mirror of
https://gitcode.com/JianFeeeee/ModelRouter.git
synced 2026-09-20 00:48:00 +00:00
c9c09b2ba2
两处都源于同一次排查：pi 到底有没有带会话标识、超窗为什么触发不了压缩。 ## 1) 客户端会话 id：pi 一直在发，只是被配置关掉了 之前结论是「通用客户端不发会话 id」——只对了一半。pi 有会话 id，且能发： pi-ai 的 createClient 在 compat.sendSessionAffinityHeaders 为真时，会把 平台会话 id（uuidv7，整个会话恒定）放到 x-session-affinity / x-client-request-id / session_id 上。该开关默认 false，而 llmsproxy 的 provider 配置里没开，所以此前一直收不到。 现在网关按优先级采纳：x-session-affinity → x-session-id → session_id → body 的 prompt_cache_key，并把值经 types.ChatRequest.ClientSession 传到 适配器 meta.client_session。适配器的会号种子优先级变为： 客户端会话 id > 首条 user 消息指纹 > 按源固定。 刻意不采纳 x-client-request-id：名字含 request，部分客户端每请求都换， 拿它当会话会让上游前缀缓存永不命中（pi 总会同时发 x-session-affinity，够用）。 实测：抓 127.0.0.1:8081 的真实 pi 请求，配置打开后收到 x-session-affinity = session_id = x-client-request-id = <子会话 uuid>。 上游缓存确为会话级隔离（同前缀、不同会号：A 冷→命中，B 首次仍为 0）， 两个不同 header 值互不命中，反证网关确实采纳了客户端会话 id。 ## 2) 超窗消息必须「干净」，否则被同链的限流措辞反向封杀 pi 的 isContextOverflow 先查 NON_OVERFLOW_PATTERNS（/rate limit/、 /too many requests/、Bedrock 前缀），命中就直接判为「非超窗」——**即使 消息里已经有 context_length_exceeded**，pi 也不会压缩重试。 而 AUTO 链的失败消息天生是多 tier 原因的拼接，超窗 tier（gozen 400 maximum context length）常与配额/限流 tier（429 token plan exhausted、 cooling、no free slot）同时出现。此前把 tier 明细原样拼在归一化标记后面， 等于让一条限流 tier 的措辞反过来封杀超窗识别。 现在超窗走独立的干净消息： context_length_exceeded: context window is full; reduce the length of the messages (gozen/deepseek-v4.1-flash) 只留超窗措辞 + 超窗源名，不带任何其它 tier 的文本。 测试：TestOverflowMessageSurvivesRateLimitedSiblingTier 用 pi 的完整判定 顺序（先 NON_OVERFLOW 后 OVERFLOW）断言同链限流 tier 不再封杀超窗识别； TestClientSessionFromRequestHeaders / TestClientRequestIDIsNotUsedAsSession / TestOpenCodePrefersClientSessionID 覆盖会话采纳与优先级。
316 lines
14 KiB
Lua
316 lines
14 KiB
Lua
local adapter = {}
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adapter.name = "opencodezen"
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adapter.version = "1.0.0"
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adapter.endpoint = "/chat/completions"
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-- OpenCode Zen（按量付费端点，https://opencode.ai/zen/v1）
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--
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-- 与 OpenCode Go（opencodego.lua，https://opencode.ai/zen/go/v1）是两个不同的
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-- 服务，行为要求并不相同，因此各有专用适配器：
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--
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-- * 本适配器（Zen）服务免费池 / 按量付费池。免费模型必须带 opencode 客户端
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-- 指纹（UA + x-opencode-*），否则上游拒绝："free tier can only be used in
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-- OpenCode"。Zen 的免费池以非 thinking 模型为主，历史上回传
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-- reasoning_content 会引出上游报错，故这里剥掉（Go 侧相反，见 opencodego.lua）。
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-- * Go 订阅读者请看 opencodego.lua：那边**必须**回传 reasoning_content，
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-- 否则 thinking 模式直接 400。
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--
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-- 缺 x-opencode-client/session/request/project 身份头会被判为匿名客户端，
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-- 部分模型在带 tools 时上游直接失败（流式返回单 chunk
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-- "finish_reason":"network_error" 空 content，非流式 503
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-- "Endpoint is unavailable"，表现为"空回复"）。
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adapter.headers = {
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["User-Agent"] = "opencode/1.18.21 ai-sdk/provider-utils/4.0.23 runtime/bun/1.3.14",
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}
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-- 每请求生成身份头。沙箱无 os/math，用 meta.timestamp + 请求体哈希派生：
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-- 同秒内重复请求 id 相同可接受（zen 只校验存在性，不校验格式）。
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local function rand_id(prefix, seed)
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return prefix .. string.sub(sha256_hex(seed), 1, 24)
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end
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-- 会话指纹：取历史里**第一条 user 消息**。
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--
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-- 为什么不直接用客户端的会话 id：实测抓包（tcpdump 抓 127.0.0.1:8081 的真实
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-- agent 请求）确认通用 OpenAI 客户端**根本不发**任何会话标识 —— body 里没有
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-- user / session_id / conversation_id / metadata，请求头也只有 X-Stainless-*
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-- （OpenAI JS SDK）与 User-Agent。opencode 原生客户端那套 x-opencode-session
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-- 是它自己的概念，通用客户端无从转发。
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--
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-- 退而求其次但要够用：历史被逐轮重放，**第一条 user 消息在整个会话里恒定**，
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-- 用它做指纹即可得到"每会话一个 session"，而不是"每源一个 session"。
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-- 拿不到时（无 user 消息）返回空串，调用方回退到按源稳定。
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local function conversation_fingerprint(body)
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if type(body) ~= "string" or body == "" then return "" end
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local ok, req = pcall(json.decode, body)
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if not ok or type(req) ~= "table" then return "" end
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for _, m in ipairs(req.messages or {}) do
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if type(m) == "table" and m.role == "user" then
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local c = m.content
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if type(c) == "string" then
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if c ~= "" then return c end
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elseif type(c) == "table" then
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for _, part in ipairs(c) do
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if type(part) == "table" and part.type == "text" and part.text then
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return part.text
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end
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end
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end
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return ""
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end
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end
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return ""
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end
