diff --git a/README.md b/README.md index d5cd2fc..5d13a6c 100644 --- a/README.md +++ b/README.md @@ -280,15 +280,23 @@ worker///__admin__ - **网关登记/注销 + 心跳租约**：网关启动时 `register_gateway()` 加入在线列表，并每 15s `heartbeat_gateway()` 刷新自身时间戳；超过租约（60s）未心跳的死网关会被自动清理（crash/kill -9 也不残留，避免配额失真）。当前由 `CHONGMING_GATEWAY_ID` 环境变量指定（多实例需唯一，尤其**同宿主多网关必须显式指定**；缺省回退 `hostname`，稳定且重启不变，不残留）；关闭时 `unregister_gateway()` 移除，其余网关实时重算分摊。 - **分摊算法**：`own_quota()` 将全局总量按在线网关 sorted(id) 均分，余量按序补前若干。`/admin/workers//scale`（body `{count:<全局总量>}`）写全局 count 后，各网关把自己的 session 副本调到自己的 quota。 - **共享方式与后端**：单实例本机 `sqlite` 即可；**多实例必须共享同一 cache 后端**（同一共享卷的 sqlite 或 redis），否则各写各的 cache 无法收敛成全局量。 -- **启动优先级开关**：根 `config.toml` 的 `[cache].launch_worker_count` 决定网关启动时副本数的来源： +- **配置优先来源模式**：根 `config.toml` 的 `[cache].launch_worker_count` 决定启动时 **`[workers.config]` 与 `count` 从哪一侧取值**（两种模式下"前端显示 / 插件实际使用 / 重启后行为"三处都自洽）： ```toml [cache] backend = "sqlite" # "sqlite"（默认，本机共享） | "redis"（跨主机） path = "./cache_data/cache.db" - launch_worker_count = "toml" # "toml"（默认)=启动用 toml 的 count 覆盖并写回 cache；"cache"=cache 为单一事实来源，toml 仅在缺失时引导 + launch_worker_count = "toml" # "toml"（默认）=以文件为准；"cache"=以缓存为准 ``` + | 环节 | `"toml"`（默认） | `"cache"` | + | --- | --- | --- | + | 启动时 | 用 toml 的 `[workers.config]` 与 `count` **覆盖写入缓存**（前端读缓存，因此随之显示 toml 值） | 以缓存为准；插件初始化即读缓存值，缓存缺失才用 toml 引导并写回 | + | 插件实际使用 | toml 值 | 缓存值 | + | 管理接口改动的持久性 | 仅本次运行有效，重启网关被文件覆盖 | 跨重启保持 | + + 两种模式都不回写 `config.toml`：管理接口的改动只进缓存。`cache` 模式下启动日志会打印 toml 与缓存的差异键（以缓存为准）；如需让 toml 的改动生效，先删除 `worker:cm:configs:`（运行时配置）或 `worker:cm:counts:`（副本数）缓存键再重启，或改用 `"toml"` 模式。`GET /admin/workers//config` 的响应带 `source`（cache/toml）与 `mode`，前端据此标注展示值的来路。 + - **进程插件（external）实例粒度参与分摊**：网关只对 **inline** 插件用 cache 解析启动副本数（见「启动流程」第 5 步 `load_workers`），external 插件的启动副本数由外部编排按自身配置决定；但**运行时的缩放**上，external 并不退化为“每进程全额”，而是同样在**共享 cache 上登记实例参与方**来分摊，避免多实例把副本翻倍： - **实例登记 + 心跳租约**：每个 external 进程启动时向 `worker:cm:instances:` 登记自身参与方（`[instance_id, ts]`），并每 15s 心跳续约；超过租约（60s）未心跳的死实例会被清理。`divmod` 按存活参与方 N 均分全局 count（余量补靠前实例），`N==1` 时退化为全额（单部署零影响）。 - **实例标识默认唯一**：`--instance` / 环境变量 `CHONGMING_WORKER_INSTANCE` 显式指定（跨重启稳定、逐实例精细扩缩可持续命中）；缺省回退 `{hostname}:{pid}`——**同一机器并行多个未指定 `--instance` 的进程也能靠 pid 区分**，不会因为 id 相同被并成一个参与方导致副本翻倍或前端只显示一个实例。注意缺省 id 随进程重启变化。 @@ -821,7 +829,7 @@ uv pip install -e utils/ # 安装/更新工具包子包 | 字段 | 位置 | 说明 | | -------------------- | --------------------- | --------------------------------------- | | `count` | `<插件>/config.toml` | Worker 副本数（`[workers]` 节） | -| `launch_worker_count`| `根 config.toml` | 启动时副本数来源：`"toml"`=用 toml count 覆盖 cache（默认）；`"cache"`=以 cache 为单一事实来源（`[cache]` 节） | +| `launch_worker_count`| `根 config.toml` | 配置优先来源模式：`"toml"`=以文件为准（启动用 toml 的 `[workers.config]`/count 覆盖 cache，默认）；`"cache"`=以 cache 为单一事实来源（插件初始化即读缓存，跨重启保持）（`[cache]` 节） | | `router_prefix` | `<插件>/config.toml` | API 路由前缀 | | `defaults.timeout` | `<插件>/config.toml` | 