mirror of
https://gitcode.com/JianFeeeee/ModelRouter.git
synced 2026-09-23 02:18:01 +00:00
2bc1d0e67a
- adapters/opencode.lua: opencode.ai zen free pool adapter — sends the opencode client User-Agent (zen fingerprints clients by UA; non-official clients hit FreeUsageLimitError); pairs with api_key: public - config: no config file ships in the repo; first run generates a default config at the -config path with a random admin key, loopback listen and a keyless zen source (config.EnsureDefault); remove config.example.yaml - lua: seed bundled adapters from the embedded FS instead of a hardcoded name list - ui: widen model kind select (chat was clipped to 'cha') - phase 5 bugfixes: stats ms/s bucket mixing, cleanScopes nil, ctx.Err guards, direct-path ModelAvailable, empty stream body failure, bestImageModel rewrite, transform failure recording, Core.mu, timer, effective model for tool-calls
96 lines
3.2 KiB
Lua
96 lines
3.2 KiB
Lua
local adapter = {}
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adapter.name = "opencode"
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adapter.version = "1.0.0"
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adapter.endpoint = "/chat/completions"
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-- opencode.ai zen 网关按 User-Agent 指纹识别官方客户端并把请求分到免费额度池；
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-- 非官方 UA（curl/Go 默认等）会被分到匿名池并触发 FreeUsageLimitError。
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-- 因此固定发送 opencode 客户端的 UA；配合源配置 api_key: "public"（官方无 key
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-- 客户端实际发送 Bearer public）即可走免费池。
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adapter.headers = {
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["User-Agent"] = "opencode/0.1.0",
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}
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-- OpenAI /chat/completions format (pass-through, 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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req.disable_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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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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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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end
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if type(ch.message.tool_calls) == "table" 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 args_ok, args = pcall(json.decode, tc["function"].arguments)
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if not args_ok then args = {} 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 = tc["function"].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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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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if not chunk.choices or #chunk.choices == 0 then return "" end
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local delta = chunk.choices[1].delta or {}
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local fr = chunk.choices[1].finish_reason
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local unified = {
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content = delta.content or "",
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done = (fr ~= nil)
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}
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if delta.reasoning_content then
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unified.reasoning_content = delta.reasoning_content
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end
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if delta.tool_calls then
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-- pass raw streaming fragments through; OpenAI clients accumulate index+id+name+arguments
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unified.tool_calls = delta.tool_calls
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end
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return json.encode(unified)
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end
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return adapter
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