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-- session_seed 决定上游会话号（x-opencode-session 的种子）。
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--
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-- 优先级：
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-- 1) 客户端自带的会话标识（meta.client_session）——pi 等在开启
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-- compat.sendSessionAffinityHeaders 后会发 x-session-affinity，
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-- 这是平台真实的会话 id，整个会话恒定且天然按会话隔离。
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-- 2) 退路：历史里**第一条 user 消息**做会话指纹。
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-- 3) 再退：只按源固定（连 user 消息都没有时）。
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--
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-- 为什么需要 2/3：通用 OpenAI 客户端默认**根本不发**会话标识 —— 实测抓包
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-- （tcpdump 抓 127.0.0.1:8081 真实 agent 请求）确认 body 里没有
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-- user / session_id / conversation_id / metadata，请求头也只有
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-- X-Stainless-*（OpenAI JS SDK）与 User-Agent。opencode 原生客户端那套
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-- x-opencode-session 是它自己的概念，通用客户端无从转发。
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--
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-- 为什么必须稳定：上游前缀缓存是**会话级**的。会话号每请求一变，
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-- 缓存永不命中（实测：固定会号第 2 次命中 5888，每请求换会号则恒为 0）。
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local function session_seed(meta)
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local src = (meta.source and meta.source.name) or ""
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local base = "session|llmsproxy|" .. src
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local cs = meta.client_session
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if type(cs) == "string" and cs ~= "" then
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return base .. "|client|" .. cs
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end
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return base .. "|" .. conversation_fingerprint(meta.body)
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end
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function adapter.build_headers(meta)
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local ts = tostring(meta.timestamp or "")
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local src = (meta.source and meta.source.name) or ""
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return {
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["User-Agent"] = adapter.headers["User-Agent"],
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["x-opencode-client"] = "cli",
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-- project 固定：同网关实例共享一个工作区身份
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["x-opencode-project"] = string.sub(sha256_hex("llmsproxy|" .. src), 1, 32),
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-- session 必须**按源稳定**，不能每请求换：上游的前缀缓存在同一 session
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-- 内才复用。实测（同一段 6032 token 提示词）：
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-- 固定 session -> 第 2 次命中 5888/6032，cached_tokens=5888
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-- 每请求换 session -> 永远 0 命中
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-- 原先用 meta.timestamp 派生，等于每请求都是新会话，缓存永远无效，
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-- 上游也无法做会话亲和路由。
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["x-opencode-session"] = rand_id("ses_", session_seed(meta)),
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-- request id 仍每请求唯一（它只是请求标识，不参与缓存键）
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["x-opencode-request"] = rand_id("msg_", "request|" .. ts .. "|" .. tostring(meta.body or "")),
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}
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end
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-- OpenAI /chat/completions format (pass-through, strip provider-specific fields)
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-- zen 上游 schema 只接受 text content part（无视觉/音频能力）：多模态 part
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-- （image_url / input_audio / file 等）一律剥离。剥离后 content 变空的消息
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-- 若不再携带 tool_calls / tool_call_id 才整条丢弃（避免上游
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-- "unknown variant `image_url`, expected `text`"）；带工具调用的必须保留，
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-- 否则会把紧随其后的 tool 结果变成孤儿，模型会反复重发同一个调用。
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-- zen 上游角色白名单只有 system / user / assistant / tool / latest_reminder：
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-- OpenAI 的 developer（及 function 等）不在其中，直接透传会触发上游
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-- "unknown variant `developer`, expected one of ..." 错误；统一归一化为 system。
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local ROLE_WHITELIST = {
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system = true,
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user = true,
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assistant = true,
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tool = true,
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latest_reminder = true,
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}
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function adapter.transform_request(raw_body)
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local ok, req = pcall(json.decode, raw_body)
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if not ok then return raw_body end
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req.disable_thinking = nil
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req.extra_body = nil
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-- stream_options is only valid alongside stream:true; sending it on a
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-- non-streaming request is rejected by strict upstreams.
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if req.stream then
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if type(req.stream_options) ~= "table" then req.stream_options = {} end
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req.stream_options.include_usage = true
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end
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if req.messages then
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local kept = {}
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for _, msg in ipairs(req.messages) do
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if type(msg.role) == "string" and not ROLE_WHITELIST[msg.role] then
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msg.role = "system"