默认超时（秒） | | `defaults.cacheable` | `<插件>/config.toml` | 是否缓存 RPC 结果 | diff --git a/config.toml b/config.toml index f195c2e..cf3e7bf 100644 --- a/config.toml +++ b/config.toml @@ -15,9 +15,16 @@ json5_path = "./config/zenoh_config.json5" backend = "redis" # path = "./cache_data/cache.db" -# 启动时该类 worker 的全局副本数优先来源（指 config/workers//config.toml 的 count）： -# "toml" （默认） = 经典模式：启动时用 toml 的 count 覆盖 cache 并写回为新的全局总量 -# "cache" = 全局模式：chongming-cache 为单一事实来源，toml 仅在 cache 缺失时引导 +# 配置优先来源模式（同时决定 [workers.config] 与 count 在启动时的取舍）： +# "toml" （默认） = 以文件为准：启动时用 config/workers//config.toml 的 +# [workers.config] 与 count 覆盖写入 cache（前端读 cache，因此随之显示 +# toml 值）；运行期经管理接口（/admin/workers//config、/scale） +# 改的值仅本次运行有效，重启网关即被文件覆盖。 +# "cache" = 以缓存为准：chongming-cache 为单一事实来源，插件初始化即读缓存值， +# 管理接口改动跨重启保持；toml 仅在 cache 缺失时引导。启动日志会提示 +# toml 与 cache 的差异键（以 cache 为准）；如需让 toml 改动生效，先删除 +# worker:cm:configs:（运行时配置）/ worker:cm:counts:（副本数） +# 缓存键再重启，或改用 "toml" 模式。 launch_worker_count = "toml" # redis 后端专用（backend = "redis" 时生效，均有默认值） diff --git a/docs/process-plugin.md b/docs/process-plugin.md index 76ba144..5789d60 100644 --- a/docs/process-plugin.md +++ b/docs/process-plugin.md @@ -195,6 +195,13 @@ tags = ["demo", "process-plugin"] greeting_prefix = "Hello" ``` +> **运行时配置的来源（两种模式）**：`[workers.config]` 与 `count` 在启动时按 +> `[workers.cache].launch_worker_count` 取值——`"toml"`（默认）以本文件为准，并把该段覆盖 +> 写入共享缓存（网关 `GET /admin/workers//config` 读缓存，因此前端显示文件值）； +> `"cache"` 以缓存为准（插件初始化即读缓存值，管理接口改动跨重启保持，本文件仅在缓存缺失时 +> 引导）。进程插件未配置 `[workers.cache]` 时无缓存句柄，恒为 toml 语义，且与网关内同名 +> 副本可能读到不同来源——需要与网关共享"改完即持久"的语义时请补上与网关一致的 `[workers.cache]`。 + ### 第 3 步：端点 TOML 定义 每个端点一个文件，如 `workers//config/workers//hello.toml`： diff --git a/docs/rust-plugin.md b/docs/rust-plugin.md index 0b31b83..4d9e279 100644 --- a/docs/rust-plugin.md +++ b/docs/rust-plugin.md @@ -178,6 +178,23 @@ Rust 进程插件支持两种共享缓存后端（schema 与 Python `chongming-c 编译启用：`bash build.sh dist "redis-cache"`（或 Cargo 依赖加 `chongming-worker-rs/redis-cache`）。 未配置时单实例直接读写本地 `config.toml`（默认无缓存），行为一致。 +#### 5.2.1 配置优先来源模式（`launch_worker_count`） + +`[workers.cache].launch_worker_count` 与网关根 `config.toml` 的同名键语义一致，决定启动时 +`[workers.config]` 与 count 从哪一侧取值（SDK 的 `config::resolve_runtime_config` / +`cache::resolve_worker_count` 按同一规则实现，与 Python SDK 对位）： + +| 环节 | `"toml"`（默认） | `"cache"` | +| ---- | ---------------- | --------- | +| 启动时 | 以 `config/workers//config.toml` 为准，并把该段**覆盖写入缓存**（网关读缓存 → 显示 toml 值） | 以缓存为准，插件初始化即读缓存值；缓存缺失才用 toml 引导并写回 | +| 插件实际使用 | toml 值 | 缓存值（跨重启保持） | +| `config_set` 改动的持久性 | 仅本次运行有效，下次启动被文件覆盖 | 跨重启保持（写入缓存） | + +> 插件初始化读配置（如 `[workers.config].database`）请用 `config::effective_config_section` +> 或 `database::init_database`（内部已按模式解析），**不要**直接读 +> `load_plugin_config(...).runtime["config"]`——后者恒为 toml 种子，cache 模式下会与网关 +> `get_config` 显示的缓存值不一致（表现为"前端显示缓存值、实际跑 toml"）。 + ### 5.3 数据库 `[workers.config.database]`（可选） 见 §7。 