From 16404ccf711ee0d73d92aeb15e89773d338e5c0e Mon Sep 17 00:00:00 2001
From: "2569718930@qq.com" <2569718930@qq.com>
Date: Mon, 30 Mar 2026 00:46:01 +0800
Subject: [PATCH] Switch repository licensing to AGPL-3.0
---
LICENSE | 674 +++++++++++++++++++++++++++-
README.md | 14 +-
README_ZH.md | 13 +-
contracts/PolyWeatherCheckout.sol | 2 +-
contracts/PolyWeatherCheckoutV2.sol | 2 +-
docs/API_ZH.md | 6 +-
docs/COMMERCIALIZATION.md | 10 +-
docs/OPEN_CORE_POLICY.md | 78 ++--
docs/deep-research-report.md | 10 +-
frontend/README.md | 6 +-
scripts/train_lgbm_daily_high.py | 56 ++-
11 files changed, 753 insertions(+), 118 deletions(-)
diff --git a/LICENSE b/LICENSE
index 1a8485e3..be3f7b28 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,21 +1,661 @@
-MIT License
+ GNU AFFERO GENERAL PUBLIC LICENSE
+ Version 3, 19 November 2007
-Copyright (c) 2026 Yuanzhen Yang (yangyuan-zhen)
+ Copyright (C) 2007 Free Software Foundation, Inc.
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+author or copyright holder as a result of your choosing to follow a
+later version.
+
+ 15. Disclaimer of Warranty.
+
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+ 16. Limitation of Liability.
+
+ IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+ 17. Interpretation of Sections 15 and 16.
+
+ If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
+ If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+ To do so, attach the following notices to the program. It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+
+ Copyright (C)
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU Affero General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU Affero General Public License for more details.
+
+ You should have received a copy of the GNU Affero General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If your software can interact with users remotely through a computer
+network, you should also make sure that it provides a way for users to
+get its source. For example, if your program is a web application, its
+interface could display a "Source" link that leads users to an archive
+of the code. There are many ways you could offer source, and different
+solutions will be better for different programs; see section 13 for the
+specific requirements.
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU AGPL, see
+.
diff --git a/README.md b/README.md
index 0608183c..db63d475 100644
--- a/README.md
+++ b/README.md
@@ -3,6 +3,7 @@
Production weather-intelligence stack for temperature settlement markets.
Official dashboard: [polyweather-pro.vercel.app](https://polyweather-pro.vercel.app/)
+中文说明: [README_ZH.md](README_ZH.md)
Public docs center: `/docs/intro` on the main site (bilingual product documentation, including intraday signals, TAF, settlement sources, history, and extension).
@@ -32,14 +33,15 @@ Public docs center: `/docs/intro` on the main site (bilingual product documentat
- Trade cue now combines upper-air structure, `TAF`, market crowding, and `edge_percent`.
- Browser extension now uses `DEB` for multi-day forecast and stays positioned as a lightweight lead-in to the main site.
-## Open-Core Boundary (Important)
+## License & Commercial Boundary
-This repository follows an **Open-Core** strategy:
+This repository is licensed under **GNU AGPL-3.0 only** from `2026-03-30` onward.
-- Public in repo: weather aggregation, core analysis, dashboard, bot baseline, standard payment flow.
-- Private in production: commercial risk rules, operational thresholds, pricing strategy details, internal reconciliation policies, and growth operations tooling.
+- Public in repo: weather aggregation, core analysis, dashboard, bot baseline, and standard payment flow.
+- Not included in this repository: private production data, internal operating thresholds, commercial risk rules, pricing strategy details, and growth tooling.
+- Trademark, brand, domain, production databases, and hosted-service operations are **not** granted by the code license.