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end
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-- Zen 免费池不接受回传 reasoning_content（Go 侧相反）
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msg.reasoning_content = nil
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local drop = false
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if type(msg.content) == "table" then
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local parts = {}
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for _, part in ipairs(msg.content) do
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if type(part) == "table" and part.type ~= nil and part.type ~= "text" then
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-- multimodal part not supported by zen
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else
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table.insert(parts, part)
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end
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end
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if #parts == 0 then
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-- Content collapsed to nothing after stripping unsupported
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-- parts. A message that still carries a tool call must
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-- NEVER be dropped: the very next message is its tool
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-- result, and dropping the call orphans that result. The
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-- model then sees a result for a call it never made and
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-- re-issues the same tool call on every turn (observed as
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-- an infinite "repeated tool call" loop).
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if (type(msg.tool_calls) == "table" and #msg.tool_calls > 0)
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or msg.tool_call_id ~= nil then
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msg.content = ""
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else
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drop = true
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end
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else
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msg.content = parts
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end
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end
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if not drop then
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table.insert(kept, msg)
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end
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end
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req.messages = kept
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end
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return json.encode(req)
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end
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function adapter.transform_response(raw_body)
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local ok, resp = pcall(json.decode, raw_body)
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if not ok or resp == nil then return raw_body end
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local unified = {
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content = "",
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finish_reason = "",
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token_usage = { prompt = 0, completion = 0, total = 0 }
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}
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if type(resp.usage) == "table" then
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unified.token_usage.prompt = resp.usage.prompt_tokens or 0
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unified.token_usage.completion = resp.usage.completion_tokens or 0
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unified.token_usage.total = resp.usage.total_tokens or 0
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local hit = 0
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if type(resp.usage.prompt_tokens_details) == "table" and resp.usage.prompt_tokens_details.cached_tokens ~= nil then
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hit = resp.usage.prompt_tokens_details.cached_tokens
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unified.token_usage.prompt_tokens_details = { cached_tokens = hit }
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end
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if (resp.usage.prompt_cache_hit_tokens or 0) > 0 then
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unified.token_usage.prompt_cache_hit_tokens = resp.usage.prompt_cache_hit_tokens
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unified.token_usage.prompt_cache_miss_tokens = resp.usage.prompt_cache_miss_tokens or 0
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if hit == 0 then
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unified.token_usage.prompt_tokens_details = { cached_tokens = resp.usage.prompt_cache_hit_tokens }
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end
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end
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end
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if type(resp.choices) == "table" and #resp.choices > 0 then
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local ch = resp.choices[1]
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if type(ch.message) == "table" then
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unified.content = ch.message.content or ""
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local reasoning = ch.message.reasoning_content or ch.message.reasoning
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if reasoning then
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unified.reasoning_content = reasoning
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end
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if type(ch.message.tool_calls) == "table" then
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local tcs = {}
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for _, tc in ipairs(ch.message.tool_calls) do
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local args_ok, args = pcall(json.decode, tc["function"].arguments)
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if not args_ok then args = {} end
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table.insert(tcs, {
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id = tc.id,
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type = tc.type or "function",
