ModelRouter/internal/lua/adapters/sensenova.lua

-- sensenova API format adapter
-- streaming: delta only has reasoning_content, no content field
-- non-streaming: has both content and reasoning_content

local adapter = {}
adapter.name = "sensenova"
adapter.version = "1.0.0"
adapter.endpoint = "/chat/completions"
adapter.headers = {}

-- Same as openai - strip provider-specific fields
function adapter.transform_request(raw_body)
    local ok, req = pcall(json.decode, raw_body)
    if not ok then return raw_body end
    -- The gateway's private control fields are GONE from the body (v2): the
    -- neutral `thinking` field carries that intent and each adapter maps it in
    -- its own protocol terms. These upstreams have no thinking switch at all,
    -- so the field is simply dropped here — which is what the nil-ing below
    -- used to do, except the field being dropped is no longer the kernel's
    -- private one.
    req.thinking = nil
    req.extra_body = nil
    if req.messages then
        for _, msg in ipairs(req.messages) do
            msg.reasoning_content = nil
        end
    end
    return json.encode(req)
end

-- Same as openai - extract content from response
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 ""
            if ch.message.reasoning_content then
                unified.reasoning_content = ch.message.reasoning_content
            elseif ch.message.reasoning then
                -- sensenova-6.8-flash-lite 用 reasoning 字段而不是 reasoning_content
                unified.reasoning_content = ch.message.reasoning
            end
            -- Tool calls MUST be forwarded. Dropping them while keeping
            -- finish_reason="tool_calls" makes the client replay an assistant
            -- message whose function name/arguments are empty, and sensenova
            -- then rejects the next turn with
            --   400 invalid tool_call function, function/name/arguments cannot be empty
            -- i.e. a tool-using conversation dies on its second request.
            if type(ch.message.tool_calls) == "table" and #ch.message.tool_calls > 0 then
                local tcs = {}
                for _, tc in ipairs(ch.message.tool_calls) do
                    local fn = tc["function"] or {}
                    -- arguments arrives as a JSON *string* on the wire; the
                    -- unified shape expects a decoded object.
                    local args = fn.arguments
                    if type(args) == "string" then
                        local args_ok, decoded = pcall(json.decode, args)
                        args = args_ok and decoded or {}
                    elseif type(args) ~= "table" then
                        args = {}
                    end
                    table.insert(tcs, {
                        id = tc.id,
                        type = tc.type or "function",
                        name = fn.name,
                        arguments = args
                    })
                end
                unified.tool_calls = tcs
            end
        end
        unified.finish_reason = ch.finish_reason or ""
    end

    return json.encode(unified)
end

-- Sensenova-specific stream handling
-- Upstream puts content in reasoning_content only (no content field)
-- Also sends finish_reason="" (empty string) on every chunk
function adapter.transform_stream_chunk(raw_chunk)
    local ok, chunk = pcall(json.decode, raw_chunk)
    if not ok then return "" end

    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
            return json.encode({ usage = uses, done = false })
        end
        return ""
    end

    local delta = chunk.choices[1].delta or {}

    -- Sensenova: delta has reasoning_content (deepseek-v4-flash) or reasoning
    -- (sensenova-6.8-flash-lite) but no content field
    local content = delta.content or ""
    if content == "" and (delta.reasoning_content or delta.reasoning) then
        content = delta.reasoning_content or delta.reasoning
    end

    -- Sensenova: finish_reason is "" on every chunk, "stop" on last
    local fr = chunk.choices[1].finish_reason
    local done = (fr == "stop" or fr == "length")

    local unified = {
        content = content,
        done = done,
    }
    if chunk.choices[1].finish_reason and chunk.choices[1].finish_reason ~= "" then
        unified.finish_reason = chunk.choices[1].finish_reason
    end
    if delta.tool_calls then
        unified.tool_calls = delta.tool_calls
    end
    if uses ~= nil then
        unified.usage = uses
    end

    return json.encode(unified)
end

-- 错误收敛：sensenova 为 OpenAI 风格 {error:{message,...}}；
-- 配额类错误单独点出便于客户端识别重置周期。
function adapter.transform_error(status, body)
    -- OpenAI 风格错误体抽消息。此前在 deepseek/github/groq/kimicode/
    -- openai/sensenova 六个适配器里逐字节相同（各 293B），已抽到共享前导。
    return __prelude.openai_error(status, body)
end

return adapter