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https://gitcode.com/JianFeeeee/ModelRouter.git
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c744ee151e
回答「opencodego 的用量与费用透传呢」时逐字段核对上游产出，发现 usage 漏了
一项、费用整项丢失。
## 上游实际发什么（实测 opencode.ai/zen/go/v1）
{
"choices": [...],
"usage": { "prompt_tokens": 37, "completion_tokens": 40, "total_tokens": 77,
"prompt_cache_hit_tokens": 0, "prompt_cache_miss_tokens": 37,
"prompt_tokens_details": {"cached_tokens": 0},
"completion_tokens_details": {"reasoning_tokens": 40} },
"cost": "0"
}
cost 在**顶层**且是**字符串**。流式时还会单独发一帧：
{"choices":[],"cost":"0"}
## 此前丢了两样
1. completion_tokens_details.reasoning_tokens —— 输出里有多少是思考 token。
没有它，客户端无法判断 completion_tokens 里多少是可见回答、多少是思考，
而两者都按输出计费。
2. cost —— 唯一的费用信号，网关整个丢弃。Go 订阅是包月制恒为 "0"，
但 Zen 按量付费模型（以及未来的其它源）有信息量。
顺带修掉一处流式/非流式不一致：命中缓存时上游同时给
prompt_tokens_details.cached_tokens 和独立的 hit/miss，流式路径写成了 elseif，
只留 details，与非流式产出不同（只认独立字段的老客户端会看不到缓存）。
## 实现
- types.TokenUsage += CompletionTokensDetails；UnifiedResponse / UnifiedChunk += Cost
- opencodego/opencodezen 适配器映射两个字段；空 choices 帧改成 usage 与 cost
都可带（早退只带 usage 会把同帧的 cost 丢干净 —— 新测试先抓到的就是这个）
- Gateway ChatCompletion / ChatChunk += cost，随终帧发（对齐上游的
{"choices":[],"cost":"0"} 形态）
- Go 兜底 standardSSEChunk 同步支持（openai 系适配器不再漏 reasoning_tokens；
纯 cost 帧不再被整体丢弃），新增 rawCostString 兼容字符串/数字两种形态
费用只做**搬运**：不解析、不换算、不汇总 —— 它是上游事实，且只有部分上游提供。
## 验证
经网关实测 gozen:deepseek-v4.1-flash，流式与非流式产出逐字段一致：
prompt_tokens_details.cached_tokens=6784
prompt_cache_hit_tokens=6784 / miss=148
completion_tokens_details.reasoning_tokens=16
cost="0"
测试：TestOpenCodeCostAndReasoningPassthrough（含「无数据不得凭空造字段」反例）、
TestOpenCodeStreamCacheFieldsMatchNonStream、TestTokenUsageMarshalsCompletionTokensDetails。
343 lines
16 KiB
Lua
343 lines
16 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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-- 上游报告输出里有多少是思考 token。不给客户端的话，无法判断
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-- completion_tokens 里多少是「可见回答」、多少是「思考」（都按输出计费）。
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local ctd = resp.usage.completion_tokens_details
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if type(ctd) == "table" and ctd.reasoning_tokens ~= nil then
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unified.token_usage.completion_tokens_details = { reasoning_tokens = ctd.reasoning_tokens }
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end
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end
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-- 本次调用的费用，上游放在**顶层**且是**字符串**（如 "0"、"0.0012"）。
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-- Go 订阅是包月制，恒为 "0"；只有 Zen 按量付费模型才有信息量。
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-- 原样透传：网关不解析、不换算、不汇总 —— 它只是上游事实的搬运者。
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if resp.cost ~= nil then
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unified.cost = tostring(resp.cost)
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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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-- 独立字段与 prompt_tokens_details **并存**透传，不要写成 elseif：
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-- 上游命中缓存时两者都发，非流式路径也是两个都带。写成 elseif 会让
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-- 流式丢掉 prompt_cache_hit_tokens/miss，与同一源的**非流式**产出不一致
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-- （dsh 优先读 details，但只认独立字段的老客户端会看不到缓存）。
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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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end
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if (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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if uses.prompt_tokens_details == nil then
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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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local ctd = chunk.usage.completion_tokens_details
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if type(ctd) == "table" and ctd.reasoning_tokens ~= nil then
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uses.completion_tokens_details = { reasoning_tokens = ctd.reasoning_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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-- 空 choices 的帧既不是内容也不是结束信号。上游发两种：
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-- {"choices":[],"usage":{...}} —— 终帧用量
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-- {"choices":[],"cost":"0"} —— 单独的费用帧
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-- 两者可能落在同一帧上，必须都转出去；早退只带 usage 会把费用丢干净。
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local out = { done = false }
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if uses ~= nil then out.usage = uses end
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if chunk.cost ~= nil then out.cost = tostring(chunk.cost) end
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if uses == nil and chunk.cost == nil then return "" end
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return json.encode(out)
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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
|
||
end
|
||
return json.encode(unified)
|
||
end
|
||
|
||
-- 错误收敛（可选钩子）：zen 错误信封固定为 {error={type,message}}；
|
||
-- 免费池限流 FreeUsageLimitError 单独标注。返回 nil 走通用兜底。
|
||
function adapter.transform_error(status, body)
|
||
local ok, resp = pcall(json.decode, body)
|
||
if not ok or type(resp) ~= "table" then return nil end
|
||
local e = resp.error
|
||
if type(e) ~= "table" then return nil end
|
||
if e.type == "FreeUsageLimitError" then
|
||
return "zen free pool quota exhausted"
|
||
end
|
||
return e.message
|
||
end
|
||
|
||
return adapter
|