diff --git a/public/config.toml b/public/config.toml index f29143e..a7ac02e 100644 --- a/public/config.toml +++ b/public/config.toml @@ -13,6 +13,15 @@ json5_path = "./config/zenoh_config.json5" [cache] backend = "sqlite" path = "./cache_data/cache.db" +# 配置优先来源模式（同时决定 [workers.config] 与 count 在启动时的取舍）： +# "cache"（本模板默认）= 以缓存为准：chongming-cache 为单一事实来源，插件初始化即读缓存值， +# 管理接口（/admin/workers//config、/scale）改动跨重启保持； +# toml 仅在缓存缺失时引导。启动日志会提示 toml 与缓存的差异键 +# （以缓存为准）；如需让 toml 改动生效，先删除 worker:cm:configs: +# （运行时配置）/ worker:cm:counts:（副本数）缓存键再重启。 +# "toml" = 以文件为准：启动时用 config/workers//config.toml 的 +# [workers.config] 与 count 覆盖写入缓存（前端读缓存 → 显示 toml 值）； +# 管理接口改动仅本次运行有效，重启网关即被文件覆盖。 launch_worker_count = "cache" [security] diff --git a/pyproject.toml b/pyproject.toml index b6bd29d..530d0b2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,7 +12,7 @@ dependencies = [ "module-bank", "openai", "python-multipart", - "sqlite-vfs==0.2.0", + "sqlite-vfs", "tomli", "typing-extensions", "uvicorn", diff --git a/src/chongming/app/core/worker_manager.py b/src/chongming/app/core/worker_manager.py index e71dfdf..af7d768 100644 --- a/src/chongming/app/core/worker_manager.py +++ b/src/chongming/app/core/worker_manager.py @@ -123,6 +123,17 @@ class WorkerManager: self._worker_starters: Dict[str, Callable[[], Awaitable[List[Any]]]] = {} self._started_extra: List[Any] = [] + @property + def config_mode(self) -> str: + """本网关 inline 插件的配置优先来源模式。 + + "toml"（默认）= 以 config/workers//config.toml 为准，启动时覆盖缓存； + "cache" = 以 chongming-cache 为准（跨重启保持），toml 仅作引导。 + 对应 config.toml 的 [cache].launch_worker_count，与 worker 侧 + chongming_worker.runtime._resolve_mode 取值一致。 + """ + return "cache" if str(self._launch_worker_count).lower() == "cache" else "toml" + # ── 全局副本数协调（chongming-cache 单一事实来源）──────────── # count/quota 的读写与分摊已收归 worker 层（chongming_worker.runtime）： # 网关不再直写这些缓存键，仅维护「在线网关列表」（register/heartbeat/unregister）。 @@ -1014,7 +1025,8 @@ class WorkerManager: 由 worker 访问自身缓存（或回退 toml 种子）返回；网关不直接接触外部 worker 的缓存后端。 Returns: - {"status", "config": {...}, "source": "cache"|"toml", "worker_id", ...} + {"status", "config": {...}, "source": "cache"|"toml", "mode": "toml"|"cache", + "worker_id", ...} Raises: RuntimeError: 无存活副本 / 副本未响应（可能运行旧版运行时无 get_config 能力） @@ -1037,6 +1049,9 @@ class WorkerManager: "status": reply.get("status"), "config": reply.get("config"), "source": reply.get("source", "toml"), + # 旧版运行时回复无 mode：按本网关 inline 模式兜底（external 副本以自身 + # [workers.cache].launch_worker_count 为准，新运行时会在回复里带回） + "mode": reply.get("mode") or self.config_mode, } async def update_worker_config( diff --git a/src/chongming/app/routes/worker_admin.py b/src/chongming/app/routes/worker_admin.py index 6f80d26..6fb7c55 100644 --- a/src/chongming/app/routes/worker_admin.py +++ b/src/chongming/app/routes/worker_admin.py @@ -250,6 +250,10 @@ async def read_worker_config( 不支持 get_config 时，回退回直读 config/workers//config.toml 的 [workers].config。 