-See: [Open-Core & Commercial Boundary](docs/OPEN_CORE_POLICY.md)
+See: [AGPL-3.0 & Commercial Boundary](docs/OPEN_CORE_POLICY.md)
## Core Capabilities
@@ -168,7 +170,7 @@ docker compose logs -f polyweather | egrep "polymarket wallet activity watcher s
- Chinese API guide: [docs/API_ZH.md](docs/API_ZH.md)
- TAF signal guide (ZH): [docs/TAF_SIGNAL_ZH.md](docs/TAF_SIGNAL_ZH.md)
- Commercialization: [docs/COMMERCIALIZATION.md](docs/COMMERCIALIZATION.md)
-- Open-Core policy: [docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
+- AGPL-3.0 policy: [docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
- Supabase setup (ZH): [docs/SUPABASE_SETUP_ZH.md](docs/SUPABASE_SETUP_ZH.md)
- Configuration & secrets (ZH): [docs/CONFIGURATION_ZH.md](docs/CONFIGURATION_ZH.md)
- LightGBM daily-high model (ZH): [docs/LGBM_DAILY_HIGH_ZH.md](docs/LGBM_DAILY_HIGH_ZH.md)
diff --git a/README_ZH.md b/README_ZH.md
index cd6c0234..2edc54fc 100644
--- a/README_ZH.md
+++ b/README_ZH.md
@@ -26,14 +26,15 @@
- 运行态状态与缓存已支持 SQLite 渐进迁移:`file / dual / sqlite`。
- 已接入 EMOS/CRPS 校准链路,但当前仍保持 `emos_shadow`。
-## 开源边界(重要)
+## 许可证与商用边界(重要)
-本项目采用 **Open-Core** 策略:
+本仓库自 `2026-03-30` 起采用 **GNU AGPL-3.0-only**。
-- 仓库公开部分:天气聚合、基础分析、前端看板、Bot 基础能力、支付标准流程示例。
-- 生产私有部分:商业风控规则、运营阈值、收费策略细节、付费用户运营脚本、内部对账与审计策略。
+- 仓库公开部分:天气聚合、基础分析、前端看板、Bot 基础能力、标准支付流程。
+- 不包含在仓库中的部分:生产私有数据、商业风控规则、运营阈值、收费策略细节、内部对账与增长工具。
+- 商标、品牌、域名、生产数据库与托管服务运营能力,不因代码许可证一并授权。
-详细见:[Open-Core 与商用边界](docs/OPEN_CORE_POLICY.md)
+详细见:[AGPL-3.0 与商用边界](docs/OPEN_CORE_POLICY.md)
## 核心能力
@@ -158,7 +159,7 @@ docker compose logs -f polyweather | egrep "polymarket wallet activity watcher s
- 英文总览:[README.md](README.md)
- API 文档(中文):[docs/API_ZH.md](docs/API_ZH.md)
- 商业化说明:[docs/COMMERCIALIZATION.md](docs/COMMERCIALIZATION.md)
-- Open-Core 边界:[docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
+- AGPL-3.0 边界:[docs/OPEN_CORE_POLICY.md](docs/OPEN_CORE_POLICY.md)
- Supabase 接入:[docs/SUPABASE_SETUP_ZH.md](docs/SUPABASE_SETUP_ZH.md)
- 配置与密钥管理:[docs/CONFIGURATION_ZH.md](docs/CONFIGURATION_ZH.md)
- 前端部署(Vercel):[docs/FRONTEND_DEPLOYMENT_ZH.md](docs/FRONTEND_DEPLOYMENT_ZH.md)
diff --git a/contracts/PolyWeatherCheckout.sol b/contracts/PolyWeatherCheckout.sol
index ba3bc854..b46c325b 100644
--- a/contracts/PolyWeatherCheckout.sol
+++ b/contracts/PolyWeatherCheckout.sol
@@ -1,4 +1,4 @@
-// SPDX-License-Identifier: MIT
