diff --git a/.gitignore b/.gitignore index 23c966c..08f7838 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,5 @@ claude-server.tar +.DS_Store dist .task bin @@ -8,8 +9,12 @@ logs.zip frontend/bindings dist node_modules +*.tsbuildinfo cursor-server.tar /cursor-server/target/ +/cursor-server/*.db +/cursor-server/*.db-shm +/cursor-server/*.db-wal server-node/cursor.tar server-go/cursor.tar server-go/log/ diff --git a/Cursor上下文与状态同步抓包分析.md b/Cursor上下文与状态同步抓包分析.md index 380ef65..f9d1775 100644 --- a/Cursor上下文与状态同步抓包分析.md +++ b/Cursor上下文与状态同步抓包分析.md @@ -47,8 +47,8 @@ BidiAppend(request_id, append_seqno, data) | ID | 作用域 | 用途 | | --- | --- | --- | | `conversation_id` | 跨 Turn | 持久会话、最新 checkpoint、子会话 | -| `request_id` | 一次 Run | 关联 RunSSE 与 BidiAppend | -| `run_id` | 一次执行 | 当前样本中常与 `request_id` 相同，但不应假设永远相同 | +| `request_id` | 一次具体执行/传输尝试 | 关联 RunSSE 与 BidiAppend；Cursor adapter 以它创建内部 RunId | +| `run_id` | Cursor 逻辑 Run 元数据 | 普通样本中常与 `request_id` 相同；队列/子代理恢复时可能跨新 request 复用，不能作为执行表主键 | | `append_seqno` | 单个 request | Bidi 上行排序与去重 | | KV `id` | 单个 request | 配对 KV request/result | | Exec `id` | 单个 request | 配对本地执行 request/result | @@ -79,6 +79,8 @@ BidiAppend(request_id, append_seqno, data) - `requested_model`、候选子 Agent 模型和模型覆盖； - 客户端能力位。 +`conversation_state` 的字段存在性不能用来判断是否已有历史。Cursor 在新对话中也会发送一个已分配但 roots 为空的 state；它表示空历史基线，首份 checkpoint 才写入 system root。只有 roots 非空的恢复历史才要求其中恰好存在一个 system prompt root。 + 主会话首轮模型为 `grok-4.6`，参数为 `effort=high`、`fast=true`。首轮引用的 rules 为 1,114 字节、skills 为 5,207 字节、MCP 为 28,089 字节；空 subagents 使用 SHA-256 空串地址： ```text @@ -812,7 +814,7 @@ LLM 本身不保存会话。Loop 引擎反复把当前完整上下文投射成 ```text Provider SSE → OpenAI Chat / Responses / Anthropic Adapter -→ Canonical ResponseEvent +→ 统一 ModelEvent → Loop State Machine → Cursor AgentServerMessage → Connect RunSSE @@ -825,13 +827,36 @@ start text_start / text_delta / text_end thinking_start / thinking_delta / thinking_end toolcall_start / toolcall_delta / toolcall_end -done(stop | length | toolUse | error | aborted) -error +done(stop | length | toolUse) +stream_error / cancellation ``` +其中 `error` 与 cancellation 是流错误和 Run 终态，不伪装成成功事件序列中的 `done(error/aborted)`；`length/incomplete` 也不是正常完成。 + 模型端点差异只留在 Adapter。Loop、Blob、checkpoint 和 Cursor transport 不依赖具体 provider。 -### 16.3 RunSSE 的线格式 +### 16.3 上游调用的最小知识边界 + +当前自然的数据流是： + +```text +selected revision +→ 纯 model/projection：canonical messages → typed history +→ PromptSpec + ModelSpec + typed history = ModelRequest +→ ModelInvocation(call_id + cancellation + ModelRequest) +→ 固定 Provider adapter 的 request projector +→ HTTP response headers → SSE decoder +→ ModelEvent +→ 严格 ModelCycle +``` + +`ModelRequest` 只保存可重放输入，不含 request id、时间、`model_call_id` 或 Cursor mode；调用 ID 和取消属于 `ModelInvocation`。每一轮都显式发送完整请求，不使用 `previous_response_id` 等服务端隐式会话作为上下文事实源。相同 PromptSpec、ModelSpec 和 selected revision 必须产生可比较的同一请求；下一 revision 只扩展旧历史前缀。 + +Provider adapter 只认识 typed text/image/assistant/call/result 和自己的 endpoint JSON，不读 SQLite，不发 Cursor protobuf，不构造 checkpoint，也不执行工具。Chat、Responses、Anthropic 分别保存并回传自己的 reasoning replay state；跨端点不解码、不伪造。usage 的累计语义由各 adapter 在内部消化，对公共 ModelCycle 只发一次端点本轮最终可信总量；第二个 Usage 是协议错误，不能静默覆盖前值。缺失时保持缺失。 + +同一个 CancellationToken 必须同时覆盖等待 HTTP 响应头和读取 SSE。若只在 SSE 建立后监听取消，新 Run 会无法及时中断仍卡在上游握手中的旧 Run。HTTP 非成功状态、裸 EOF、未闭合 content/tool block、`length/incomplete` 都是显式失败，不能 fallback 成正常 Done。 + +### 16.4 RunSSE 的线格式 `RunSSE` 虽然使用流式 HTTP，但正文不是浏览器式文本 `data: ...\n\n`。它是 Connect 流式二进制 envelope： @@ -866,30 +891,31 @@ Runtime tag 虽然是实时产生的，但首次追加后也立即成为不可 `model_call_id` 只是一次模型调用的关联 ID，不是 provider 前缀缓存条件。跨模型时正常构造新请求即可，不应为了复用 `model_call_id` 改写历史。 +PromptSpec 只在单个 Run 内冻结。新 Run 切换模型或模式时，如果 system prompt 内容发生变化，Cursor checkpoint 应以新的内容寻址 Blob 替换 system root，同时复用其余历史 message roots；不能因为旧 system root 文本不同而拒绝对话。该请求自然进入新的模型/Prompt 缓存域，不要求跨模型共享缓存。上游 ModelRequest 始终使用本 Run 的 PromptSpec，旧 system root 只用于恢复时验证历史结构，不进入 canonical messages。 + ### 17.2 Tool call/result 的完整性约束 -工具可以并行执行并乱序完成，但下一次模型调用不能看到悬空 tool call。内部状态应把每个调用和结果一对一关联： +工具可以并行执行并乱序完成，但下一次模型调用不能看到悬空 tool call。每个完成结果以一组相邻消息原子提交： ```text -ToolBatch -├─ slot 0: call0 ↔ result0 -├─ slot 1: call1 ↔ result1 -└─ slot 2: call2 ↔ result2 +assistant(call3) → tool(result3) +assistant(call1) → tool(result1) +assistant(call0) → tool(result0) ``` -只有当前模型产生的 Tool Batch 全部具有可投射结果后，才能构造下一轮 provider request。该约束保证相同 committed state 总能产生相同请求。 +这里的 pair 顺序就是真实 `completion_seq`，不为恢复原始 call 顺序而阻塞已完成工具。只有当前模型产生的 ToolRound 全部具有可投射结果后，公共 projector 才按 durable ToolRoundId 折叠成一个 assistant batch；assistant 内 calls 恢复 Provider 原始 index，随后的 result messages 保持 completion_seq。该约束保证相同 committed revision 总能产生相同请求。 抓包中的模型 transcript 采用 AI SDK/OpenAI Chat 风格： ```text assistant: [call0, call1, call2, call3] -tool: result0 tool: result1 -tool: result2 tool: result3 +tool: result2 +tool: result0 ``` -真实执行完成顺序为 `result1、result3、result2、result0`，但最终持久化顺序恢复成原始 call 顺序。这里的“一对一”是语义配对和原子投射约束，不要求所有 provider 都使用字面上的 `call0,result0,call1,result1` 排列；具体线格式由端点 Adapter 决定。 +这里的“一对一”是语义配对、相邻原子提交和整批完整性约束，不要求 result 与 call index 同序；具体线格式由端点 Adapter 决定。 ## 18. Tool 流事件与客户端占位卡片 @@ -932,7 +958,7 @@ tool name → execution delta/result mapper ``` -## 19. Checkpoint 的时机与单 Tool 回滚 +## 19. Checkpoint 的时机与 ToolRound 恢复 ### 19.1 Checkpoint 是可恢复提交，不只是 UI 快照 @@ -963,35 +989,52 @@ checkpoint pending=1 但抓包中的四工具样本没有把第一个完成结果单独写进 Turn。第一个 `tool_call_completed` 后发出的 checkpoint 仍只有 Thinking 和 Assistant 两个 Step；等四个工具全完成后，四个 Tool Step 才一起进入新 Turn。因此当前样本能恢复到“工具批次正在执行”，不能恢复到“其中某一个工具已经完成且结果已持久化”。 -### 19.3 服务端目标：单 Tool 粒度 +### 19.3 服务端目标：忠实实现 ToolRound 粒度 -为了避免崩溃后重复执行写文件、shell、MCP 等有副作用的工具，服务端实现应提高到单 Tool 粒度。每个 call 使用固定 slot，完成状态可以和其他工具交叉： +服务端不能以“减少副作用重放”为理由发明抓包中不存在的部分完成 checkpoint。正确提交点只有两个： ```text -slot[0] = call0 pending -slot[1] = call1 completed(result1) -slot[2] = call2 pending +Provider 完整结束为 tools +→ 原子保存 ToolRound assistant 与全部有序 calls +→ checkpoint(stable roots 不变，pending assistant = 1) +→ 执行工具 + +每个 Tool Result 到达 +→ 按真实完成顺序原子追加 assistant(call) → tool(result) +→ 中间结果不发布 checkpoint +→ 最后一个结果使 ToolRound settled +→ Blob SET/ACK +→ checkpoint(assistant batch + 全部 results 进入 stable roots，pending = 0) +→ 下一轮 LLM ``` -建议两个提交点： +SQLite 的 durable ToolRound 可以记录单 call 完成状态，用于进程内一致性和诊断；它不是客户端已经持有的恢复点。Cursor 自动恢复只以客户端下一次带回的 eligible checkpoint 为事实，因此 staged 状态中断后会重新执行整批工具。若未来要避免某类副作用重复执行，需要新的 wire 证据或客户端幂等键，不能把部分 ToolResult 塞进当前 checkpoint 语义。 + +### 19.4 当前版本复核：exchange 9005 与 Cursor.app + +当前 Cursor `3.16.17` 的完整 exchange `9005` 给出更精确的序列。frame `467/493/504/526/543/565/579/613/625/1643/1644/1645` 的 `(stable roots, pending)` 依次为： ```text -Tool 参数完整 -→ 持久化 Tool Intent -→ Blob 确认 -→ checkpoint(call=pending) -→ 才向客户端发 ExecServerMessage - -Tool Result 返回 -→ 服务端本地 SQLite 先记 working state -→ 生成 Result JSON Blob、Completed Tool Step Blob、新 Turn Blob -→ Blob 确认 -→ checkpoint(call=completed) +(31,0) → (31,1) → (35,0) +→ (35,1) → (39,0) +→ (39,1) → (43,0) +→ (43,1) → (48,0) +→ (48,1) → (49,0) → (49,0) ``` -Checkpoint 可以记录部分完成的 Tool Batch，但 LLM Projector 仍须等待整批 call/result 完整，不能把部分完成状态投射为下一轮模型请求。这样同时满足单 Tool 回滚与 LLM tool protocol 完整性。 +四个 ToolRound 的 settled checkpoint 都严格早于下一轮首个模型 interaction：`504 < 505`、`543 < 544`、`579 < 580`、`625 < 626`。这证明 settled checkpoint 是继续 Loop 前的 client-state barrier，但不代表存在 wire checkpoint ACK；protobuf 只有 Blob SET 的 `set_blob_result(id)`。 -## 20. Blob 确认、重试与 Checkpoint 送达 +最终新 Blob 位于 RunSSE frame `1638..1641`，分别是 thinking Step、assistant Step、更新后的 Turn wrapper 和 assistant root JSON；同一 request 的 Bidi `id=122..125` 都返回成功 SET result。RunSSE 随后是 frame `1642` 的 `turn_ended`，再是 `1643..1645` 的 staged、settled、相同 settled 重发。抓包数据库没有保存两条独立 HTTP 流中每个 frame 的统一时间戳，因此不能仅凭 frame index 声称 ACK 与 `turn_ended` 的跨流先后；能够确认的是四个 ACK 均在 RunSSE 结束前到达。实现采用更强且确定的安全屏障：这四个新增 Blob 全部 ACK 后才解除 final state barrier，并发送 `turn_ended`/checkpoint。三份终局 checkpoint 的最后一个 Turn BlobID 相同，因此终局 presentation delta 只能消费一次。 + +Cursor.app 的运行代码把 `turn_ended` 前的 checkpoint 标为 `eligible`，之后标为 `ineligible_terminal_turn`。断流恢复会带回最新 eligible state 并改用 `resume_action`；若该 state 含完整 pending assistant，服务端恢复 ToolRound 并先执行工具，不得再次调用 LLM。`pendingToolCallStartedAtMs`、未知 reasoning signature 和旧 Step 时间都必须原样保留。 + +这个标记发生在客户端消费帧时，因此 `turn_ended` 与第一份终局 checkpoint 之间存在一个很窄的断流窗口：客户端已见 `turn_ended`，但还没有见 `ineligible_terminal_turn`，此时仍可能用上一份 eligible checkpoint 重试。这不改变协议顺序，也不构成 checkpoint ACK 的理由；服务端只能以下一次 `run_request` 实际带回的 state 为准。 + +stable root JSON 的 wire `id` 也不是内部身份：同一 exchange 的四个不同 assistant 工具批次都使用字符串 `"1"`，tool result root 的 `id` 等于 `toolCallId`。内部 MessageId/ToolRoundId 必须从 BlobID、序位和 durable round 产生，不能按 wire id 合并。 + +checkpoint 的非 canonical 元数据并非全部冻结。exchange `9005` 的 `read_paths` 随成功 Read 从 11 项增加到 12 项；Todo/Plan/UpdateCurrentStep 也由 typed completion 或 canonical messages 确定性推进。`token_details.used_tokens` 是当前一次完整模型上下文的占用，不等于整个 Turn 的累计 provider input。服务端以最后一次 provider 调用返回的 `input_tokens + output_tokens` 更新它；`max_tokens` 来自 Cursor 既有 checkpoint 或请求模型的 `context` 参数。breakdown 的分类值是展示估算，不冒充 provider usage，但其 token 合计必须严格等于权威 `used_tokens`。 + +## 20. Blob 确认与 Checkpoint 送达 ### 20.1 Blob SET 的确认语义 @@ -1012,7 +1055,7 @@ message SetBlobResult { `SetBlobResult {}` 表示成功，带 `error` 表示失败。当前完整 exchange 372 中 154 个 `set_blob_args` 对应 154 个无错误 `set_blob_result`，成功样本没有发现缺失确认。 -BlobID 是内容哈希，所以重发同一个 `blob_id + blob_data` 是幂等操作。KV `id` 用于匹配一次尝试；同一 Blob 可以在超时后以新的 KV `id` 重试，迟到或重复结果按 BlobID 合并为已确认状态。 +BlobID 是内容哈希，因此相同内容天然得到相同 ID；但当前会话协议仍把每次 SET 表达为唯一 KV `id` 对应唯一 `set_blob_result`。实现不在超时后生成新 KV id 重试同一 Blob，也不合并迟到尝试。 服务端应区分： @@ -1021,7 +1064,7 @@ Working State：结果已经到达服务端，但客户端 Blob 是否持久化 Committed Checkpoint：只引用已经得到成功确认的 Blob ``` -如果某个确认暂时没有返回，不应把它立即判为写入失败，也不能发布引用该 Blob 的 checkpoint。继续保持 working state、重试内容寻址写入，并保留上一个 committed checkpoint。 +如果确认在配置的等待期限内没有返回，当前 checkpoint job 失败，并进入该 Run 的 typed Error/取消生命周期；绝不能发布引用该 Blob 的 checkpoint，也不保存跨 RunSSE working/outbox 等待以后续传。 候选 checkpoint 不必等待与它无关的所有 Blob，只需要满足： @@ -1034,7 +1077,7 @@ Checkpoint C 可以发布 抓包中 `turn_ended` 后可能先发送一个过渡 checkpoint，随后相同的稳定最终 checkpoint 连续发送两到三次，最后才发送 Connect EndStream。exchange 372 的尾部是 `pending=1` 的过渡 checkpoint，接着两次 `roots=59、pending=0` 的相同最终 checkpoint。正常未断流的 RunSSE 是有序可靠字节流：客户端如果收到了后面的 EndStream，就一定先收到了位于它之前的完整 checkpoint 帧。因此在正常完成路径上，可以断言最终 checkpoint 已经通过 RunSSE 送达客户端，不需要额外 checkpoint ACK 才结束。 -需要严格区分“传输送达”和“应用层确认”：协议没有单独的 `checkpoint_ack`。重复帧说明客户端必须幂等接受相同 checkpoint，也增强了尾部发送的稳健性，但仅凭重复本身不能证明断线之后客户端已经持久化了哪一份状态。断流时应以客户端下一次 `run_request` 实际带回的 checkpoint 为恢复事实，并从服务端 SQLite working/outbox 状态继续同步。 +需要严格区分“传输送达”和“应用层确认”：协议没有单独的 `checkpoint_ack`。重复帧说明客户端必须幂等接受相同 checkpoint，也增强了尾部发送的稳健性，但仅凭重复本身不能证明断线之后客户端已经持久化了哪一份状态。断流时只以客户端下一次 `run_request` 实际带回的 checkpoint 为恢复事实；服务端不重放旧 RunSSE 帧，也不从不存在的 outbox 猜测客户端状态。 ## 21. Usage 与 Turn 收口 @@ -1058,7 +1101,32 @@ message TurnEndedUpdate { } ``` -最小实现不需要生成 `token_delta`。权威 usage 只信任各 LLM Adapter 从 provider 最终事件读取到的值：不根据文本 delta 自己 tokenize，不推算 cache token，也不推算 reasoning token。provider 未返回的可选字段保持缺失。 +exchange `9005` 明确包含 378 个 `token_delta`，合计 5022；它们穿插在 thinking、text、tool/exec 流事件之间。该流最终的 `turn_ended` 是 `input=388564、output=5870、cache_read=346112、reasoning=2736`，因此 `token_delta` 既不是 Turn input，也不是最终 output 的逐块拆分。checkpoint 的 `used_tokens` 同时从 35302 前进到 44492，`max_tokens=256000`。三者职责必须分开： + +```text +token_delta 生成期间供 Cursor UI 增量刷新 +checkpoint.token_details 当前上下文占用/上限 +turn_ended 整个 Run 的 provider 权威累计量 +``` + +通用 provider 端点通常只在流末给出可信 token 数，无法复现 Cursor 私有服务逐 chunk 的估算。当前实现因此在每次模型调用的 terminal Usage 到达时发送一个 `token_delta(output_tokens)`，不根据文本、thinking 或工具参数自行 tokenize；随后用该次调用的 `input_tokens + output_tokens` 更新 checkpoint。这样 UI 会更新，数值仍全部来自 provider，只是刷新粒度为一次模型调用而非每个 chunk。 + +同一抓包还证明 breakdown 不是把权威总量按比例平摊。六个非对话分类在所有 checkpoint 中保持固定： + +| id | label | character_count | estimated_tokens | +| --- | --- | ---: | ---: | +| `system_prompt` | System prompt | 3372 | 920 | +| `tools` | Tool definitions | 40174 | 10965 | +| `rules` | Rules | 7684 | 2097 | +| `skills` | Skills | 6305 | 1720 | +| `mcp` | MCP & dynamic tools | 11916 | 3252 | +| `subagents` | Subagent definitions | 3413 | 931 | + +`summarized_conversation` 在该样本为零；`conversation` 随消息增长，并取得 `used_tokens` 扣除其他分类估算后的剩余值。例如最终 `used_tokens=44492`，其他分类合计 19885，故 conversation 恰为 24607。实现遵守同一结构：按实际投射内容分别统计 UTF-16 `character_count`；system prompt、静态工具、rules、skills、动态 MCP、subagent 和已有 summary 独立估算；普通 user/assistant/tool 内容进入 conversation；最后由 conversation 吸收权威总量的余数。若分类估算异常超过权威总量，则只按最大余数法压缩非 conversation 分类，保证八类非负且总和始终精确。 + +分类边界来自实际数据流而不是工具名猜测：静态 prompt 和 ToolDefinition 由当前 PromptSpec 提供，动态 MCP ToolDefinition 进入 `mcp`，只有 `origin=runtime` 的消息才解析其中明确的 ``、``、``、`` 区段；用户正文即使含相似文本也仍属于 conversation。分类估算器按 Cursor/JavaScript 的 UTF-16 字符口径统计，ASCII 使用每字符约 `0.273` token、非 ASCII 使用每 UTF-16 code unit 约 `0.55` token；这只决定分类分布，不改变 provider 权威总量。当前抓包的 `prompt_context_usage_tree` 为空，因此只生成已被证实的八类 breakdown，不编造 tree/node 或 snapshot Blob。 + +权威 usage 只信任各 LLM Adapter 从 provider 最终事件读取到的值：不推算 cache token，也不推算 reasoning token。adapter 可读取多个端点累计快照，但必须先汇总并只交付一个 terminal total；公共状态机收到重复 Usage 直接失败。provider 未返回的可选字段保持缺失。 `turn_ended` 表达整个 Cursor Run/Turn 的汇总，而不是一次 provider 调用。exchange 372 的最终值为： @@ -1072,14 +1140,15 @@ reasoning_tokens = 5004 `input_tokens` 已明显超过单次 256K 上下文，证明它是同一 Run 内多次 LLM 调用的累计值。实现时只对 provider 返回的可信调用总量求和，然后在最终 `turn_ended` 一次汇报。 -最终收口顺序建议为： +当前实现的固定收口顺序为： ```text 最终 provider done(stop) → 最终 text_delta / step_completed -→ SET 最终 assistant JSON / Step / Turn Blob +→ 构造并 SET 最终 assistant JSON / Step / Turn Blob +→ 等待这些新增 Blob 的配对 SET ACK → turn_ended(整轮可信 usage 总量) -→ 等待所引用 Blob 成功确认并发送过渡 checkpoint（如果需要） +→ 发送 pending=1 的过渡 checkpoint → final checkpoint(pending=0) → 幂等重复 final checkpoint → Connect EndStream @@ -1186,7 +1255,7 @@ request_id → 一次 Run/传输尝试 RunSSE → request_id 的下行通道 ``` -当前抓包没有 abort/error 尾部，因此异常路径只能作为实现约束：用户打断时取消旧 provider 和尚未继续的工具，提交最后安全 checkpoint，以 canceled/aborted EndStream 结束旧 Run；不能伪造正常成功的 `turn_ended`。单纯的 RunSSE 断线也不等于 Turn 已结束，恢复事实应来自客户端下一次带回的 checkpoint。 +当前抓包没有 abort/error 尾部，因此异常路径只能作为实现约束：用户打断时取消旧 provider 和尚未继续的工具，保留此前已经发布的最后安全 checkpoint，不再为取消制造新 checkpoint，并以 canceled/aborted EndStream 结束旧 Run；不能伪造正常成功的 `turn_ended`。单纯的 RunSSE 断线也不等于 Turn 已结束，恢复事实应来自客户端下一次带回的 checkpoint。 ## 23. Runtime tag：运行时产生、严格追加一次 @@ -1291,54 +1360,80 @@ CreatePlan 参数/成功结果 → 更新 current_plan 投影 ## 25. 多模式 Prompt 与 Tool 资产 -`main` 分支已有完整的静态 prompt、模式工具定义和 reminder 模板。已将其中 18 个语言无关资产原样复制到当前分支的 `prompt/`： +当前静态资产已经收敛到 `prompt/cursor/`。完整工具 schema 只有根目录一个 catalog，各模式只保存有序 manifest；共享 schema 不在不同模式间复制： ```text -prompt/ -├─ common_prefix.md -├─ agent/ prompt.md + tools.json -├─ ask/ prompt.md + tools.json -├─ plan/ prompt.md + tools.json + system_reminder.txt -├─ debug/ prompt.md + tools.json + initial/continuing reminder -├─ multitask/ prompt.md + tools.json -├─ subagent/ prompt.md + tools.json -├─ compaction/ prompt.md -└─ commit/ prompt.md +prompt/cursor/ +├─ tools.json # 完整 schema catalog + Task.subagent variant +├─ modes/ # 每个模式的有序工具 manifest +│ ├─ agent.json +│ ├─ ask.json +│ ├─ plan.json +│ ├─ debug.json +│ ├─ multitask.json +│ ├─ subagent.json +│ └─ compaction.json +├─ agent/ +│ ├─ prompt.md # 静态 system prompt +│ └─ runtime.md # 本模式的 user-role runtime 模板 +├─ ask/{prompt.md,runtime.md} +├─ plan/{prompt.md,runtime.md} +├─ debug/{prompt.md,runtime.md} +├─ multitask/{prompt.md,runtime.md} +├─ subagent/{prompt.md,runtime.md} +└─ compaction/{prompt.md,runtime.md} ``` 工具数量： | 模式 | Tools | | --- | ---: | -| Agent | 21 | -| Ask | 19 | -| Plan | 17 | -| Debug | 19 | -| Multitask | 21 | -| Subagent | 4 | +| Agent | 20 | +| Ask | 15 | +| Plan | 13 | +| Debug | 15 | +| Multitask | 17 | +| Subagent | 20 | +| Compaction | 0 | Rust 服务端应在启动时加载、解析并校验这些资产： ```rust struct ModeAssets { - system_prompt: Arc, + prompt: Arc, + runtime: Arc, tools: Arc<[ToolDefinition]>, - runtime_reminders: Arc<[RuntimeTemplate]>, } ``` -模式映射： +模式映射和消费规则： ```text -AGENT_MODE_AGENT → common prefix + agent prompt/tools -AGENT_MODE_ASK → common prefix + ask prompt/tools -AGENT_MODE_PLAN → common prefix + plan prompt/tools/reminder -AGENT_MODE_DEBUG → debug prompt/tools + initial/continuing reminder -AGENT_MODE_MULTITASK → common prefix + multitask prompt/tools -子 Agent conversation → subagent prompt +受限 tools +UserMessage.mode → 当前 Run 的 prompt.md + runtime.md + tools manifest +conversation_state.mode → 仅给没有 UserMessage.mode 的后台完成等动作提供模式 +subagent_type_name → 明确选择 subagent 资产 ``` -静态 prompt 和工具目录按 mode 选择；运行时 reminder 必须遵守第 23 节的 exactly-once append，不能因为每轮加载同一个模板而重复加入 messages。模式或工具集合切换可以形成新的 provider cache 边界，但已提交的模型 messages 仍然保持严格只追加。 +不能用恢复出来的 `conversation_state.mode` 覆盖当前 `UserMessage.mode`；否则 UI 刚切换 Ask/Plan/Debug/Multitask 时，本轮仍会用旧模式的 prompt 和 tools。也不使用目录别名或缺失资产 fallback：每个可用模式都必须显式维护自己的 `prompt.md` 和 `runtime.md`，缺失或模板占位符非法时服务启动失败。 + +`runtime.md` 是一次性渲染的 Markdown 模板。通用占位符为： + +```text +{{REQUEST_CONTEXT}} +{{OPEN_FILES}} +{{SELECTED_CONTEXT}} +{{ACTION_CONTEXT}} +{{TIMESTAMP}} +{{USER_QUERY}} +``` + +Debug 额外使用 `{{DEBUG_SERVER_ENDPOINT}}`、`{{DEBUG_LOG_PATH}}` 和 `{{DEBUG_SESSION_ID}}`。模板必须包含 `TIMESTAMP` 和 `USER_QUERY`；其他区块完全取决于当前 RunRequest：有数据就加入，没有就渲染为空，不从历史猜测，不制造空标签，不使用默认内容托底。渲染是单遍替换，用户文本中恰好出现 `{{...}}` 不会被当成第二层模板执行。 + +当前请求的 `RequestContextRulesPart`、`RequestContextSkillsPart`、`RequestContextSubagentsPart` 和 `RequestContextMcpsPart` 先按 BlobID 取回，校验 hash 和 byte length，再按明确 protobuf 类型解码；缺 Blob、长度不符或类型错误都是协议错误，不能忽略。公共请求上下文按抓包顺序编译为 `user_info → git_status → agent_transcripts → rules/skills/subagents/MCP`，后四类同样只在当前请求携带时出现。 + +每个携带用户语义的 RunRequest 最终只产生一条 `role=user, origin=runtime` 的 canonical message：模式 reminder、当前请求上下文、时间、`user_query` 和图片都在同一条 message 中。原始 `UserMessage.text` 不再另行投射，避免同一用户问题出现两次。该 message 以 `run-request:{request_id}` 作为 runtime event identity，在 Start 或 Resume 进入 provider 前与 messages 一起持久化；恢复和 provider 重试只能重放已持久化文本，不能重新取时间或重新渲染。 + +静态 prompt 和工具目录按 mode 选择；运行时 message 必须遵守第 23 节的 exactly-once append。模式或工具集合切换可以形成新的 provider cache 边界，但已提交的模型 messages 仍然保持严格只追加。 @@ -1355,7 +1450,7 @@ BidiAppend.run_request → 投射 RunSSE 流事件 → 客户端执行 Tool → BidiAppend 返回结果 -→ 单 Tool checkpoint +→ ToolRound settled checkpoint → 下一轮 LLM → turn_ended → final checkpoint @@ -1367,7 +1462,7 @@ Runtime event 恰好追加一个 runtime-origin/user-role message。 Provider 重试只重放，不能重复追加任何 message。 Tool call/result 必须一对一完整，不能向 LLM 投射悬空调用。 Tool 可以乱序完成，但下一轮 LLM 必须等待整个 Tool Batch 完整。 -每个 Tool 单独持久化和 checkpoint，避免有副作用工具被重复执行。 +每个 Tool Result 单独原子持久化，但只在整个 ToolRound staged/settled 边界发布 checkpoint。 Blob 先确认，checkpoint 后发布。 turn_ended、final checkpoint、EndStream 是三个独立边界。 