net/2026/Sep/12/astra-running-routes ## AI 摘要 Simon Willison 用 GPT-6 Astra 和 ChatGPT Work 从家出发生成 5K 和 10K 环形跑步路线，运行 27 分钟，基于 Nominatim 定位地址、Overpass 下载 OpenStreetMap 道路数据，产出嵌入式地图可视化和可下载的 GPX 与 GeoJSON 文件。 ## 正文 I live at . Figure out 5K and 10K running routes from me that loop from my house. Use OSM data. It worked for 27 minutes and produced exactly what I'd asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here's that 5K route: When I asked it how it had created the route, it replied: I used Nominatim to locate the address and Overpass to download local OpenStreetMap roads and trails, then calculated the loops locally. Frustratingly, the actual code it ran and exact details of what it did weren't visible to me in the ChatGPT UI. I see this lack of transparency is an anti-feature. By the time I thought to ask for a copy of the Python code it had used, ChatGPT was unable to provide it. This appears to be because the thread had been compacted. I think any LLM system that uses compaction needs to both preserve the pre-compacted text and make that text available via agent tool calls, to protect against this kind of problem. As for displaying the map to me, that used the visualize skill. It created a file called /workspace/el-granada-5k-share.html to embed directly into the ChatGPT UI. Here's a copy of that HTML, which starts like this:

El Granada harbor loop