路由配置（add.toml 等）不在此范围。 + 响应中的 source/mode 供前端如实标注展示值的来路（避免把回退读到的 toml 值当成缓存值）： + - source="cache"：值来自运行时缓存；source="toml"：缓存缺失或副本未响应，值取自文件； + - mode：该类插件的配置优先来源模式（toml 模式以文件为准、cache 模式以缓存为准）。 + - worker_type: 插件类型（如 example） """ manager = _get_manager(request) @@ -261,6 +265,7 @@ async def read_worker_config( "worker_type": worker_type, "worker_id": info.get("worker_id"), "source": info.get("source", "cache"), + "mode": info.get("mode") or manager.config_mode, "config": cfg, "success": True, } @@ -279,6 +284,7 @@ async def read_worker_config( "worker_type": worker_type, "config": cfg if isinstance(cfg, dict) else {}, "source": "toml", + "mode": manager.config_mode, "success": True, } diff --git a/test/test_worker_config_mode.py b/test/test_worker_config_mode.py new file mode 100644 index 0000000..892619a --- /dev/null +++ b/test/test_worker_config_mode.py @@ -0,0 +1,241 @@ +""" +[workers.config] 两种配置模式（toml / cache）语义单测 —— 无需网关与缓存后端。 + +用 dict 作缓存桩，验证： + - cache 模式：以缓存为准（插件初始化前解析即读到缓存值），缓存缺失才用 toml 引导； + - toml 模式：以 config.toml 为准，启动时覆盖缓存，使前端（读缓存）与运行值一致； + - count：toml 模式用文件值覆盖缓存，cache 模式缓存有值用缓存、缺失用文件值引导； + - get_config 的来源标注（值来自缓存 vs 回退读 toml 种子）如实区分。 + +对应改动：chongming_worker.runtime.resolve_runtime_config / resolve_startup_config / +_read_worker_config_section_with_source（Plugin.create_workers 在 on_init 前调用）。 +""" +import os +import shutil +import sys +import tempfile + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), "../utils/worker/src")) + +import chongming_worker.runtime as r + +PASS = 0 +FAIL = 0 + +WT = "demo" +TOML_CFG = {"api_key": "TOML-KEY", "model": "toml-model", "heartbeat": {"interval": 5}} + + +def report(name, cond, detail=""): + global PASS, FAIL + if cond: + PASS += 1 + print(f"✅ {name}" + (f" — {detail}" if detail else "")) + else: + FAIL += 1 + print(f"❌ {name}" + (f" — {detail}" if detail else "")) + + +def write_plugin_toml(root: str) -> None: + """在工作目录下写 config/workers//config.toml（_plugin_config_path 相对 cwd）。""" + d = os.path.join(root, "config", "workers", WT) + os.makedirs(d, exist_ok=True) + with open(os.path.join(d, "config.toml"), "w", encoding="utf-8") as f: + f.write( + "[workers]\n" + f'type = "{WT}"\n' + 'module = "plugins.demo"\n' + "count = 3\n" + "\n" + "[workers.config]\n" + 'api_key = "TOML-KEY"\n' + 'model = "toml-model"\n' + "\n" + "[workers.config.heartbeat]\n" + "interval = 5\n" + ) + + +def run() -> int: + workdir = tempfile.mkdtemp(prefix="cm_cfg_mode_") + cwd = os.getcwd() + try: + write_plugin_toml(workdir) + os.chdir(workdir) + + key = r._configs_cache_key(WT) + # _discover_plugins 展平出来的形态：注册字段 + [workers.config] 各键平铺到顶层 + base = { + "type": WT, "count": 3, + "api_key": "TOML-KEY", "model": "toml-model", + "heartbeat": {"interval": 5}, + } + cached_cfg = {"api_key": "CACHE-KEY", "model": "cache-model"} + + # ── 1. cache 