Usage 只信任 provider，最终按整个 Turn 汇总。 @@ -1484,29 +1579,28 @@ is_expected = false 成功路径： ```text -业务消息 -→ Blob SET / ACK barrier -→ turn_ended + final checkpoint +最终 assistant revision 提交 +→ staged/settled 所需 Blob SET / ACK barrier +→ turn_ended +→ staged pending=1 +→ settled pending=0 +→ 幂等重发同一 settled → EndStream {} → 关闭 RunSSE 输出 ``` -真实抓包的客户端可见尾序列是 `turn_ended → 重复 final checkpoint → EndStream {}`。`main` 分支现有 Go 实现是 `Blob ACK → checkpoint → turn_ended → EndStream {}`；两者的最终语义相同，但 Rust 的协议兼容测试应固定所采用的客户端可见顺序。 +真实抓包稳定呈现 `turn_ended → staged → settled → settled 重发 → EndStream {}`。Cursor.app 将 `turn_ended` 之前的 checkpoint 视为 eligible，将其后的终局快照视为 `ineligible_terminal_turn`；这些顺序不能因“最终语义相同”而交换。 Provider 失败路径： ```text 停止 provider -→ 保存已经收到并确认的部分 assistant 输出 → 保存 provider 已汇报的 usage 与失败元数据 -→ 从当前已提交 messages 构造 checkpoint -→ Blob SET / ACK barrier -→ 发布 checkpoint → Error EndStream → 关闭 RunSSE 输出 ``` -失败路径不发送 `turn_ended`，不发送错误 `TextDelta`，也不把错误字符串追加为 assistant message。已经作为正常 provider delta 发出的部分内容可以保留；错误本身只存在于 run 元数据和 Connect error 中。若在 checkpoint Blob 同步失败时采用超时策略，可以跳过未获确认的 checkpoint，但仍必须发送 Error EndStream，不能让流永久悬挂。 +失败路径不发送 `turn_ended`，不发送错误 `TextDelta`，不把错误字符串或半截 assistant 追加进 canonical messages，也不伪造新的成功 checkpoint；失败前已经发布的 initial/settled checkpoint 仍然有效。已经发送到 UI 的 partial text/thinking 只作为诊断展示；错误本身进入 Run 元数据和 Connect error。checkpoint Blob 构造或 ACK 失败同样直接进入 Error 生命周期。 用户取消或新 Run 打断旧 Run： @@ -1518,7 +1612,7 @@ Provider 失败路径： → 关闭旧 RunSSE 输出 ``` -取消不发送 `turn_ended`，也不发布一个代表成功完成的新 checkpoint。Cursor 对 Connect `canceled` 有专门处理，不应将它显示为普通错误。已在更早的单 Tool checkpoint 中确认的副作用和消息保持有效；未完成工具不能投射进下一轮 LLM。 +取消不发送 `turn_ended`，也不发布一个代表成功完成的新 checkpoint。Cursor 对 Connect `canceled` 有专门处理，不应将它显示为普通错误。此前已经发布的 settled ToolRound checkpoint 保持有效；尚未 settled 的工具批次不能投射进下一轮 LLM。 ### 26.5 统一终结不变量 @@ -1591,13 +1685,13 @@ RunRegistry 下发 Exec 前在内存中建立 `id → call_id`，客户端结果到达时用 `message.id` O(1) 查找，不查 SQLite。数字 ID 在整个 request 内单调递增，条目在 result/exit 到达后标记为 `ResultReceived`，在随后的 `stream_close` 到达时删除。Run 取消或失败时对仍为 `Running` 的 ID 发送 abort，然后清空全部条目。 -这个映射是运行期协议状态，不是上下文事实源。SQLite 只保存已经关联成功的 `run_tool_results` 和 checkpoint，不参与每个 Shell 流片段的实时查找。 +这个映射是运行期协议状态，不是上下文事实源。SQLite 只在 durable `tool_round_calls` 中保存已经关联成功的 ToolResult，不参与每个 Shell 流片段的实时查找；checkpoint 也不是 SQLite 中的第二份会话状态。 -客户端会在 result/exit 之后紧接着发送 `stream_close`。因此 `run_tool_results` 的持久化不能使用“事务内先 SELECT completion_seq，再将 deferred transaction 升级为写事务”的方式，它会和 Bidi `append_seqno` 的并发更新产生 `SQLITE_BUSY_SNAPSHOT`。completion_seq 的计算和 ToolResult 插入必须合并为单条原子 `INSERT ... SELECT`。 +客户端会在 result/exit 之后紧接着发送 `stream_close`。ToolResult 的 completion_seq、call 状态、assistant/result message pair、ToolRound version 和新 revision 必须在同一个 immediate transaction 中推进，不能先读序号再把 deferred transaction 升级为写事务，否则会留下竞态或 `SQLITE_BUSY_SNAPSHOT`。 ### 26.8 ToolResult 向 LLM 的字符串投射 -Canonical `ToolResult.output` 允许保存任意 JSON Value，因为 Todo/Plan fold、checkpoint 和调试都需要保留工具结果的结构。但是投射到 LLM 请求时，ToolResult content 必须始终是字符串，不能把 JSON object、array、number、boolean 或 null 直接放入 message content。这是所有 provider adapter 的共同输入不变量，不应由 OpenAI Chat、Responses 或 Anthropic 各自补救。 +Canonical `ToolResult.content` 本身就是字符串。adapter 在 typed Cursor 结果进入核心之前只做一次规范化：文本原样保存，结构化结果用确定性的 JSON 序列化保存。OpenAI Chat、Responses 和 Anthropic 因而都读取同一个 String，不在各端点重复猜测 JSON 类型。 已观测的失败是 `TodoWrite` 将对象结果持久化后，projector 直接生成： @@ -1620,12 +1714,13 @@ OpenAI Chat 因此拒绝 `messages[7]`，报错 `content should be a string or a 统一规则： ```text -output 是 JSON string → 直接使用原字符串，不二次加引号 -output 是其他 JSON 类型 → serde_json::to_string(output) -最终 ProviderMessage.content → 始终 Value::String +typed terminal result +→ Cursor adapter 生成 String ToolResult.content +→ SQLite/canonical message 原样保存该 String +→ Provider adapter 按本端点的 tool-result 字段放入同一个 String ``` -字符串化只发生在 `CanonicalMessage → ProviderMessage` 边界；SQLite、Blob 和 derived state 仍保留原始结构化 JSON。这样既满足 LLM 端点约束，又不破坏幂等状态投影。 +Todo/Plan/UpdateCurrentStep 等派生状态需要结构时，从已知工具的字符串 content 严格解析自己的 JSON schema；解析失败是协议错误或表示该工具没有可派生状态，不能把 canonical 类型重新放宽成任意 Value。这样 core 与 Provider 都不需要知道 Cursor protobuf。 ### 26.9 Thinking 历史的端点投射 @@ -1640,12 +1735,13 @@ The `reasoning_content` in the thinking mode must be passed back to the API. 公共投射必须保持中性结构： ```text -ProviderMessage -├─ content = assistant text -└─ thinking = assistant thinking +ProjectedMessage::Assistant +├─ text = 可展示 assistant text +├─ thinking = 可展示 thinking summary +└─ replay_state = 端点产生的不透明续传状态 ``` -具体 provider adapter 再负责端点字段映射。OpenAI Chat 必须生成： +具体 provider adapter 再负责端点字段映射。OpenAI Chat 只有在 replay state 的 `provider_kind=openai_chat` 且其中确实包含 `reasoning_content` 时才生成： ```json { @@ -1656,10 +1752,9 @@ ProviderMessage } ``` -DeepSeek 官方文档进一步明确了这里不是“字段存在即可”的校验： +DeepSeek 的 Chat 兼容端点进一步明确了这里不是“字段存在即可”的校验： -- 未调用工具的 assistant thinking，在后续请求中可以不回传；即使回传也会被忽略。 -- 只要 assistant 调用了工具，该次模型响应的 `reasoning_content` 就必须完整、原样参与后续请求。 +- 只要 assistant 调用了工具，该次模型响应的 `reasoning_content` 就必须完整参与后续请求。 - 官方示例直接追加完整的 `response.choices[0].message`，即同一条 assistant message 同时包含 `content`、`reasoning_content` 和该次响应的全部 `tool_calls`。 - 用 `reasoning_content: ""` 给拆分出的 assistant tool-call message 补字段不是正确修复；它仍然丢失了原始思维内容。 @@ -1670,7 +1765,7 @@ DeepSeek 官方文档进一步明确了这里不是“字段存在即可”的 ```text Cursor 持久化与 checkpoint 视图 assistant(call 1) → tool result 1 → assistant(call 2) → tool result 2 - 单工具完成、单工具 checkpoint + 单结果原子提交；ToolRound 完整后 settled checkpoint LLM provider 请求视图 assistant( @@ -1685,11 +1780,12 @@ assistant( 服务端继续按已完成工具保存 1:1 pair，因此中断时不会把尚未得到结果的 tool call 投射给下一次 LLM。每条 canonical assistant tool message 额外保存： ```text -model_call_id 同一次 provider 响应的分组键 +model_call_id 同一次 provider 调用的 UI/观测关联值 tool.index provider 返回的原始 tool-call 顺序 +tool_round_id durable assistant/result 分组身份 ``` -公共 projector 在编译模型请求时，按 `model_call_id` 合并同一响应的 assistant pair，取唯一的非空 `text` 和完整 `thinking`，按 `tool.index` 恢复全部 tool calls，再按同一顺序投射 ToolResult。这样 SQLite/Blob 与 Cursor 仍保留单工具粒度，而 OpenAI Chat 端点看到的是其要求的原始 assistant 响应形状。 +公共 projector 以 durable `tool_round_id` 合并同一响应的 assistant pair，取唯一的非空 `text`、完整 `thinking` 和 provider replay state，按 `tool.index` 恢复全部 tool calls，再按真实 `completion_seq` 投射 ToolResult。`model_call_id` 只用于 UI/调用关联，不承担持久分组身份。这样 SQLite 保留真实完成顺序，而 OpenAI Chat 端点看到的是其要求的原始 assistant 响应形状。 关键不变量： @@ -1701,9 +1797,9 @@ ToolBatch 未完整时不发起下一轮 LLM 请求 完成后的 provider messages 中不存在悬空 tool_calls ``` -普通模型从未返回 thinking 时，请求形状不变。OpenAI Responses 和 Anthropic 不能直接复用 `reasoning_content` 字段，应由各自 adapter 按端点原生结构处理；公共层不将 thinking 降级为普通文本。 +普通模型从未返回 replay state 时，请求形状不变。OpenAI Responses 要回传完整 reasoning output items/encrypted content，Anthropic 要回传完整 thinking blocks/signatures；两者都不能复用 `reasoning_content` 字段。公共层不将可展示 thinking 冒充任一端点的续传状态，跨 Provider 时也不解码其他端点的 capsule。 -旧版本已写入的 assistant tool pair 没有 `model_call_id` 和 `tool.index`，无法无歧义恢复原始 provider 响应。服务端不猜测旧分组；验证本修复应新建对话。新数据不需要额外迁移。 +当前实现不兼容旧 schema 或猜测缺失分组；初始 schema 直接保存 ToolRoundId、call index、completion sequence 和 replay state。 ### 26.10 Tool 完成事件与 UI 生命周期 @@ -1736,7 +1832,7 @@ ToolCallCompletedUpdate - `ExecClientMessage.message = None` 不是完成结果，只表示尚无载荷；必须保持 Pending，随后等待 typed result、Shell exit、throw 或异常 stream close。 - `PendingExecRegistry` 在下发 Exec 时保存完整 `ToolCall`、真实 `started_at_ms` 和 Shell 流缓冲；数字 ID 只在当前 Run 内用于关联。 -- Shell、Delete、Grep、Ls、ReadMcpResource、WriteShellStdin 等可直接复用上行 typed result；Read、Write、Diagnostics、MCP、Subagent、PiEdit 按 Cursor ToolCall 所需结果类型做无损或语义等价转换。 +- Shell、Delete、Grep、ReadMcpResource 等可直接复用上行 typed result；Read、Write、Diagnostics、MCP、Subagent 与编辑工具按 Cursor ToolCall 所需结果类型做无损或语义等价转换。 - `TodoWrite` 这类服务端本地工具必须构造明确 typed success。`ExecClientThrow` 不是工具结果，直接进入统一 Error 生命周期，不伪造成某个 typed result。 - Canonical `ToolResult` 继续用于 LLM 和持久化；不能用它替代 UI 所需的 typed protobuf result。 - 成败不能通过完整 protobuf `Debug` 字符串搜索 `Error`、`Failure` 等单词判断。成功写入的文件内容可能恰好包含这些词，从而产生假失败。已知 oneof 必须按具体 success/error variant 判定。 @@ -1750,50 +1846,50 @@ ToolCallStarted(args, started_at_ms) → ExecClientMessage(id, typed result) / Shell exit ├→ take(id) 消费 PendingExec 的唯一所有权 └→ 同时生成 Canonical ToolResult 与完整 typed ToolCall -→ Blob 存储确认与单 Tool checkpoint → ToolCallCompleted(args + typed result + timestamps) -→ ToolBatch 全部完整后进入下一轮 LLM +→ 最后一个结果提交后构造 ToolRound settled Blob/Turn +→ Blob ACK + settled checkpoint +→ 下一轮 LLM ``` -客户端通常在 typed result 后立即发送 `stream_close`。终态 result 已经消费 PendingExec，因此 close 只是幂等尾包；不能再维护额外的 Finished/Closed 状态。`ToolCallCompleted` 必须在该工具的消息与 checkpoint 已经提交后发布。 +客户端通常在 typed result 后立即发送 `stream_close`。终态 result 已经消费 PendingExec，因此 close 只是幂等尾包；不能再维护额外的 Finished/Closed 状态。`ToolCallCompleted` 与 staged checkpoint 没有伪全局顺序；硬约束是 typed result 对应的 canonical 消息已经提交，且整个 ToolRound 的 settled checkpoint 先于下一轮模型 interaction。 ### 26.11 Tool completion 的模块边界 -首次实现虽然修正了协议，但将 pending registry、结果通道和 typed protobuf 转换同时塞进了 `run/tool_batch.rs`、`cursor/exec.rs` 与 `cursor/interaction.rs`，使运行期关联、Exec 解析、UI 投射互相穿插。