+// SPDX-License-Identifier: AGPL-3.0-only
pragma solidity ^0.8.24;
interface IERC20 {
diff --git a/contracts/PolyWeatherCheckoutV2.sol b/contracts/PolyWeatherCheckoutV2.sol
index cf5b2a8f..149d6212 100644
--- a/contracts/PolyWeatherCheckoutV2.sol
+++ b/contracts/PolyWeatherCheckoutV2.sol
@@ -1,4 +1,4 @@
-// SPDX-License-Identifier: MIT
+// SPDX-License-Identifier: AGPL-3.0-only
pragma solidity ^0.8.24;
interface IERC20 {
diff --git a/docs/API_ZH.md b/docs/API_ZH.md
index 14b92326..7d3a09c1 100644
--- a/docs/API_ZH.md
+++ b/docs/API_ZH.md
@@ -235,8 +235,8 @@ curl -s http://127.0.0.1:8000/api/system/status | python3 -m json.tool
docker compose logs -f polyweather | egrep "payment event loop started|payment confirm loop started|payment auto-confirmed"
```
-## 10. 开源口径说明
+## 10. AGPL 与公开口径说明
-对外公开文档仅覆盖通用 API 契约。生产商业策略参数不在公开文档披露。
+本仓库代码自 `2026-03-30` 起采用 `AGPL-3.0-only`。对外公开文档仅覆盖通用 API 契约;生产商业策略参数、私有运营阈值与托管服务能力不在公开文档披露。
-详见:[Open-Core 与商用边界](OPEN_CORE_POLICY.md)
+详见:[AGPL-3.0 与商用边界](OPEN_CORE_POLICY.md)
diff --git a/docs/COMMERCIALIZATION.md b/docs/COMMERCIALIZATION.md
index 0702688d..9857f1ca 100644
--- a/docs/COMMERCIALIZATION.md
+++ b/docs/COMMERCIALIZATION.md
@@ -41,14 +41,14 @@ PolyWeather 是面向温度结算场景的气象决策层,不是通用天气
> 说明:具体运营策略可按阶段调整,生产参数建议放私有仓库。
-## 5. 建议的开源边界
+## 5. 许可证与商用边界
-请按 Open-Core 执行:
+当前仓库代码采用 `AGPL-3.0-only`:
-- 开源:基础能力与通用支付流程。
-- 私有:商业风控、营销策略、关键运营参数、内部审计策略。
+- 公开:基础能力与通用支付流程源码。
+- 不随代码许可证授权:商业风控、营销策略、关键运营参数、内部审计策略、品牌与托管服务资产。
-详见:[Open-Core 与商用边界](OPEN_CORE_POLICY.md)
+详见:[AGPL-3.0 与商用边界](OPEN_CORE_POLICY.md)
## 6. 上线检查清单(收费前)
diff --git a/docs/OPEN_CORE_POLICY.md b/docs/OPEN_CORE_POLICY.md
index f7e8b2b9..cb3676b2 100644
--- a/docs/OPEN_CORE_POLICY.md
+++ b/docs/OPEN_CORE_POLICY.md
@@ -1,63 +1,45 @@
-# Open-Core 与商用边界
+# AGPL-3.0 与商用边界
-最后更新:`2026-03-14`
+最后更新:`2026-03-30`
-## 1. 目标
+## 1. 当前许可证
-在保持社区可用性的前提下,保护商业化阶段的核心经营资产。
+- 本仓库代码自 `2026-03-30` 起采用 **GNU Affero General Public License v3.0 only**(`AGPL-3.0-only`)。
+- 该许可证适用于仓库中未另行声明许可证的源代码与文档。
+- 如果你修改本项目并通过网络向用户提供服务,需按 AGPL 第 13 条向用户提供对应源码。
-## 2. 仓库公开范围(可开源)
+## 2. 旧版本说明
-- 天气数据采集与标准化(METAR / Open-Meteo / MGM 接口层)。
-- DEB 与基础趋势分析、概率桶计算。
-- Dashboard 基础体验与 API/BFF 结构。
-- Telegram Bot 基础命令与基础积分机制。
-- 合约支付标准流程(钱包绑定、intent、提交、确认、补单)。
+- 在本次切换前已经发布的 MIT 版本,仍按其原始许可证生效。
+- 本次变更不会追溯撤销既往已发布版本的 MIT 授权。
-## 3. 生产私有范围(建议不公开)
+## 3. 仓库公开范围
-- 商业风控参数与规则库:
- - 错价信号阈值组合、推送阈值、异常检测策略。
