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feat(adapters): split opencode into opencodezen and opencodego

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Zen (https://opencode.ai/zen/v1) and Go (https://opencode.ai/zen/go/v1)
are different services with different requirements, and one shared adapter
could not satisfy both.

The decisive difference is reasoning_content:

  * OpenCode Go runs thinking models and REQUIRES the assistant turn's
    reasoning_content to be echoed back. The shared adapter stripped it
    (msg.reasoning_content = nil), so every replay of a thinking turn
    failed with:
      400 invalid_request_error: The `reasoning_content` in the thinking
      mode must be passed back to the API.
    Reproduced directly: the same request with reasoning_content -> 200,
    without -> 400. That is why the Go tier never worked in an agent loop.

  * The Zen free pool must not receive it, so it keeps stripping.

Both adapters keep the earlier fixes they share (never drop an assistant
turn carrying tool_calls; send stream_options only when streaming; role
whitelist; multimodal strip) and the opencode client fingerprint headers —
the Go endpoint additionally REQUIRES x-opencode-session, which the
adapter already sends.

config: localzen -> opencodezen, gozen -> opencodego.
Verified: all 25 gozen models answer correctly through the gateway with a
thinking + tool_call + tool_result history (was 0/25 before), streaming
included; the Zen free models still pass.

Test: TestOpenCodeGoVsZenReasoning pins the Go-keeps / Zen-strips split.
This commit is contained in:
JianFeeeee
2026-09-11 15:00:45 +08:00
parent 0528941e24
commit 71e9040a45
3 changed files with 549 additions and 0 deletions
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248
internal/lua/adapters/opencodego.lua Normal file
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@ -0,0 +1,248 @@
local adapter = {}
adapter.name = "opencodego"
adapter.version = "1.0.0"
adapter.endpoint = "/chat/completions"
-- OpenCode Go（包月订阅端点，https://opencode.ai/zen/go/v1）
--
-- 与 OpenCode Zen（opencodezen.lua，https://opencode.ai/zen/v1）是两个不同的
-- 服务，行为要求并不相同，因此各有专用适配器：
--
-- * 本适配器（Go）服务包月订阅池。上游**强制要求**
-- `x-opencode-session` 头，缺失直接 400 "MissingSessionID"。
-- * Go 的 thinking 模型（deepseek-v4.1-flash 等）**必须回传** assistant 轮的
-- `reasoning_content`，否则 400：
-- The `reasoning_content` in the thinking mode must be passed back to the API.
-- 这是本适配器与 Zen 适配器最关键的差异 —— Zen 会剥掉它，Go 必须原样保留。
-- * Go 上游对协议更严格：非流式请求带 `stream_options` 会被拒
-- （"stream_options should be set along with stream"）。
--
-- 同样需要 opencode 客户端指纹（UA + x-opencode-*）才能被正确识别与路由。
adapter.headers = {
["User-Agent"] = "opencode/1.18.21 ai-sdk/provider-utils/4.0.23 runtime/bun/1.3.14",
}
-- 每请求生成身份头。沙箱无 os/math，用 meta.timestamp + 请求体哈希派生：
-- 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）。
local function rand_id(prefix, seed)
return prefix .. string.sub(sha256_hex(seed), 1, 24)
end
function adapter.build_headers(meta)
local ts = tostring(meta.timestamp or "")
return {
["User-Agent"] = adapter.headers["User-Agent"],
["x-opencode-client"] = "cli",
-- project 固定：同网关实例共享一个工作区身份
["x-opencode-project"] = string.sub(sha256_hex("llmsproxy|" .. (meta.source and meta.source.name or "")), 1, 32),
["x-opencode-session"] = rand_id("ses_", "session|" .. ts),
["x-opencode-request"] = rand_id("msg_", "request|" .. ts .. "|" .. tostring(meta.body or "")),
}
end
-- OpenAI /chat/completions format (pass-through, strip provider-specific fields)
-- zen 上游 schema 只接受 text content part（无视觉/音频能力）：多模态 part
-- （image_url / input_audio / file 等）一律剥离。剥离后 content 变空的消息
-- 若不再携带 tool_calls / tool_call_id 才整条丢弃（避免上游
-- "unknown variant `image_url`, expected `text`"）；带工具调用的必须保留，
-- 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。
-- zen 上游角色白名单只有 system / user / assistant / tool / latest_reminder：
-- OpenAI 的 developer（及 function 等）不在其中，直接透传会触发上游
-- "unknown variant `developer`, expected one of ..." 错误；统一归一化为 system。
local ROLE_WHITELIST = {
system = true,
user = true,
assistant = true,
tool = true,
latest_reminder = true,
}
function adapter.transform_request(raw_body)
local ok, req = pcall(json.decode, raw_body)
if not ok then return raw_body end
req.disable_thinking = nil
req.extra_body = nil
-- stream_options is only valid alongside stream:true; sending it on a
-- non-streaming request is rejected by strict upstreams.
if req.stream then
if type(req.stream_options) ~= "table" then req.stream_options = {} end
req.stream_options.include_usage = true
end
if req.messages then
local kept = {}
for _, msg in ipairs(req.messages) do
if type(msg.role) == "string" and not ROLE_WHITELIST[msg.role] then
msg.role = "system"
end
-- Go 的 thinking 模式**必须**回传 reasoning_content：剥掉它会让
-- 上游直接 400（"The `reasoning_content` in the thinking mode must
-- be passed back to the API"），agent 的每一轮都会失败。