整理后的职责为： +整理后的职责为： ```text -cursor/pending.rs -└─ id → ToolCall/timing/stream buffer；存在即 Running，take 即终态 +cursor/tools/runtime.rs +└─ 当前 Cursor Run 的 wire_id → PendingExec/PendingInteraction 与完成墓碑 -cursor/tools.rs -└─ 工具批次的 Cursor step index、唯一 transport 和本地立即完成工具 +cursor/tools/dispatch/ +└─ 完整 ToolCall → 唯一 Exec/Interaction/Local transport -cursor/exec.rs -└─ 解析 ExecClientMessage/ShellStream，产生 ToolCompletion +cursor/tools/codec/{request,response}.rs +└─ ExecServerMessage 编码与 ExecClientMessage/ShellStream 解码 -cursor/tool_result.rs -├─ ToolCompletion 与结果 channel -├─ typed Exec/Interaction result → canonical 字符串结果 + typed ToolCall -└─ 本地 TodoWrite/CommunicateUpdate 的明确终态 +cursor/tools/result/ +└─ typed terminal result → String ToolResult + typed ToolCall -cursor/interaction.rs -└─ text/thinking/tool started/completed/usage 的事件外壳与 args 渲染 +cursor/interaction/ +└─ 模型流、InteractionQuery 和 typed ToolCall UI 渲染 -run/loop_engine.rs -└─ 只决定何时持久化、checkpoint、发布 completion 和进入下一轮 +run/tool_round.rs +└─ 只提交 canonical call/result、等待整批完成与 client state barrier + +cursor/checkpoint/worker.rs +└─ 串行构造 staged/settled/final Blob 图并发布 checkpoint ``` -原 `run/tool_batch.rs` 和 `model::ToolBatch` 均已删除。Loop 已经持有有序 `ordered_calls`，只需一个 `completed call_id` 集合判断 barrier；再复制一份 calls/results 容器没有增加信息。Cursor 数字 ID、protobuf typed result 和 UI 卡片状态也不再伪装成 Loop 领域状态。 - -`ToolCompletion` 对 Loop 是一个需要延迟发布的不透明完成信封：Loop 读取其中的 canonical `ToolResult` 完成消息和 checkpoint，Cursor adapter 读取 presentation payload 生成 UI typed result。Loop 不匹配 protobuf oneof，也不决定某种工具在 Cursor UI 中如何展示。 +`ToolCompletion` 不越过 client boundary。CursorSession 读取其中的 String ToolResult 发送通用 `ClientCommand::ToolResult`，同时保留 typed presentation，等核心回送对应 `StateCommitted` 后发布 UI completion。Loop 从未持有 protobuf oneof，也不决定某种工具在 Cursor UI 中如何展示。 ### 26.12 自然状态与无 fallback 约束 本轮整理删除了几类会掩盖协议错误的级联和猜测： -- 工具不会再依次尝试 `Exec → Interaction → Local`。名称在 `cursor/tools.rs` 映射到唯一 transport，Loop 不持有 `ToolRoute`；未知工具立即报 Protocol error。动态 MCP 只有在本轮定义表中存在时才走 Exec。 +- 工具不会再依次尝试 `Exec → Interaction → Local`。名称在 `cursor/tools/dispatch/` 映射到唯一 transport，Loop 不持有 `ToolRoute`；未知工具立即报 Protocol error。动态 MCP 只有在本轮定义表中存在时才走 Exec。 - Pending 项不存在 `Running/Finished/Closed` 并行标志。存在于 map 就是 Running；terminal result、throw、提前 close 都通过 `take(id)` 消费唯一所有权。 -- `ToolCompletion` 不允许只有 canonical result、没有 UI presentation 的半成品。构造成功即同时拥有可稳定投射给 LLM 的结果与完整 typed ToolCall；结构化本地结果只在 provider 边界字符串化。 +- `ToolCompletion` 不允许只有 canonical result、没有 UI presentation 的半成品。构造成功即同时拥有 String ToolResult 与完整 typed ToolCall；结构化本地结果在 Cursor result adapter 边界只字符串化一次。 - `ToolCall.name` 与 `ExecClientMessage` oneof 必须精确匹配。Read 对上 WriteResult 等组合直接报 Protocol error，且已经消费该 terminal ID，不能继续复用。 - 不再通过 protobuf `Debug` 文本生成 tool result 或判断成败；每个支持的 oneof 都显式读取。 - LLM 返回的工具参数必须是合法 JSON；不再在解析失败时降级成普通字符串。 @@ -1806,7 +1902,8 @@ run/loop_engine.rs ```text tool name → 唯一 transport pending id → take → ToolCompletion -ToolCompletion → persist/checkpoint → publish +ToolCompletion → ClientCommand → durable commit → UI publish +ToolRound settled → checkpoint barrier → next model call ``` 默认值只保留在协议本身定义为 optional 的字段上；它不能用来掩盖缺少必需字段、未知消息类型或不匹配的生命周期。 @@ -1839,7 +1936,7 @@ Cursor tool dispatcher - Task 返回 `agent_id` 与 `background_reason` 后，父 Tool 即完成；子代理随后通过独立 conversation/RunSSE 继续。父 Loop 不等待子 Run 结束。 - `request_context` 和 `execute_hook` 虽然也使用 ExecServer/ClientMessage，但不是 LLM Tool，不能追加 assistant/tool pair。 -`AwaitShell` 不是该协议中的工具。proto 中的 `AwaitToolCall / SubagentAwaitArgs` 属于 Task/Subagent 语义，不能因为字段形状相近就把 `shell_id` 填入 `agent_id`。服务端不暴露 `AwaitShell`，也不保留该错误映射；后台 Shell 只使用实际存在的 Shell、ForceBackgroundShell 与 WriteShellStdin 消息。 +`AwaitShell` 是抓包确认的模型工具，Cursor pending contract 的 identifier 为 `AWAIT`，typed UI 使用 `AwaitToolCall`。它通过终端输出文件、等待时间和可选正则表达多阶段等待；不能把 `shell_id` 错填进 Subagent 的 `agent_id`。`ForceBackgroundShell` 与 `WriteShellStdin` 不是当前模型工具，不出现在 tool catalog，也不作为 Shell 的 fallback；后台化只由 Shell stream 的真实 `Backgrounded` 结果表达。 `CommunicateUpdateSuccess.message_index` 是当前 Turn 中该 ToolCall 对应的 `ConversationStep` 一基位置，不是本地调用次数。抓包第一组事件依次产生 thinking、assistant text、CommunicateUpdate，因此结果为 `message_index = 3`；同一 Turn 后续样本累计为 `6`。服务端按已提交步骤数、当前 thinking/text 和本批 call 位置确定该值。 @@ -1859,25 +1956,24 @@ WebFetch 的第二阶段可以由 proto 无歧义确定：approval 后将同一 Cursor adapter 识别 typed terminal → ToolCompletion(canonical result + typed UI result) → Loop 统一持久化 -→ Blob ACK barrier -→ 单 Tool checkpoint → ToolCallCompleted -→ 整批完整后下一轮 LLM +→ 整批完整后 Blob ACK + settled checkpoint barrier +→ 下一轮 LLM ``` 具体落点： -- `cursor/tools.rs` 独占工具路由和本地工具启动，并计算 Cursor step index。 -- `cursor/exec.rs` 独占 Shell 流阶段与 Exec wire event。 -- `cursor/tool_result.rs` 独占 typed result 到 `ToolCompletion` 的转换。 -- `run/loop_engine.rs` 不再包含 `ToolRoute` 或工具名称表。 +- `cursor/tools/dispatch/` 独占工具路由和本地工具启动。 +- `cursor/tools/codec/response.rs` 独占 Shell 流阶段与 Exec wire event 解码。 +- `cursor/tools/result/` 独占 typed result 到 `ToolCompletion` 的转换。 +- `run/engine.rs` 和 `run/tool_round.rs` 不包含 `ToolRoute` 或工具名称表。 - 未知工具与不匹配 oneof 立即返回 Protocol Error；不尝试 Exec → Interaction → Local fallback。 ## 27. Run 进度观测：provider_call_index 必须随 Loop 更新 -对运行中的 `4468e12f-4f90-4bd9-90ed-d57c9c2bc7a9` 复核后，最初看到的状态并不是卡在第一个 Ls：Ls 的 typed result、messages 和 checkpoint 都已经完成，Run 随后继续完成 Write、ReadLints、Shell 等调用，最终形成 8 轮 provider call 并正常结束。此前数据库始终显示 `provider_call_index = 0`，只是该字段从未被 Loop 更新，因而给出了错误的观测结果。 +对运行中的 `4468e12f-4f90-4bd9-90ed-d57c9c2bc7a9` 复核后，UI loading 不能仅凭数据库某一列判断 Loop 是否越过工具 barrier。该 Run 随后继续完成编辑、ReadLints、Shell 等调用，最终形成 8 轮 provider call 并正常结束。此前数据库始终显示 `provider_call_index = 0`，只是该字段从未被 Loop 更新，因而给出了错误的观测结果。 -`append_seqno` 只表示 BidiAppend 上行序号推进，不能回答当前正在执行第几轮 LLM。`run_tool_results` 在批次完成后会被清除，outbox ACK 也只能说明 checkpoint 已确认；它们都不能替代 provider 调用进度。 +`append_seqno` 只表示 BidiAppend 上行序号推进，不能回答当前正在执行第几轮 LLM。ToolRound 状态和 Blob SET ACK 也不能替代 provider 调用进度；协议不存在 checkpoint ACK 或持久 outbox。 固定规则为： @@ -1981,3 +2077,278 @@ ShellStream Backgrounded(shell_id + pid) - Backgrounded 终态生成成功的 canonical 字符串结果，其中包含 shell_id、pid、terminals_folder 和后台化前已收到的输出；typed ShellResult 同时保留这些字段供 Cursor UI 使用。 - Runtime environment prompt 明确追加 terminals folder，使下一轮 LLM 可以按 Shell 工具规则读取后台日志。 - Backgrounded 已是当前 ToolCall 的终态。后台输出不重新打开 ToolCall，也不引入不存在的 AwaitShell。 +- `Backgrounded` 只结束当前 ToolCall，不结束客户端持有的后台进程；成功 `TurnEnded/EndStream` 不发送 `ExecServerAbort`。失败或取消也只 abort 尚未返回终态的 Exec，不能回收已经后台化的 Shell。 +- 后台化只有一层：长驻命令本身保持前台形式，例如 `python3 -m http.server 9000`，并以 `block_until_ms=0` 交给 Cursor 管理。不能同时使用 `nohup`、`&` 或 `disown`；否则 Cursor 管理的是很快退出的外层 shell，真实子进程不再具有后台 Shell 生命周期。 + +本地异常样本 `run_id=2aacf882-3b6b-4b66-9c08-5342ee5cd6b6` 正是双重后台化：Shell 参数已经是 `block_until_ms=0`，command 又执行 `nohup python3 -m http.server 9000 ... &`。Run 正常 completed，服务端没有 abort；终端 `121702` 记录外层命令成功结束，而真正 server 子进程随后消失。因此修复位于 Shell 模型契约，codec 保持官方 ShellArgs，不对用户命令做字符串改写。 + +## 30. Write / StrReplace 的参数流、展示流与执行边界 + +provider 的 `ToolCallArgumentsDelta` 是原始 JSON 文本增量，Cursor 的 `EditToolCallDelta.stream_content_delta` 是编辑卡片消费的语义内容增量。两者不是同一种事件。 + +最新官方抓包中的两个编辑分别写入 10414 字符和修改 6 字符。两者在 Cursor UI 层都表现为 `EditToolCall`，Exec 层都实际执行 `ReadArgs → ReadResult → WriteArgs → WriteResult`，没有出现 `PiEditArgs`。第一次使用数字 id 46/47，第二次使用缺省 id 0/1；每组 Read 和 Write 都复用同一个原始 `tool_call_id`。 + +固定事件映射为： + +```text +LLM ToolCallStart +→ PartialToolCallUpdate(call_id/name, 空 Edit 占位) + +LLM ToolCallArgumentsDelta(raw JSON) +→ 增量 JSON 字符串解码 +→ Write.contents / StrReplace.new_string 的已解码字符 + 立即发布 ToolCallDelta(EditToolCallDelta.stream_content_delta) +→ path 完整后发布 PartialToolCall(EditArgs.path) + +LLM 参数完整 +→ 对完整 arguments_text 做一次严格 JSON 解析 +→ ToolCallStarted(EditArgs.path + 已累计的完整 stream_content) +→ 隐藏 ReadArgs(path, 同一个 tool_call_id) + +BidiAppend ReadResult +→ Write：得到 before；file_not_found 表示 before 为空 +→ StrReplace：在 before 上执行规范化后的精确 old_string/new_string 替换 +→ 隐藏 WriteArgs(path, 完整 after, 同一个 tool_call_id) + +BidiAppend WriteResult +→ 用 before/after 构造 diff、lines_added、lines_removed 和 EditResult +→ 持久化完整 assistant/tool pair +→ ToolCallCompleted +→ 若为本轮最后结果：Blob ACK 与 ToolRound settled checkpoint +``` + +`EditToolCallDelta` 不依赖 path，也不依赖 `ToolCallStarted`。官方抓包明确出现“完整内容 delta → path partial → started”的顺序，因此服务端不能把内容缓存到 path 到达之后。`ToolCallStarted` 是参数已经完整、即将执行的边界，不是编辑增量的前置条件。 + +Read 和 Write 是两个独立 Exec 请求，各有自己的数字 `id`，由 `PendingExecRegistry` 分别匹配 BidiAppend 返回；它们共享同一个 `tool_call_id`，因为对 UI 和 LLM 来说仍是同一个工具。客户端只执行普通 Read/Write，不知道服务端内部的两阶段状态。 + +编辑域的文本统一使用 LF：JSON 的 `\\n` 先解码为真实换行，再将 CRLF 和单独 CR 规范化为 LF。Read 内容、Write 完整内容、StrReplace 的 old/new、UI stream delta、精确匹配、diff 和 `WriteArgs.file_text` 使用同一规范文本。流式规范化必须保留 chunk 末尾未决的 CR，等下一 chunk 判断它是否与 LF 组成 CRLF，不能重复发布换行。 + +抓包中的 `tool_call_id` 含真实内部换行，例如 `call-...\nfc_..._0`。它是 Cursor wire 的不透明标识，不得拆分、重建或清理内部换行；Partial、Delta、Started、隐藏 Read、隐藏 Write、Completed 必须逐字复用。Provider 的 call id/item id 应作为独立元数据保存，不能靠反向解析这个组合值恢复。 + +实现保持 Loop 工具无关：`run/model_cycle.rs` 只消费统一 provider 事件，`cursor/tools/stream.rs` 只做实时 UI 投射，`cursor/tools/edit.rs` 负责 LF 规范化、替换计算和 diff，`cursor/tools/codec/response.rs` 负责隐藏 Read/Write 状态推进，`cursor/tools/runtime.rs` 保存当前阶段。没有 post-read、Windows path 猜测、内容不一致自动修复或旧编辑消息兼容路径。 + +messages、Blob 和 checkpoint 只保存最终完整 ToolCall 与 ToolResult。`PartialToolCall` 和 `EditToolCallDelta` 都是可丢弃的实时 UI 投影，不进入上下文事实源，也不影响下一轮 LLM 的前缀稳定性。 + +## 31. 本地 Agent 路由与 Cursor backend 转发边界 + +`--test-backend-url` 或等价 endpoint 配置会把大量 Cursor backend 请求送入本地服务，不只有 Agent loop。官方抓包中的这些请求具有统一上游 `https://api2.cursor.sh`。因此 Rust 服务不能把尚未实现的接口当作本地 404；否则模型列表、服务配置、对话 metadata、认证及其他旁路业务都会被误判为不存在。 + +固定路由顺序为： + +```text +incoming request +├─ POST /agent.v1.AgentService/RunSSE +│ └─ 本地 RunSSE handler +├─ POST /aiserver.v1.BidiService/BidiAppend +│ └─ 本地 BidiAppend handler +└─ 其他 method/path + └─ https://api2.cursor.sh + 原 path/query +``` + +转发保持 method、path/query、端到端 headers 和 body；响应保持上游 status、端到端 headers 和 body。