-- 运营策略资产:
- - 用户分层规则、促销规则、留存策略、活动模板。
-- 付费系统敏感细节:
- - 实时对账容错阈值、退款审计策略、内部财务映射规则。
-- 私有运维资产:
- - 生产告警路由、内部频道映射、应急脚本与排障手册。
+- 天气数据采集与标准化(METAR / Open-Meteo / MGM / 官方结算源接口层)。
+- DEB、基础趋势分析、概率桶、历史对账、前端看板与 Bot 基础能力。
+- 标准支付流程、链上收款合约与公开 API/BFF 结构。
-## 4. 配置与数据安全红线
+## 4. 不在仓库许可证授权范围内的资产
-- 不提交:`.env`、私钥、API key、机器人 token。
-- 不提交:生产数据库、运行时状态文件、支付流水快照。
-- 不提交:用户身份信息、钱包映射、订阅原始审计日志。
+- 商标、品牌名、域名、Logo、商店素材与市场宣传文案。
+- 生产数据库、用户资料、钱包映射、订阅审计日志、内部报表。
+- 私有运营脚本、增长工具、内部风控参数、收费策略细节与内部阈值。
+- 托管服务本身、SLA、客服、运维值守与内部告警路由。
-## 5. 推荐发布模式
+## 5. 配置与数据安全红线
-### 5.1 Community Edition(开源)
+- 不提交:`.env`、私钥、API key、机器人 token、第三方 service role key。
+- 不提交:生产数据库、运行态快照、支付流水快照、用户身份信息。
+- 不提交:仅用于线上商业判断的私有规则库与内部操作手册。
-- 提供基础分析与基础看板。
-- 可选保留只读市场扫描。
-- 默认关闭商业化运营规则。
+## 6. 对部署者的要求
-### 5.2 Production Edition(私有)
+- 若你提供公开网络服务,应在产品界面中提供清晰可访问的源码入口。
+- 若你修改了本项目再对外提供网络服务,应公开与你实际运行版本对应的源码。
+- 若你使用了仓库外的私有数据、商标或运营资产,这些额外资产不因 AGPL 自动获得授权。
-- 启用收费、订阅、积分抵扣、风控、私有监控。
-- 仅在私有仓库维护运营策略与敏感参数。
+## 7. 法务与运营建议
-## 6. 文档口径规范
-
-对外文档仅描述:
-
-- 能力边界与使用方式。
-- 可公开的技术架构。
-- 不包含可被直接复刻的商业参数。
-
-不对外文档描述:
-
-- 具体策略阈值、用户分层细则、收益归因规则。
-
-## 7. 许可证与法务建议(简版)
-
-- 建议保持仓库代码许可证与商标/品牌授权分离。
-- 若提供商业服务,建议在官网补充服务条款与隐私政策。
-- 对“订阅权益”与“可用性”做明确 SLA 与免责边界。
+- 代码许可证与商标/品牌授权应继续分离管理。
+- 官网应补充服务条款、隐私政策与付费权益说明。
+- 若后续接受外部贡献,再次调整许可证前应先确认贡献者版权归属与再许可条件。
diff --git a/docs/deep-research-report.md b/docs/deep-research-report.md
index d66004b5..3b0f49f9 100644
--- a/docs/deep-research-report.md
+++ b/docs/deep-research-report.md
@@ -2,7 +2,7 @@
## 执行摘要
-PolyWeather(仓库:`yangyuan-zhen/PolyWeather`)定位为**面向温度类结算预测市场(如 Polymarket 的温度结算合约)**的“生产级气象情报系统”,核心在于把多源天气观测/预报转化为**结算导向的概率桶(μ + bucket distribution)**,并进一步映射到市场报价完成**错价扫描**;同时提供 Web 仪表盘与 Telegram Bot 两套交互入口,并包含 Polygon 链上 USDC/USDC.e 支付、自动补单与订阅/积分体系。项目 README 明确其“Open-Core”边界:仓库公开天气聚合、基础分析、看板、Bot、标准支付流程;生产私有部分包含商业风控、阈值与运营工具等。
+PolyWeather(仓库:`yangyuan-zhen/PolyWeather`)定位为**面向温度类结算预测市场(如 Polymarket 的温度结算合约)**的“生产级气象情报系统”,核心在于把多源天气观测/预报转化为**结算导向的概率桶(μ + bucket distribution)**,并进一步映射到市场报价完成**错价扫描**;同时提供 Web 仪表盘与 Telegram Bot 两套交互入口,并包含 Polygon 链上 USDC/USDC.e 支付、自动补单与订阅/积分体系。项目 README 现明确仓库代码采用 `AGPL-3.0-only`,同时将品牌、商标、生产私有数据与运营阈值保留在代码许可证之外。
从工程实现看,截至 `2026-03-21`,项目已经完成一轮明确的工程化收口:多源天气采集仍保持现有业务能力,同时已完成采集层与 Web API 大文件拆分、CI 质量门禁、配置分级(`.env.example` / `.env.secrets.example` / 中文部署文档)、EMOS/CRPS 校准链路、运行态状态与缓存向 SQLite 的渐进迁移,以及基础可观测性接口(`/healthz`、`/api/system/status`、`/metrics`)。
