From 3cb0570eb21f86ca864e5fba4c943d53f2f1575f Mon Sep 17 00:00:00 2001 From: IceCodeNew <32576256+IceCodeNew@users.noreply.github.com> Date: Thu, 16 Jul 2026 20:24:00 +0800 Subject: [PATCH] refactor: adopt any-llm providers --- AGENTS.md | 2 + README.md | 2 +- docs/design.md | 6 +- docs/notes.md | 32 + docs/requirements.md | 4 +- env.example | 13 +- pyproject.toml | 3 + tests/test_any_llm_provider.py | 142 + tests/test_api_client.py | 23 +- tests/test_cli.py | 65 +- tests/test_config.py | 68 +- tests/test_deepseek_provider.py | 36 - tests/test_llm.py | 596 ++-- tests/test_openai_compatible_provider.py | 41 - tests/test_service.py | 8 +- uv.lock | 3347 +++++++++++++++++++++- weather_briefing/api_client.py | 18 +- weather_briefing/cli.py | 37 +- weather_briefing/config.py | 31 +- weather_briefing/llm.py | 325 ++- 20 files changed, 3977 insertions(+), 822 deletions(-) create mode 100644 tests/test_any_llm_provider.py delete mode 100644 tests/test_deepseek_provider.py delete mode 100644 tests/test_openai_compatible_provider.py diff --git a/AGENTS.md b/AGENTS.md index 62a91089..e1528e81 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -64,6 +64,7 @@ Usage notes: - Keep this file limited to development judgment, workflow constraints, and lessons that future agents could otherwise miss. Link to the other documents instead of duplicating them. - Update the document that owns a changed decision in the same change as the implementation. - Use `docs/notes.md` to explain the rationale, trade-offs, and operating boundaries behind key architecture choices when the current contract alone would not make them clear. For accepted design concerns that remain intentionally unresolved, also state the assumptions that make the choice acceptable and concrete triggers for reevaluation; update or remove the note when those assumptions change. +- Keep local audit-risk documents limited to unresolved or actively monitored findings. Remove a finding in the same change that resolves it instead of retaining a completed-history section, and never add the local audit document to version control. ## Engineering judgment @@ -71,6 +72,7 @@ Usage notes: - Separate domain reference data from implementation. Geographic bounds, classification tables, matching patterns, and similar values belong in validated data files rather than Python constants. - Treat privacy as broader than secret scanning. Locations, coordinates, private feed URLs, source content, state, and other contextual identifiers can expose a user even when they are not credentials. Use runtime configuration and public examples in committed code and tests. - Keep dependencies minimal and justify every third-party package. Use high-level security interfaces for authentication and cryptography; do not implement protocols with low-level primitives when a maintained high-level library exists. +- Before implementing an external protocol, authentication flow, structured-response validator, retry policy, rate limiter, or service client, evaluate the provider's official SDK and mature maintained high-level libraries. Prefer a thin adapter over duplicating wire formats or reusable infrastructure. If a custom implementation is necessary, document the dependency, privacy, observability, or compatibility reason in `docs/notes.md`. Do not replace small domain-specific adapters or suitable standard-library code merely to reduce line count. - Prefer timezone-aware Pendulum values in Python. Reject ambiguous timestamps, keep timezone assumptions at provider boundaries, and centralize unavoidable provider-specific fallback rules instead of spreading guesses through business logic. - Do not retain compatibility paths for abandoned internal formats unless the current requirements explicitly require them. - Keep code comments concise and in English. diff --git a/README.md b/README.md index deffc0b6..d002ad9d 100644 --- a/README.md +++ b/README.md @@ -43,7 +43,7 @@ uv run --frozen weather-briefing run briefing `env.example` 将必填项、条件必填项和选填项分别写在注释中，所有凭据和投递标识均为无效占位值。复制 `locations.example.json` 为被 Git 忽略的 `locations.json` 后可配置多个地点；示例使用北京市西城区中南海的公开坐标。每项必须有稳定 `id`，并在 `name` 与成对的 `latitude`、`longitude` 之间至少提供一项：只有名称时程序正向解析并支持降精度回退，只有坐标时通过 Nominatim 反查规范地点名和行政信息，两者都有时不发起定位请求。解析结果缓存到 `state/`。 -`LLM_PROVIDER=deepseek` 使用 `DEEPSEEK_API_KEY`、`DEEPSEEK_MODEL` 和可选的 `DEEPSEEK_BASE_URL`；DeepSeek provider 已预置官方 Base URL。`LLM_PROVIDER=openai-compatible` 使用 `LLM_API_KEY`、`LLM_MODEL` 和 `LLM_BASE_URL`。两套配置互不回退。 +LLM 调用由 any-llm SDK 承担。`LLM_PROVIDER` 使用 any-llm 的 provider ID，`LLM_MODEL` 是该 provider 接受的模型 ID；凭据、API Base 和其他认证配置直接使用 any-llm 为对应 provider 定义的环境变量。开发环境安装 `any-llm-sdk[all]` 以验证全部 provider，应用的基础运行依赖只安装 SDK 核心包；生产安装可按实际选择合并 extras，例如 `uv pip install 'weather-briefing' 'any-llm-sdk[deepseek,openai]>=1.19,<2'`。为兼容已有 DeepSeek 部署，`DEEPSEEK_MODEL` 可作为 `LLM_MODEL` 的后备，`DEEPSEEK_BASE_URL` 可作为 `DEEPSEEK_API_BASE` 的后备。 应用将带时间、级别和 logger 名称的运行日志写入标准错误；INFO 日志记录每个地点的天气 provider 顺序和逻辑降级过程，并为天气、空气质量、地理编码、LLM、RSS、辅助上下文及 Telegram 的每个实际 HTTP 请求记录 provider、operation、方法、成功或失败、耗时和 HTTP 状态或异常类型，因此可从容器日志还原外部 API 调用历史。RSS 重试与 Telegram 分片分别按实际请求次数记录。常规 INFO 日志及仅由 `DEBUG=true` 启用的非敏感诊断不记录坐标、标题、正文、URL、token、chat ID、请求 endpoint 或异常消息；DEBUG 元数据覆盖从 RSS 清洗、权威预报转发和平台渲染到 Telegram 分片接受状态的链路。若仍需排查平台渲染或分片内容，可在不重启 daemon 的情况下临时记录完整渲染正文： diff --git a/docs/design.md b/docs/design.md index 8d9c0868..1e0ae002 100644 --- a/docs/design.md +++ b/docs/design.md @@ -6,7 +6,11 @@ 核心编排不判断具体 RSS 域名、地区、模型厂商、空气质量服务或投递平台。特殊全文转发规则来自私密 JSON 配置中的 `verbatim_title_patterns`；可选 `location_ids` 决定来源适用于哪些关注地点，空数组表示全部地点。 -`OpenAICompatibleChatCompletionsProvider` 实现唯一的 OpenAI-compatible 请求逻辑，统一调用 `/chat/completions`。`DeepSeekProvider` 仅继承该实现并预置官方 Base URL，不覆盖请求或解析行为，因此部署只需提供 API Key 和模型名；OpenAI 或其他兼容服务使用通用 provider 并显式配置 Base URL。核心编排只依赖 `LLMProvider` 协议；未来接入 Anthropic 等非兼容 endpoint 时新增协议实现，不修改简报 service。原样转发规则与次日预报上下文规则分别由 `verbatim_title_patterns` 和 `forecast_title_patterns` 配置，避免来源特定标题进入代码。 +`AnyLLMStructuredProvider` 是应用与 any-llm SDK 之间的薄适配器，只负责固定严格结构化输出 schema 并把 SDK 响应转换为应用字典；模型厂商的认证、API Base、请求协议和参数差异由 any-llm 及其官方 SDK 处理。`LLM_PROVIDER` 直接使用 SDK 声明的 provider ID，配置层只验证该 ID，不维护厂商分支或复制 provider 环境变量。DeepSeek 已投入使用的 `DEEPSEEK_MODEL` 与 `DEEPSEEK_BASE_URL` 只在配置边界作为通用 `LLM_MODEL` 与 SDK `DEEPSEEK_API_BASE` 的后备。 + +开发依赖安装 `any-llm-sdk[all]`，运行依赖只声明 SDK 核心包；部署者把选定的 any-llm extras 作为独立、锁定的安装要求与应用一起安装。这样仓库可以测试所有 provider 的装载边界，而生产镜像不必携带未使用厂商的 SDK。CLI 仅向继承 any-llm `BaseOpenAIProvider` 的 provider 注入现有 `LoggedAsyncClient` 并关闭 SDK 内部重试，因为该家族明确接受 OpenAI SDK 的 `http_client` 和 `max_retries`；其他官方 SDK 的客户端参数并不统一，应用不猜测或传入不兼容参数，其重试及实际 HTTP 状态遵循对应 SDK。service 的 `LLM_MAX_ATTEMPTS` 始终是外层请求与输出修复次数。 + +`LLMStructuredOutput` 以 Pydantic 声明所有必填字段、类型、非空文本、来源数组和 advice topic，同时作为 any-llm 的 `response_format` 与 service 接收 mock/provider 输出后的复验 schema。厂商 SDK 的结构化输出能力负责生成和初次解析，本地 schema 防止测试替身或 provider 兼容差异绕过契约；来源 ID 是否属于本轮输入仍是运行时领域校验。核心编排只依赖领域端口 `LLMProvider`，它不负责任何厂商映射或 wire protocol；切换 SDK provider 不修改简报 service。原样转发规则与次日预报上下文规则分别由 `verbatim_title_patterns` 和 `forecast_title_patterns` 配置，避免来源特定标题进入代码。 ## 正文清洗与全文转发 diff --git a/docs/notes.md b/docs/notes.md index 48d2a216..cbe64b06 100644 --- a/docs/notes.md +++ b/docs/notes.md @@ -2,6 +2,38 @@ 本文补充 [design.md](design.md)，解释关键架构选择背后的理由、权衡和适用边界，尤其是仅从当前功能契约中不容易看出的运行规模或环境假设。它不是待办清单，也不复述正式设计；每条备忘应帮助维护者理解为什么采用当前方案，以及什么变化会使这个理由不再成立。涉及有意暂缓的有效设计问题时，还需要明确成立条件和重新评估触发点；假设变化时，应同步更新实现、正式设计文档和本文件。 +## 审查时应保留的显式边界 + +### 配置与启动边界 + +DeepSeek 是唯一保留旧环境变量别名的 LLM provider：`DEEPSEEK_MODEL` 后备到 `LLM_MODEL`，`DEEPSEEK_BASE_URL` 后备到 any-llm 使用的 `DEEPSEEK_API_BASE`。这是已投入部署的输入兼容，不是厂商映射；新增 provider 应直接使用 any-llm 的 provider ID 和环境变量，不得把这一分支扩展成通用 provider 配置注册表。 + +日志初始化分为两个阶段。`main()` 在读取 Settings 前以非 DEBUG 级别建立基础 handler，保证参数或配置解析失败仍有统一日志；配置成功后再用实际 `DEBUG` 值更新级别。除非启动错误改由更外层的统一运行时接管，否则不应把两次调用合并。 + +### 领域模型与平台适配边界 + +`Article.id` 是带 Feed 身份的文章级稳定 ID，用于去重和模型引用；`Article.source_id` 是 Feed 配置 ID。同一内容出现在不同 Feed 时保留不同文章 ID，以维持来源隔离和可追溯性。只有在产品明确引入跨来源 canonical identity、并定义转载和更新版本的合并规则后，才应重新评估这一选择。 + +LLM schema 到 `BriefingResult` 的转换保持为领域模型之外的 `parse_result()`。领域 dataclass 不依赖 Pydantic 或 any-llm，provider 也不拥有来源 ID 归属规则。将转换放入任一对象都会让平台 SDK 或不可信输入校验进入错误的层级。 + +Telegram HTML 与纯文本 renderer 保留少量显式重复，publisher 数量只有两个时也保留清晰分支。平台 escaping、链接、attribution、可见长度和必填配置不同；在出现第三个共享相同骨架的平台前，不用 template method 或 registry 把差异隐藏进回调和条件分支。 + +### 错误、隐私与可选诊断边界 + +异常链是否保留取决于边界。CLI 先用 `logger.exception()` 保存 traceback，再以 `SystemExit(1) from None` 避免终端重复输出；RSS 最终错误隐藏可能包含私有 Feed URL 的 `HTTPError` 链，而统一 HTTP 客户端仍记录安全的异常类型和状态。不能把 `from None` 机械视为调试信息丢失，也不能在可能泄漏私密 endpoint 的路径统一恢复异常链。 + +渲染正文诊断是可选能力，其状态读取失败不得影响消息投递，因此 `_rendered_text_logging_enabled()` 有意捕获任意 `Exception`、记录 traceback 并按关闭处理。业务请求路径不享有这个例外；例如 LLM adapter 只转换 any-llm 的公开异常，适配器编程错误应原样暴露。 + +HTTPX `request.extensions` 是可扩展输入，不保证只由 `api_client.py` 写入。日志分类必须继续验证 tuple 形状、字符串类型和安全 label，防止 SDK、transport 或未来调用方把不可信对象或文本带入日志。 + +### 异步、文件与参考数据边界 + +Nominatim 限速使用 `await asyncio.sleep()`，它只挂起当前协程并把控制权交回事件循环，不是同步阻塞。改用其他异步 sleep API 不会改善当前 asyncio 应用的并发语义；只有运行时迁移到其他异步后端时才需要调整。 + +定位缓存先写固定临时文件再原子替换。替换失败会向上传播且旧缓存保持完整；遗留临时文件会被下次写入覆盖。只有观测到权限或磁盘错误造成不可接受的残留时，才需要增加清理分支。 + +大陆行政区排除规则在载入参考数据和比较 API 返回值时都使用 `casefold()`，不存在两边归一化不一致。空气质量分级数量很小且最后一档无上限，线性扫描比为 `bisect` 拆分阈值与结果更直接。provider UTC offset 接受整分钟的 ±14 小时范围，这是合法时区边界，不应收窄。 + ## 异步编排中的同步本地持久化 ### 当前选择 diff --git a/docs/requirements.md b/docs/requirements.md index 4b2f7b46..542bd0e3 100644 --- a/docs/requirements.md +++ b/docs/requirements.md @@ -41,14 +41,14 @@ ## 架构与隐私 -1. OpenAI-compatible Chat Completions provider 承担唯一的兼容协议实现。DeepSeek provider 只允许作为继承该实现、预置 Base URL 的薄配置类，不复制请求逻辑；其他兼容服务通过 API Key、模型和 Base URL 配置切换。未来非兼容协议通过 `LLMProvider` 扩展。日常开发测试使用 mock，正式端到端测试才调用真实模型。 +1. LLM 请求协议、厂商认证、API Base 和参数差异由 any-llm SDK 及其官方 provider SDK 承担；应用支持 SDK 声明且实现 completion 的全部 provider，只保留实现 `LLMProvider` 的薄适配器、严格结构化结果 schema、运行时来源校验和非敏感请求日志分类，不得自行拼装厂商 wire protocol。日常开发测试使用 mock，正式端到端测试才调用真实模型。 2. QWeather 使用官方推荐的 JWT 身份认证：运行时以 Base64 环境变量承载的 Ed25519 私钥 PEM 签发短期 Token，项目 ID、凭据 ID、API Host 和有效期均从环境变量注入。不得使用长期 API KEY 作为默认认证方式。 3. LLM provider、RSS source、正文 cleaner、天气与空气质量上下文服务、状态存储和投递 provider 均为可替换边界。LLM 输出必须先转换为平台无关的结构化结果，再由投递 provider 使用平台专用模板生成并发送消息；Telegram HTML 等平台语法不得进入 LLM 或核心编排。 4. 公开仓库不得包含凭据、真实关注地区、真实 RSS URL、经纬度、Webhook、地理编码缓存、历史简报或运行状态。仓库只维护无效或公开地点的结构示例。 5. 提交前运行通用秘密扫描，并对项目特有的隐私配置进行检查。 6. 需求变更应同步更新本文档。 7. 配置项应经过类型、范围和必填校验；provider、source 和状态存储保持明确扩展边界，避免厂商逻辑进入核心编排。 -8. DeepSeek 使用 `DEEPSEEK_*` 配置，通用 OpenAI-compatible provider 使用 `LLM_*` 配置；RSS 只从命名 JSON 文件读取。SQLite 没有原生日期时间类型，应用仅在持久化边界将时区感知时间转换为固定宽度 UTC 文本，使文本字典序等同绝对时间顺序。 +8. `LLM_PROVIDER` 使用 any-llm provider ID，`LLM_MODEL` 使用对应模型 ID，凭据与 API Base 使用 SDK 为该 provider 定义的环境变量。应用仅兼容已投入使用的 `DEEPSEEK_MODEL` 与 `DEEPSEEK_BASE_URL`。开发依赖安装 `any-llm-sdk[all]`；运行依赖只安装 SDK 核心包，由部署者显式、可复现地安装实际 provider extras。RSS 只从命名 JSON 文件读取。SQLite 没有原生日期时间类型，应用仅在持久化边界将时区感知时间转换为固定宽度 UTC 文本，使文本字典序等同绝对时间顺序。 9. 地理范围、空气质量分级与健康提示、正文清洗默认规则、provider 默认顺序及厂商指数代码等纯领域数据应存放在独立数据文件中，由实现代码加载并校验。 10. INFO 日志必须记录每个地点的有效天气 provider 顺序，并为每次天气 API 逻辑调用记录 provider、成功或失败、耗时、成功时的实际来源与观测时间，以及失败时不包含请求内容的阶段、HTTP 状态或异常类型，使自动降级可追溯。所有实际外部 HTTP 请求，包括天气、空气质量、地理编码、LLM、RSS、辅助上下文和 Telegram 投递，还必须统一记录静态 provider、operation、方法、成功或失败、耗时，以及 HTTP 状态或异常类型；重试和分片分别按实际请求次数记录。常规 INFO 日志及仅由 DEBUG 级别启用的非敏感诊断不得包含坐标、凭据、标题、正文、URL、接收方标识、私有 endpoint、响应正文或异常消息。DEBUG 非敏感诊断应以元数据覆盖 RSS 清洗、权威预报转发、平台渲染和分片投递边界，使运维可以根据来源、发布时间、字符数、分片数和平台接受状态定位内容丢失阶段。完整渲染正文属于敏感诊断数据，默认不得记录；运行时可以通过 CLI 临时启用、查询或关闭该行为，无需重启 daemon。启用时长必须为正且不超过 24 小时，到期自动失效。只有 DEBUG 日志级别与临时开关同时有效时才输出投递 provider 生成的完整消息及平台分片；这些文本可能包含来源内容、来源 URL、坐标和其他位置上下文，但仍不得包含投递凭据、接收方标识或请求 endpoint。诊断状态初始化或读取失败不得阻断正常投递。 diff --git a/env.example b/env.example index 7f8c2211..d2094013 100644 --- a/env.example +++ b/env.example @@ -2,16 +2,13 @@ # python-dotenv and Docker Compose accept quoted values, but Docker CLI # can pass the wrapping quotes into the container as literal characters. # -# Required: select one configured LLM provider. +# Required: select an any-llm provider and model. Provider credentials and API +# bases use the environment names documented by any-llm for that provider. LLM_PROVIDER=deepseek -# Required when LLM_PROVIDER=deepseek. Base URL is optional. +LLM_MODEL=deepseek-v4-flash +# DeepSeek example. DEEPSEEK_API_BASE is optional. DEEPSEEK_API_KEY=replace-in-runtime-environment -DEEPSEEK_MODEL=deepseek-v4-flash -DEEPSEEK_BASE_URL= -# Required when LLM_PROVIDER=openai-compatible. -LLM_API_KEY= -LLM_MODEL= -LLM_BASE_URL= +DEEPSEEK_API_BASE= LLM_MAX_OUTPUT_TOKENS=8192 LLM_MAX_ATTEMPTS=3 diff --git a/pyproject.toml b/pyproject.toml index a4f01d34..9d2aec24 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,17 +10,20 @@ readme = "README.md" requires-python = ">=3.11" license = { text = "MIT" } dependencies = [ + "any-llm-sdk>=1.19,<2", "apscheduler>=3.11,<4", "beautifulsoup4>=4.13,<5", "feedparser>=6.0.11,<7", "httpx[socks]>=0.27,<1", "pendulum>=3.1,<4", + "pydantic>=2.12,<3", "PyJWT[crypto]>=2.10,<3", "python-dotenv>=1.1,<2", ] [dependency-groups] dev = [ + "any-llm-sdk[all]>=1.19,<2", "anyio>=4.11,<5", "pytest>=9,<10", "pytest-cov>=7,<8", diff --git a/tests/test_any_llm_provider.py b/tests/test_any_llm_provider.py new file mode 100644 index 00000000..27535d8a --- /dev/null +++ b/tests/test_any_llm_provider.py @@ -0,0 +1,142 @@ +import json +import logging +from types import SimpleNamespace +from typing import cast +from unittest.mock import AsyncMock + +import httpx +import pytest +from any_llm import AnyLLM + +from weather_briefing.api_client import LoggedAsyncClient +from weather_briefing.llm import ( + AnyLLMStructuredProvider, + LLMStructuredOutput, + create_any_llm_provider, +) + + +async def test_any_llm_provider_uses_structured_chat_completion() -> None: + model_result = { + "headline": "Briefing", + "headline_source_ids": ["source"], + "conclusions": [], + "active_warnings": [], + "resolved_warning_ids": [], + "advice": [], + "disaster_tracking": [], + "should_publish": True, + } + client = SimpleNamespace( + acompletion=AsyncMock( + return_value=SimpleNamespace( + choices=[SimpleNamespace(message=SimpleNamespace(content=json.dumps(model_result)))] + ) + ) + ) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="deepseek", + model="requested-model", + max_output_tokens=4096, + ) + + result = await provider.summarize("Return JSON", {"input": "数据"}) + + client.acompletion.assert_awaited_once_with( + model="requested-model", + messages=[ + {"role": "system", "content": "Return JSON"}, + {"role": "user", "content": '{"input": "数据"}'}, + ], + response_format=LLMStructuredOutput, + temperature=0.2, + max_tokens=4096, + ) + assert result == model_result + + +async def test_factory_accepts_every_any_llm_completion_provider(monkeypatch) -> None: + created: list[tuple[str, dict[str, object]]] = [] + + def fake_create(provider: str, **options: object) -> SimpleNamespace: + created.append((provider, options)) + return SimpleNamespace() + + monkeypatch.setattr(AnyLLM, "create", fake_create) + async with httpx.AsyncClient() as http_client: + completion_providers = [ + provider + for provider in AnyLLM.get_supported_providers() + if AnyLLM.get_provider_class(provider).SUPPORTS_COMPLETION + ] + adapters = [create_any_llm_provider(provider, "model", 1024, http_client) for provider in completion_providers] + + assert [adapter.provider for adapter in adapters] == completion_providers + assert [provider for provider, _ in created] == completion_providers + + +async def test_factory_rejects_provider_without_completion() -> None: + async with httpx.AsyncClient() as http_client: + with pytest.raises(ValueError, match="does not support completion"): + create_any_llm_provider("voyage", "model", 1024, http_client) + + +async def test_any_llm_deepseek_uses_injected_logged_http_client(caplog) -> None: + requests: list[httpx.Request] = [] + model_result = { + "headline": "Briefing", + "headline_source_ids": ["source"], + "conclusions": [], + "active_warnings": [], + "resolved_warning_ids": [], + "advice": [], + "disaster_tracking": [], + "should_publish": True, + } + + def handler(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response( + 200, + json={ + "id": "completion-id", + "object": "chat.completion", + "created": 1, + "model": "requested-model", + "choices": [ + { + "index": 0, + "finish_reason": "stop", + "message": { + "role": "assistant", + "content": json.dumps(model_result), + }, + } + ], + }, + ) + + caplog.set_level(logging.INFO, logger="weather_briefing.api_client") + async with LoggedAsyncClient(transport=httpx.MockTransport(handler)) as http_client: + sdk_client = AnyLLM.create( + "deepseek", + api_key="runtime-key", + api_base="https://api.example.invalid", + http_client=http_client, + ) + provider = AnyLLMStructuredProvider( + sdk_client, + provider="deepseek", + model="requested-model", + max_output_tokens=4096, + ) + + result = await provider.summarize("Return JSON", {"input": "data"}) + + request_body = json.loads(requests[0].content) + assert requests[0].url.path == "/chat/completions" + assert request_body["model"] == "requested-model" + assert request_body["max_tokens"] == 4096 + assert result == model_result + assert "provider=deepseek operation=chat-completions method=POST" in caplog.text diff --git a/tests/test_api_client.py b/tests/test_api_client.py index 615e596f..60072d72 100644 --- a/tests/test_api_client.py +++ b/tests/test_api_client.py @@ -3,7 +3,7 @@ import httpx import pytest -from weather_briefing.api_client import LoggedAsyncClient, api_call_extensions +from weather_briefing.api_client import LoggedAsyncClient, api_call_context, api_call_extensions async def test_logged_client_records_annotated_success_without_request_data(caplog) -> None: @@ -68,6 +68,27 @@ async def test_logged_client_records_unannotated_requests_as_unclassified(caplog assert "API call started provider=unclassified operation=request method=GET" in caplog.text +async def test_context_classifies_sdk_request_without_extensions(caplog) -> None: + caplog.set_level(logging.INFO, logger="weather_briefing.api_client") + async with LoggedAsyncClient(transport=httpx.MockTransport(lambda _: httpx.Response(200))) as client: + with api_call_context("deepseek", "chat-completions"): + await client.get("https://private.example.invalid/v1/chat/completions") + + assert "API call started provider=deepseek operation=chat-completions method=GET" in caplog.text + + +async def test_request_extensions_override_sdk_context(caplog) -> None: + caplog.set_level(logging.INFO, logger="weather_briefing.api_client") + async with LoggedAsyncClient(transport=httpx.MockTransport(lambda _: httpx.Response(200))) as client: + with api_call_context("deepseek", "chat-completions"): + await client.get( + "https://private.example.invalid/weather", + extensions=api_call_extensions("open-meteo", "weather-forecast"), + ) + + assert "API call started provider=open-meteo operation=weather-forecast method=GET" in caplog.text + + @pytest.mark.parametrize( "identity", ("invalid", ("provider",), (1, "operation"), ("unsafe label", "operation")), diff --git a/tests/test_cli.py b/tests/test_cli.py index 65c2acfd..e444ee6e 100644 --- a/tests/test_cli.py +++ b/tests/test_cli.py @@ -37,7 +37,6 @@ run, ) from weather_briefing.config import Settings -from weather_briefing.llm import OpenAICompatibleChatCompletionsProvider from weather_briefing.models import LocationSpec, ResolvedLocation from weather_briefing.state import SQLiteStateStore @@ -887,42 +886,52 @@ async def fake_service_run(kind: str, n: object, **kwargs: object) -> str | None class TestLLMProvider: - async def test_deepseek_with_custom_base_url(self, async_client: httpx.AsyncClient) -> None: + async def test_deepseek_with_custom_base_url(self, async_client: httpx.AsyncClient, monkeypatch) -> None: + calls: list[tuple[tuple[object, ...], dict[str, object]]] = [] + sdk_client = SimpleNamespace() + monkeypatch.setattr( + "weather_briefing.cli.create_any_llm_provider", + lambda *args, **kwargs: calls.append((args, kwargs)) or sdk_client, + ) settings = _make_fake_settings( llm_provider="deepseek", llm_base_url="https://custom.example.invalid", ) provider = _llm_provider(settings, async_client) - assert isinstance(provider, OpenAICompatibleChatCompletionsProvider) - assert provider.base_url == "https://custom.example.invalid" - - async def test_deepseek_without_base_url(self, async_client: httpx.AsyncClient) -> None: + assert provider is sdk_client + assert calls == [ + ( + ("deepseek", "m", 8192, async_client), + { + "api_key": "k", + "api_base": "https://custom.example.invalid", + }, + ) + ] + + async def test_deepseek_without_base_url(self, async_client: httpx.AsyncClient, monkeypatch) -> None: + calls: list[tuple[tuple[object, ...], dict[str, object]]] = [] + monkeypatch.setattr( + "weather_briefing.cli.create_any_llm_provider", + lambda *args, **kwargs: calls.append((args, kwargs)) or SimpleNamespace(), + ) settings = _make_fake_settings(llm_provider="deepseek", llm_base_url=None) provider = _llm_provider(settings, async_client) - assert isinstance(provider, OpenAICompatibleChatCompletionsProvider) - assert provider.base_url == "https://api.deepseek.com" - - async def test_openai_compatible_missing_base_url(self, async_client: httpx.AsyncClient) -> None: - settings = _make_fake_settings( - llm_provider="openai-compatible", - llm_base_url=None, - ) - with pytest.raises(ValueError, match="LLM_BASE_URL"): - _llm_provider(settings, async_client) - - async def test_openai_compatible_with_base_url(self, async_client: httpx.AsyncClient) -> None: - settings = _make_fake_settings( - llm_provider="openai-compatible", - llm_base_url="https://compatible.example.invalid/v1", + assert provider is not None + assert calls[0][0][:3] == ("deepseek", "m", 8192) + assert calls[0][1]["api_base"] is None + + async def test_arbitrary_any_llm_provider_is_forwarded(self, async_client: httpx.AsyncClient, monkeypatch) -> None: + calls: list[tuple[tuple[object, ...], dict[str, object]]] = [] + monkeypatch.setattr( + "weather_briefing.cli.create_any_llm_provider", + lambda *args, **kwargs: calls.append((args, kwargs)) or SimpleNamespace(), ) + settings = replace(_make_fake_settings(llm_provider="mistral"), api_key=None, llm_base_url=None) provider = _llm_provider(settings, async_client) - assert isinstance(provider, OpenAICompatibleChatCompletionsProvider) - assert provider.base_url == "https://compatible.example.invalid/v1" - - async def test_unsupported_provider(self, async_client: httpx.AsyncClient) -> None: - settings = _make_fake_settings(llm_provider="unsupported") - with pytest.raises(ValueError, match="Unsupported LLM provider"): - _llm_provider(settings, async_client) + assert provider is not None + assert calls[0][0][:3] == ("mistral", "m", 8192) + assert calls[0][1] == {"api_key": None, "api_base": None} class TestDeliveryProvider: diff --git a/tests/test_config.py b/tests/test_config.py index a74e4944..de5d4f4c 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -9,7 +9,7 @@ def _required_environment(monkeypatch) -> None: values = { "DEEPSEEK_API_KEY": "test-key", - "DEEPSEEK_MODEL": "test-model", + "LLM_MODEL": "test-model", "BRIEFING_LOCATIONS_FILE": str(Path(__file__).parents[1] / "locations.example.json"), "RSS_SOURCES_FILE": str(Path(__file__).parents[1] / "rss-sources.example.json"), } @@ -301,19 +301,49 @@ def test_positive_operational_settings_reject_zero(monkeypatch, name: str) -> No Settings.from_env() -def test_generic_llm_provider_uses_generic_configuration(monkeypatch) -> None: +def test_any_llm_provider_uses_sdk_managed_configuration(monkeypatch) -> None: _required_environment(monkeypatch) - monkeypatch.setenv("LLM_PROVIDER", "openai-compatible") - monkeypatch.setenv("LLM_API_KEY", "generic-key") + monkeypatch.setenv("LLM_PROVIDER", "mistral") + monkeypatch.setenv("MISTRAL_API_KEY", "generic-key") monkeypatch.setenv("LLM_MODEL", "generic-model") - monkeypatch.setenv("LLM_BASE_URL", "https://compatible.example.invalid/v1") + monkeypatch.setenv("MISTRAL_API_BASE", "https://compatible.example.invalid/v1") settings = Settings.from_env() - assert settings.api_key == "generic-key" - assert settings.llm_provider == "openai-compatible" + assert settings.api_key is None + assert settings.llm_provider == "mistral" assert settings.llm_model == "generic-model" - assert settings.llm_base_url == "https://compatible.example.invalid/v1" + assert settings.llm_base_url is None + + +def test_deepseek_model_name_remains_compatible(monkeypatch) -> None: + _required_environment(monkeypatch) + monkeypatch.delenv("LLM_MODEL") + monkeypatch.setenv("DEEPSEEK_MODEL", "existing-model") + + settings = Settings.from_env() + + assert settings.llm_model == "existing-model" + + +def test_deepseek_prefers_any_llm_api_base_name(monkeypatch) -> None: + _required_environment(monkeypatch) + monkeypatch.setenv("DEEPSEEK_BASE_URL", "https://existing.example.invalid") + monkeypatch.setenv("DEEPSEEK_API_BASE", "https://sdk.example.invalid") + + settings = Settings.from_env() + + assert settings.llm_base_url == "https://sdk.example.invalid" + + +def test_deepseek_accepts_any_llm_api_base_name(monkeypatch) -> None: + _required_environment(monkeypatch) + monkeypatch.delenv("DEEPSEEK_BASE_URL", raising=False) + monkeypatch.setenv("DEEPSEEK_API_BASE", "https://sdk.example.invalid") + + settings = Settings.from_env() + + assert settings.llm_base_url == "https://sdk.example.invalid" class TestScheduleSettings: @@ -377,12 +407,26 @@ def test_greeting_minute_out_of_bounds_rejected(self, monkeypatch, value: str) - class TestConfigErrorPaths: - def test_missing_required_llm_key_raises_error(self, monkeypatch) -> None: + def test_missing_required_llm_model_raises_error(self, monkeypatch) -> None: + _required_environment(monkeypatch) + monkeypatch.delenv("LLM_MODEL") + monkeypatch.delenv("DEEPSEEK_MODEL", raising=False) + + with pytest.raises(ConfigurationError, match="LLM_MODEL"): + Settings.from_env() + + def test_unsupported_llm_provider_raises_error(self, monkeypatch) -> None: + _required_environment(monkeypatch) + monkeypatch.setenv("LLM_PROVIDER", "unsupported") + + with pytest.raises(ConfigurationError, match="Unsupported LLM_PROVIDER"): + Settings.from_env() + + def test_llm_provider_without_completion_raises_error(self, monkeypatch) -> None: _required_environment(monkeypatch) - monkeypatch.setenv("LLM_PROVIDER", "openai-compatible") - monkeypatch.delenv("DEEPSEEK_API_KEY", raising=False) + monkeypatch.setenv("LLM_PROVIDER", "voyage") - with pytest.raises(ConfigurationError, match="LLM_API_KEY"): + with pytest.raises(ConfigurationError, match="does not support completion"): Settings.from_env() def test_invalid_float_env_value_raises_error(self, monkeypatch) -> None: diff --git a/tests/test_deepseek_provider.py b/tests/test_deepseek_provider.py deleted file mode 100644 index 4b7f36a2..00000000 --- a/tests/test_deepseek_provider.py +++ /dev/null @@ -1,36 +0,0 @@ -import json - -import httpx - -from weather_briefing.llm import DeepSeekProvider - - -async def test_deepseek_provider_reuses_chat_completions_with_default_base_url() -> None: - requests: list[httpx.Request] = [] - model_result = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - def handler(request: httpx.Request) -> httpx.Response: - requests.append(request) - return httpx.Response( - 200, - json={"choices": [{"message": {"content": json.dumps(model_result)}}]}, - ) - - async with httpx.AsyncClient(transport=httpx.MockTransport(handler)) as client: - provider = DeepSeekProvider( - client, - api_key="runtime-key", - model="requested-model", - max_output_tokens=4096, - ) - result = await provider.summarize("Return JSON", {"input": "data"}) - - assert requests[0].url == "https://api.deepseek.com/chat/completions" - assert result == model_result diff --git a/tests/test_llm.py b/tests/test_llm.py index 24d261fa..9eadcd93 100644 --- a/tests/test_llm.py +++ b/tests/test_llm.py @@ -1,40 +1,38 @@ import json +from copy import deepcopy +from types import SimpleNamespace +from typing import Any, cast +from unittest.mock import AsyncMock -import httpx import pendulum import pytest +from any_llm import AnyLLM +from any_llm.exceptions import ProviderError -from weather_briefing.llm import ( - LLMError, - OpenAICompatibleChatCompletionsProvider, - parse_result, -) +from weather_briefing.llm import AnyLLMStructuredProvider, LLMError, LLMStructuredOutput, parse_result -def test_rejects_model_invented_source() -> None: - payload = { +def _valid_payload() -> dict[str, Any]: + return { "headline": "Briefing", "headline_source_ids": ["source"], - "conclusions": [{"text": "Claim", "source_ids": ["invented"]}], + "conclusions": [], "active_warnings": [], "resolved_warning_ids": [], - "advice": [], "disaster_tracking": [], + "advice": [], + "should_publish": True, } - with pytest.raises(LLMError, match="unknown source"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"real"}, - ) -def test_accepts_suppressed_message_with_unchanged_active_warning() -> None: - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [ +def _now() -> pendulum.DateTime: + return pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai") + + +def test_accepts_complete_suppressed_message_with_active_warning() -> None: + payload = _valid_payload() + payload.update( + active_warnings=[ { "id": "warning", "title": "Warning", @@ -43,172 +41,99 @@ def test_accepts_suppressed_message_with_unchanged_active_warning() -> None: "source_ids": ["source"], } ], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - "should_publish": False, - } - - result = parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, + advice=[{"topic": "clothing", "text": "Wear layers", "source_ids": ["source"]}], + conclusions=[{"text": "Cool morning", "source_ids": ["source"]}], + disaster_tracking=[{"text": "Storm nearby", "source_ids": ["source"]}], + should_publish=False, ) + result = parse_result(payload, _now(), {"source"}) + assert not result.should_publish assert result.active_warnings[0].id == "warning" + assert result.advice[0].topic.value == "clothing" + assert result.conclusions[0].text == "Cool morning" + assert result.disaster_tracking[0].text == "Storm nearby" + assert result.raw_payload == payload -def test_rejects_result_time_without_timezone() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - +def test_rejects_result_time_without_timezone_before_schema_validation() -> None: with pytest.raises(ValueError, match="timezone information"): - parse_result(payload, pendulum.naive(2026, 7, 13, 9), set()) - - -def test_rejects_conclusions_not_an_array() -> None: - payload = { - "headline": "Briefing", - "conclusions": "not-an-array", - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - with pytest.raises(LLMError, match="must be an array"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) - - -def test_rejects_conclusion_entry_not_a_dict() -> None: - payload = { - "headline": "Briefing", - "conclusions": ["not-a-dict"], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - with pytest.raises(LLMError, match="entries must be objects"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) - - -def test_rejects_conclusion_without_source_ids() -> None: - payload = { - "headline": "Briefing", - "conclusions": [{"text": "Claim"}], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - with pytest.raises(LLMError, match="must cite at least one source"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + parse_result({}, pendulum.naive(2026, 7, 13, 9), set()) -@pytest.mark.parametrize("source_ids", [None, "source", [None], [""]]) -def test_rejects_malformed_source_ids(source_ids) -> None: - payload = { - "headline": "Briefing", - "conclusions": [{"text": "Claim", "source_ids": source_ids}], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } +@pytest.mark.parametrize("field", tuple(_valid_payload())) +def test_rejects_every_missing_required_top_level_field(field: str) -> None: + payload = _valid_payload() + del payload[field] - with pytest.raises(LLMError, match="source_ids must"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) + with pytest.raises(LLMError, match=rf"schema validation failed at {field}"): + parse_result(payload, _now(), {"source"}) -@pytest.mark.parametrize("key", ["conclusions", "disaster_tracking", "advice"]) -@pytest.mark.parametrize("text", [None, "", " ", 42]) -def test_rejects_sourced_item_without_non_empty_text(key: str, text) -> None: - item = {"text": text, "source_ids": ["source"]} - if key == "advice": - item["topic"] = "clothing" - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - key: [item], - } +@pytest.mark.parametrize( + ("field", "value"), + ( + ("headline", None), + ("headline", " "), + ("headline_source_ids", []), + ("headline_source_ids", "source"), + ("conclusions", "not-an-array"), + ("active_warnings", "not-an-array"), + ("resolved_warning_ids", "warning"), + ("disaster_tracking", "not-an-array"), + ("advice", "not-an-array"), + ("should_publish", "yes"), + ), +) +def test_rejects_invalid_top_level_field(field: str, value: object) -> None: + payload = _valid_payload() + payload[field] = value - with pytest.raises(LLMError, match=f"{key} entries