Commit Graph

1794 Commits

Author SHA1 Message Date
2569718930@qq.com 89a71d1bc0 Add Qingdao to the tradable city network
Qingdao needs the same airport-settlement path as the other Wunderground-backed APAC cities, so the registry, aliases, timezone, prewarm, official links, market focus, and tests now point to ZSQD / Qingdao Jiaodong International Airport.

Constraint: User supplied Wunderground Qingdao/ZSQD settlement URL.
Rejected: Add a partial registry-only entry | it would show in APIs without frontend links, prewarm coverage, or alias support.
Confidence: high
Scope-risk: narrow
Reversibility: clean
Tested: pytest tests/test_country_networks.py tests/test_web_observability.py::test_cities_endpoint_includes_new_wunderground_cities -q
Tested: npm run build
Not-tested: Live Wunderground fetch for ZSQD in production.
2026-04-28 07:08:33 +08:00
2569718930@qq.com e6010d8242 Make city decision cards easier to trust at a glance
The decision card now exposes deterministic guard state, data freshness, AI readiness and market sync directly in the card header so users can understand whether they are looking at fresh evidence, a fallback, or a stale/exception case before reading the full explanation.

Constraint: Keep the first useful read available while DeepSeek airport/HKO details are still streaming.\nRejected: Add another expanded evidence panel | header-level badges are faster to scan and avoid increasing card depth.\nConfidence: high\nScope-risk: narrow\nReversibility: clean\nTested: npm run build\nNot-tested: Browser visual QA on production data.
2026-04-28 06:52:00 +08:00
2569718930@qq.com de0effc40b Make city AI helpers maintainable outside scan service
The scan terminal service had grown into a 3.5k-line file that mixed endpoint orchestration, AI provider calls, fallback copy, JSON repair, and deterministic evidence guards. This extracts the city-AI helper layer into a focused module while preserving the old private names through imports for existing tests and callers.

Constraint: Keep behavior unchanged after the previous evidence-guard fixes and avoid a broad service rewrite.

Rejected: Split every scan-terminal concern at once | too much regression risk for this maintenance pass.

Confidence: high

Scope-risk: narrow

Tested: pytest tests/test_web_observability.py -q

Tested: npm run build
2026-04-28 06:40:53 +08:00
2569718930@qq.com 0c9b07faaf Keep provider reads behind deterministic evidence guards
DeepSeek can return a polished city forecast that conflicts with already-computed stale-observation, observed-break, or peak-window evidence. The completion path now carries the deterministic fallback guard state and overwrites only the critical fields when provider text or numbers contradict those local facts.

Constraint: Airport-read latency optimization keeps provider output narrow, so backend completion remains the authority for final highs and evidence conflicts.

Rejected: Trust provider final wording when present | it can reintroduce stale METAR anchors or miss observed high breaks.

Confidence: high

Scope-risk: narrow

Tested: pytest tests/test_web_observability.py -q

Tested: npm run build
2026-04-28 06:36:33 +08:00
2569718930@qq.com 0eab2fe628 Treat stale observations as weak evidence
City-card fallback reads now stop using stale METAR or official observations as strong live anchors. A stale observation no longer forces high/low revisions, and both backend and browser AI cache keys include the observation fingerprint so updated report times, receipt times, temperatures, or stale status invalidate old AI text.

Constraint: Cached city AI reads must not survive a material observation update

Rejected: Let stale METAR trigger observed-break revisions | stale reports can be older than the active temperature path

Confidence: high

Scope-risk: moderate

Tested: pytest tests/test_web_observability.py -q

Tested: npm run build
2026-04-28 06:28:29 +08:00
2569718930@qq.com 0a3242c6ec Tighten fallback reads around peak-window evidence
Fallback city-card reads now distinguish three cases that previously collapsed into the generic fast-evidence copy: observed highs above the model path, observed highs still lagging after the peak window, and low observations before the peak window that should wait for confirmation rather than down-revise immediately. The same pass removes three unused private helpers from the scan terminal service.