-- 注意：与 opencodezen.lua 的行为**相反**，不要在这里剥。
local drop = false
if type(msg.content) == "table" then
local parts = {}
for _, part in ipairs(msg.content) do
if type(part) == "table" and part.type ~= nil and part.type ~= "text" then
-- multimodal part not supported by zen
else
table.insert(parts, part)
end
end
if #parts == 0 then
-- Content collapsed to nothing after stripping unsupported
-- parts. A message that still carries a tool call must
-- NEVER be dropped: the very next message is its tool
-- result, and dropping the call orphans that result. The
-- model then sees a result for a call it never made and
-- re-issues the same tool call on every turn (observed as
-- an infinite "repeated tool call" loop).
if (type(msg.tool_calls) == "table" and #msg.tool_calls > 0)
or msg.tool_call_id ~= nil then
msg.content = ""
else
drop = true
end
else
msg.content = parts
end
end
if not drop then
table.insert(kept, msg)
end
end
req.messages = kept
end
return json.encode(req)
end
function adapter.transform_response(raw_body)
local ok, resp = pcall(json.decode, raw_body)
if not ok or resp == nil then return raw_body end
local unified = {
content = "",
finish_reason = "",
token_usage = { prompt = 0, completion = 0, total = 0 }
}
if type(resp.usage) == "table" then
unified.token_usage.prompt = resp.usage.prompt_tokens or 0
unified.token_usage.completion = resp.usage.completion_tokens or 0
unified.token_usage.total = resp.usage.total_tokens or 0
local hit = 0
if type(resp.usage.prompt_tokens_details) == "table" and resp.usage.prompt_tokens_details.cached_tokens ~= nil then
hit = resp.usage.prompt_tokens_details.cached_tokens
unified.token_usage.prompt_tokens_details = { cached_tokens = hit }
end
if (resp.usage.prompt_cache_hit_tokens or 0) > 0 then
unified.token_usage.prompt_cache_hit_tokens = resp.usage.prompt_cache_hit_tokens
unified.token_usage.prompt_cache_miss_tokens = resp.usage.prompt_cache_miss_tokens or 0
if hit == 0 then
unified.token_usage.prompt_tokens_details = { cached_tokens = resp.usage.prompt_cache_hit_tokens }
end
end
end
if type(resp.choices) == "table" and #resp.choices > 0 then
local ch = resp.choices[1]
if type(ch.message) == "table" then
unified.content = ch.message.content or ""
local reasoning = ch.message.reasoning_content or ch.message.reasoning
if reasoning then
unified.reasoning_content = reasoning
end
if type(ch.message.tool_calls) == "table" then
local tcs = {}
for _, tc in ipairs(ch.message.tool_calls) do
local args_ok, args = pcall(json.decode, tc["function"].arguments)
if not args_ok then args = {} end
table.insert(tcs, {
id = tc.id,
type = tc.type or "function",
name = tc["function"].name,
arguments = args
})
end
unified.tool_calls = tcs
end
end
unified.finish_reason = ch.finish_reason or ""
end
return json.encode(unified)
end
function adapter.transform_stream_chunk(raw_chunk)
local ok, chunk = pcall(json.decode, raw_chunk)
if not ok then return "" end
-- OpenAI-style streams may attach usage to a chunk with empty choices
-- (the final usage chunk). Preserve it; the gateway emits it as the
-- terminal usage chunk. Note: keys must match Go's TokenUsage json tags
-- (prompt/completion/total); the gateway re-emits standard *_tokens.
local uses = nil
if type(chunk.usage) == "table" then
uses = {
prompt = chunk.usage.prompt_tokens or chunk.usage.prompt or 0,
completion = chunk.usage.completion_tokens or chunk.usage.completion or 0,
total = chunk.usage.total_tokens or chunk.usage.total or 0,
}
if type(chunk.usage.prompt_tokens_details) == "table" and chunk.usage.prompt_tokens_details.cached_tokens ~= nil then
uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_tokens_details.cached_tokens }
elseif (chunk.usage.prompt_cache_hit_tokens or 0) > 0 then
uses.prompt_cache_hit_tokens = chunk.usage.prompt_cache_hit_tokens
uses.prompt_cache_miss_tokens = chunk.usage.prompt_cache_miss_tokens or 0
uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_cache_hit_tokens }
end
end
if not chunk.choices or #chunk.choices == 0 then
if uses ~= nil then
-- usage-only chunk is not a content/finish signal; the gateway
-- emits its own terminal stop chunk and merges this usage.
return json.encode({ usage = uses, done = false })
end
return ""
end
local delta = chunk.choices[1].delta or {}
local fr = chunk.choices[1].finish_reason
local finish = (type(fr) == "string" and fr ~= "") and fr or nil
local unified = {
content = delta.content or "",
done = (finish ~= nil)
}
if finish then
unified.finish_reason = finish
end
if uses ~= nil then
unified.usage = uses
end
-- zen 用 reasoning 字段承载推理文本（OpenAI 惯例是 reasoning_content）
local reasoning = delta.reasoning_content or delta.reasoning
if reasoning then
unified.reasoning_content = reasoning
end
if delta.tool_calls then
-- pass raw streaming fragments through; OpenAI clients accumulate index+id+name+arguments
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