must contain non-empty text"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) + with pytest.raises(LLMError, match=rf"schema validation failed at {field}"): + parse_result(payload, _now(), {"source"}) -def test_rejects_active_warnings_not_an_array() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": "not-an-array", - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } +@pytest.mark.parametrize("section", ("conclusions", "disaster_tracking")) +@pytest.mark.parametrize( + "item", + ( + "not-an-object", + {"text": "Claim"}, + {"text": "", "source_ids": ["source"]}, + {"text": 42, "source_ids": ["source"]}, + {"text": "Claim", "source_ids": []}, + {"text": "Claim", "source_ids": [None]}, + ), +) +def test_rejects_invalid_sourced_item(section: str, item: object) -> None: + payload = _valid_payload() + payload[section] = [item] - with pytest.raises(LLMError, match="active_warnings must be an array"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + with pytest.raises(LLMError, match=rf"schema validation failed at {section}.0"): + parse_result(payload, _now(), {"source"}) -def test_rejects_warning_entry_not_a_dict() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": ["not-a-dict"], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], +@pytest.mark.parametrize("field", ("id", "title", "status", "detail", "source_ids")) +def test_rejects_incomplete_warning(field: str) -> None: + warning = { + "id": "w1", + "title": "Warning", + "status": "active", + "detail": "Details", + "source_ids": ["source"], } + del warning[field] + payload = _valid_payload() + payload["active_warnings"] = [warning] - with pytest.raises(LLMError, match="active_warnings entries must be objects"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + with pytest.raises(LLMError, match=rf"schema validation failed at active_warnings.0.{field}"): + parse_result(payload, _now(), {"source"}) @pytest.mark.parametrize("field", ("id", "title", "status", "detail")) @pytest.mark.parametrize("value", (None, "", " ", 42)) -def test_rejects_warning_without_required_text(field: str, value: object) -> None: +def test_rejects_invalid_warning_text(field: str, value: object) -> None: warning = { "id": "w1", "title": "Warning", @@ -217,249 +142,162 @@ def test_rejects_warning_without_required_text(field: str, value: object) -> Non "source_ids": ["source"], } warning[field] = value - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [warning], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } + payload = _valid_payload() + payload["active_warnings"] = [warning] - with pytest.raises(LLMError, match=rf"active_warnings entries: {field} must be a non-empty string"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) + with pytest.raises(LLMError, match=rf"schema validation failed at active_warnings.0.{field}"): + parse_result(payload, _now(), {"source"}) -def test_rejects_warning_without_source_ids() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [{"id": "w1", "title": "W", "status": "active", "detail": "D"}], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } +@pytest.mark.parametrize( + "advice", + ( + ["not-an-object"], + [{"text": "Advice", "source_ids": ["source"]}], + [{"topic": "unknown", "text": "Advice", "source_ids": ["source"]}], + ), +) +def test_rejects_invalid_advice(advice: object) -> None: + payload = _valid_payload() + payload["advice"] = advice - with pytest.raises(LLMError, match="source_ids must cite at least one source"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + with pytest.raises(LLMError, match=r"schema validation failed at advice.0"): + parse_result(payload, _now(), {"source"}) -@pytest.mark.parametrize("source_ids", [None, "source", [1], [""]]) -def test_rejects_warning_with_malformed_source_ids(source_ids: object) -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [{"id": "w1", "title": "W", "status": "active", "detail": "D", "source_ids": source_ids}], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } +@pytest.mark.parametrize( + ("section", "item"), + ( + ("headline_source_ids", ["invented"]), + ("conclusions", [{"text": "Claim", "source_ids": ["invented"]}]), + ( + "active_warnings", + [ + { + "id": "w1", + "title": "Warning", + "status": "active", + "detail": "Details", + "source_ids": ["invented"], + } + ], + ), + ("disaster_tracking", [{"text": "Storm", "source_ids": ["invented"]}]), + ("advice", [{"topic": "mask", "text": "Mask", "source_ids": ["invented"]}]), + ), +) +def test_rejects_unknown_source_in_every_cited_section(section: str, item: object) -> None: + payload = _valid_payload() + payload[section] = deepcopy(item) - with pytest.raises(LLMError, match="source_ids must"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) + with pytest.raises(LLMError, match="unknown source"): + parse_result(payload, _now(), {"source"}) -def test_rejects_warning_with_unknown_source_id() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [{"id": "w1", "title": "W", "status": "active", "detail": "D", "source_ids": ["unknown"]}], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } +def test_rejects_unexpected_response_field() -> None: + payload = _valid_payload() + payload["unexpected"] = True - with pytest.raises(LLMError, match="unknown source ID"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + with pytest.raises(LLMError, match=r"schema validation failed at unexpected"): + parse_result(payload, _now(), {"source"}) -@pytest.mark.parametrize("headline", (None, "", " ", 42)) -def test_rejects_result_without_headline_text(headline: object) -> None: - payload = { - "headline": headline, - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - with pytest.raises(LLMError, match="headline must be a non-empty string"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, +async def test_provider_accepts_typed_parsed_response() -> None: + parsed = LLMStructuredOutput.model_validate(_valid_payload()) + client = SimpleNamespace( + acompletion=AsyncMock( + return_value=SimpleNamespace( + choices=[SimpleNamespace(message=SimpleNamespace(parsed=parsed, content=None))] + ) ) + ) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) + assert await provider.summarize("prompt", {}) == _valid_payload() -@pytest.mark.parametrize("resolved_warning_ids", [None, "warning", [1], [""]]) -def test_rejects_malformed_resolved_warning_ids(resolved_warning_ids: object) -> None: - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": resolved_warning_ids, - "advice": [], - "disaster_tracking": [], - } - with pytest.raises(LLMError, match="resolved_warning_ids must"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, +async def test_provider_rejects_empty_json_content() -> None: + client = SimpleNamespace( + acompletion=AsyncMock( + return_value=SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content=""))]) ) + ) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) - -def test_rejects_non_boolean_should_publish() -> None: - payload = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - "should_publish": "yes", - } - - with pytest.raises(LLMError, match="should_publish must be a boolean"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - set(), - ) + with pytest.raises(LLMError, match="empty JSON"): + await provider.summarize("prompt", {}) -@pytest.mark.parametrize("field", ("headline_source_ids",)) -def test_rejects_summary_without_source_ids(field: str) -> None: - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - del payload[field] - - with pytest.raises(LLMError, match=rf"{field} must cite"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) +@pytest.mark.parametrize( + ("response", "message"), + ( + (SimpleNamespace(choices=[]), "no completion choices"), + (SimpleNamespace(choices=[SimpleNamespace()]), "missing a message"), + ), +) +async def test_provider_rejects_malformed_completion_response(response: object, message: str) -> None: + client = SimpleNamespace(acompletion=AsyncMock(return_value=response)) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) + with pytest.raises(LLMError, match=message): + await provider.summarize("prompt", {}) -def test_rejects_advice_without_a_valid_topic() -> None: - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [{"text": "Advice", "source_ids": ["source"]}], - "disaster_tracking": [], - } - with