这意味着报告里最初最突出的“工程地基缺失”问题,已经有一部分被关闭:`src/data_collection/weather_sources.py` 与 `web/app.py` 不再是原来的超大单文件;GitHub Actions 已覆盖 Python、前端和 Docker build;配置与密钥治理已成体系;运行态状态不再只能依赖 JSON/JSONL 文件;EMOS 也不再只是概念,而是进入了可训练、可评估、可 shadow、可门禁判断的阶段。
但项目仍处在“从可用走向稳态”的中段,而不是终局。当前真正的高优先级问题已收敛为三类:第一,**SQLite 迁移仍处于推荐的 dual 过渡模式**,线上真正切主读路径前仍需跑一段时间验证;第二,**可观测性只完成了轻量级指标层**,还没有形成完整的外部监控、阈值告警与趋势面板;第三,**EMOS 仍未达到生产切换标准**,当前门禁结论明确为 `hold`,阻塞原因是 shadow bucket brier 明显退化。支付链路方面,链下审计与容灾已明显增强:事件重放、SQLite 审计事件、RPC 多节点容灾、合约静态检查、`/ops` 支付异常单、按邮箱恢复脚本都已补齐;当前剩余风险主要集中在**链上合约本身仍是最小实现**,尚未升级到 SafeERC20、Pausable、链上套餐绑定等更强防护版本。
@@ -18,7 +18,7 @@ DEB(Dynamic Error Balancing)基于过去 N 天模型误差(MAE)倒数加
**市场层(Polymarket 行情对照)**:只读模式从 Gamma API 发现市场、从 CLOB(`py-clob-client` 或 REST 回退)读取价格/盘口并计算 edge(模型概率 − 市场概率)生成信号标签。
**商业化与支付**:订阅(`Pro Monthly 5 USDC`)、积分抵扣、Polygon 链上收款合约(USDC/USDC.e),并提供“事件监听 + 周期确认”的自动补单机制。
**支持的数据集/数据源**:项目不是传统“训练数据集+模型训练”的机器学习仓库;其“数据集”本质是外部实时/预报 API 与站点观测数据。对外部数据的使用需要遵守来源方的访问与速率限制,例如 AviationWeather Data API 明确限制请求频率(含每分钟请求上限/建议降低频率与使用缓存文件)。
-**许可证**:仓库根目录 `LICENSE` 为 MIT。 同时 README 强调 Open-Core 策略与生产私有组件边界,意味着“可复现/可审计”的范围以公开部分为准。
+**许可证**:仓库根目录 `LICENSE` 当前为 `AGPL-3.0-only`。同时 README 与策略文档明确:品牌、商标、生产私有数据与运营策略不随代码许可证一并授权。
(插图:项目 README 中包含产品截图,可用于快速理解信息架构与 UI 形态)

@@ -147,7 +147,7 @@ Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引
项目强依赖外部 API(Open-Meteo、AviationWeather、NWS、HKO、CWA、Polymarket、Supabase)。其中 AviationWeather Data API 有明确速率限制;Polymarket 官方说明 Gamma/Data/CLOB 三套 API 分属不同域,CLOB 交易端点需鉴权且策略可能变化;Supabase 明确强调 `service_role`/secret keys 绝不可暴露。若缺乏集中治理(重试/退避/熔断/降级/配额监控/密钥轮换),稳定性与合规不可控。
**可观测性已起步,但仍不构成完整监控体系**:项目现在已有 `/healthz`、`/api/system/status`、`/metrics`,并为 HTTP 与关键第三方源增加了轻量指标;但仍缺少 Prometheus/Grafana 级别的外部抓取、告警阈值、趋势面板和运行日报。这部分现在属于“已开始,不算完成”。
**EMOS 已完成工程接入,但未完成生产发布**:EMOS/CRPS 校准、shadow 观测、rollout report、上线门禁都已实现;当前真实门禁结果为 `hold`,阻塞原因是 shadow bucket brier 明显退化。因此概率引擎标准化并非未做,而是“工程完成、发布未通过”。
-**许可证/商业使用的潜在冲突点**:仓库自身是 MIT,但如果未来尝试引入外部 AI 预报模型,需要非常谨慎:GraphCast 仓库代码 Apache-2.0,但权重使用 CC BY-NC-SA 4.0(非商业),Pangu-Weather 权重同样 BY-NC-SA 且明确禁止商业用途;不加区分地把这些模型用于付费产品会留下法律风险。
+**许可证/商业使用的潜在冲突点**:仓库自身现为 `AGPL-3.0-only`,但如果未来尝试引入外部 AI 预报模型,仍需单独核验第三方代码与权重的商用条件:GraphCast 仓库代码 Apache-2.0,但权重使用 CC BY-NC-SA 4.0(非商业),Pangu-Weather 权重同样 BY-NC-SA 且明确禁止商业用途;不加区分地把这些模型用于付费产品会留下法律风险。
## 对标分析
为满足“至少 3 个相似开源项目或近期论文”对标,本报告选择三类代表:
@@ -158,7 +158,7 @@ Web/Telegram 请求 → FastAPI 调用采集器抓取/复用缓存 → 分析引