Constraint: Fallback output must be useful before the full AI airport-bulletin read returns

Rejected: Treat any low latest METAR as a down-revision | early-day observations can be below the forecast before the peak window

Rejected: Keep unused helper wrappers | they were unreferenced and added noise to an already large module

Confidence: high

Scope-risk: moderate

Tested: pytest tests/test_web_observability.py -q

Tested: npm run build
2026-04-28 06:22:07 +08:00
2569718930@qq.com d1d9f80f0f Revise fallback highs after observed breaks
Fast evidence mode should not say DEB and models support the center when the latest METAR has already exceeded that center or the model upper edge. The fallback now treats the live observation as a lower bound for the daily high and explains the upward revision pressure.

Constraint: Fallback output must remain useful before the full AI bulletin read returns

Rejected: Keep the original DEB center until AI completes | it can be lower than an already-observed temperature

Confidence: high

Scope-risk: narrow

Tested: pytest tests/test_web_observability.py::test_city_ai_fallback_revises_up_when_latest_metar_breaks_above_models tests/test_web_observability.py::test_city_ai_fallback_reasoning_identifies_fast_evidence_mode tests/test_web_observability.py::test_city_ai_stream_request_only_asks_provider_for_observation_read -q

Tested: npm run build
2026-04-27 12:33:56 +08:00
2569718930@qq.com c3f092fc28 Speed up streamed airport bulletin reads
The city card only needs the provider to interpret the latest METAR or official observation. Deterministic fields such as the high-temperature center, model cluster note and fallback risks are already available server-side, so the stream request now asks DeepSeek for only the observation read and concise reasoning.

Constraint: City cards still need a complete payload for both Chinese and English UI modes

Rejected: Keep generating the full decision schema in the stream | too much model output for every card

Rejected: Retry failed streams by default | it can double latency and the fallback can use partial streamed text

Confidence: high

Scope-risk: moderate

Tested: pytest tests/test_web_observability.py::test_city_ai_stream_request_only_asks_provider_for_observation_read tests/test_web_observability.py::test_city_ai_fallback_reasoning_identifies_fast_evidence_mode tests/test_web_observability.py::test_city_ai_partial_json_trims_dangling_taf_clause tests/test_web_observability.py::test_city_ai_schema_completion_trims_dangling_taf_clause -q

Tested: npm run build
2026-04-27 09:51:09 +08:00
2569718930@qq.com ee2a5338bb Avoid overstating fallback AI bulletin reads
The city decision fallback path is generated when the full DeepSeek city-airport read has not completed, so the reasoning copy now labels the state as fast evidence mode instead of saying the AI read is normal.

Constraint: Fallback output may use only DEB, model cluster, and latest observation evidence

Rejected: Keep 'AI read normal' wording | it implies a completed AI interpretation when the fallback path is active

Confidence: high

Scope-risk: narrow

Tested: pytest tests/test_web_observability.py::test_city_ai_fallback_reasoning_identifies_fast_evidence_mode tests/test_web_observability.py::test_city_ai_partial_json_trims_dangling_taf_clause tests/test_web_observability.py::test_city_ai_schema_completion_trims_dangling_taf_clause -q
2026-04-27 09:45:11 +08:00
2569718930@qq.com 504efcbb49 Clarify weather-first decision card label
The prior label said the weather decision layer had no market price connected, which could be read as a broken market integration. The card now says weather-first read with market prices shown separately.

Constraint: Market price layer is already rendered below the weather decision band

Rejected: Keep 'no market price input' | accurate internally but misleading in user-facing Chinese copy

Confidence: high

Scope-risk: narrow

Tested: npm run build

Not-tested: Visual screenshot review
2026-04-27 09:10:57 +08:00
2569718930@qq.com 4eb50ce880 Prevent dangling TAF fragments in city AI reads
City AI can return a partially streamed JSON string when the provider truncates output. The fallback previously kept an unfinished clause such as '但TAF显示', which made the forecast explanation look broken even though earlier evidence was usable.

