# Should I Go Out? A Local Gemma Agent That Picks One Outdoor Plan, Then Tells You to Put Your Phone Away > Source: > Published: 2026-10-09 05:09:29+00:00 *This is a submission for the [Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass](https://dev.to/challenges/hacktoberfest-week1-2026-10-05)* *Should I go out?* is a web app that answers one question and then tells you to put your phone away. You tap once. The app checks the weather, the air quality, and the parks around you, and Gemma, running on your own computer, suggests one outdoor plan that fits the time you have: a park or landmark, a round-trip route, a few things to do there, and what to wear. Then the screen tells you to put your phone in your pocket. Apps that send you outside usually still want your attention, with feeds, streaks, and leaderboards. I wanted the screen to be the shortest part of the trip. You get one plan, and "Another place" if you don't like it. Goals and badges only move when you check in at the park with "I'm here", and the check-in compares your location in the browser without sending it anywhere. On the first visit, four quick questions ask how you like to move, what you enjoy, who comes along, and whether you ride public bikes, or you can let the AI decide. Each suggestion also comes with a music video of about 30 seconds that flies over the real streets to the park in 3D. Once the app has loaded on your phone, check-ins work with no signal. It speaks English and Korean, because I live in Seoul. It's for anyone who opens their phone on a free Saturday to find something to do and is still scrolling at sunset, and for parents who want a playground 20 minutes away on foot. The model runs on your own Mac, so there's no public deployment. Here's the whole flow, from the questionnaire to the check-in: And the walk preview it makes for every suggestion: I'm a total homebody and rarely go out. While building the app, I tested it on my phone. It suggested 까치 어린이공원, a small park nearby that I didn't even know was there. I walked over, checked in, and got my first badge. Going somewhere because of an app I built myself felt refreshing. One thing was off. After I checked in, it suggested "a quick game of soccer at the sports field", but the park has no sports field. The app had counted a field just outside the park as part of it, so I had the agent fix that in the afternoon: only what's inside a park's outline counts now ([83df1d5](https://github.com/scs0209/touch-grass-agent/commit/83df1d5)). Using it on my phone had also turned up two bugs earlier, a "Walk there" button that didn't respond and a start point shown as a plus code. Session 6 below covers both. One tap, one suggestion, then put your phone away. It checks the weather, the air, and the parks near you, and Gemma, running on your own computer, suggests one outdoor plan that fits the time you have. Then it tells you to put your phone away. It's a pnpm monorepo with `apps/server` (Hono and Mastra on Node) and `apps/web` (Vite and React). The README has a short setup, and `AGENTS.md` lets a coding agent set everything up for you, including pulling the model. | Piece | What it does here | |---|---| | Gemma 3 4B (open weights) | Picks the place, writes the reason and the things to do, picks the outfit, and translates the answer into Korean | | Ollama (local inference) | Runs Gemma on my Mac through its OpenAI-compatible endpoint | | Mastra (open-source agent framework) | The agent, and a four-step workflow around it | | OpenStreetMap data via Nominatim, Overpass, and OSRM | Parks and landmarks, what each park has (playground, water, viewpoint), and real walking and cycling routes | | Open-Meteo | Weather and air quality | | MapLibre GL JS and OpenFreeMap | The 3D flyover in the walk preview | All of these are free and need no API key. My first version gave Gemma the parks and asked it to plan. It made up walking times, and the card disagreed with the map. Now the server handles everything that can be measured, and Gemma handles the parts that need judgment. Each request is a four-step Mastra workflow: `roundTripMin` and features, and answers in JSON: one park by id, a reason, things to do, and an outfit from a fixed catalog. It can't invent coordinates or clothes. Korean answers come from a second Gemma call that translates the checked English answer, with place names masked so they come back unchanged. With `SENTRY_DSN` set, each request is one Sentry trace: the four steps, the agent run, every Gemma call with its tokens, and every outgoing API request. The public Overpass server is often slow, so the app waits at most 3 seconds for it and caches park features for a day. In this trace the route step takes 1 ms, because the route was measured during that