| 项目/论文 | 解决的问题 | 输出形态 | 性能/效果(公开描述) | 易用性与依赖 | 许可证要点 |
| --------------------------------------------------------- | ---------------------------------------------------- | ------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
-| **PolyWeather**(本仓库) | 温度结算市场气象情报:多源→概率桶→错价扫描→订阅/支付 | 生产级应用(Web+Bot+API+支付) | 以工程能力为主;内置 DEB、概率桶、死盘判定、市场扫描;覆盖 20 城市。 | 主要依赖外部 API;Docker Compose 一键启动。 | 仓库 MIT;Open-Core(部分生产规则私有)。 |
+| **PolyWeather**(本仓库) | 温度结算市场气象情报:多源→概率桶→错价扫描→订阅/支付 | 生产级应用(Web+Bot+API+支付) | 以工程能力为主;内置 DEB、概率桶、死盘判定、市场扫描;覆盖 20 城市。 | 主要依赖外部 API;Docker Compose 一键启动。 | 仓库 `AGPL-3.0-only`;品牌、生产私有数据与运营规则不随代码许可证授权。 |
| **GraphCast**(google-deepmind/graphcast) | 10 天全球中期预报(ML 替代/增强 NWP) | 模型代码+权重+notebooks | 论文与介绍提到在大量指标上优于主流确定性系统;仓库提供预训练权重与示例数据入口,并提示 ERA5/HRES 数据条款需另行遵守。 | 完整训练需 ERA5 等;更适合科研/平台级推理,不是产品级 BFF。 | 代码 Apache-2.0;权重 CC BY-NC-SA 4.0(商业限制)。 |
| **FourCastNet**(NVlabs/FourCastNet) | 高分辨率 data-driven 全球预报(AFNO/ViT) | 模型训练/推理代码+数据/权重链接 | README 描述:0.25° 分辨率、周尺度推理非常快,并可做大规模集合;适合平台型预报。 | 训练/数据依赖大(ERA5 子集 TB 级);工程集成成本高。 | BSD 3-Clause(代码)。 |
| **Pangu-Weather**(198808xc/Pangu-Weather + Nature 论文) | 3D Transformer 架构的中期全球预报 | ONNX 推理代码+预训练模型 | Nature 论文称在 reanalysis 上对比 IFS 有更强确定性预报表现,并强调速度优势;仓库提供 ONNX 推理与 lite 版训练说明。 | 模型文件大(多份 ~GB 级),训练资源需求高;更适合科研推理或内部平台。 | 权重 BY-NC-SA 4.0、明确禁止商业用途。 |
@@ -244,7 +244,7 @@ PolyWeather 的评测应围绕“结算场景”而非传统数值天气预报
**密钥泄露与权限滥用**:Supabase 明确强调 `service_role` 属高权限密钥,绝不可出现在前端或公开环境。缓解:密钥分级、CI secret scan、运行时最小权限、日志脱敏。
**支付链路最终一致性与链上不确定性**:链上事件索引延迟、RPC 不稳定、交易确认数不足都会导致误判。当前项目已经补齐“事件监听 + 确认补单”双路径、事件重放脚本、SQLite 审计事件与多 RPC fallback;现阶段的主要剩余风险不再是“没有防护”,而是链上合约仍为最小实现,owner 为单地址管理,且没有 pause 开关与 SafeERC20。
**引入外部 AI 预报模型的商业合规风险**:GraphCast/Pangu-Weather 的权重许可均带非商业限制(CC BY-NC-SA/BY-NC-SA);若 PolyWeather 是付费产品,必须先做法务与授权评审。缓解:只在研究环境评估;商用优先选择可商用权重/购买授权/自研。
-**Open-Core 边界导致的“公开仓库与生产行为不一致”**:README 明确生产存在私有风控与阈值。缓解:把“公开核心”的可复现与评测做扎实(接口/数据 schema/测试/评测),私有策略只作为可插拔 policy layer 接入。
+**代码公开与生产私有资产边界导致的“公开仓库与生产行为不一致”**:README 明确品牌、商标、生产私有数据与运营阈值不在代码许可证授权范围内。缓解:把“公开核心”的可复现与评测做扎实(接口/数据 schema/测试/评测),私有策略只作为可插拔 policy layer 接入。
## 参考链接
- PolyWeather 仓库(本次评估对象):https://github.com/yangyuan-zhen/PolyWeather
diff --git a/frontend/README.md b/frontend/README.md
index 56d70d0c..b2088731 100644
--- a/frontend/README.md
+++ b/frontend/README.md
@@ -170,10 +170,10 @@ Ops:
- `summary?force_refresh=true`:`no-store`
- 支付相关路由:`no-store`