请求和响应都使用流，不先聚合完整正文，因此 Connect/SSE 和大请求不会被代理层阻塞。目标 `Host`/authority 必须改为上游，`Connection`、`Transfer-Encoding`、`Upgrade` 等 hop-by-hop headers 不能跨连接复制。 + +本地 `RequestDecompressionLayer` 只作用于两个被接管的 protobuf 路由。代理请求不经过本地解压，避免 body 已改变而 `Content-Encoding` 仍沿用原值。只有无法建立上游连接时才由本地返回 `502 unavailable`；上游实际返回的 4xx/5xx 不改写。 + +每次代理在收到上游响应头后记录 method、path、status 和耗时；连接失败记录 error。由此客户端出现 404 时可以明确区分：它是上游真实 404，而不是 Rust Router 漏注册产生的默认 404。 + +## 32. 子代理的写入、MCP 能力与工具集合 + +主对话 `conversation_id = c7e5502c-8953-4a73-b5bb-226dd9c0b8f3` 中，`request_id = 37fca97d-4f8a-487e-a465-bf6975654ffb` 的用户指令为： + +```text +接下来发起三个子代理，测试他们的文件写入和mcp能力 +其中2个是后台的，一个是前台的 +``` + +该轮实际创建了三个独立子对话：两个 `run_in_background = true`，一个 `run_in_background = false`。子代理能够执行文件写入和 MCP 操作，因此子代理不是只读搜索器，也不是只能返回文本的缩减 Loop。 + +抓包 checkpoint 中的 `pendingToolExecutionContracts.allowedToolNames` 确认，子代理当前工具集合为： + +```text +Shell +Grep +Delete +WebSearch +WebFetch +GenerateImage +ReadLints +EditNotebook +TodoWrite +StrReplace +Write +Read +Glob +Task +AwaitShell +GetMcpTools +FetchMcpResource +SwitchMode +UpdateCurrentStep +CallMcpTool +``` + +关键结论： + +- 子代理明确包含 `Write`、`StrReplace`、`EditNotebook` 和 `Delete`，具备写文件及修改工作区的能力。 +- 子代理明确包含 `GetMcpTools`、`CallMcpTool` 和 `FetchMcpResource`，具备 MCP 发现、调用和资源读取能力。 +- `run_in_background` 只决定父 Run 是否等待子代理完成，不改变子代理的 tools、messages、Blob/checkpoint 或 LLM Loop 语义。前台和后台子代理都是完整的独立 Run。 +- 子代理工具集不含 `AskQuestion`，而是用 `UpdateCurrentStep` 向父 Task 的时间线报告进度和最终摘要。 +- `Task` 仍在子代理工具集中；是否允许再创建子代理由子 Run 末尾的 runtime/system reminder 和服务端策略约束，不应靠删除 wire tool 来猜测。 + +因此，服务端不应为“前台子代理”、“后台子代理”或“MCP 子代理”建立不同 Loop。它们共享同一个 `RunActor + ToolDispatcher`；差异只来自子 `RunRequest` 的代理类型、模型配置、runtime reminder 和父子关系字段。 + +## 33. Agent 工具资产与子代理自然派生 + +工具资产现在只有一个完整 schema 事实源：`prompt/cursor/tools.json`。不存在 `tools-full.json`，也不存在 Agent/Subagent 各自复制的完整 schema。`prompt/cursor/modes/*.json` 只按抓包保存有序名称；需要不同参数形状的 `Task.subagent` 是同一 catalog 中的显式 variant，`UpdateCurrentStep` 也在 catalog 中定义一次。 + +模型请求编译时按抓包关系形成最终工具集： + +```text +主 Agent = tools.json catalog + × modes/agent.json 的有序选择 + +子 Agent = tools.json catalog + × modes/subagent.json 的有序选择 + - AskQuestion + + Task.subagent（无 environment/cloud_base_branch） + + UpdateCurrentStep +``` + +`suppress_subagent_progress_update_tool = true` 时再移除 `UpdateCurrentStep`。这不是 fallback 或兼容分支，而是 RunRequest 中有明确 wire 字段控制的能力。子代理仍保留 `Task`，但没有 Cloud 参数；`PatchEdit` 不再存在，统一使用当前协议中的 `StrReplace`。 + +抓包中主代理和子代理的基础 system prompt 使用相同 Blob hash。子代理身份、父任务和运行期要求由追加的 user/runtime 信息表达，因此子代理编译也使用 Agent prompt，不使用另一份容易漂移的缩减 system prompt。这同时保持 messages 的只追加语义和前缀稳定性。 + +### 33.1 Task 与子代理模型 + +`Task` 的自然链路为： + +```text +LLM Task arguments +→ TaskToolCall.args（UI） +→ ExecServerMessage.subagent_args（客户端执行） +→ 独立子 RunRequest +``` + +`generalPurpose` 在 `TaskArgs.subagent_type` 中编码为 `unspecified`，但在 `SubagentArgs.subagent_type` 中发送字符串 `generalPurpose`；`cursor-guide` 使用明确的 `cursor_guide` oneof，其余具有协议 oneof 的类型同理，自定义类型保留原始名称，不能先转小写再回写。 + +`SubagentArgs.parent_conversation_id` 使用当前 conversation；`root_parent_conversation_id` 使用 `conversation_group_id`，根对话没有 group 时才等于当前 conversation。`accept_hook_additional_contexts = false`，与抓包一致。模型在父 Run 内一次解析：`subagent_model_overrides` 的显式 model 优先，inherit 解析为父模型，disabled 直接拒绝该类型；没有 override 时，`Task.model = inherit` 或缺省同样解析为父模型，显式 model 则原样使用。确定的 `model_id` 才进入 SubagentArgs，子 RunRequest 再通过 `requested_model` 把模型和参数传给独立 Run。父子模型不同不改变 messages 或前缀缓存规则。 + +### 33.2 UpdateCurrentStep 与 checkpoint + +模型工具名是 `UpdateCurrentStep`，Cursor protobuf 的表现类型仍叫 `CommunicateUpdateToolCall`。服务端必须保持这两个命名层次，不能向模型暴露旧名 `CommunicateUpdate`。 + +该工具本地立即完成，成功结果写入 canonical messages： + +```text +arguments.current_step / final_summary / completed_subtitle +→ CommunicateUpdateToolCall +→ success(current_step, message_index) +→ canonical ToolResult +``` + +子 BidiAppend 的 `X-Parent-Agent-Tool-Call-Id` 被绑定到 `RunHandle`，同一 Run 若收到冲突值直接报协议错误。checkpoint 不维护第二套可变进度状态，而是从已持久化的 assistant ToolCall 和对应 ToolResult fold 出 `CommunicateUpdateTurnState`，写入： + +```text +communicate_update_states_by_parent_tool_call_id[parent Task call_id] +``` + +其中 `history[]` 保存每次 `current_step + message_index`，最后一次带值的调用提供 `final_summary` 和 `completed_subtitle`。因此恢复、重放和 checkpoint 都由 messages 唯一决定。 + +### 33.3 GetMcpTools 使用客户端实时状态 + +旧实现直接读取初始 RunRequest 的 MCP descriptor 快照并在服务端本地完成，这是错误的：它绕过了客户端当前连接状态。抓包确认的链路为： + +```text +GetMcpTools started +→ ExecServerMessage.mcp_state_exec_args +→ BidiAppend McpStateExecResult(success.servers / error / rejected) +→ 按 server、toolName、pattern 过滤 +→ GetMcpTools completed +``` + +现在 `GetMcpTools` 与其他客户端 Exec 一样先在 `PendingExecRegistry` 以数字 id 登记，再等待该 id 的 Bidi 结果。`McpStateExecArgs.server_identifiers` 只在请求指定 server 时填写，`kick_only = false`、`accept_hook_additional_contexts = false`。成功、错误和拒绝都生成相应 typed tool result，并以字符串内容追加到下一轮 LLM messages；不再从数据库或旧 descriptor 旁路完成。 + +请求 `790aff97-8c6a-4717-b9db-ccdae211c67c` 暴露了调用阶段的第二个协议要求：`GetMcpTools` 能正常列出 `server=plugin-browser-use-browser-use, toolName=browser_exec`，但旧服务端随后把 `McpArgs.name` 也写成 `browser_exec`、把 `provider_identifier` 写成空字符串，因此 Cursor 三次都返回 `MCP tool not found: browser_exec`。 + +官方抓包的 `McpStateExecResult` 已经给出完整定义，例如： + +```text +server_identifier = plugin-browser-use-browser-use +definition.name = plugin-browser-use-browser-use-browser_exec +provider_identifier = browser-use +tool_name = browser_exec +``` + +后续官方 `McpArgs` 原样使用这四个值。因此 Run 内的 MCP 定义表必须由成功的 `McpStateExecResult` 更新，以 `(server_identifier, tool_name)` 为键；`CallMcpTool` 只从这张客户端实时表取回完整 `McpToolDefinition` 并填写 Exec。不能从 server 名称截取 provider，也不能自行拼接 definition name；当精确定义不存在时，应明确要求先执行 `GetMcpTools`，不发送字段不完整的 MCP Exec。这个定义表属于 `CursorToolRuntime`，在 Run 结束时与其他 Exec 态一起释放，不读写 SQLite。 + +官方 conversation `c62e79ea-1bb2-4190-adae-cadf584d9976`（request `b0562e27-4b0e-4373-afd9-e19c74b2838e`）还给出了完整成功闭环：RunSSE frame 45/49 分别要求 `user-context7` 和 `user-codegraph` 的 MCP state；frame 157 以 `id=8` 发送 Context7 `McpArgs`，frame 184 以 `id=9` 发送 Codegraph `McpArgs`。Bidi exchange 11084 以同一 `id=8` 返回真实文本内容，exchange 11095 以 `id=9` 返回 `No results found for "main"`，两者均为 `McpResult.success`。因此 MCP 成功结果不能被压缩成 `mcp success content=N` 这类调试摘要；必须把 text、output location 和 structured content 编译成 canonical 字符串 ToolResult，`is_error` 原样保留，再进入下一轮 LLM。 + +### 33.4 证据边界 + +当前抓包已经给出 Shell、Read/Write/Edit、Delete、Glob/Grep、WebFetch、Task、AwaitShell、MCP、SwitchMode、UpdateCurrentStep 等 wire 生命周期。`WebSearch` 抓包还证明客户端只返回 approval，搜索结果由官方服务端产生；`GenerateImage` 同样属于服务端外部执行能力。它们不能伪装成本地成功，也不能仅凭 proto 编造执行器：在接入明确的搜索/图像 provider 前，现有代码只实现其 Cursor approval wire，批准后仍必须显式报未配置的服务端能力，而不是产生虚假 ToolResult。 + +### 33.5 子代理/队列恢复中的 Run 身份 + +本地异常样本显示，`001e763b-fcd4-4945-969f-57721dd827d2` 是根 Run；它派生了四个独立子 Run：`dd0971a8…`（explore）、`5ddee013…`（generalPurpose）、`2412aab8…`（shell）和 `dea4c0f5…`（cursor-guide）。`cursor-guide` 失败回传期间，Cursor 以新的 RunSSE/Bidi `request_id=2bfd06f0…` 发起一次尝试，但 `AgentRunRequest.run_id` 复用了根值 `001e763b…`。因此该 wire 字段不能作为 `runs.run_id` 的执行唯一键。 + +Cursor adapter 现在使用每次 RunSSE/Bidi 的 `request_id` 创建通用内部 RunId；wire `run_id` 不越过 adapter 成为 Store 主键。这样队列恢复是新执行，可以按客户端带回的 revision 取得 conversation ownership 并取消旧执行，而不会撞旧行。 + +此外，Run claim 失败发生在新执行尚未拥有数据库状态之前。该失败只能向当前客户端返回 typed Error，绝不能调用 `finish_run` 修改同 ID 的既有记录。旧实现正是违反了这一点：重复 INSERT 失败后又把仍在工作的根 `001e…` 标成 failed。现在只有 claim 成功的 Run 才有资格持久化 Completed/Cancelled/Failed 终态。 + +### 33.6 后台子代理完成通知 + +Task 首次创建子代理时，客户端 `SubagentSuccess` 已返回 `agent_id`，Task 调用参数中的 `description` 是该子代理的用户可见 name。两者必须立即进入 canonical ToolResult 字符串： + +```text +Subagent name: {description} +Subagent ID: {agent_id} +``` + +这条 ToolResult 表达“Task 创建出了哪个对象”，即使后台 Task 此时没有 `final_message` 也不能返回空字符串；否则 Cursor typed UI 虽持有 `TaskSuccess.agent_id`，下一轮 LLM 却不知道刚创建的子代理身份，只能从 transcript 文件或后续 completion 猜测。若首次创建时已经有 `final_message`，它接在身份之后。`resume={已有 agent_id}` 不是创建，不重复包装身份，仍只返回本次执行结果；`resume=self` 会创建新子代理，因此使用新返回的 name 和 ID。 + +官方抓包确认，后台子代理结束后客户端会为父 conversation 发起新的 RunSSE/Bidi。该 `AgentRunRequest.action` 不是普通 `user_message_action`，而是 `background_task_completion_action`；每个 completion 明确携带 `task_id`、`subagent_id`、父 `tool_call_id`、`title`、`status`、`reason`、`detail` 和 transcript `output_path`。服务端不应自行轮询子 Run，也不应从 Task 文本猜测哪个子代理完成。 + +当 `kind = SUBAGENT` 且 `reason = TASK_FINISHED` 时，completion 的 detail 先成为本轮模型可见的完成上下文，随后以 user/runtime 身份追加官方完整版 follow-up： + +```text +Perform any necessary follow-up actions in response to the subagent completion above. If no follow-up work is needed, no further action is required. If you mention an agent or subagent in your response, link it with the `[Name](id)` Don't use generic label such as `[agent]`, `[worker]`, or `[subagent]`. For cloud subagents, when the agent has edited code, link to `[Review](bc-id#changes)`, or, if you know the exact added and deleted line counts, `[Review +A −D](bc-id#changes)`, replacing A and D with those counts. Never write A or D literally. Use `[Try Live](bc-id#desktop)` only when the agent used computer use. Don't repeat the same confirmation every time. +``` + +抓包中四个后台子代理依次完成时，客户端发起了四个 completion Run，以上完整提醒也出现四次。它不是 conversation 级一次性提示，而是每个完成事件各追加一次；幂等键为 `subagent-completed:{subagent_id}`。