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fix: empty-array content becomes invalid {} on every pass-through adapter; gemini/ollama drop tool calls

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Three related forwarding defects found by auditing every adapter with a
tool-calling replay (assistant turn with content:[] + tool_calls).

1) content:[] -> content:{} (all 12 openai-adapter sources, plus
   deepseek/trae/sensenova/agentrouter/github/groq/kimicode/mistral)

   Lua adapters json.decode the request and re-encode it, and an empty Lua
   table is indistinguishable from an empty JSON array — the encoder emits
   {} for both. Agent clients serialise a tool-calling assistant turn with
   no text as content:[], so every pass-through adapter rewrote it to
   content:{} — not valid OpenAI (content is string|array|null). Verified
   against a live upstream: content:[] produced "400 invalid arguments"
   while content:"" was accepted.

   Fixed once at the decode boundary (types.ChatMessage.UnmarshalJSON):
   empty-array content normalises to "" and an empty tool_calls array is
   dropped, so every adapter — including future ones — sees a valid shape.

2) gemini dropped tool_calls and never emitted functionCall /
   functionResponse; the tool role also stayed as an invalid role inside
   contents and system was not moved to systemInstruction.

3) ollama copied only role/content, dropping tool_calls and the call
   attribution entirely (it needs tool_name, not tool_call_id).

Test: TestAdaptersPreserveToolCalls asserts, for every adapter, that the
call id (or function name where the wire format has no id), the function
name, the tool result and the trailing user turn all survive, plus a
negative control for plain text.
This commit is contained in:
JianFeeeee
2026-09-10 21:57:54 +08:00
parent 611e975456
commit 9114468753
5 changed files with 345 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files

103
internal/lua/adapters/gemini.lua
View File

@ -7,6 +7,10 @@ adapter.headers = {}
-- Gemini API: POST /v1/models/{model}:generateContent
-- Auth: API key in query param ?key=XXX or Authorization: Bearer XXX
--
-- 请求方向必须把 OpenAI 的工具调用翻译成 Gemini 的 functionCall /
-- functionResponse，否则 agent 回放的历史里助手那一轮的调用会凭空消失，
-- 紧随其后的工具结果就成了「无来源」的孤立结果，模型只能反复重发同一个调用。
function adapter.transform_request(raw_body)
local ok, req = pcall(json.decode, raw_body)
if not ok then return raw_body end
@ -14,16 +18,23 @@ function adapter.transform_request(raw_body)
-- 将 OpenAI 风格 content（字符串或 [{type:*}] 数组）拆成 Gemini parts
local function to_parts(content)
if type(content) == "string" then
if content == "" then return {} end
return { { text = content } }
end
local parts = {}
for _, p in ipairs(content or {}) do
if p.type == "text" then
table.insert(parts, { text = p.text })
elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
local mt, b64 = string.match(p.image_url.url, "^data:([^,]+);base64,(.+)$")
if b64 then
table.insert(parts, { inline_data = { mime_type = mt or "image/png", data = b64 } })
if type(p) == "string" then
if p ~= "" then table.insert(parts, { text = p }) end
elseif type(p) == "table" then
if p.type == "text" then
if p.text ~= nil and p.text ~= "" then
table.insert(parts, { text = p.text })
end
elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
local mt, b64 = string.match(p.image_url.url, "^data:([^,]+);base64,(.+)$")
if b64 then
table.insert(parts, { inline_data = { mime_type = mt or "image/png", data = b64 } })
end
end
end
end
@ -31,11 +42,59 @@ function adapter.transform_request(raw_body)
end
local contents = {}
local system = ""
local call_names = {} -- tool_call_id -> 函数名（functionResponse 只认名字）
for _, m in ipairs(req.messages or {}) do
table.insert(contents, {
role = (m.role == "assistant") and "model" or m.role,
parts = to_parts(m.content)
})
local role = m.role or "user"
if role == "system" then
if type(m.content) == "string" then
system = system .. m.content .. "\n"
end
elseif role == "assistant" then
local parts = to_parts(m.content)
if type(m.tool_calls) == "table" then
for _, tc in ipairs(m.tool_calls) do
if type(tc) == "table" then
local fn = tc["function"] or {}
local args = fn.arguments
if type(args) == "string" and args ~= "" then
local aok, decoded = pcall(json.decode, args)
args = aok and decoded or {}
elseif type(args) ~= "table" then
args = {}
end
if tc.id ~= nil then call_names[tc.id] = fn.name or "" end
table.insert(parts, {
functionCall = { name = fn.name or "", args = args }
})
end
end
end
-- Gemini 不接受空的 parts 数组；无可发送内容的轮次直接跳过
if #parts > 0 then
table.insert(contents, { role = "model", parts = parts })
end
elseif role == "tool" then
local name = call_names[m.tool_call_id] or m.name or ""
local text = type(m.content) == "string" and m.content or ""
table.insert(contents, {
role = "user",
parts = { { functionResponse = {
name = name,
response = { content = text },
} } }
})
else
local parts = to_parts(m.content)
if #parts > 0 then
table.insert(contents, { role = "user", parts = parts })
end
end
end
local gemini_req = {
@ -46,6 +105,30 @@ function adapter.transform_request(raw_body)
}
}
if system ~= "" then
gemini_req.systemInstruction = { parts = { { text = system } } }
end
-- tools -> functionDeclarations
if type(req.tools) == "table" then
local decls = {}
for _, t in ipairs(req.tools) do
if type(t) == "table" and type(t["function"]) == "table" then
local fn = t["function"]
local params = fn.parameters
if type(params) ~= "table" then params = { type = "object", properties = {} } end
table.insert(decls, {
name = fn.name or "",
description = fn.description or "",
parameters = params,
})
end
end
if #decls > 0 then
gemini_req.tools = { { functionDeclarations = decls } }
end
end
if req.stream then
gemini_req.stream = true
end