-## 开源边界说明
+## AGPL 与商用边界说明
-此前端仓库包含通用产品界面和标准支付体验。
-商业策略调优、私有运营流程和敏感生产参数不在公开文档范围内。
+此前端代码随仓库一起采用 `AGPL-3.0-only`。
+生产私有运营流程、商业策略调优、敏感生产参数、品牌与托管服务能力不在代码许可证授权范围内。
详见根目录策略文档:`docs/OPEN_CORE_POLICY.md`
diff --git a/scripts/train_lgbm_daily_high.py b/scripts/train_lgbm_daily_high.py
index f788b543..f0c7bfe1 100644
--- a/scripts/train_lgbm_daily_high.py
+++ b/scripts/train_lgbm_daily_high.py
@@ -4,20 +4,13 @@ import json
import os
import sys
from datetime import datetime
-from typing import Any, Dict, List
+from typing import TYPE_CHECKING, Any, Dict, List
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-if ROOT_DIR not in sys.path:
- sys.path.insert(0, ROOT_DIR)
-import lightgbm as lgb
-import numpy as np
-
-from src.models.lgbm_features import (
- FEATURE_NAMES,
- build_training_samples,
- schema_payload,
-)
+if TYPE_CHECKING:
+ import lightgbm as lgb
+ import numpy as np
MODEL_PATH = os.path.join(ROOT_DIR, "artifacts", "models", "lgbm_daily_high.txt")
@@ -58,15 +51,21 @@ def _chronological_split(samples: List[Dict[str, Any]]) -> tuple[List[Dict[str,
return ordered[:-validation_count], ordered[-validation_count:]
-def _dataset_from_samples(samples: List[Dict[str, Any]]) -> tuple[np.ndarray, np.ndarray]:
+def _dataset_from_samples(samples: List[Dict[str, Any]], np: Any) -> tuple[Any, Any]:
features = np.asarray([row["vector"] for row in samples], dtype=np.float32)
targets = np.asarray([row["target"] for row in samples], dtype=np.float32)
return features, targets
-def _train_model(train_samples: List[Dict[str, Any]], valid_samples: List[Dict[str, Any]]) -> lgb.Booster:
- train_x, train_y = _dataset_from_samples(train_samples)
- train_data = lgb.Dataset(train_x, label=train_y, feature_name=FEATURE_NAMES, free_raw_data=True)
+def _train_model(
+ train_samples: List[Dict[str, Any]],
+ valid_samples: List[Dict[str, Any]],
+ lgb: Any,
+ np: Any,
+ feature_names: List[str],
+) -> Any:
+ train_x, train_y = _dataset_from_samples(train_samples, np)
+ train_data = lgb.Dataset(train_x, label=train_y, feature_name=feature_names, free_raw_data=True)
valid_sets = [train_data]
valid_names = ["train"]
@@ -85,8 +84,8 @@ def _train_model(train_samples: List[Dict[str, Any]], valid_samples: List[Dict[s
callbacks = []
if valid_samples:
- valid_x, valid_y = _dataset_from_samples(valid_samples)
- valid_data = lgb.Dataset(valid_x, label=valid_y, feature_name=FEATURE_NAMES, reference=train_data)