pytest.raises(LLMError, match="must use a valid topic"): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, +async def test_provider_rejects_invalid_structured_response() -> None: + client = SimpleNamespace( + acompletion=AsyncMock( + return_value=SimpleNamespace( + choices=[SimpleNamespace(message=SimpleNamespace(content=json.dumps([1, 2, 3])))] + ) ) + ) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) + with pytest.raises(LLMError, match="schema validation"): + await provider.summarize("prompt", {}) -@pytest.mark.parametrize( - ("advice", "message"), - (("not-an-array", "advice must be an array"), (["not-an-object"], "advice entries must be objects")), -) -def test_rejects_invalid_advice_structure(advice: object, message: str) -> None: - payload = { - "headline": "Briefing", - "headline_source_ids": ["source"], - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": advice, - "disaster_tracking": [], - } - with pytest.raises(LLMError, match=message): - parse_result( - payload, - pendulum.datetime(2026, 7, 13, 9, tz="Asia/Shanghai"), - {"source"}, - ) +async def test_provider_wraps_sdk_error() -> None: + client = SimpleNamespace(acompletion=AsyncMock(side_effect=ProviderError("upstream failed"))) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) + with pytest.raises(LLMError, match="LLM request"): + await provider.summarize("prompt", {}) -async def test_openai_provider_rejects_empty_json_content() -> None: - async with httpx.AsyncClient( - transport=httpx.MockTransport( - lambda _: httpx.Response( - 200, - json={"choices": [{"message": {"content": ""}}]}, - ) - ) - ) as client: - provider = OpenAICompatibleChatCompletionsProvider( - client, - api_key="key", - base_url="https://api.example.invalid/v1", - model="model", - max_output_tokens=1024, - ) - with pytest.raises(LLMError, match="empty JSON"): - await provider.summarize("prompt", {}) +async def test_provider_does_not_mask_programming_errors() -> None: + client = SimpleNamespace(acompletion=AsyncMock(side_effect=AttributeError("adapter bug"))) + provider = AnyLLMStructuredProvider( + cast("AnyLLM", client), + provider="openai", + model="model", + max_output_tokens=1024, + ) -async def test_openai_provider_rejects_non_dict_response() -> None: - async with httpx.AsyncClient( - transport=httpx.MockTransport( - lambda _: httpx.Response( - 200, - json={"choices": [{"message": {"content": json.dumps([1, 2, 3])}}]}, - ) - ) - ) as client: - provider = OpenAICompatibleChatCompletionsProvider( - client, - api_key="key", - base_url="https://api.example.invalid/v1", - model="model", - max_output_tokens=1024, - ) - with pytest.raises(LLMError, match="JSON object"): - await provider.summarize("prompt", {}) - - -async def test_openai_provider_rejects_http_error_response() -> None: - async with httpx.AsyncClient(transport=httpx.MockTransport(lambda _: httpx.Response(500))) as client: - provider = OpenAICompatibleChatCompletionsProvider( - client, - api_key="key", - base_url="https://api.example.invalid/v1", - model="model", - max_output_tokens=1024, - ) - with pytest.raises(LLMError, match="LLM request"): - await provider.summarize("prompt", {}) + with pytest.raises(AttributeError, match="adapter bug"): + await provider.summarize("prompt", {}) diff --git a/tests/test_openai_compatible_provider.py b/tests/test_openai_compatible_provider.py deleted file mode 100644 index 304aa226..00000000 --- a/tests/test_openai_compatible_provider.py +++ /dev/null @@ -1,41 +0,0 @@ -import json - -import httpx - -from weather_briefing.llm import OpenAICompatibleChatCompletionsProvider - - -async def test_openai_compatible_provider_uses_chat_completions_json_mode() -> None: - requests: list[httpx.Request] = [] - model_result = { - "headline": "Briefing", - "conclusions": [], - "active_warnings": [], - "resolved_warning_ids": [], - "advice": [], - "disaster_tracking": [], - } - - def handler(request: httpx.Request) -> httpx.Response: - requests.append(request) - return httpx.Response( - 200, - json={"choices": [{"message": {"content": json.dumps(model_result)}}]}, - ) - - async with httpx.AsyncClient(transport=httpx.MockTransport(handler)) as client: - provider = OpenAICompatibleChatCompletionsProvider( - client, - api_key="runtime-key", - base_url="https://api.example.invalid/v1", - model="requested-model", - max_output_tokens=4096, - ) - result = await provider.summarize("Return JSON", {"input": "data"}) - - request_body = json.loads(requests[0].content) - assert requests[0].url.path == "/v1/chat/completions" - assert request_body["model"] == "requested-model" - assert request_body["response_format"] == {"type": "json_object"} - assert request_body["messages"][0] == {"role": "system", "content": "Return JSON"} - assert result == model_result diff --git a/tests/test_service.py b/tests/test_service.py index 2c5edcd6..fe764c50 100644 --- a/tests/test_service.py +++ b/tests/test_service.py @@ -1153,6 +1153,7 @@ async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dic "resolved_warning_ids": [], "advice": [], "disaster_tracking": [], + "should_publish": True, } if self._omit_headline: del invalid_result["headline"] @@ -1169,6 +1170,7 @@ async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dic "resolved_warning_ids": [], "advice": [], "disaster_tracking": [], + "should_publish": True, } @@ -1248,6 +1250,7 @@ async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dic "resolved_warning_ids": [], "advice": [], "disaster_tracking": [], + "should_publish": True, } publisher = RecordingPublisher() @@ -1265,9 +1268,12 @@ async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dic delivery, StaticWeatherContextProvider(), ) - with pytest.raises(LLMError, match="validation failed"): + with pytest.raises(LLMError, match="validation failed") as exc_info: await service.run("briefing", now) + assert exc_info.value.__cause__ is not None + assert "visible characters; limit is 10" in str(exc_info.value.__cause__) + async def test_is_forecast_article_returns_false_for_unknown_feed(tmp_path: Path) -> None: timezone = pendulum.timezone("Asia/Shanghai") diff --git a/uv.lock b/uv.lock index 4ae2cf77..bb8197cc 100644 --- a/uv.lock +++ b/uv.lock @@ -1,6 +1,254 @@ version = 1 revision = 3 requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.14' and sys_platform == 'win32'", + "python_full_version >= '3.14' and sys_platform == 'emscripten'", + 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import Iterator +from contextlib import contextmanager +from contextvars import ContextVar from typing import Any import httpx @@ -12,6 +15,7 @@ _LOGGER = logging.getLogger("weather_briefing.api_client") _API_CALL_EXTENSION = "weather_briefing.api_call" _SAFE_LABEL = re.compile(r"[a-z0-9]+(?:-[a-z0-9]+)*") +_CURRENT_API_CALL: ContextVar[tuple[str, str] | None] = ContextVar("current_api_call", default=None) def api_call_extensions(provider: str, operation: str) -> dict[str, object]: @@ -23,6 +27,18 @@ def api_call_extensions(provider: str, operation: str) -> dict[str, object]: return {_API_CALL_EXTENSION: (provider, operation)} +@contextmanager +def api_call_context(provider: str, operation: str) -> Iterator[None]: + """Classify requests made by an SDK that cannot set HTTPX extensions.""" + # Validate labels before storing them in the request context. + api_call_extensions(provider, operation) + token = _CURRENT_API_CALL.set((provider, operation)) + try: + yield + finally: + _CURRENT_API_CALL.reset(token) + + class LoggedAsyncClient(httpx.AsyncClient): """Record outbound HTTP calls without logging request data.""" @@ -72,7 +88,7 @@ async def send(self, request: httpx.Request, **kwargs: Any) -> httpx.Response: def _api_call_identity(request: httpx.Request) -> tuple[str, str]: - value = request.extensions.get(_API_CALL_EXTENSION) + value = request.extensions.get(_API_CALL_EXTENSION, _CURRENT_API_CALL.get()) if not isinstance(value, tuple) or len(value) != 2: return "unclassified", "request" provider, operation = value diff --git a/weather_briefing/cli.py b/weather_briefing/cli.py index ba142c29..637cf30a 100644 --- a/weather_briefing/cli.py +++ b/weather_briefing/cli.py @@ -34,9 +34,8 @@ PrecisionReducingGeocodingProvider, ) from .llm import ( - DeepSeekProvider, LLMProvider, - OpenAICompatibleChatCompletionsProvider, + create_any_llm_provider, ) from .models import ResolvedLocation from .publishers import DeliveryProvider, RenderedTextDiagnostics, StdoutPublisher, TelegramPublisher @@ -294,32 +293,14 @@ async def run( def _llm_provider(settings: Settings, client: httpx.AsyncClient) -> LLMProvider: - if settings.llm_provider == "deepseek": - if settings.llm_base_url: - return DeepSeekProvider( - client, - api_key=settings.api_key, - model=settings.llm_model, - max_output_tokens=settings.llm_max_output_tokens, - base_url=settings.llm_base_url, - ) - return DeepSeekProvider( - client, - api_key=settings.api_key, - model=settings.llm_model, - max_output_tokens=settings.llm_max_output_tokens, - ) - if settings.llm_provider == "openai-compatible": - if not settings.llm_base_url: - raise ValueError("OpenAI-compatible provider requires LLM_BASE_URL") - return OpenAICompatibleChatCompletionsProvider( - client, - api_key=settings.api_key, - base_url=settings.llm_base_url, - model=settings.llm_model, - max_output_tokens=settings.llm_max_output_tokens, - ) - raise ValueError(f"Unsupported LLM provider: {settings.llm_provider}") + return create_any_llm_provider( + settings.llm_provider, + settings.llm_model, + settings.llm_max_output_tokens, + client, + api_key=settings.api_key, + api_base=settings.llm_base_url, + ) def _delivery_provider( diff --git a/weather_briefing/config.py b/weather_briefing/config.py index 81f80f0f..a5fb1467 100644 --- a/weather_briefing/config.py +++ b/weather_briefing/config.py @@ -9,6 +9,7 @@ from typing import Any, overload import pendulum +from any_llm import AnyLLM from apscheduler.triggers.cron import CronTrigger from .models import ContextSourceConfig, FeedConfig, LocationSpec, ResolvedLocation @@ -36,11 +37,11 @@ def _clean_env(value: str | None) -> str | None: return value -def _required(name: str) -> str: - value = _clean_env(os.getenv(name, "")) - if not value: - raise ConfigurationError(f"Missing required environment variable: {name}") - return value +def _first_configured(*names: str) -> str | None: + for name in names: + if value := _clean_env(os.getenv(name, "")): + return value + return None def _integer(name: str, default: int) -> int: @@ -199,7 +200,7 @@ def _feeds(path: Path) -> tuple[FeedConfig, ...]: class Settings: """Collect validated runtime settings used to compose the application.""" - api_key: str + api_key: str | None llm_provider: str llm_model: str llm_base_url: str | None @@ -276,14 +277,20 @@ def from_env(cls) -> Settings: daily_cron_minute = _bounded_integer("GREETING_MINUTE", 0, 0, 59) hourly_cron = _cron_hour("BRIEFING_CRON", "9-23") llm_provider = _clean_env(os.getenv("LLM_PROVIDER", "deepseek")) + if llm_provider not in AnyLLM.get_supported_providers(): + raise ConfigurationError(f"Unsupported LLM_PROVIDER: {llm_provider}") + if not AnyLLM.get_provider_class(llm_provider).SUPPORTS_COMPLETION: + raise ConfigurationError(f"LLM_PROVIDER does not support completion: {llm_provider}") + llm_model = _clean_env(os.getenv("LLM_MODEL")) if llm_provider == "deepseek": - api_key = _required("DEEPSEEK_API_KEY") - llm_model = _required("DEEPSEEK_MODEL") - llm_base_url = _clean_env(os.getenv("DEEPSEEK_BASE_URL")) + api_key = _clean_env(os.getenv("DEEPSEEK_API_KEY")) or None + llm_model = llm_model or _clean_env(os.getenv("DEEPSEEK_MODEL")) + llm_base_url = _first_configured("DEEPSEEK_API_BASE", "DEEPSEEK_BASE_URL") else: - api_key = _required("LLM_API_KEY") - llm_model = _required("LLM_MODEL") - llm_base_url = _required("LLM_BASE_URL") + api_key = None + llm_base_url = None + if not llm_model: + raise ConfigurationError("Missing required environment variable: LLM_MODEL") locations = _locations(locations_path) location_ids = {location.id for location in locations} unknown_feed_locations = { diff --git a/weather_briefing/llm.py b/weather_briefing/llm.py index 5af2ba3d..957537de 100644 --- a/weather_briefing/llm.py +++ b/weather_briefing/llm.py @@ -4,12 +4,16 @@ import json from collections.abc import Mapping -from typing import Any, Protocol +from typing import Annotated, Any, Literal, Protocol, TypeAlias import httpx import pendulum +from any_llm import AnyLLM +from any_llm.exceptions import AnyLLMError +from any_llm.providers.openai.base import BaseOpenAIProvider +from pydantic import AfterValidator, BaseModel, ConfigDict, Field, ValidationError -from .api_client import api_call_extensions +from .api_client import api_call_context from .models import Advice, AdviceTopic, BriefingResult, Conclusion, Warning from .time_utils import require_aware_datetime @@ -26,85 +30,152 @@ async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dic ... -class OpenAICompatibleChatCompletionsProvider: - """Call an OpenAI-compatible chat-completions endpoint.""" +def _non_empty(value: str) -> str: + if not value.strip(): + raise ValueError("must not be empty") + return value - API_PROVIDER = "openai-compatible" + +NonEmptyString: TypeAlias = Annotated[str, AfterValidator(_non_empty)] +CitedSourceIds: TypeAlias = Annotated[list[NonEmptyString], Field(min_length=1)] + + +class _StrictLLMPayload(BaseModel): + """Reject coercion, defaults, and undeclared fields at the LLM boundary.""" + + model_config = ConfigDict(extra="forbid", strict=True) + + +class SourcedTextPayload(_StrictLLMPayload): + """Describe one source-cited statement in the model response.""" + + text: NonEmptyString + source_ids: CitedSourceIds + + +class WarningPayload(_StrictLLMPayload): + """Describe one active warning in the model response.""" + + id: NonEmptyString + title: NonEmptyString + status: NonEmptyString + detail: NonEmptyString + source_ids: CitedSourceIds + + +class AdvicePayload(SourcedTextPayload): + """Describe one categorized lifestyle recommendation.""" + + topic: Literal["clothing", "dehumidification", "exercise", "mask", "allergen"] + + +class LLMStructuredOutput(_StrictLLMPayload): + """Define the complete, strict response contract requested from every LLM.""" + + headline: NonEmptyString + headline_source_ids: CitedSourceIds + conclusions: list[SourcedTextPayload] + active_warnings: list[WarningPayload] + resolved_warning_ids: list[NonEmptyString] + disaster_tracking: list[SourcedTextPayload] + advice: list[AdvicePayload] + should_publish: bool + + +def _validate_structured_output(payload: Mapping[str, Any]) -> LLMStructuredOutput: + try: + return LLMStructuredOutput.model_validate(payload) + except ValidationError as exc: + location = ".".join(str(part) for part in exc.errors()[0]["loc"]) + raise LLMError(f"LLM response schema validation failed at {location}") from exc + + +def _decode_structured_response(response: Any) -> LLMStructuredOutput: + """Decode the normalized any-llm response without masking programming errors.""" + choices = getattr(response, "choices", None) + if not isinstance(choices, list) or not choices: + raise LLMError("LLM returned no completion choices") + message = getattr(choices[0], "message", None) + if message is None: + raise LLMError("LLM completion choice is missing a message") + parsed = getattr(message, "parsed", None) + if isinstance(parsed, LLMStructuredOutput): + return parsed + content = getattr(message, "content", None) + if not isinstance(content, str) or not content: + raise LLMError("LLM returned empty JSON content") + try: + return LLMStructuredOutput.model_validate_json(content) + except ValidationError as exc: + location = ".".join(str(part) for part in exc.errors()[0]["loc"]) + raise LLMError(f"LLM response schema validation failed at {location}") from exc + + +class AnyLLMStructuredProvider: + """Adapt an any-llm provider to the application's structured LLM boundary.""" def __init__( self, - client: httpx.AsyncClient, + client: AnyLLM, *, - api_key: str, - base_url: str, + provider: str, model: str, max_output_tokens: int, ) -> None: - """Configure one OpenAI-compatible model endpoint and output limit.""" + """Configure a reusable any-llm client and output limit.""" self._client = client - self._api_key = api_key - self._base_url = base_url + self._provider = provider self._model = model self._max_output_tokens = max_output_tokens @property - def base_url(self) -> str: - """Return the configured API base URL.""" - return self._base_url + def provider(self) -> str: + """Return the application-facing provider name used for diagnostics.""" + return self._provider async def summarize(self, system_prompt: str, payload: dict[str, object]) -> dict[str, object]: """Request and decode one structured JSON response.""" try: - response = await self._client.post( - f"{self._base_url}/chat/completions", - headers={"Authorization": f"Bearer {self._api_key}"}, - json={ - "model": self._model, - "messages": [ + with api_call_context(self._provider, "chat-completions"): + response = await self._client.acompletion( + model=self._model, + messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": json.dumps(payload, ensure_ascii=False)}, ], - "response_format": {"type": "json_object"}, - "temperature": 0.2, - "max_tokens": self._max_output_tokens, - }, - extensions=api_call_extensions(self.API_PROVIDER, "chat-completions"), - ) - response.raise_for_status() - content = response.json()["choices"][0]["message"]["content"] - if not content: - raise LLMError("LLM returned empty JSON content") - result = json.loads(content) - except (httpx.HTTPError, KeyError, TypeError, json.JSONDecodeError) as exc: - raise LLMError("LLM request or structured response failed") from exc - if not isinstance(result, dict): - raise LLMError("LLM response must be a JSON object") - return result - - -class DeepSeekProvider(OpenAICompatibleChatCompletionsProvider): - """Use DeepSeek through the shared OpenAI-compatible adapter.""" - - DEFAULT_BASE_URL = "https://api.deepseek.com" - API_PROVIDER = "deepseek" - - def __init__( - self, - client: httpx.AsyncClient, - *, - api_key: str, - model: str, - max_output_tokens: int, - base_url: str = DEFAULT_BASE_URL, - ) -> None: - """Configure DeepSeek through the shared chat-completions adapter.""" - super().__init__( - client, - api_key=api_key, - base_url=base_url, - model=model, - max_output_tokens=max_output_tokens, - ) + response_format=LLMStructuredOutput, + temperature=0.2, + max_tokens=self._max_output_tokens, + ) + except AnyLLMError as exc: + raise LLMError("LLM request failed") from exc + result = _decode_structured_response(response) + return result.model_dump(mode="json") + + +def create_any_llm_provider( + provider: str, + model: str, + max_output_tokens: int, + http_client: httpx.AsyncClient, + *, + api_key: str | None = None, + api_base: str | None = None, +) -> AnyLLMStructuredProvider: + """Create an application adapter for any supported any-llm completion provider.""" + provider_class = AnyLLM.get_provider_class(provider) + if not provider_class.SUPPORTS_COMPLETION: + raise ValueError(f"any-llm provider does not support completion: {provider}") + client_options: dict[str, object] = {} + if issubclass(provider_class, BaseOpenAIProvider): + client_options.update(http_client=http_client, max_retries=0) + sdk_client = AnyLLM.create(provider, api_key=api_key, api_base=api_base, **client_options) + return AnyLLMStructuredProvider( + sdk_client, + provider=provider, + model=model, + max_output_tokens=max_output_tokens, + ) def parse_result( @@ -114,105 +185,45 @@ def parse_result( ) -> BriefingResult: """Validate an LLM payload and convert it to a briefing result.""" require_aware_datetime(now, context="Briefing result time") + structured = _validate_structured_output(payload) - def string_ids(value: Mapping[str, Any], field: str) -> tuple[str, ...]: - raw_ids = value.get(field, []) - if not isinstance(raw_ids, list): - raise LLMError(f"{field} must be an array") - if not all(isinstance(item, str) and item.strip() for item in raw_ids): - raise LLMError(f"{field} must contain non-empty strings") - return tuple(raw_ids) - - def cited_source_ids(value: Mapping[str, Any], field: str) -> tuple[str, ...]: - parsed = string_ids(value, field) - if not parsed: - raise LLMError(f"{field} must cite at least one source ID") - unknown = set(parsed) - valid_source_ids + def cited_source_ids(source_ids: list[str]) -> tuple[str, ...]: + unknown = set(source_ids) - valid_source_ids if unknown: raise LLMError(f"Model cited unknown source IDs: {sorted(unknown)}") - return parsed - - def sourced_text(value: Mapping[str, Any], key: str) -> str: - text = value.get("text") - if not isinstance(text, str) or not text.strip(): - raise LLMError(f"{key} entries must contain non-empty text") - return text - - def required_text(value: Mapping[str, Any], field: str, *, context: str = "") -> str: - text = value.get(field) - if not isinstance(text, str) or not text.strip(): - raise LLMError(f"{context}{field} must be a non-empty string") - return text - - def parse_sourced_text_items(key: str) -> tuple[Conclusion, ...]: - values = payload.get(key, []) - if not isinstance(values, list): - raise LLMError(f"{key} must be an array") - parsed: list[Conclusion] = [] - for value in values: - if not isinstance(value, dict): - raise LLMError(f"{key} entries must be objects") - parsed.append( - Conclusion( - text=sourced_text(value, key), - source_ids=cited_source_ids(value, "source_ids"), - ) - ) - return tuple(parsed) - - def advice() -> tuple[Advice, ...]: - values = payload.get("advice", []) - if not isinstance(values, list): - raise LLMError("advice must be an array") - parsed: list[Advice] = [] - for value in values: - if not isinstance(value, dict): - raise LLMError("advice entries must be objects") - try: - topic = AdviceTopic(str(value["topic"])) - except (KeyError, ValueError): - allowed = ", ".join(item.value for item in AdviceTopic) - raise LLMError(f"advice entries must use a valid topic: {allowed}") from None - parsed.append( - Advice( - topic=topic, - text=sourced_text(value, "advice"), - source_ids=cited_source_ids(value, "source_ids"), - ) - ) - return tuple(parsed) - - warning_values = payload.get("active_warnings", []) - if not isinstance(warning_values, list): - raise LLMError("active_warnings must be an array") - warnings: list[Warning] = [] - for value in warning_values: - if not isinstance(value, dict): - raise LLMError("active_warnings entries must be objects") - warnings.append( - Warning( - id=required_text(value, "id", context="active_warnings entries: "), - title=required_text(value, "title", context="active_warnings entries: "), - status=required_text(value, "status", context="active_warnings entries: "), - detail=required_text(value, "detail", context="active_warnings entries: "), - source_ids=cited_source_ids(value, "source_ids"), - last_confirmed_at=now, - ) + return tuple(source_ids) + + def sourced_text_items(values: list[SourcedTextPayload]) -> tuple[Conclusion, ...]: + return tuple(Conclusion(text=value.text, source_ids=cited_source_ids(value.source_ids)) for value in values) + + warnings = tuple( + Warning( + id=value.id, + title=value.title, + status=value.status, + detail=value.detail, + source_ids=cited_source_ids(value.source_ids), + last_confirmed_at=now, ) - should_publish = payload.get("should_publish", True) - if not isinstance(should_publish, bool): - raise LLMError("should_publish must be a boolean") - parsed_conclusions = parse_sourced_text_items("conclusions") - parsed_advice = advice() - parsed_disaster_tracking = parse_sourced_text_items("disaster_tracking") + for value in structured.active_warnings + ) + advice = tuple( + Advice( + topic=AdviceTopic(value.topic), + text=value.text, + source_ids=cited_source_ids(value.source_ids), + ) + for value in structured.advice + ) + raw_payload = structured.model_dump(mode="json") return BriefingResult( - headline=required_text(payload, "headline"), - headline_source_ids=cited_source_ids(payload, "headline_source_ids"), - conclusions=parsed_conclusions, - active_warnings=tuple(warnings), - resolved_warning_ids=string_ids(payload, "resolved_warning_ids"), - advice=parsed_advice, - disaster_tracking=parsed_disaster_tracking, - should_publish=should_publish, - raw_payload=dict(payload), + headline=structured.headline, + headline_source_ids=cited_source_ids(structured.headline_source_ids), + conclusions=sourced_text_items(structured.conclusions), + active_warnings=warnings, + resolved_warning_ids=tuple(structured.resolved_warning_ids), + advice=advice, + disaster_tracking=sourced_text_items(structured.disaster_tracking), + should_publish=structured.should_publish, + raw_payload=raw_payload, )