wait. Most of the wait is Gemma. Three requests on an M3 Pro MacBook, with the model already loaded: | | Input tokens | Output tokens | Time | |---|---|---|---| | Gemma picks the place and writes the plan | 2,151 to 2,592 | 218 to 236 | 9.0 to 9.7 s | | Gemma translates the answer into Korean | 523 | 73 | 3.2 s | | The whole request | | | 12.6 to 15.2 s | That's 75 to 80% of every request, and it costs $0. When Gemma returns invalid JSON, the retry shows up in the same step: This app knows where you are, when you go out, who you go with, and which parks you visit. With a closed model API, all of that would sit in someone else's logs. Here the prompt never leaves my Mac. The map and weather services get only the coordinates they need, Kakao Map gets the start and the destination when you tap directions in Korea, and check-ins stay in the browser. Because it's free to run, I kept calls I'd probably have cut with a paid API: "Another place" asks Gemma again, every answer gets a second call for Korean, and broken JSON gets a retry. The small local model shaped the design too: measured routes, a fixed outfit catalog, rule checks, and a fallback. Swapping models is one environment variable (`OLLAMA_MODEL`), and the same checks apply to any open model. There's no sign-up and no API key. Clone it, pull the model, and it works anywhere OpenStreetMap, Open-Meteo, and OSRM cover. The catch is that the Mac has to be awake, and the first answer takes 10 to 20 seconds while Gemma loads. I built this with Cursor agents, and [Entire](https://entire.io) recorded the sessions and linked each one to its commit: 104 of the 126 commits carry an `Entire-Checkpoint:` trailer. The records are in a private repository because they also include my work setup. DEV's parser doesn't read Cursor transcripts yet, so I converted the sessions to the Claude Code format, which is why they show a Claude Code icon. Sessions 1 to 5 come from Entire's records and session 6 from the Cursor chat. Cursor doesn't keep tool results, so you'll see my prompts, the agent's replies, and the commands it ran. My prompts were in Korean, so I added English translations, and I redacted local paths and account names. The card and the map disagreed on the walk because Gemma was estimating the minutes. The agent moved route measurement in front of Gemma: OSRM measures every candidate's round trip, parks that don't fit are dropped, and Gemma gets each park's `roundTripMin`. After this I stopped asking a 4B model for numbers I could measure. Commit: [b94354b](https://github.com/scs0209/touch-grass-agent/commit/b94354b) "keep only parks whose round trip fits" 카드랑 경로 시간이 다른건 수정해야지 [Translation] The card and the route show different times. Fix that. I'll look at how routes are prefetched and how the plan-route step picks the route, then make the server pick a park whose real round trip fits the time you chose. Looking at where durationMin gets computed, the mismatch happens when the route time exceeds available time. The fix should swap in a park whose prefetched round trip actually fits the available window, preferring one with matching features, and update the activity name and regenerate accordingly. If no park fits, I'll keep the closest one but show its real round trip time honestly rather than hiding the mismatch. I want to check the route-fetching and condition logic before committing to this. ``` bash $ cd ~/touch-grass-agent/apps/server/src && ls conditions && cat conditions/route*.ts 2>/dev/null | head -150; cat workflow.ts ``` I want to check places.ts to see how the walking range is calculated, along with the preferredPark and matchScore logic, and whether the Park type includes a distanceMeters field. ``` bash $ cd ~/touch-grass-agent/apps/server/src && rg -n "availableMinutes|walkingRadius|radius|METERS|speed|distanceMeters" conditions/places.ts recommend.ts geo.ts | head -40; rg -n "function preferredPark|function matchScore|function wantedFeatures" -A 14 recommend.ts ~/touch-grass-agent/apps/server/src/conditions/places.ts ~/touch-grass-agent/apps/server/src/recommend.ts ``` I noticed I already had a PLACE_WORDS constant separate from PARK_WORDS—different purposes, so I'll leave them as is for now. The real issue is that candidate parks get filtered by straight-line distance with an assumed 1.3x detour factor, but actual routes can be much longer than that estimate; since routes are already being prefetched in parallel with Gemma, I could use the real route data for the decision without adding delay. I'm thinking the cleanest approach is to await the route round trips in getConditions and filter out parks whose round trip exceeds availableMinutes before passing anything to Gemma — that way Gemma's description always matches reality, with no