Constraint: Provider JSON can be truncated after useful fields have already streamed

Rejected: Drop all partial AI text | would lose valid METAR interpretation already returned before truncation

Confidence: high

Scope-risk: narrow

Tested: pytest city AI truncation regression tests

Tested: npm run build

Not-tested: Live DeepSeek provider response
2026-04-27 08:28:00 +08:00
2569718930@qq.com e4cf570820 Promote calendar snapshot to v1.5.5 release
The calendar local-time and AI airport-read fixes are a numbered product release rather than a temporary snapshot, so the changelog and package/version metadata now use 1.5.5 consistently.

Constraint: Existing snapshot tag was already pushed before the numbered release correction

Rejected: Keep snapshot label in changelog | user clarified this should be the 1.5.5 version

Confidence: high

Scope-risk: narrow

Tested: Reviewed git diff for CHANGELOG, VERSION, frontend package metadata

Not-tested: No runtime tests; metadata-only version correction
v1.5.5
2026-04-27 07:20:49 +08:00
2569718930@qq.com e90ea2b350 Document calendar local-time snapshot release
The release snapshot is no longer unreleased, so the changelog now names the published calendar-local-time tag and records the AI wording and actionable-window behavior.

Constraint: Existing snapshot tag was already pushed before this documentation correction