247
internal/lua/adapters/opencodezen.lua Normal file
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@ -0,0 +1,247 @@
local adapter = {}
adapter.name = "opencodezen"
adapter.version = "1.0.0"
adapter.endpoint = "/chat/completions"
-- OpenCode Zen（按量付费端点，https://opencode.ai/zen/v1）
--
-- 与 OpenCode Go（opencodego.lua，https://opencode.ai/zen/go/v1）是两个不同的
-- 服务，行为要求并不相同，因此各有专用适配器：
--
-- * 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
-- 指纹（UA + x-opencode-*），否则上游拒绝："free tier can only be used in
-- OpenCode"。Zen 的免费池以非 thinking 模型为主，历史上回传
-- reasoning_content 会引出上游报错，故这里剥掉（Go 侧相反，见 opencodego.lua）。
-- * Go 订阅读者请看 opencodego.lua：那边**必须**回传 reasoning_content，
-- 否则 thinking 模式直接 400。
--
-- 缺 x-opencode-client/session/request/project 身份头会被判为匿名客户端，
-- 部分模型在带 tools 时上游直接失败（流式返回单 chunk
-- "finish_reason":"network_error" 空 content，非流式 503
-- "Endpoint is unavailable"，表现为"空回复"）。
adapter.headers = {
["User-Agent"] = "opencode/1.18.21 ai-sdk/provider-utils/4.0.23 runtime/bun/1.3.14",
}
-- 每请求生成身份头。沙箱无 os/math，用 meta.timestamp + 请求体哈希派生：
-- 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）。
local function rand_id(prefix, seed)
return prefix .. string.sub(sha256_hex(seed), 1, 24)
end
function adapter.build_headers(meta)
local ts = tostring(meta.timestamp or "")
return {
["User-Agent"] = adapter.headers["User-Agent"],
["x-opencode-client"] = "cli",
-- project 固定：同网关实例共享一个工作区身份
["x-opencode-project"] = string.sub(sha256_hex("llmsproxy|" .. (meta.source and meta.source.name or "")), 1, 32),
["x-opencode-session"] = rand_id("ses_", "session|" .. ts),
["x-opencode-request"] = rand_id("msg_", "request|" .. ts .. "|" .. tostring(meta.body or "")),
}
end
-- OpenAI /chat/completions format (pass-through, strip provider-specific fields)
-- zen 上游 schema 只接受 text content part（无视觉/音频能力）：多模态 part
-- （image_url / input_audio / file 等）一律剥离。剥离后 content 变空的消息
-- 若不再携带 tool_calls / tool_call_id 才整条丢弃（避免上游
-- "unknown variant `image_url`, expected `text`"）；带工具调用的必须保留，
-- 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。
-- zen 上游角色白名单只有 system / user / assistant / tool / latest_reminder：
-- OpenAI 的 developer（及 function 等）不在其中，直接透传会触发上游
-- "unknown variant `developer`, expected one of ..." 错误；统一归一化为 system。
local ROLE_WHITELIST = {
system = true,
user = true,
assistant = true,
tool = true,
latest_reminder = true,
}
function adapter.transform_request(raw_body)
local ok, req = pcall(json.decode, raw_body)
if not ok then return raw_body end
req.disable_thinking = nil
req.extra_body = nil
-- stream_options is only valid alongside stream:true; sending it on a
-- non-streaming request is rejected by strict upstreams.
if req.stream then
if type(req.stream_options) ~= "table" then req.stream_options = {} end
req.stream_options.include_usage = true
end
if req.messages then
local kept = {}
for _, msg in ipairs(req.messages) do
if type(msg.role) == "string" and not ROLE_WHITELIST[msg.role] then
msg.role = "system"
end
-- Zen 免费池不接受回传 reasoning_content（Go 侧相反）
msg.reasoning_content = nil
local drop = false
if type(msg.content) == "table" then
local parts = {}
for _, part in ipairs(msg.content) do
if type(part) == "table" and part.type ~= nil and part.type ~= "text" then
-- multimodal part not supported by zen
else
table.insert(parts, part)
end
end
if #parts == 0 then
-- Content collapsed to nothing after stripping unsupported
-- parts. A message that still carries a tool call must
-- NEVER be dropped: the very next message is its tool
-- result, and dropping the call orphans that result. The
-- model then sees a result for a call it never made and
-- re-issues the same tool call on every turn (observed as
-- an infinite "repeated tool call" loop).
if (type(msg.tool_calls) == "table" and #msg.tool_calls > 0)
or msg.tool_call_id ~= nil then
msg.content = ""
else
drop = true
end
else
msg.content = parts
end
end
if not drop then
table.insert(kept, msg)
end
end
req.messages = kept
end