post-hoc mismatches. If I run the route fetch in parallel with the features fetch (which already waits up to 3s), the added latency should be close to zero. The remaining question is what to do if OSRM fails or if no parks fit within the time budget — fall back to straight-line filtering, or keep the closest park anyway and let the card show it exceeds available time. That way the preview and the walk scene stay consistent, both showing the honest route time. I'm also considering attaching the round-trip minutes to each park object so the model gets informed context, and sketching a helper that fetches or caches round-trip walks per origin-destination pair, filling in missing entries before returning them all. This makes the separate prefetch step somewhat redundant since routes get fetched during getConditions anyway — though I need to be careful about the unsafe-weather case where prefetching is normally skipped. Simplest approach is to just always fetch routes in parallel with weather/air data since it's a single cheap OSRM request either way, and then update the README and docs that reference the old prefetch timing behavior. I'll keep the Sentry screenshot but reword its caption to something generic and still accurate, since I can't regenerate the actual trace. For timeout handling, routes should have a bound similar to the feature fetch so total latency stays close to the slower of the two, and if routes time out the park objects simply carry a null round-trip time, which buildResponse can display honestly — I need to check how the Gemma prompt in agent.ts handles that null field. Since straight-line distance underestimates real walking routes, I'll fetch actual round-trip times and park features in parallel, filter out parks that don't actually fit before Gemma picks, and ensure the card reflects the real route. First, I'll check how the prompt currently describes parks. ``` bash $ cd ~/touch-grass-agent/apps/server/src && rg -n "distanceMeters|nearbyParks|features|durationMin|availableMinutes" agent.ts; rg -n "prefetch" -r '' . ; rg -n "Park\b|nearbyParks" --type ts . | rg -v "recommend.ts|agent.ts" | head ~/touch-grass-agent/apps/server/src/agent.ts ``` I should add a roundTripMin field to the park data and update the prompt to clarify that durationMin must be at least the measured round-trip walking time when known, keeping the change minimal since the server already enforces a max route constraint. Now I'm updating route.ts to replace the prefetch function for round-trip walks. Writing the batch fetch logic... Actually I want to simplify so a cache miss falls back to a direct per-destination fetch rather than relying on remember's returned array, since a rejected cached promise might linger before its cleanup runs and cause duplicate refetch attempts on failure—better to just treat failures as null results in getConditions rather than retrying individually. I'm now updating getConditions in recommend.ts to handle the nearby parks lookup with a safe fallback. Writing the park details helper, pulling features and round-trip routes in parallel with Overpass/OSRM, then filtering out parks whose measured round trip exceeds the available time, with a timeout wrapper so a slow external call doesn't block the whole plan. I'm spotting a logical gap: if every park gets filtered out by the round-trip check, the user just gets a generic "walk around your neighborhood" suggestion, which feels honest but maybe too easy to trigger. There's also an edge case where the "worth the walk" distance filter discards closer parks before the route check, but those closer parks might actually have fit if the farther ones got dropped for exceeding time -- I should move that distance-based filtering to happen after the route filtering instead. Weighing whether to overhaul `getNearbyParks` to handle this properly versus accepting the rare edge case and moving on. I decide it's not worth the added complexity for an infrequent scenario, so I'll leave the current ordering and just make sure `buildResponse` correctly takes the max of the recommended duration and the actual round-trip route time. I also confirm removing the old prefetch functions since routing now happens inside the gather-conditions step, and note that fetching routes even when the weather is unsafe to go outside causes one wasted OSRM call -- acceptable tradeoff rather than adding sequencing delay. Time to write the actual code now. I'll measure the actual round-trip travel time to each park before passing data to Gemma, so the "reachable within time" guarantee in the prompt is backed by real numbers rather than assumed. ``` ~/touch-grass-agent/apps/server/src/conditions/route.