模式：以缓存为准（插件必须读到缓存值）────────────── + cache = {key: dict(cached_cfg)} + got = r.resolve_runtime_config(WT, base, cache, "cache") + report( + "cache 模式：返回值取缓存值（覆盖 toml 同键）", + got.get("api_key") == "CACHE-KEY" and got.get("model") == "cache-model", + f"api_key={got.get('api_key')}", + ) + report( + "cache 模式：toml 独有键保留（缓存缺该键时兜底）", + got.get("heartbeat") == {"interval": 5}, + f"heartbeat={got.get('heartbeat')}", + ) + report( + "cache 模式：不覆盖既有缓存值", + cache[key] == cached_cfg, + f"cache={cache[key]}", + ) + + # 插件初始化路径（process.py 先 set_worker_cache/set_worker_mode 再 create_workers） + r.set_worker_cache(WT, cache) + r.set_worker_mode(WT, "cache") + startup = r.resolve_startup_config(WT, base, worker_manager=None) + report( + "cache 模式：resolve_startup_config 让插件初始化读到缓存值（本次核心修复）", + startup.get("api_key") == "CACHE-KEY", + f"api_key={startup.get('api_key')}", + ) + vs_front = r._read_worker_config_section_with_source(cache, WT) + report( + "cache 模式：插件初始化值与前端( get_config )读到的一致", + vs_front[0].get("api_key") == startup.get("api_key") == "CACHE-KEY" + and vs_front[1] == "cache", + f"source={vs_front[1]}", + ) + + # ── 2. cache 模式：缓存缺失 → 用 toml 引导并写回 ──────────────── + cache2 = {} + got2 = r.resolve_runtime_config(WT, base, cache2, "cache") + report( + "cache 模式：缓存缺失用 toml 引导并写回", + got2.get("api_key") == "TOML-KEY" and cache2.get(key, {}).get("api_key") == "TOML-KEY", + f"cache={cache2.get(key)}", + ) + + # ── 3. toml 模式：以文件为准，启动时覆盖缓存 ──────────────────── + cache3 = {key: dict(cached_cfg)} + got3 = r.resolve_runtime_config(WT, base, cache3, "toml") + report( + "toml 模式：返回值取 toml 值", + got3.get("api_key") == "TOML-KEY" and got3.get("model") == "toml-model", + f"api_key={got3.get('api_key')}", + ) + report( + "toml 模式：启动时用 toml 覆盖缓存（前端随之显示 toml 值）", + cache3.get(key, {}).get("api_key") == "TOML-KEY", + f"cache={cache3.get(key)}", + ) + r.set_worker_cache(WT, cache3) + r.set_worker_mode(WT, "toml") + startup3 = r.resolve_startup_config(WT, base, worker_manager=None) + report( + "toml 模式：插件初始化值与缓存/前端一致（均为 toml 值）", + startup3.get("api_key") == "TOML-KEY" + and r._read_worker_config_section(cache3, WT).get("api_key") == "TOML-KEY", + f"api_key={startup3.get('api_key')}", + ) + + # ── 4. 无缓存：保持 toml 种子 ──────────────────────────────── + got4 = r.resolve_runtime_config(WT, base, None, "toml") + report( + "无缓存后端：保持 toml 种子（经典行为）", + got4.get("api_key") == "TOML-KEY", + f"api_key={got4.get('api_key')}", + ) + + # ── 5. get_config 来源标注 ────────────────────────────────── + only_missing_key = {"worker:cm:configs:other": {"api_key": "X"}} + cfg5, src5 = r._read_worker_config_section_with_source(only_missing_key, WT) + report( + "来源标注：缓存对象存在但键缺失 → 回退 toml 且标 toml", + src5 == "toml" and cfg5.get("api_key") == "TOML-KEY", + f"source={src5}", + ) + cfg6, src6 = r._read_worker_config_section_with_source({key: {"api_key": "C"}}, WT) + report("来源标注：命中缓存 → cache", src6 == "cache" and cfg6.get("api_key") == "C", f"source={src6}") + + # ── 6. count：toml 模式覆盖 / cache 模式以缓存为准 ────────────── + counts_key = r._SCALE_COUNTS_KEY.format(type=WT) + cache7 = {counts_key: 1} + n_toml = r.resolve_worker_count(WT, 3, cache7, "toml") + report( + "count toml 模式：用 toml 的 count 覆盖缓存", + n_toml == 3 and cache7.get(counts_key) == 3, + f"got={n_toml}, cache={cache7.get(counts_key)}", + ) + cache8 = {counts_key: 1} + n_cache = r.resolve_worker_count(WT, 3, cache8, "cache") + report( + "count cache 模式：缓存有值用缓存（跨重启保持）", + n_cache == 1 and cache8.get(counts_key) == 1, + f"got={n_cache}", + ) + cache9 = {} + n_seed = r.resolve_worker_count(WT, 3, cache9, "cache") + report( + "count cache 模式：缓存缺失用 toml 引导并写回", + n_seed == 3 and cache9.get(counts_key) == 3, + f"got={n_seed}, cache={cache9.get(counts_key)}", + ) + + # ── 7. Plugin.create_workers：初始化（on_init）前即应用模式语义 ────── + # 这是本次主 bug：cache 模式下插件此前按 toml 建客户端，只有 RPC/管理通道读缓存。 + import asyncio + + from chongming_worker.plugin import Plugin + + seen = {} + + class DemoPlugin(Plugin): + type = WT + auto_bind = False + + async def _bootstrap(self): # 隔离数据库/对象存储引导，只验证配置来源 + return None + + async def on_init(self): + seen["on_init"] = self.config.get("api_key") + + def _create_workers_impl(self, session, config, count=1, worker_manager=None): + seen["impl"] = (config or {}).get("api_key") + return [] + + r.set_worker_cache(WT, {key: {"api_key": "CACHE-KEY"}}) + r.set_worker_mode(WT, "cache") + asyncio.run(DemoPlugin().create_workers(None, dict(base), 1)) + report( + "Plugin.create_workers：cache 模式 on_init 读到缓存值", + seen.get("on_init") == "CACHE-KEY", + f"on_init={seen.get('on_init')}", + ) + report( + "Plugin.create_workers：下发给 WorkerPool 的配置同为缓存值", + seen.get("impl") == "CACHE-KEY", + f"impl={seen.get('impl')}", + ) + + r.set_worker_cache(WT, {key: {"api_key": "CACHE-KEY"}}) + r.set_worker_mode(WT, "toml") + seen.clear() + asyncio.run(DemoPlugin().create_workers(None, dict(base), 1)) + report( + "Plugin.create_workers：toml 模式 on_init 读到文件值", + seen.get("on_init") == "TOML-KEY" and seen.get("impl") == "TOML-KEY", + f"on_init={seen.get('on_init')}, impl={seen.get('impl')}", + ) + + print("\n" + "=" * 56) + print(f"测试结果: ✅ {PASS} 通过 ❌ {FAIL} 失败") + return 0 if FAIL == 0 else 1 + finally: + os.chdir(cwd) + shutil.rmtree(workdir, ignore_errors=True) + + +if __name__ == "__main__": + sys.exit(run()) diff --git a/uv.lock b/uv.lock index ac5dd80..e346dfb 100644 --- a/uv.lock +++ b/uv.lock @@ -35,7 +35,7 @@ wheels = [ [[package]] name = "amqtt" -version = "0.12.0" +version = "0.12.1" source = { registry = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple" } dependencies = [ { name = "dacite" }, @@ -47,9 +47,9 @@ dependencies = [ { name = "typing-extensions" }, { name = "websockets" }, ] -sdist = { url = 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