local adapter = {}

adapter.name = "opencode"
adapter.version = "1.0.0"
adapter.endpoint = "/chat/completions"

-- opencode.ai zen 网关按客户端指纹（UA + x-opencode-* 头）路由请求池：
-- 缺少 x-opencode-client/session/request/project 身份头的请求会被判为匿名
-- 客户端，x-preview-f-free 等模型在带 tools 时上游直接失败——流式返回单
-- chunk "finish_reason":"network_error" 空 content，非流式返回 503
-- "Endpoint is unavailable"，表现为"空回复"。因此除 UA 外必须附带
-- x-opencode-* 身份头；session/request 每请求派生唯一值（见 build_headers）。
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 stricter upstreams (OpenCode Go:
    -- "stream_options should be set along with stream"), which failed every
    -- non-stream call. Only attach it when the request actually streams.
    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
            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).
                    --
                    -- This is the common shape for agent clients: an assistant
                    -- turn whose content is only [thinking, toolCall] serialises
                    -- to content:[] with tool_calls — exactly the case that used
                    -- to vanish here. Emit "" instead, which zen accepts.
                    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