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ``` I'm updating the duration calculation to take the max of the recommendation's duration and the route's duration when a route exists, then checking whether availableMinutes is still needed elsewhere in the function before removing it. ``` ~/touch-grass-agent/apps/server/src/recommend.ts bash $ cd ~/touch-grass-agent/apps/server/src && rg -n "availableMinutes" recommend.ts | sed -n '1,40p' | tail -8; rg -n "prefetchRoutes|Routes" workflow.ts ~/touch-grass-agent/apps/server/src/workflow.ts ~/touch-grass-agent/apps/server/src/workflow.ts ~/touch-grass-agent/apps/server/src/workflow.ts ~/touch-grass-agent/apps/server/src/agent.ts ``` I should also check the forbidden-terms rule about field names like distanceMeters and windKmh, and make sure roundTripMin gets added to that list too. ``` ~/touch-grass-agent/apps/server/src/agent.ts ~/touch-grass-agent/apps/server/src/agent.ts bash $ cd ~/touch-grass-agent && pnpm typecheck 2>&1 | rg -v "^$" | tail -8 ``` Typecheck passes. Now calling `getConditions` directly for 15, 30, and 60 minutes at two locations, to see the measured round trips and which parks are dropped: Since the typecheck passed, other places constructing Park objects should be fine. Now I want to test getConditions directly at 15, 30, and 60 minutes for Seoul and a few other locations, printing out parks with distance and round-trip time along with how many got dropped, before moving on to real requests. ``` /tmp/roundtrip-test.mts bash $ cd ~/touch-grass-agent/apps/server && npx tsx /tmp/roundtrip-test.mts 2>&1 | rg -v '^\s*$' ``` Ah, that park actually is in the list — the mismatch was a curly apostrophe versus a straight one in the name, which is why my matching failed. My unlisted-park fallback worked around it, but the real fix is to normalize apostrophes when comparing names. Checking the 30/15 min filters for Seoul City Hall, the drop counts look right, and the Overpass timeout delays are pre-existing and unaffected by the gather change. I want to patch the sanitize logic to normalize curly and straight apostrophes before matching the activity text against park names, and make sure the Hangul replacement uses the normalized activity string too — let me look at that code section to apply the fix. Filtering is working as expected, and I've traced the earlier "unlisted park" issue to a curly vs. straight apostrophe mismatch in "Postal Administration Citizen's Park." I'll now fix the name matching logic to ignore apostrophe style differences. ``` ~/touch-grass-agent/apps/server/src/recommend.ts ``` I'm normalizing curly quotes to straight ones in the activity text so it matches consistently between the named park and stray Hangul checks, using that normalized version for the output title. I also need to handle the case where the model picks a park that got filtered out for being too far. ``` ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts ~/touch-grass-agent/apps/server/src/recommend.ts PARK_WORDS.test ~/touch-grass-agent/apps/server/src/recommend.ts ``` That replace didn't go through even though the string looked identical—maybe the file changed underneath me. I'll retry with a smaller, more targeted string. ``` ~/touch-grass-agent/apps/server/src/recommend.ts ``` Now testing `sanitize` with the curly apostrophe, and confirming earlier cases still behave: ``` /tmp/quote-test.mts bash $ cd ~/touch-grass-agent && pnpm typecheck 2>&1 | rg "error|Done" ; cd apps/server && npx tsx /tmp/quote-test.mts 2>&1 | rg -v '^\s*$' ``` That "Gyeonghui Palace Garden" case seems fine since the name does contain the real palace name. Now I want to test against the actual running server with real requests—30 min in Seoul, 15 min, and 60 min for kids—to verify the card duration matches or exceeds the route duration. Apostrophe matching checks out and earlier cases still pass. Now I'll send real requests for 15, 30, and 60 minutes to the running server to verify the card time covers the route and stays within budget. ``` bash $ cd /tmp && for spot in "37.566 126.9784" "37.4979 127.0276"; do set -- $spot; for m in 15 30 60; do curl -s -X POST localhost:8787/api/recommend -H 'content-type: application/json' -d "{\"lat\":$1,\"lon\":$2,\"availableMinutes\":$m,\"preferences\":null}" | node -e "let s='';process.stdin.on('data',d=>s+=d).on('end',()=>{const r=JSON.parse(s);const c=r.recommendation;console.log('$1 avail $m | card',c.durationMin,'| route',r.route?.durationMin??'