return json.encode(req)
end
function adapter.transform_response(raw_body)
local ok, resp = pcall(json.decode, raw_body)
if not ok or resp == nil then return raw_body end
local unified = {
content = "",
finish_reason = "",
token_usage = { prompt = 0, completion = 0, total = 0 }
}
if type(resp.usage) == "table" then
unified.token_usage.prompt = resp.usage.prompt_tokens or 0
unified.token_usage.completion = resp.usage.completion_tokens or 0
unified.token_usage.total = resp.usage.total_tokens or 0
local hit = 0
if type(resp.usage.prompt_tokens_details) == "table" and resp.usage.prompt_tokens_details.cached_tokens ~= nil then
hit = resp.usage.prompt_tokens_details.cached_tokens
unified.token_usage.prompt_tokens_details = { cached_tokens = hit }
end
if (resp.usage.prompt_cache_hit_tokens or 0) > 0 then
unified.token_usage.prompt_cache_hit_tokens = resp.usage.prompt_cache_hit_tokens
unified.token_usage.prompt_cache_miss_tokens = resp.usage.prompt_cache_miss_tokens or 0
if hit == 0 then
unified.token_usage.prompt_tokens_details = { cached_tokens = resp.usage.prompt_cache_hit_tokens }
end
end
end
if type(resp.choices) == "table" and #resp.choices > 0 then
local ch = resp.choices[1]
if type(ch.message) == "table" then
unified.content = ch.message.content or ""
local reasoning = ch.message.reasoning_content or ch.message.reasoning
if reasoning then
unified.reasoning_content = reasoning
end
if type(ch.message.tool_calls) == "table" then
local tcs = {}
for _, tc in ipairs(ch.message.tool_calls) do
local args_ok, args = pcall(json.decode, tc["function"].arguments)
if not args_ok then args = {} end
table.insert(tcs, {
id = tc.id,
type = tc.type or "function",
name = tc["function"].name,
arguments = args
})
end
unified.tool_calls = tcs
end
end
unified.finish_reason = ch.finish_reason or ""
end
return json.encode(unified)
end
function adapter.transform_stream_chunk(raw_chunk)
local ok, chunk = pcall(json.decode, raw_chunk)
if not ok then return "" end
-- OpenAI-style streams may attach usage to a chunk with empty choices
-- (the final usage chunk). Preserve it; the gateway emits it as the
-- terminal usage chunk. Note: keys must match Go's TokenUsage json tags
-- (prompt/completion/total); the gateway re-emits standard *_tokens.
local uses = nil
if type(chunk.usage) == "table" then
uses = {
prompt = chunk.usage.prompt_tokens or chunk.usage.prompt or 0,
completion = chunk.usage.completion_tokens or chunk.usage.completion or 0,
total = chunk.usage.total_tokens or chunk.usage.total or 0,
}
if type(chunk.usage.prompt_tokens_details) == "table" and chunk.usage.prompt_tokens_details.cached_tokens ~= nil then
uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_tokens_details.cached_tokens }
elseif (chunk.usage.prompt_cache_hit_tokens or 0) > 0 then
uses.prompt_cache_hit_tokens = chunk.usage.prompt_cache_hit_tokens
uses.prompt_cache_miss_tokens = chunk.usage.prompt_cache_miss_tokens or 0
uses.prompt_tokens_details = { cached_tokens = chunk.usage.prompt_cache_hit_tokens }
end
end
if not chunk.choices or #chunk.choices == 0 then
if uses ~= nil then
-- usage-only chunk is not a content/finish signal; the gateway
-- emits its own terminal stop chunk and merges this usage.
return json.encode({ usage = uses, done = false })
end
return ""
end
local delta = chunk.choices[1].delta or {}
local fr = chunk.choices[1].finish_reason
local finish = (type(fr) == "string" and fr ~= "") and fr or nil
local unified = {
content = delta.content or "",
done = (finish ~= nil)
}
if finish then
unified.finish_reason = finish
end
if uses ~= nil then
unified.usage = uses
end
-- zen 用 reasoning 字段承载推理文本（OpenAI 惯例是 reasoning_content）
local reasoning = delta.reasoning_content or delta.reasoning
if reasoning then
unified.reasoning_content = reasoning
end
if delta.tool_calls then
-- pass raw streaming fragments through; OpenAI clients accumulate index+id+name+arguments
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

