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ModelRouter/internal/lua/adapters/deepseek.lua

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local adapter = {}
adapter.name = "deepseek"
adapter.version = "2.1.0"
adapter.endpoint = "/chat/completions"
adapter.headers = {}
function adapter.transform_request(raw_body)
local ok, req = pcall(json.decode, raw_body)
if not ok then return raw_body end
-- V4 已替换 legacy 模型名deepseek-chat/reasoner 2026-07-24 停用)
req.model = req.model or "deepseek-v4-flash"
if req.model == "deepseek-chat" or req.model == "deepseek-reasoner" then
req.model = "deepseek-v4-flash"
end
req.stream = req.stream or false
if req.disable_thinking then
req.extra_body = req.extra_body or {}
req.extra_body.thinking = { type = "disabled" }
end
req.disable_thinking = nil
-- V4 thinking 模式要求:带 tool_calls 的 assistant 消息必须回传 reasoning_content。
-- OpenAI 兼容客户端不会发该字段,补空串即可通过校验。
if req.messages then
for _, msg in ipairs(req.messages) do
if msg.role == "assistant" and msg.tool_calls and msg.tool_calls[1] then
if msg.reasoning_content == nil then
msg.reasoning_content = ""
end
end
end
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
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
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
if not chunk.choices or #chunk.choices == 0 then return "" end
local delta = chunk.choices[1].delta or {}
local fr = chunk.choices[1].finish_reason
local unified = {
content = delta.content or "",
done = (fr ~= nil)
}
if delta.reasoning_content then
unified.reasoning_content = delta.reasoning_content
end
if delta.tool_calls then
unified.tool_calls = delta.tool_calls
end
return json.encode(unified)
end
return adapter