-','|',r.source,'|',c.activity)})"; done; done ``` All six requests failed right away with no `recommendation` in the response. Checking what the server returned and its log: ``` bash $ curl -s -X POST localhost:8787/api/recommend -H 'content-type: application/json' -d '{"lat":37.566,"lon":126.9784,"availableMinutes":30,"preferences":null}' | head -c 600; echo; tail -25 ~/.cursor/projects/Users-me-touch-grass-agent/terminals/4264.txt | cut -c1-300 ``` The server works now. The earlier failures happened while it was restarting after my edits. Running the six requests again: The server's working now, so that earlier failure was likely just a mid-edit restart crash. I'll rerun the loop with more error-tolerant parsing, keeping in mind Gemma's existing "street food vendors" entry might be pre-existing content. ``` bash $ cd /tmp && for spot in "37.566 126.9784" "37.4979 127.0276"; do set -- $spot; for m in 15 30 60; do curl -s -X POST localhost:8787/api/recommend -H 'content-type: application/json' -d "{\"lat\":$1,\"lon\":$2,\"availableMinutes\":$m,\"preferences\":null}" | node -e "let s='';process.stdin.on('data',d=>s+=d).on('end',()=>{const r=JSON.parse(s);const c=r.recommendation;if(!c)return console.log('ERR',s.slice(0,200));console.log('$1 avail $m | card',c.durationMin,'| route',r.route?.durationMin??'-','|',r.source,'|',c.activity,'|',r.bikeStation?'bike':'')})"; done; done ``` The loop itself was wrong: zsh doesn't split `$spot` into words. Fixing the shell loop: Right, zsh doesn't word-split unquoted variables by default like bash does, so `set -- $spot` won't split on whitespace. I need to use `${=spot}` to force word-splitting in zsh. ``` bash $ cd /tmp && for spot in "37.566,126.9784" "37.4979,127.0276"; do lat=${spot%,*}; lon=${spot#*,}; for m in 15 30 60; do curl -s -X POST localhost:8787/api/recommend -H 'content-type: application/json' -d "{\"lat\":$lat,\"lon\":$lon,\"availableMinutes\":$m,\"preferences\":null}" | node -e "let s='';process.stdin.on('data',d=>s+=d).on('end',()=>{const r=JSON.parse(s);const c=r.recommendation;if(!c)return console.log('ERR',s.slice(0,200));console.log('$lat avail $m | card',c.durationMin,'| route',r.route?.durationMin??'-','|',r.source,'|',c.activity,'|',r.bikeStation?'bike':'')})"; done; done ``` I'm checking that all card values stay within range, noting the bike fallback is fine since the route shown is just a pre-existing walking path. For Seoul's Hwangudan Park entry, I'm double-checking whether the place name mismatch matters since a route exists, suggesting the model likely matched by place ID rather than exact name. On the Gangnam 30-minute case, picking the closest 11-minute card is just Gemma's existing behavior and not something I need to fix now. The durationMin-vs-route consistency looks fine with the max() handling in place, so I'm ready to commit and move on to updating the README: revising the "how it works" section to mention routes are fetched in parallel while Gemma thinks, adjusting the walking-range bullet to clarify parks are filtered by measured round trip, and fixing the now-inaccurate claim that plan-route takes 0ms since routing isn't purely cached anymore. All six real requests now show card times matching or exceeding their routes within the chosen window—e.g., Seoul City Hall's card went from 30 vs 40 to a correct 29 vs 29. Committing this fix, then updating the README's route fetching notes. ``` bash $ cd ~/touch-grass-agent && git add apps/server && git commit -q -F - <<'EOF' fix: keep only parks whose round trip fits - Measure round trips with the park features, before Gemma picks - Drop parks whose real walk is longer than the time chosen - Give Gemma each park's roundTripMin - The card always covers the real route time - Match park names written with curly apostrophes EOF git log --oneline -1; rg -n "OSRM|walking range|Gemma is thinking" README.md ``` I can't recapture the Sentry screenshot since I don't have UI access, so I'll keep the existing image but write generic alt text that's accurate either way—describing it as a trace of one recommendation showing the workflow steps, the Gemma call, and outgoing API requests, while noting in the report that fresh access is needed to confirm details like the OSRM span. ``` ~/touch-grass-agent/README.md ~/touch-grass-agent/README.md ~/touch-grass-agent/README.md ``` I'm double-checking the constants and claims I mentioned—detour factor, cache TTL, wait time—all line up, and the README's park example still holds. I'm also confirming the demo cards behave correctly for the 60-minute case, and noting that if routes time out, the park list stays unfiltered which is still an honest fallback. There's a minor edge case with the "worth the walk" filter potentially dropping all nearby parks if none clear the distance threshold, but checking Seoul's 15 and 30-minute scenarios shows it's working fine in practice—this is low risk and only matters in rare all-fail situations, so I'll just note it briefly rather than fix it now. Time to commit the docs and push since the README checks out. ``` bash $ cd ~/touch-grass-agent && git add