同一 completion 重试不会产生第二条 message，不同子代理完成则保持原始时间顺序继续追加。 + +```text +后台 Task 启动，父 Turn 结束 +→ 子代理完成 +→ 客户端发送 background_task_completion_action +→ 服务端验证 SUBAGENT + TASK_FINISHED + subagent_id +→ 持久化完成 detail 与完整 follow-up user/runtime message +→ checkpoint 确认 +→ 父 conversation 新一轮 LLM +``` + +该事件同时生成 `is_simulated_msg = true`、`simulated_msg_reason = BACKGROUND_TASK_COMPLETION` 的 Cursor UserMessage/Turn，因此 UI、Blob 图和模型上下文表达同一事实。服务端此前虽然能读取普通 UserMessage 的 `subagent_system_reminder`，却完全忽略 `background_task_completion_action`；这正是后台子代理完成后父代理不会自然汇报的原因。 + +runtime message 的 checkpoint wire ID 是稳定身份 `runtime:{event_id}`，恢复时必须原样保留。`cursor-root:{blob_id}:{ordinal}` 只用于 wire ID 会重复、仅表达投射位置的普通 Cursor message，例如 assistant 的 `id = "1"`；不能替换 runtime 身份。请求 `9c1b5252-38a9-4829-87f5-2d2dda3ea37c` 的失败正是因为恢复代码把已有 `runtime:subagent-completed:{subagent_id}` 改成了位置 ID：数据库按相同 `runtime_event_id` 找到旧事件，却发现完整 canonical message 的 `message_id` 已改变，于是正确拒绝“同一事件、不同内容”。修复应恢复稳定身份，不能放宽唯一约束、覆盖旧消息或吞掉冲突。 + +### 33.7 编辑历史消息与活动后缀截断 + +`UserMessageAction` 没有 `edited` 标志；协议提供的稳定逻辑身份是 `UserMessage.message_id`。Cursor 在用户修改历史消息后会复用这个 ID 并发送新的内容。它不能继续直接充当不可变 canonical message 的主键，否则同 ID、不同 payload 会触发 `message id or runtime event reused with different content`。 + +服务端把客户端逻辑输入身份记为 `cursor:user:{message_id}`，并在第一次看到它时绑定“该输入追加前”的 `base_revision_id`： + +```text +第一次发送 M +input anchor(M) = revision before M +→ append immutable runtime message for this Run +→ append assistant/tool suffix + +编辑并再次发送 M +→ resolve input anchor(M) +→ conversation active head 回到 revision before M +→ append a new immutable runtime message +→ 生成新的 assistant/tool suffix +``` + +因此活动上下文的实际结果就是“编辑点之前的前缀 + 修改后的用户消息 + 新后缀”。原用户消息以及它后面的 assistant/tool 消息不会进入新的 LLM 请求，也不会出现在新 checkpoint 的活动 Turn 图中。旧 revision 和不可变 Blob 不做覆盖或物理删除，仍可用于历史回滚；这里所谓删除是从当前 revision 的可达集合中删除。 + +输入 anchor 使用 `(conversation_id, input_id)` 唯一键并持久化，不能只放在 Run 内存中：编辑可能发生在进程重启后。重复请求通过同一个 anchor 得到同一 base；不同内容则形成新的不可变分支。Run claim 已具备把 conversation head 原子切到所选 base 的能力，后续 append 仍受 active Run ownership 保护。 diff --git a/README.md b/README.md index ca5b4ab..1a4e922 100644 --- a/README.md +++ b/README.md @@ -1,170 +1,87 @@ -# Cursor Rust 服务端实施与验收计划 +# cursor-byok -## 项目说明 +`cursor-byok` 是一个基于真实 Cursor Agent 流量与 protobuf 实现的自托管服务端，用于把 Cursor 客户端接入用户指定的 LLM Provider。 -`cursor-byok` 是一个兼容 Cursor Agent 客户端协议的自托管服务端项目，用于把 Cursor 客户端接入用户指定的 LLM Provider。项目根据真实客户端流量和提取出的 protobuf 协议实现，不依赖 Cursor 原服务保存对话状态。 +当前 Rust 服务 `cursor-server` 已实现： -当前 Rust 服务 `cursor-server` 实现以下完整链路： +- Cursor `RunSSE + BidiAppend` 双向协议与 Connect envelope。 +- OpenAI Chat、OpenAI Responses、Anthropic 三种无状态流式端点。 +- `LLM → 客户端工具 → 结果提交 → 下一轮 LLM` 的通用 Loop。 +- append-only canonical messages、不可变 revision 分支和同对话 Run 抢占。 +- Cursor typed tool UI、Exec/Interaction、多阶段编辑、MCP 与子代理。 +- Blob CAS、KV GET/SET ACK、两阶段 checkpoint 和 pending ToolRound 恢复。 +- 未匹配 Cursor backend 路由原样流式转发到上游。 +- React + Vite + TypeScript + Tailwind 管理台，支持 Provider 配置、模型发现和调用明细。 +- 每次 Provider 调用的时间、模型快照、状态和 authoritative usage；详细模式保存脱敏请求与原始流响应。 -- 通过 `RunSSE + BidiAppend` 组成的双向协议与 Cursor 客户端通信。 -- 将 OpenAI Chat、OpenAI Responses 和 Anthropic 的流式响应统一为内部 `ResponseEvent`。 -- 运行无状态 LLM Loop：`LLM → 客户端工具执行 → 结果追加 → 下一轮 LLM`，直到 Turn 完成或被新 Run 打断。 -- 以 append-only messages 作为上下文唯一事实源，保证相邻 LLM 请求的稳定前缀和可重复投射。 -- 支持文本、thinking、tool start、参数增量、tool result、usage、model、rules、commands、skills、MCP 和 subagent 上下文。 -- 使用 SQLite 持久化 messages、Run 状态、Blob CAS、引用边和 outbox。 -- 使用不可变 Blob 对象图表达 Conversation、Turn、UserMessage 和 Steps；BlobID 为原始内容的 `SHA-256`。 -- 在客户端确认 Blob 已存储后发布 checkpoint，并提供单工具粒度的历史回滚和未确认操作恢复。 +启动方式见 [cursor-server/README.md](./cursor-server/README.md)。协议证据见 [Cursor上下文与状态同步抓包分析.md](./Cursor上下文与状态同步抓包分析.md)，当前实现约束见 [一次性重构计划计划.md](./docs/一次性重构计划计划.md)。 -运行时职责划分如下：Cursor 客户端负责真正执行本地工具并保存服务端同步的 Blob；`cursor-server` 负责 Loop 决策、上下文投射、Provider 调用、状态持久化和 checkpoint 构造。Todo/Plan 等业务状态不单独维护，而是从 messages 确定性推导。 - -协议与状态模型的抓包结论见 [Cursor上下文与状态同步抓包分析.md](./Cursor上下文与状态同步抓包分析.md)。Rust 服务的启动方式和运行配置见 [cursor-server/README.md](./cursor-server/README.md)。 - -## 目录硬约束 - -下列目录、文件名和职责是实现验收条件，不是建议。首版只允许一个 `cursor-server` crate；代码必须落在对应文件，不得用 `core.rs`、`service.rs` 等总入口替代，也不得提前创建 MCP/subagent 空模块。新增文件必须说明为何现有职责无法容纳；删除、改名或移动下列文件必须先同步修改本计划。 +## 核心数据流 ```text -cursor-byok/ -├── cursor-server/ # 新 Rust 服务 -│ ├── Cargo.toml -│ ├── build.rs # 从 cursor-proto/proto 生成 prost 类型 -│ ├── README.md # 启动方式、架构和核心不变量 -│ │ -│ ├── migrations/ -│ │ └── 0001_initial.sql # Blob、messages、runs、outbox -│ │ -│ ├── src/ -│ │ ├── main.rs # 进程入口 -│ │ ├── lib.rs # 模块出口 -│ │ ├── app.rs # 依赖组装、启动和关闭 -│ │ ├── config.rs # 地址、数据库、provider 配置 -│ │ ├── error.rs # 服务统一错误 -│ │ │ -│ │ ├── model/ # 纯领域类型，不依赖 Cursor/provider -│ │ │ ├── mod.rs -│ │ │ ├── message.rs # CanonicalMessage、Role、Origin -│ │ │ ├── runtime_tag.rs # RuntimeEvent、exactly-once 约束 -│ │ │ ├── conversation.rs # Conversation、Turn、revision -│ │ │ ├── tool.rs # ToolCall、ToolResult -│ │ │ └── usage.rs # provider usage 与 Turn usage -│ │ │ -│ │ ├── run/ # Loop 引擎和一次 request 的状态机 -│ │ │ ├── mod.rs -│ │ │ ├── registry.rs # request_id → RunHandle -│ │ │ ├── actor.rs # 每个 Run 一个 actor -│ │ │ ├── command.rs # run_request、exec/KV result、abort -│ │ │ ├── inbox.rs # append_seqno 排序、去重 -│ │ │ ├── loop_engine.rs # LLM → Tool → LLM 主循环 -│ │ │ └── lifecycle.rs # turn_ended/checkpoint/EndStream -│ │ │ -│ │ ├── cursor/ # Cursor 协议适配器 -│ │ │ ├── mod.rs -│ │ │ ├── proto.rs # include prost 生成代码 -│ │ │ ├── connect.rs # 5-byte Connect envelope -│ │ │ ├── handlers.rs # Axum 路由入口 -│ │ │ ├── bidi_append.rs # 上行 AgentClientMessage -│ │ │ ├── run_sse.rs # 下行 AgentServerMessage -│ │ │ ├── interaction.rs # 交互事件、Tool args 和 usage 投射 -│ │ │ ├── exec.rs # Exec 上行/下行解析 -│ │ │ ├── pending.rs # Exec/Interaction 的运行期 ID 关联 -│ │ │ ├── tools.rs # 唯一工具路由、本地工具和 Cursor step index -│ │ │ ├── tool_result.rs # typed result、UI completion 和结果通道 -│ │ │ ├── blob_sync.rs # KV GET/SET、ACK、重试 -│ │ │ └── checkpoint.rs # Blob 图和 checkpoint 构造 -│ │ │ -│ │ ├── provider/ # LLM 端点适配器 -│ │ │ ├── mod.rs # Provider trait -│ │ │ ├── event.rs # Canonical ResponseEvent -│ │ │ ├── openai_chat.rs # 第一条可运行链路 -│ │ │ ├── openai_responses.rs -│ │ │ └── anthropic.rs -│ │ │ -│ │ ├── prompting/ # 模型请求编译 -│ │ │ ├── mod.rs -│ │ │ ├── assets.rs # 校验并嵌入根目录 prompt/ -│ │ │ ├── compiler.rs # messages + mode + tools -│ │ │ ├── projector.rs # CanonicalMessage → provider 格式 -│ │ │ └── derived_state.rs # 从 messages fold Todo/Plan -│ │ │ -│ │ └── store/ # SQLite 持久化 -│ │ ├── mod.rs -│ │ ├── sqlite.rs # pool、事务、PRAGMA -│ │ ├── messages.rs # append-only messages -│ │ ├── blobs.rs # CAS 与引用边 -│ │ ├── conversations.rs # conversation head/revision -│ │ ├── runs.rs # 活动 Run 和恢复信息 -│ │ └── outbox.rs # KV/checkpoint 待确认操作 -│ │ -│ └── tests/ -│ ├── support/ -│ │ ├── fake_provider.rs -│ │ ├── fake_cursor.rs -│ │ └── fixtures.rs -│ ├── text_turn.rs # 纯文本完整 Turn -│ ├── tool_loop.rs # LLM → Tool → LLM -│ ├── runtime_tag_once.rs # Runtime tag 不重复追加 -│ ├── prefix_stability.rs # M(n) 是 M(n+1) 前缀 -│ ├── checkpoint_recovery.rs # 单 Tool 回滚 -│ ├── interrupt.rs # 新 Run 打断旧 Run -│ └── connect_wire.rs # Connect 二进制兼容性 -│ -├── cursor-proto/ # 现有 protobuf 提取和源文件 -├── cursor-backend/ # 现有 Go 抓包调试器 -├── prompt/ # 已复制的完整模式资产 -└── docs/ +HTTP / Connect + ↓ +Cursor adapter + ↓ ClientCommand / ClientEvent +RunEngine + ↓ +canonical messages + selected revision + ↓ +typed ModelRequest + ↓ +Provider adapter → HTTP/SSE → ModelEvent ``` -## 按文件实施顺序与通过条件 +Loop 不依赖 Cursor protobuf、Blob、checkpoint、数字 wire id 或具体 Provider JSON。Cursor adapter 和 Provider adapter 只在各自边界做协议投射。 -1. `Cargo.toml`、`build.rs`、`src/{main,lib,app,config,error}.rs`：服务能加载配置、迁移数据库、生成 Cursor protobuf 并启动/优雅关闭。 -2. `src/model/*.rs`、`src/store/*.rs`、`migrations/0001_initial.sql`：实现纯领域消息、runtime tag、tool/usage，以及 append-only messages、Blob CAS/引用边、revision、run 恢复与 outbox；`tests/runtime_tag_once.rs` 和 `tests/prefix_stability.rs` 必须通过。 -3. `src/cursor/{proto,connect,handlers,bidi_append,run_sse}.rs`：实现抓包一致的 5-byte Connect envelope、二进制 RunSSE、BidiAppend 解码和 `append_seqno` 排序去重；`tests/connect_wire.rs` 必须通过。 -4. `src/provider/{event,openai_chat,openai_responses,anthropic}.rs`、`src/prompting/*.rs`：三个端点统一为 canonical `ResponseEvent`；所有 mode 的 prompt/tool 资产可加载；messages 投射幂等且保持严格前缀。 -5. `src/run/*.rs`、`src/cursor/{tools,interaction,exec,pending,tool_result}.rs`：一个 request 一个 RunActor；Loop 只处理统一 `ToolCompletion`，工具名称到 Exec/Interaction/Local 的唯一映射只存在于 `cursor/tools.rs`；完成 toolstart 占位、参数增量、客户端执行、打断与 usage。每个完成的工具必须原子追加 `assistant(tool_call) → tool(result)`，整批完成前不得进入下一次 LLM。 -6. `src/cursor/{blob_sync,checkpoint}.rs`、`src/store/{blobs,outbox}.rs`：构造不可变 Blob 对象图，KV SET 未 ACK 前不得发布引用它的 checkpoint；checkpoint 达到单工具粒度，最终状态重复发布后再 EndStream；`tests/checkpoint_recovery.rs` 必须通过。 -7. `tests/{text_turn,tool_loop,interrupt}.rs` 与 `tests/support/*.rs`：覆盖纯文本 Turn、完整工具循环、新 Run 打断旧 Run和恢复路径。最终验收命令固定为 `cargo fmt --check`、`cargo clippy --all-targets -- -D warnings`、`cargo test --all-targets`。 +## 状态与 checkpoint +- SQLite 中的 immutable messages 与 revision 父链是对话事实源；回滚只选择旧 revision 并建立新分支。 +- ToolRound 保存完整 assistant、原始 call 顺序和真实 result 完成顺序；结果未齐时不会把悬空 tool call 投给下一轮模型。 +- BlobID 是 `SHA-256(data)`；Blob 类型来自引用字段，不编码在 ID 中。 +- checkpoint 引用的新 Blob 必须先收到对应 KV SET ACK。协议中不存在 checkpoint ACK，也不保存跨流 outbox。 +- staged checkpoint 内联完整 pending assistant；ToolRound 全部结果提交后才折叠进 stable roots。抓包没有单 ToolResult checkpoint，因此实现也不制造该状态。 +- settled checkpoint 必须先于下一轮 LLM 调用。最终文本轮严格发送 `turn_ended → staged → settled → settled 重发 → EndStream`。 +- Cursor.app 只把 `turn_ended` 前的 checkpoint 作为自动恢复候选；恢复 pending assistant 时先继续工具，不重复调用 LLM。 -模块依赖方向固定为： +## 目录边界 -HTTP/Connect - ↓ -cursor adapter - ↓ -run actor - ↓ -model + prompting - ↓ -provider / client tools - ↓ -store + checkpoint +```text +cursor-server/src/ +├── control/ # 客户端无关的 Provider、模型、调用观测 HTTP API +├── client/ # 所有客户端共用的最小 command/event port +├── model/ # canonical message、revision、ModelSpec、typed history +├── run/ # 协议无关 Loop、ModelCycle、ToolRound 和 RunRegistry +├── provider/ # 各 LLM 端点请求与流事件适配 +├── cursor/ +│ ├── request/ # RunRequest → PreparedRun/CursorRunContext +│ ├── prompting/ # Cursor prompt、工具 catalog 和 mode manifest +│ ├── projection/ # Cursor AI-SDK stable/pending JSON 编解码 +│ ├── interaction/ # UI 更新、InteractionQuery、typed ToolCall 渲染 +│ ├── tools/ # Cursor 工具 transport、runtime、dispatch 和 result +│ └── checkpoint/ # root/Turn/derived/recovery 与串行 worker +└── store/ # SQLite messages、revision、ToolRound、Run 和 Blob CAS -几个关键决定： -model/ 不引用 Cursor protobuf，也不引用具体 provider。 -cursor/ 只负责协议转换，不能包含 Loop 业务决策。 -provider/ 只把不同端点转换为统一 ResponseEvent。 -prompting/derived_state.rs 只 fold messages，不持久化 Todo/Plan。 -store/messages.rs 是上下文唯一事实源。 -store/outbox.rs 保存尚未确认的 Blob/checkpoint 操作。 -MCP 和 subagent 暂时不建空目录：MCP 先作为动态 Tool 接入；subagent 复用 RunActor，需求落地时再加入 run/subagent.rs。 - -依赖建议： -``` -tokio 异步运行时 -axum + hyper Connect HTTP 服务 -prost + prost-build protobuf -protoc-bin-vendored 避免系统 protoc 依赖 -sqlx/sqlite 持久化和事务 -reqwest provider HTTP -eventsource-stream provider SSE -serde/serde_json 模型和工具 JSON -sha2 + base64 BlobID -bytes 二进制载荷 -tokio-util CancellationToken -thiserror + tracing 错误和日志 -include_dir 编译期嵌入 prompt/ 资产 +console/ # React 管理台；只依赖 control API，不依赖 Cursor protobuf ``` -Cursor上下文与状态同步抓包分析.md 来告诉你很多信息，你需要一次性读他 +详细到文件的目标目录和验收项只在重构计划中维护，README 不复制第二份易漂移的完整文件清单。 -Users/leokun/Library/Application Support/cursor-byok/cursor-proxy-debugger.db 是cursor的原服务抓包信息，内容由/Users/leokun/Documents/cursor-byok/cursor-backend产生 +## 工程原则 + +- 不保留旧路径、兼容层或失败后的隐式 fallback。 +- 同一状态只有一个所有者；协议层不做 Loop 决策。 +- PromptSpec、ModelSpec 和 selected revision 决定可重放的 ModelRequest；request id、时间和 model call id 不进入模型输入。 +- 前缀稳定限定在相同 PromptSpec/ModelSpec/Provider route；新 Run 切换模型或模式时只替换 Cursor system root，其他历史 message roots 继续复用。 +- Provider replay state 只回传给产生它的端点；可展示 thinking 不是跨端点 reasoning 字段。 +- Provider usage 只采用端点报告的单轮最终值，不自行估算。 +- 同一个取消信号覆盖等待 HTTP 响应头和读取 SSE 两段。 + +## 验证 + +```bash +cd cursor-server +cargo fmt --check +cargo clippy --all-targets -- -D warnings +cargo test --all-targets +``` diff --git a/console/index.html b/console/index.html new file mode 100644 index 0000000..ea0724d --- /dev/null +++ b/console/index.html @@ -0,0 +1,12 @@ + + + + + + Cursor BYOK + + +
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true + }, + "less": { + "optional": true + }, + "lightningcss": { + "optional": true + }, + "sass": { + "optional": true + }, + "sass-embedded": { + "optional": true + }, + "stylus": { + "optional": true + }, + "sugarss": { + "optional": true + }, + "terser": { + "optional": true + }, + "tsx": { + "optional": true + }, + "yaml": { + "optional": true + } + } + }, + "node_modules/yallist": { + "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", + "dev": true, + "license": "ISC" + } + } +} diff --git a/console/package.json b/console/package.json new file mode 100644 index 0000000..43efb1d --- /dev/null +++ b/console/package.json @@ -0,0 +1,26 @@ +{ + "name": "cursor-byok-console", + "private": true, + "version": "0.1.0", + "type": "module", + "scripts": { + "dev": "vite", + "build": "tsc -b && vite build", + "typecheck": "tsc -b --pretty false" + }, + "dependencies": { + "@tanstack/react-query": "^5.90.0", + "react": "^19.2.0", + "react-dom": "^19.2.0", + "react-router-dom": "^7.9.0" + }, + "devDependencies": { + "@tailwindcss/vite": "^4.1.0", + "@types/react": "^19.2.0", + "@types/react-dom": "^19.2.0", + "@vitejs/plugin-react": "^5.0.0", + "tailwindcss": "^4.1.0", + "typescript": "~5.9.0", + "vite": "^7.1.0" + } +} diff --git a/console/src/api/client.ts b/console/src/api/client.ts new file mode 100644 index 0000000..20406ea --- /dev/null +++ b/console/src/api/client.ts @@ -0,0 +1,38 @@ +import type { CallDetail, LlmCall, Provider, ProviderInput, ProviderModel } from './types' + +async function request(path: string, init?: RequestInit): Promise { + const response = await fetch(path, { + ...init, + headers: { 'content-type': 'application/json', ...init?.headers }, + }) + if (!response.ok) { + const error = await response.json().catch(() => ({ message: response.statusText })) + throw new Error(error.message ?? `HTTP ${response.status}`) + } + if (response.status === 204) return undefined as T + return response.json() as Promise +} + +export const api = { + providers: () => request('/api/providers'), + createProvider: (input: ProviderInput) => + request('/api/providers', { method: 'POST', body: JSON.stringify(input) }), + updateProvider: (id: number, input: ProviderInput) => + request(`/api/providers/${id}`, { method: 'PUT', body: JSON.stringify(input) }), + deleteProvider: (id: number) => request(`/api/providers/${id}`, { method: 'DELETE' }), + discoverModels: (id: number) => + request<{ models: string[] }>(`/api/providers/${id}/models/discover`, { method: 'POST' }), + saveModels: (id: number, models: unknown[]) => + request(`/api/providers/${id}/models`, { + method: 'POST', + body: JSON.stringify({ models }), + }), + models: () => request('/api/models'), + deleteModel: (hash: string) => request(`/api/models/${hash}`, { method: 'DELETE' }), + calls: () => request('/api/llm-calls'), + call: (id: string) => request(`/api/llm-calls/${encodeURIComponent(id)}`), + observability: () => request<{ detailed: boolean }>('/api/settings/observability'), + setObservability: (detailed: boolean) => request<{ detailed: boolean }>('/api/settings/observability', { + method: 'PUT', body: JSON.stringify({ detailed }), + }), +} diff --git a/console/src/api/types.ts b/console/src/api/types.ts new file mode 100644 index 0000000..b18c828 --- /dev/null +++ b/console/src/api/types.ts @@ -0,0 +1,61 @@ +export type ProviderType = 'openai-chat' | 'openai-responses' | 'anthropic' + +export interface Provider { + provider_id: number + name: string + provider_type: ProviderType + base_url: string + has_api_key: boolean + custom_headers: Record + created_at_ms: number + updated_at_ms: number +} + +export interface ProviderInput { + name: string + provider_type: ProviderType + base_url: string + api_key?: string + custom_headers: Record +} + +export interface ProviderModel { + model_hash: string + provider_id: number + model_id: string + display_name: string + enabled: boolean + sort_order: number + context_window_tokens?: number + max_output_tokens?: number + reasoning_enabled: boolean + reasoning_effort?: string + extra_params: Record + created_at_ms: number + updated_at_ms: number +} + +export interface LlmCall { + call_id: string + run_id: string + conversation_id: string + model_hash?: string + model_id: string + display_name: string + provider_type: ProviderType + status: string + created_at_ms: number + duration_ms?: number + ttfb_ms?: number + ttft_ms?: number + input_tokens?: number + output_tokens?: number + total_tokens?: number + detailed: boolean +} + +export interface CallDetail { + call: LlmCall + request?: { headers: Record; body: unknown; byte_count: number } + response_chunks: { seq: number; received_offset_ms: number; data: string; byte_count: number }[] +} diff --git a/console/src/app/App.tsx b/console/src/app/App.tsx new file mode 100644 index 0000000..bb18f70 --- /dev/null +++ b/console/src/app/App.tsx @@ -0,0 +1,48 @@ +import { NavLink, Route, Routes } from 'react-router-dom' + +import { CallDetailPage } from '../features/calls/CallDetailPage' +import { CallsPage } from '../features/calls/CallsPage' +import { ModelsPage } from '../features/models/ModelsPage' +import { ProvidersPage } from '../features/providers/ProvidersPage' +import { ObservabilityPage } from '../features/settings/ObservabilityPage' + +const links = [ + ['/', 'Providers'], + ['/models', 'Models'], + ['/calls', 'LLM Calls'], + ['/settings', 'Settings'], +] as const + +export function App() { + return ( +
+
+
+
Cursor BYOK
+ +
+
+
+ + } /> + } /> + } /> + } /> + } /> + +
+
+ ) +} diff --git a/console/src/features/calls/CallDetailPage.tsx b/console/src/features/calls/CallDetailPage.tsx new file mode 100644 index 0000000..a4e9c5f --- /dev/null +++ b/console/src/features/calls/CallDetailPage.tsx @@ -0,0 +1,28 @@ +import { useQuery } from '@tanstack/react-query' +import { useParams } from 'react-router-dom' + +import { api } from '../../api/client' + +export function CallDetailPage() { + const { callId = '' } = useParams() + const detail = useQuery({ queryKey: ['call', callId], queryFn: () => api.call(callId) }) + if (!detail.data) return