54
internal/lua/toolcall_preservation_test.go
View File

@ -151,3 +151,57 @@ func TestOpenCodeStreamOptionsOnlyWhenStreaming(t *testing.T) {
t.Fatalf("streaming request must carry stream_options.include_usage: %s", sout)
}
}
// TestOpenCodeGoVsZenReasoning pins the one behavioural difference that made a
// shared adapter wrong: OpenCode Go's thinking mode REQUIRES the assistant
// turn's reasoning_content to be echoed back ("The `reasoning_content` in the
// thinking mode must be passed back to the API"), while the Zen free pool must
// not receive it. Hence two purpose-built adapters.
func TestOpenCodeGoVsZenReasoning(t *testing.T) {
vm := NewVM(freshAdapterDir(t))
if err := vm.Start(); err != nil {
t.Fatal(err)
}
defer vm.Stop()
body := `{"model":"m","messages":[
{"role":"user","content":"hi"},
{"role":"assistant","content":"","reasoning_content":"I should read the file.","tool_calls":[{"id":"call_1","type":"function","function":{"name":"read","arguments":"{\"path\":\"/x\"}"}}]},
{"role":"tool","tool_call_id":"call_1","content":"r"}
]}`
// Go: reasoning_content must survive, and the tool call must stay paired.
gout, err := vm.Transform("opencodego", "transform_request", body)
if err != nil {
t.Fatalf("opencodego: %v", err)
}
if !strings.Contains(gout, "I should read the file.") {
t.Errorf("opencodego must pass reasoning_content back (thinking mode requires it): %s", gout)
}
if !strings.Contains(gout, "call_1") || !strings.Contains(gout, "tool_call_id") {
t.Errorf("opencodego must keep the tool call paired with its result: %s", gout)
}
// Zen: reasoning_content is stripped.
zout, err := vm.Transform("opencodezen", "transform_request", body)
if err != nil {
t.Fatalf("opencodezen: %v", err)
}
if strings.Contains(zout, "I should read the file.") {
t.Errorf("opencodezen must strip reasoning_content: %s", zout)
}
if !strings.Contains(zout, "call_1") {
t.Errorf("opencodezen must still keep the tool call: %s", zout)
}
// Both must still omit stream_options on non-streaming requests.
for _, a := range []string{"opencodego", "opencodezen"} {
out, err := vm.Transform(a, "transform_request", `{"model":"m","messages":[{"role":"user","content":"hi"}]}`)
if err != nil {
t.Fatalf("%s: %v", a, err)
}
if strings.Contains(out, "stream_options") {
t.Errorf("%s must not send stream_options when not streaming: %s", a, out)
}
}
}