+ valid_x, valid_y = _dataset_from_samples(valid_samples, np)
+ valid_data = lgb.Dataset(valid_x, label=valid_y, feature_name=feature_names, reference=train_data)
valid_sets.append(valid_data)
valid_names.append("valid")
callbacks.append(lgb.early_stopping(stopping_rounds=15, verbose=False))
@@ -101,7 +100,7 @@ def _train_model(train_samples: List[Dict[str, Any]], valid_samples: List[Dict[s
)
-def _evaluate(booster: lgb.Booster, samples: List[Dict[str, Any]]) -> Dict[str, Any]:
+def _evaluate(booster: Any, samples: List[Dict[str, Any]], np: Any) -> Dict[str, Any]:
if not samples:
return {
"sample_count": 0,
@@ -111,7 +110,7 @@ def _evaluate(booster: lgb.Booster, samples: List[Dict[str, Any]]) -> Dict[str,
"median_mae": None,
}
- features, _ = _dataset_from_samples(samples)
+ features, _ = _dataset_from_samples(samples, np)
preds = booster.predict(features, num_iteration=booster.best_iteration)
lgbm_pairs: List[tuple[float, float]] = []
deb_pairs: List[tuple[float, float]] = []
@@ -144,14 +143,25 @@ def _evaluate(booster: lgb.Booster, samples: List[Dict[str, Any]]) -> Dict[str,
def main() -> int:
+ if ROOT_DIR not in sys.path:
+ sys.path.insert(0, ROOT_DIR)
+
+ import lightgbm as lgb
+ import numpy as np
+ from src.models.lgbm_features import (
+ FEATURE_NAMES,
+ build_training_samples,
+ schema_payload,
+ )
+
samples = build_training_samples()
if len(samples) < 16:
raise SystemExit(f"Not enough supervised samples for LightGBM training: {len(samples)}")
train_samples, valid_samples = _chronological_split(samples)
- booster = _train_model(train_samples, valid_samples)
+ booster = _train_model(train_samples, valid_samples, lgb, np, FEATURE_NAMES)
- all_features, all_targets = _dataset_from_samples(samples)
+ all_features, all_targets = _dataset_from_samples(samples, np)
final_train = lgb.Dataset(all_features, label=all_targets, feature_name=FEATURE_NAMES, free_raw_data=True)
final_booster = lgb.train(
params={
@@ -174,8 +184,8 @@ def main() -> int:
final_booster.save_model(MODEL_PATH)
metrics = {
- "validation": _evaluate(booster, valid_samples),
- "full_sample": _evaluate(final_booster, samples),
+ "validation": _evaluate(booster, valid_samples, np),
+ "full_sample": _evaluate(final_booster, samples, np),
}
schema = schema_payload(
model_path=os.path.relpath(MODEL_PATH, ROOT_DIR),