Confidence: high

Scope-risk: narrow

Tested: Documentation-only change reviewed with git diff

Not-tested: No runtime tests; changelog-only update
2026-04-27 07:15:34 +08:00
2569718930@qq.com 421222a52d feat: add CalendarView component for visualizing actionable scan opportunities snapshot-2026-04-27-calendar-local-time 2026-04-27 07:09:16 +08:00
2569718930@qq.com d609d3803e feat: implement scan terminal service with caching and background refresh logic 2026-04-27 06:23:09 +08:00
2569718930@qq.com 9ded30b125 feat: implement AI-driven weather scan terminal with decision utilities and forecast visualization 2026-04-27 02:18:34 +08:00
2569718930@qq.com 6819787d44 docs: add deep research report documentation 2026-04-27 01:45:44 +08:00
2569718930@qq.com e2ad51ee65 feat: implement AI city forecast streaming service and documentation 2026-04-27 01:38:37 +08:00
2569718930@qq.com 8fe25d06a5 feat: implement AiPinnedForecastView component with associated data hooks and decision utilities for AI-driven weather analysis 2026-04-27 01:14:31 +08:00
2569718930@qq.com 7e66b026b9 feat: implement AI city forecast streaming hook and utility functions for scan terminal 2026-04-27 00:54:24 +08:00
2569718930@qq.com 97719a7ff0 feat: implement market scan data utilities and service for city weather card decisioning 2026-04-27 00:50:14 +08:00
2569718930@qq.com 6f9d75c68f feat: implement ScanTerminalDashboard component for real-time weather opportunity tracking 2026-04-27 00:30:51 +08:00
2569718930@qq.com d46e0c2e81 feat: implement AI-powered pinned city forecast dashboard with real-time METAR and market analysis integration 2026-04-27 00:19:52 +08:00
2569718930@qq.com ef8ef833b9 feat: implement AI-driven METAR summary service and dashboard UI components 2026-04-26 14:03:13 +08:00
2569718930@qq.com f9ad34d7c0 feat: implement scan terminal service with AI-powered city analysis and caching support 2026-04-26 13:50:46 +08:00
2569718930@qq.com d42cdf6b51 feat: implement AI city forecast streaming service and UI components for scan terminal 2026-04-26 13:43:55 +08:00
2569718930@qq.com 5344779e32 feat: implement streaming AI city forecast service and frontend hook for real-time terminal updates 2026-04-26 13:12:03 +08:00
2569718930@qq.com dacefec39d feat: implement AI city forecast streaming service and UI component for scan terminal 2026-04-26 12:58:33 +08:00
2569718930@qq.com 670c0328c8 feat: add read-only Polymarket data collection layer for market discovery and price tracking 2026-04-26 12:47:24 +08:00
2569718930@qq.com 03eca3f93b feat: implement AiPinnedForecastView component with associated decision utilities and data hooks 2026-04-26 12:39:16 +08:00
2569718930@qq.com f39f59f47a feat: implement AI city forecasting and market scan hooks with backend API integration for the scan terminal dashboard 2026-04-26 11:28:36 +08:00
2569718930@qq.com 9b77a3a0e2 feat: implement AI city forecast and market scan integration for terminal dashboard 2026-04-26 11:08:58 +08:00
2569718930@qq.com e374ad4bf0 feat: add AI city forecast terminal and integration components 2026-04-26 10:43:14 +08:00
2569718930@qq.com 312b366a50 feat: implement PolyWeather dashboard UI with Leaflet map integration and backend data collection support 2026-04-26 10:22:11 +08:00
2569718930@qq.com 1ee8408b1f feat: implement Leaflet map hook and AI-assisted city card forecast view for dashboard 2026-04-26 10:13:44 +08:00
2569718930@qq.com d54050ceb0 feat: implement AI-driven city weather analysis and market decision dashboard components 2026-04-26 10:02:54 +08:00
2569718930@qq.com 0f23d8af9d feat: implement dashboard types, Polymarket data collection, and decision utilities for AI-driven city weather analysis 2026-04-26 09:40:02 +08:00
2569718930@qq.com da2126e33e feat: implement ScanTerminalDashboard with AI-driven city streaming and analysis features 2026-04-26 09:13:18 +08:00
2569718930@qq.com 1c644a59c6 feat: implement ScanTerminalDashboard component with AI streaming forecast and queue management 2026-04-26 08:19:00 +08:00
2569718930@qq.com 1595f4a92e feat: implement ScanTerminalDashboard with AI-driven city forecast streaming and opportunity tracking 2026-04-26 08:12:31 +08:00
2569718930@qq.com 763f131850 feat: implement AI city scanning terminal with streaming SSE support and concurrency-limited request queueing 2026-04-26 07:58:19 +08:00
2569718930@qq.com 922431d730 feat: implement agentic framework with modular skills, prompts, and agent configurations 2026-04-26 07:41:43 +08:00
2569718930@qq.com 9ef998e9e0 feat: implement ScanTerminalDashboard UI and backend service for AI-driven city weather forecasting 2026-04-26 07:24:39 +08:00
2569718930@qq.com f3f75c8cd8 feat: create DetailPanel component for displaying city weather data and charts 2026-04-26 07:12:26 +08:00
2569718930@qq.com b25c9312da feat: add multi-model Open-Meteo data collection and implement scan terminal dashboard service 2026-04-26 06:55:16 +08:00
2569718930@qq.com 901b870240 feat: implement scan terminal service with caching and add corresponding dashboard UI components 2026-04-26 05:58:07 +08:00
2569718930@qq.com 62dd1201db feat: implement scan terminal service with caching, background refresh, and AI-driven analysis capabilities 2026-04-26 05:20:38 +08:00
2569718930@qq.com 7e3146d612 feat: implement scan_terminal_service for market data analysis and caching 2026-04-26 05:03:49 +08:00
2569718930@qq.com 963b2098c0 feat: implement AI city scan proxy route and add premium dark theme dashboard styling 2026-04-26 04:32:46 +08:00
2569718930@qq.com fdf001a801 feat: implement ScanTerminalDashboard component and scan_terminal_service for real-time market opportunity monitoring 2026-04-26 04:11:20 +08:00