README.md && git commit -q -F - <<'EOF' docs: explain round trips measured before Gemma - Describe dropping parks whose real round trip is too long - The last workflow step reuses the cached route - Make the Sentry screenshot alt text match any trace EOF git rev-parse HEAD > .git/readme-checked && git push -q && git status -sb | head -1 && git log --oneline -3 ``` The card time and the route time now agree, and the card always stays within the time you chose. This is fixed, committed, and pushed. **Why they disagreed:** the server finds candidate parks by straight-line distance and assumes walking paths are about 1.3 times longer. Real streets are sometimes longer than that. Near Seoul City Hall, a 30-minute search included parks whose real round trip was 35–50 minutes. The card was capped at 30 while the map showed 40. **What changed:** - **Real round trips are measured before Gemma picks.** One routing request measures the walk to every park, at the same time as the park-features lookup, so the wait barely changes. Parks whose round trip is longer than your chosen time are removed from the list. Gemma also sees each park's measured minutes (`roundTripMin`). - **The card always covers the route.** If the routing server is too slow and the round trips can't be measured in time, the card shows the real route time instead of cutting it down to the chosen time. - **Park names with curly apostrophes now match.** While testing I found that "Postal Administration Citizen's Park" from the last session was a real listed park. Gemma had written it with a curly apostrophe (’), so the name match failed. It now matches, and Gemma's choice is kept. **Checks:** - Typecheck passes. - I called the changed functions directly for 15, 30, and 60 minutes at Seoul City Hall and Gangnam. At City Hall, 3 of 6 parks were removed for 30 minutes and 2 of 3 for 15 minutes. - I sent 6 real requests to the running server. In every one, the card time covered the route and stayed within the chosen time. City Hall at 30 minutes now gives 29 on the card and 29 on the route, where it used to be 30 vs 40. - The README now explains how round trips are measured. **Still left:** - **Sentry screenshot is outdated.** `docs/sentry-trace.png` still shows the old order, where routes were fetched while Gemma was thinking. I can't open the Sentry dashboard from here to take a new one, so I only changed its alt text to something true for any trace. - **If no park fits the time, there's no map or preview.** The suggestion becomes "Take a walk around your neighborhood". Parks very close to you are skipped when farther ones exist, so in rare cases a close park that would fit isn't checked. I didn't see this happen in testing, and changing how parks are searched is a separate change. - **Gemma sometimes picks a much shorter park than the time allows** (for example, an 11-minute park when 30 minutes were chosen). The card and route still agree; this is about how Gemma chooses, not this mismatch. 카드 시간과 경로 시간이 이제 일치하고, 카드는 항상 고른 시간 안에 들어옵니다. 수정, 커밋, push까지 끝냈습니다. **달랐던 이유:** 서버는 후보 공원을 직선거리로 찾고, 실제 걷는 길이 약 1.3배 길다고 가정합니다. 실제 길은 그보다 더 길 때가 있습니다. 서울시청 근처에서 30분으로 찾으면 실제 왕복이 35–50분인 공원이 포함됐습니다. 그래서 카드는 30분으로 잘리고 지도는 40분을 보여줬습니다. **바뀐 점:** - **Gemma가 고르기 전에 실제 왕복 시간을 잽니다.** 경로 요청 한 번으로 모든 공원까지의 왕복을 재는데, 공원 시설 조회와 동시에 해서 대기 시간은 거의 늘지 않습니다. 왕복이 고른 시간보다 긴 공원은 목록에서 뺍니다. Gemma도 공원별 실측 시간(`roundTripMin`)을 봅니다. - **카드는 항상 경로 시간을 포함합니다.** 경로 서버가 너무 느려서 미리 재지 못한 경우에는, 카드가 고른 시간으로 잘라내지 않고 실제 경로 시간을 보여줍니다. - **둥근 아포스트로피가 들어간 공원 이름도 맞춥니다.** 테스트하다 보니 지난번 "Postal Administration Citizen's Park"는 실제로 목록에 있는 공원이었습니다. Gemma가 둥근 아포스트로피(’)로 써서 이름 비교가 실패했던 것입니다. 이제 맞춰지고, Gemma가 고른 공원이 유지됩니다. **확인:** - 타입체크 통과. - 서울시청과 강남에서 15·30·60분으로 바뀐 함수를 직접 호출했습니다. 시청에서는 30분일 때 6개 중 3개, 15분일 때 3개 중 2개 공원이 빠졌습니다. - 실행 중인 서버에 실제 요청 6개를 보냈습니다. 모든 경우에 카드 시간이 경로를 포함하고 고른 시간 안에 들어왔습니다. 시청 30분은 예전에는 30 대 40이었는데, 이제 카드 29분, 경로 29분입니다. - README에 왕복 시간을 재는 방식을 적었습니다. **남은 부분:** - **Sentry 스크린샷이 예전 것입니다.** `docs/sentry-trace.png`는 Gemma가 생각하는 동안 경로를 가져오던 예전 순서를 보여줍니다. 여기서는 Sentry 대시보드를 열 수 없어서 새로 찍지 못했고, 대체 텍스트만 어떤 트레이스에도 맞는 설명으로 바꿨습니다. - **시간 안에 맞는 공원이 하나도 없으면 지도와 미리보기가 없습니다.** 추천은 "Take a walk around your neighborhood"가 됩니다. 더 먼 공원이 있으면 아주 가까운 공원은 건너뛰기 때문에, 드물게 시간에 맞을 가까운 공원을 확인하지 못할 수 있습니다. 테스트에서는 이런 경우가 없었고, 공원 검색 방식을 바꾸는 건 별도 작업입니다. - **Gemma가 가끔 시간보다 훨씬 짧은 공원을 고릅니다** (예: 30분을 골랐는데 11분짜리 공원). 카드와 경로 시간은 일치합니다. 