加载中…

+ const { call, request, response_chunks: chunks } = detail.data + return
+

{call.display_name}

{call.call_id} · {call.status}

+
+ + +
+ + +
+} + +function Metric({ label, value, suffix = '' }: { label: string; value?: number; suffix?: string }) { + return

{label}

{value ?? '—'} {value == null ? '' : suffix}
+} + +function Payload({ title, value }: { title: string; value: unknown }) { + return

{title}

{typeof value === 'string' ? value : JSON.stringify(value, null, 2)}
+} diff --git a/console/src/features/calls/CallsPage.tsx b/console/src/features/calls/CallsPage.tsx new file mode 100644 index 0000000..73f2851 --- /dev/null +++ b/console/src/features/calls/CallsPage.tsx @@ -0,0 +1,17 @@ +import { useQuery } from '@tanstack/react-query' + +import { api } from '../../api/client' +import { Link } from 'react-router-dom' + +export function CallsPage() { + const calls = useQuery({ queryKey: ['calls'], queryFn: api.calls, refetchInterval: 3000 }) + return

LLM Calls

每一行对应一次真实 Provider 请求。

+
+ + {calls.data?.map((call) => + + + )}
时间模型状态TTFT耗时Tokens
{new Date(call.created_at_ms).toLocaleString()}{call.display_name}{call.model_id}{call.status}{call.ttft_ms == null ? '—' : `${call.ttft_ms} ms`}{call.duration_ms == null ? '—' : `${call.duration_ms} ms`}{call.total_tokens ?? '—'}
+
+
+} diff --git a/console/src/features/models/ModelsPage.tsx b/console/src/features/models/ModelsPage.tsx new file mode 100644 index 0000000..e1d8eae --- /dev/null +++ b/console/src/features/models/ModelsPage.tsx @@ -0,0 +1,46 @@ +import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query' +import { useState } from 'react' + +import { api } from '../../api/client' +import type { ProviderModel } from '../../api/types' + +export function ModelsPage() { + const client = useQueryClient() + const models = useQuery({ queryKey: ['models'], queryFn: api.models }) + const save = useMutation({ + mutationFn: ({ model, input }: { model: ProviderModel; input: ModelEdit }) => + api.saveModels(model.provider_id, [{ + model_id: model.model_id, display_name: input.displayName, enabled: input.enabled, sort_order: model.sort_order, + context_window_tokens: input.contextWindow || undefined, max_output_tokens: input.maxOutput || undefined, + reasoning_enabled: input.reasoning, reasoning_effort: input.effort || undefined, + extra_params: model.extra_params, + }]), + onSuccess: () => client.invalidateQueries({ queryKey: ['models'] }), + }) + return

Models

Hash 是 Cursor 和其他客户端使用的稳定公开标识。

+
+ + {models.data?.map((model) => save.mutate({ model, input })} />)}
Hash / Provider IDDisplay nameContextMax outputReasoning状态
+
+
+} + +interface ModelEdit { displayName: string; enabled: boolean; contextWindow: number; maxOutput: number; reasoning: boolean; effort: string } + +function ModelRow({ model, onSave }: { model: ProviderModel; onSave: (input: ModelEdit) => void }) { + const [displayName, setDisplayName] = useState(model.display_name) + const [contextWindow, setContextWindow] = useState(model.context_window_tokens ?? 0) + const [maxOutput, setMaxOutput] = useState(model.max_output_tokens ?? 0) + const [reasoning, setReasoning] = useState(model.reasoning_enabled) + const [effort, setEffort] = useState(model.reasoning_effort ?? '') + const value = (enabled: boolean): ModelEdit => ({ displayName, enabled, contextWindow, maxOutput, reasoning, effort }) + return + {model.model_hash}{model.model_id} + setDisplayName(event.target.value)} /> + setContextWindow(Number(event.target.value))} /> + setMaxOutput(Number(event.target.value))} /> +
setReasoning(event.target.checked)} /> setEffort(event.target.value)} />
+ {model.enabled ? 'Enabled' : 'Disabled'} +
+ +} diff --git a/console/src/features/providers/ProviderForm.tsx b/console/src/features/providers/ProviderForm.tsx new file mode 100644 index 0000000..1c3bdd9 --- /dev/null +++ b/console/src/features/providers/ProviderForm.tsx @@ -0,0 +1,38 @@ +import { useState } from 'react' + +import type { Provider, ProviderInput, ProviderType } from '../../api/types' + +export function ProviderForm({ provider, onSave, busy }: { provider?: Provider; onSave: (value: ProviderInput) => void; busy: boolean }) { + const [name, setName] = useState(provider?.name ?? '') + const [providerType, setProviderType] = useState(provider?.provider_type ?? 'openai-chat') + const [baseUrl, setBaseUrl] = useState(provider?.base_url ?? 'https://api.openai.com/v1') + const [apiKey, setApiKey] = useState('') + const [headers, setHeaders] = useState(JSON.stringify(provider?.custom_headers ?? {}, null, 2)) + + return ( +
{ + event.preventDefault() + onSave({ name, provider_type: providerType, base_url: baseUrl, api_key: apiKey || undefined, custom_headers: JSON.parse(headers) }) + }} + > + setName(e.target.value)} required /> + + + + setBaseUrl(e.target.value)} required /> + setApiKey(e.target.value)} /> +