mirror of
https://gitcode.com/JianFeeeee/ModelRouter.git
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93eeba3762
Phase 2 收尾（入向）。ChatRequest 从"客户端发什么就是什么"改为
UnifiedRequest（最大集合）的别名，内核真正用上了那个超集类型。
改掉的具体缺陷：
1. 私有字段泄漏归零（v1 的核心问题）
v1 的 disable_thinking 是内核私有开关，却被序列化进交给适配器的 body，
迫使 10 个适配器各自写 req.disable_thinking = nil 来清理。
现在它是中立的 thinking 字段（{enabled, budget_tokens}），客户端与
适配器都认这个词：
- gateway/chat.go：thinkingFromClient() 把 disable_thinking 翻译成
thinking.enabled=false；冲突时中立字段优先（它能带预算，布尔不能）
- deepseek.lua：thinking.enabled=false → extra_body.thinking.type=disabled
- anthropic.lua：thinking.enabled=true + budget → 原生 {type,budget_tokens}
（enabled=false 时不传该字段——Anthropic 没有 type=disabled 这个写法）
- 其余 7 个适配器：把"清理内核私有字段"改成"清理中立字段"
2. Tools/ToolChoice 改 json.RawMessage
原为 []interface{}（OpenAI 原始形状 = 内核在假设某个协议）。
内核从不解释工具 schema——它原样交给适配器，所以原始形状不损失任何
内核侧统一性。ToolDef 结构化类型保留在包内供新适配器选用。
3. 删除 MarshalJSON 后门
v1 手工 splice ExtraBody 进 OpenAI 形状的 body；现在 ExtraBody 是
UnifiedRequest 上一个正正经经声明的字段。
渐进迁移：ChatRequest 保留为别名（不是新类型），49 处引用零改动编译，
语义变更不被机械改名淹没。
测试：新增 thinking_test.go（翻译链 4 例 + 泄漏回归 + tools 透传）；
vm_test.go 两处迁移到中立语义。golden 字节级未漂移。
181 lines
7.3 KiB
Lua
181 lines
7.3 KiB
Lua
-- sensenova API format adapter
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-- streaming: delta only has reasoning_content, no content field
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-- non-streaming: has both content and reasoning_content
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local adapter = {}
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adapter.name = "sensenova"
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adapter.version = "1.0.0"
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adapter.endpoint = "/chat/completions"
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adapter.headers = {}
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-- Same as openai - strip provider-specific fields
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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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-- The gateway's private control fields are GONE from the body (v2): the
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-- neutral `thinking` field carries that intent and each adapter maps it in
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-- its own protocol terms. These upstreams have no thinking switch at all,
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-- so the field is simply dropped here — which is what the nil-ing below
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-- used to do, except the field being dropped is no longer the kernel's
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-- private one.
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req.thinking = nil
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req.extra_body = nil
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if req.messages then
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for _, msg in ipairs(req.messages) do
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msg.reasoning_content = nil
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end
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end
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return json.encode(req)
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end
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-- Same as openai - extract content from response
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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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if ch.message.reasoning_content then
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unified.reasoning_content = ch.message.reasoning_content
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elseif ch.message.reasoning then
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-- sensenova-6.8-flash-lite 用 reasoning 字段而不是 reasoning_content
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unified.reasoning_content = ch.message.reasoning
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end
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-- Tool calls MUST be forwarded. Dropping them while keeping
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-- finish_reason="tool_calls" makes the client replay an assistant
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-- message whose function name/arguments are empty, and sensenova
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-- then rejects the next turn with
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-- 400 invalid tool_call function, function/name/arguments cannot be empty
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-- i.e. a tool-using conversation dies on its second request.
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if type(ch.message.tool_calls) == "table" and #ch.message.tool_calls > 0 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 fn = tc["function"] or {}
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-- arguments arrives as a JSON *string* on the wire; the
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-- unified shape expects a decoded object.
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local args = fn.arguments
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if type(args) == "string" then
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local args_ok, decoded = pcall(json.decode, args)
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args = args_ok and decoded or {}
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elseif type(args) ~= "table" then
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args = {}
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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 = fn.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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-- Sensenova-specific stream handling
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-- Upstream puts content in reasoning_content only (no content field)
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-- Also sends finish_reason="" (empty string) on every chunk
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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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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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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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-- Sensenova: delta has reasoning_content (deepseek-v4-flash) or reasoning
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-- (sensenova-6.8-flash-lite) but no content field
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local content = delta.content or ""
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if content == "" and (delta.reasoning_content or delta.reasoning) then
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content = delta.reasoning_content or delta.reasoning
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end
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-- Sensenova: finish_reason is "" on every chunk, "stop" on last
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local fr = chunk.choices[1].finish_reason
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local done = (fr == "stop" or fr == "length")
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local unified = {
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content = content,
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done = done,
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}
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if chunk.choices[1].finish_reason and chunk.choices[1].finish_reason ~= "" then
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unified.finish_reason = chunk.choices[1].finish_reason
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end
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if delta.tool_calls then
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unified.tool_calls = delta.tool_calls
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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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return json.encode(unified)
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end
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-- 错误收敛：sensenova 为 OpenAI 风格 {error:{message,...}}；
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-- 配额类错误单独点出便于客户端识别重置周期。
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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 status == 429 and type(e.code) == "string"
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and e.code == "insufficient_quota" then
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return "workspace quota exhausted (resets periodically)"
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end
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if type(e.message) == "string" then return e.message end
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return nil
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end
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return adapter
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