이번 불일치 문제가 아니라 Gemma가 고르는 방식의 문제입니다. I'm considering whether a full preview test run is needed, but since the web code itself didn't change, I can skip the heavy verification. The agent added one shared in-memory cache (`apps/server/src/cache.ts`) with a lifetime for each kind of data: 10 minutes for the same suggestion and for weather within about 1 km, a day for place searches and routes, 6 hours for park photos, and never for live bike counts. Identical requests share one Gemma call, and an older weather reading stands in when Open-Meteo fails. It also keeps the app from hammering Nominatim and Overpass, which are free public services. When I asked for numbers, it wrote a benchmark that runs the commits from before and after caching side by side in git worktrees, alternating the runs so changes in network speed hit both. | Scenario | Before | After | |---|---|---| | Reopen the same preview | 5.5 s | 4 ms | | Search the same city again | 10.3 s | 0.1 s | | 3 identical requests at once | 22.8 s | 12.1 s | | A whole six-step session | 58.8 s | 39.2 s | | Outside API calls per session | 28 | 17 | | Gemma calls per session | 8 | 5 | It also reported what didn't get faster. A first visit has nothing to reuse, and caching the data around Gemma saves only 1 to 2 seconds. The big gains all come from requests Gemma doesn't have to answer again. Commits: [5512232](https://github.com/scs0209/touch-grass-agent/commit/5512232), [550c51f](https://github.com/scs0209/touch-grass-agent/commit/550c51f), [2bdb30c](https://github.com/scs0209/touch-grass-agent/commit/2bdb30c). Method and raw runs: [docs/benchmarks/caching.md](https://github.com/scs0209/touch-grass-agent/blob/main/docs/benchmarks/caching.md) 빠른 응답과 동영상 생성 성능 개선을 위해 **현재 프로젝트에서 캐싱을 적용할 수 있는 지점을 전체적으로 분석하고 적용해주세요.** 특히 사용자가 **한 번 방문하거나 검색했던 장소**처럼 다시 사용할 가능성이 높은 데이터와, 동영상 생성 과정에서 반복적으로 사용하는 데이터/리소스를 중심으로 확인해주세요. `이전 검색` 기능과 자연스럽게 연동될 수 있는 구조를 고려해주세요. 캐싱을 통해 다음과 같은 상황에서 체감 속도가 빨라지는 것을 목표로 해주세요. 캐싱 자체가 목적이 아닙니다. **"한 번 처리한 데이터를 다시 처리하지 않음으로써 응답 시간과 동영상 생성 시간을 줄이는 것"**이 목적입니다. 따라서 작업 전에 현재 프로젝트의 데이터 흐름을 먼저 분석하고, 를 판단한 후 구현해주세요. 이미 프로젝트에서 사용 중인 상태 관리나 데이터 fetching 라이브러리가 있다면 해당 라이브러리의 캐싱 기능을 우선적으로 활용하고, 불필요하게 새로운 캐싱 라이브러리를 추가하지 마세요. 작업 완료 후에는 다음 내용을 정리해주세요. [Translation] To get faster answers and faster video generation, analyze where caching can help across the project and apply it. Focus on data that is likely to be used again, such as places the user has visited or searched once, and data or resources the video generation uses over and over. Requirements: 1. Analyze where caching is possible. Check the data flow and the video generation first, find what gets requested or generated repeatedly, and don't cache blindly: start with the areas where caching really improves performance. 2. Cache places searched or visited before. Reuse a place's name, coordinates, city, and map data instead of requesting them again, avoid calling APIs again for the same place, and fit in with the existing "recent searches" feature. 3. Cache the video generation. Check what gets regenerated for the same place or input, cache reusable intermediate results and static resources, and don't regenerate results that already exist. Start with the slow or costly work. 4. Map and 3D data. If the 3D map fetches the same data repeatedly, make it reusable, but don't blindly cache data that must be realtime. 5. Images and static resources. Pick the right kind of cache for each (browser cache, memory, local storage, server cache). Don't just put everything in localStorage. 6. Invalidation. Decide when to refresh or delete entries, use sensible TTLs so old data doesn't stay forever, and fall back to the normal API or generation when the cache is empty or wrong. 7. Duplicate requests. If several components request the same data at once, share one request's result where possible. 8. User experience. It should feel faster when reselecting a place searched before, exploring another place in the same city, making a video for a place used before, reloading map or 3D data, and reopening an earlier result. Caching is not the goal. The goal is to cut response time and video generation time by not processing the same data twice. So analyze the data flow first (what repeats, what takes longest, what can be reused, where a cache helps most) and then implement. Prefer the caching features of libraries the project already uses, and don't add a new caching library. When you're done, summarize: where you added caching, which strategy, the lifetime and invalidation rules, the expected improvement, and the changed files with the reason for each. I'll start by mapping the data flow: every outgoing request on the server and in the browser, what is already cached, and what the video preview loads. Then I'll measure the slow parts before changing anything. This is a big task, so I should plan my exploration efficiently before diving in. Given the user's preference for checking codebase structure via the memory tool first, I'll start with listing projects and checking the architecture before falling back to targeted searches. I'll inventory server outbound calls and existing caches by