54
internal/lua/adapters/ollama.lua
View File

@ -6,6 +6,10 @@ adapter.endpoint = "/api/chat"
adapter.headers = {}
-- Ollama API 格式：{ model, messages, stream, options:{temperature,num_predict} }
-- 工具调用必须一并翻译：Ollama 的 assistant 消息用 tool_calls（arguments 是对象
-- 而非 JSON 字符串），工具结果用 tool 角色 + tool_name。此前这里只复制了
-- role/content，助手那轮的调用和 tool 消息的归属全部丢失，模型看到无来源的
-- 工具结果就只能反复重发同一个调用。
function adapter.transform_request(raw_body)
local ok, req = pcall(json.decode, raw_body)
if not ok then return raw_body end
@ -22,6 +26,7 @@ function adapter.transform_request(raw_body)
-- 转换 messages 格式（Ollama messages 支持 images base64 数组）
if req.messages then
local msgs = {}
local call_names = {} -- tool_call_id -> 函数名
for _, m in ipairs(req.messages) do
local text, images
if type(m.content) == "string" then
@ -30,22 +35,61 @@ function adapter.transform_request(raw_body)
text = ""
images = {}
for _, p in ipairs(m.content or {}) do
if p.type == "text" then
text = text .. (p.text or "")
elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
if b64 then table.insert(images, b64) end
if type(p) == "table" then
if p.type == "text" then
text = text .. (p.text or "")
elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
if b64 then table.insert(images, b64) end
end
end
end
if #images == 0 then images = nil end
end
local msg = { role = m.role, content = text }
if images then msg.images = images end
-- 助手轮的工具调用：arguments 转成对象
if type(m.tool_calls) == "table" and #m.tool_calls > 0 then
local tcs = {}
for _, tc in ipairs(m.tool_calls) do
if type(tc) == "table" then
local fn = tc["function"] or {}
local args = fn.arguments
if type(args) == "string" and args ~= "" then
local aok, decoded = pcall(json.decode, args)
args = aok and decoded or {}
elseif type(args) ~= "table" then
args = {}
end
if tc.id ~= nil then call_names[tc.id] = fn.name or "" end
table.insert(tcs, {
["function"] = { name = fn.name or "", arguments = args }
})
end
end
if #tcs > 0 then msg.tool_calls = tcs end
end
-- 工具结果：Ollama 用 tool_name 标识归属（不认 tool_call_id）
if m.role == "tool" then
local name = call_names[m.tool_call_id] or m.name or ""
if m.tool_call_id ~= nil then
msg.tool_call_id = m.tool_call_id
end
if name ~= "" then msg.tool_name = name end
end
table.insert(msgs, msg)
end
ollama_req.messages = msgs
end
-- tools 透传（Ollama 的 shape 与 OpenAI 一致）
if type(req.tools) == "table" and #req.tools > 0 then
ollama_req.tools = req.tools
end
return json.encode(ollama_req)
end