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name = tc["function"].name,
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arguments = args
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})
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end
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unified.tool_calls = tcs
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end
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end
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unified.finish_reason = ch.finish_reason or ""
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end
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return json.encode(unified)
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end
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function adapter.transform_stream_chunk(raw_chunk)
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local ok, chunk = pcall(json.decode, raw_chunk)
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if not ok then return "" end
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-- OpenAI-style streams may attach usage to a chunk with empty choices
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-- (the final usage chunk). Preserve it; the gateway emits it as the
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-- terminal usage chunk. Note: keys must match Go's TokenUsage json tags
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-- (prompt/completion/total); the gateway re-emits standard *_tokens.
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local uses = nil
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if type(chunk.usage) == "table" then
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uses = {
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prompt = chunk.usage.prompt_tokens or chunk.usage.prompt or 0,
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completion = chunk.usage.completion_tokens or chunk.usage.completion or 0,
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total = chunk.usage.total_tokens or chunk.usage.total or 0,
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}
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if type(chunk.usage.prompt_tokens_details) == "table" and chunk.usage.prompt_tokens_details.cached_tokens ~= nil then
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uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_tokens_details.cached_tokens }
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elseif (chunk.usage.prompt_cache_hit_tokens or 0) > 0 then
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uses.prompt_cache_hit_tokens = chunk.usage.prompt_cache_hit_tokens
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uses.prompt_cache_miss_tokens = chunk.usage.prompt_cache_miss_tokens or 0
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uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_cache_hit_tokens }
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end
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end
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if not chunk.choices or #chunk.choices == 0 then
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if uses ~= nil then
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-- usage-only chunk is not a content/finish signal; the gateway
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-- emits its own terminal stop chunk and merges this usage.
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return json.encode({ usage = uses, done = false })
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end
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return ""
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end
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local delta = chunk.choices[1].delta or {}
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local fr = chunk.choices[1].finish_reason
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local finish = (type(fr) == "string" and fr ~= "") and fr or nil
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local unified = {
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content = delta.content or "",
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done = (finish ~= nil)
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}
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if finish then
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unified.finish_reason = finish
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end
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if uses ~= nil then
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unified.usage = uses
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end
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-- zen 用 reasoning 字段承载推理文本（OpenAI 惯例是 reasoning_content）
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local reasoning = delta.reasoning_content or delta.reasoning
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if reasoning then
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unified.reasoning_content = reasoning
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end
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if delta.tool_calls then
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-- pass raw streaming fragments through; OpenAI clients accumulate index+id+name+arguments
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unified.tool_calls = delta.tool_calls
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end
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return json.encode(unified)
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end
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-- 错误收敛（可选钩子）：zen 错误信封固定为 {error={type,message}}；
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-- 免费池限流 FreeUsageLimitError 单独标注。返回 nil 走通用兜底。
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function adapter.transform_error(status, body)
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local ok, resp = pcall(json.decode, body)
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if not ok or type(resp) ~= "table" then return nil end
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local e = resp.error
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if type(e) ~= "table" then return nil end
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if e.type == "FreeUsageLimitError" then
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return "zen free pool quota exhausted"
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end
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return e.message
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end
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return adapter
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