searching for cache-related patterns, Map usage, and fetch calls across the apps. ``` fetch\(|new Map<|CACHE|cache|TTL|expiresAt ~/touch-grass-agent/apps bash $ cd ~/touch-grass-agent && ls apps/server/src apps/server/src/conditions apps/web/src/preview apps/web/src/services && cat apps/web/package.json apps/server/package.json | rg '"(react-query|@tanstack|swr|zustand|lru|idb|maplibre|leaflet|hono|@mastra|ollama)' ``` There's no react-query or SWR in use; the server already caches Nominatim, features, routes, and image URLs with varying TTLs. But weather, air quality, bikes, Gemma (the slow ~10s call), photo searches, city geocoding, trip photos, and flyover styles are all uncached and fetched directly in the browser. Let me dig into the relevant files—photos, weather, airQuality, bikes, the workflow and API entry points, location handling, WalkPreview, flyoverMap, assets, music, and film—to see exactly where these loads happen. The server already caches park searches, features, routes, and photo URLs, but there's no data-fetching library on the web side. I'll now check the uncached parts—weather, air quality, bikes, photos, the server entry point, and browser requests. ``` ~/touch-grass-agent/apps/server/src/conditions/photos.ts ~/touch-grass-agent/apps/server/src/index.ts ~/touch-grass-agent/apps/web/src/services/api.ts ~/touch-grass-agent/apps/web/src/services/location.ts ``` Now the video side: how the preview loads the 3D map, photos, music, and assets. I'm now looking at the preview component and related loading stages—flyover map, assets, music, and film—to find where async loads happen in the preview flow. ``` bash $ cd ~/touch-grass-agent/apps/web/src && wc -l preview/*.ts components/WalkPreview.tsx && rg -n "await |new Image|loadImage|decode\(|fetch|AudioContext|decodeAudioData|import\(|createImageBitmap|toBlob|MediaRecorder|warm|prepare" components/WalkPreview.tsx preview/assets.ts preview/music.ts preview/recording.ts preview/flyoverMap.ts | head -80 ~/touch-grass-agent/apps/web/src/components/WalkPreview.tsx ~/touch-grass-agent/apps/web/src/preview/flyoverMap.ts ~/touch-grass-agent/apps/web/src/preview/assets.ts ``` Now `loadFilm` in `film.ts`, which drives the photo request, image decoding, and backdrop processing: ``` ^export async function loadFilm|fetchTripPhotos|tripPhotoUrl|softenPixels|function soften|loadPhoto|async function|await |getImageData|OffscreenCanvas|createElement\('canvas'\) ~/touch-grass-agent/apps/web/src/preview/film.ts ~/touch-grass-agent/apps/web/src/preview/film.ts ``` Before choosing what to cache, I need to know what the video shows that depends on the clock, and whether the outside services already allow browser caching. Checking both: I'm measuring where the time actually goes: the recommend endpoint takes roughly 8-15 seconds total across Nominatim, Overpass, OSRM, weather/air quality, bikes, and the Gemma call, while the preview path adds style fetching, tile warm-up, and trip photo searches on top of that. The real bottleneck is photo downloads -- fetching 2048px images server-side can take up to 7 seconds each, and since each search gets a random UUID cache key, the browser never actually reuses cached photos across searches. I'm thinking about caching the trip photo search results by entrance/destination/placeName instead, since a park's photos don't change often, but I need to account for Mapillary's signed thumbnail URLs expiring after a few days, so a safe TTL of around 1-6 hours with a fallback refetch on 403 errors seems reasonable. Switching to deterministic hash-based keys instead of random UUIDs would let the browser's own HTTP cache handle repeat requests properly, and pairing that with a bounded in-memory LRU cache for photo bytes server-side (maybe 60MB) would avoid re-downloading images from Mapillary every time the preview reopens. On the client side, I'm thinking about caching the tripPhotos response per place/destination/entrance combo in memory so reopening the same preview skips the network call entirely, plus caching the processed canvases (graded + backdrop versions) keyed by photo and mood, since that CPU work of grading and softening takes real time per photo. I'm also considering memoizing the map style JSON as a module-level promise since it's static per session, and checking whether tile responses are HTTP-cacheable. The biggest potential win might be keeping a MapLibre instance alive between opens for the same place to skip WebGL init, style parsing, and tile decoding entirely — though that costs GPU memory, so reuse would need to be limited to matching inputs. Even bigger: the already-recorded video Blob could be cached in memory keyed by input, letting a reopened preview play the actual recorded file (music included) via a `