chore(version): 1.5.3

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.

cmd/gui/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "modelrouter-gui",
-  "version": "1.4.2",
+  "version": "1.5.3",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "modelrouter-gui",
-      "version": "1.4.2",
+      "version": "1.5.3",
       "license": "Proprietary",
       "devDependencies": {
         "electron": "^33.0.0",

cmd/gui/package.json

@@ -1,6 +1,6 @@
 {
   "name": "modelrouter-gui",
-  "version": "1.4.2",
+  "version": "1.5.3",
   "description": "ModelRouter Desktop — embedded ModelRouter core with tray",
   "author": "ModelRouter",
   "main": "main.js",

internal/gateway/chat.go

@@ -7,6 +7,7 @@ import (
 	"fmt"
 	"log"
 	"net/http"
+	"regexp"
 	"strings"
 	"sync/atomic"
 	"time"
@@ -115,13 +116,15 @@ func (g *Gateway) resolveCands(ctx context.Context, req *chatRequest) ([]*provid
 }
 
 // filterCandsByModels keeps only providers exposing at least one model of the
-// scope (used for user keys with a restricted model scope). An "AUTO" scope
+// scope (used for user keys with a restricted model scope). Scope entries with
-// entry means the key is allowed to use any model. Scope entries with a
+// a Source pinned to a specific upstream narrow the candidates to that source
-// Source pinned to a specific upstream narrow the candidates to that source
 // for the matching model.
+//
+// An "AUTO" scope entry only allows the AUTO routing mode; it does NOT grant
+// access to specific models.
 func filterCandsByModels(cands []*provider.Provider, allow []config.ModelScope) []*provider.Provider {
 	for _, m := range allow {
-		if m.Model == "" || strings.EqualFold(m.Model, "AUTO") {
+		if m.Model == "" {
 			return cands
 		}
 	}
@@ -152,20 +155,18 @@ func filterCandsByModels(cands []*provider.Provider, allow []config.ModelScope)
 	return out
 }
 
-// intersectModels restricts a model list to the scope (preserving order). An
+// intersectModels restricts a model list to the scope (preserving order).
-// "AUTO" scope entry grants every model.
+// An "AUTO" scope entry only allows the AUTO routing mode; it does NOT grant
+// every model.
 func intersectModels(models []string, allow []config.ModelScope) []string {
 	allowed := make(map[string]bool, len(allow))
-	any := false
 	for _, m := range allow {
-		if m.Model == "" || strings.EqualFold(m.Model, "AUTO") {
+		if m.Model == "" {
-			any = true
+			return models
-			break
+		}
+		if !strings.EqualFold(m.Model, "AUTO") {
+			allowed[m.Model] = true
 		}
-		allowed[m.Model] = true
-	}
-	if any {
-		return models
 	}
 	out := make([]string, 0, len(models))
 	seen := map[string]bool{}
@@ -179,24 +180,16 @@ func intersectModels(models []string, allow []config.ModelScope) []string {
 }
 
 // checkModelScope validates the effective model against the key's model scope
-// and token quota. Returns an error message when rejected. A scope entry with
+// and token quota. Returns an error message when rejected.
-// model "AUTO" grants all models; its quota caps the key's total tokens.
+//
+// A scope entry with model "AUTO" only allows requests where the effective
+// model is AUTO (the routing mode). It does NOT grant access to specific model
+// ids — that requires an explicit scope entry for the model.
 func (g *Gateway) checkModelScope(ctx context.Context, model string) string {
 	allow := g.allowedModels(ctx)
 	if allow == nil {
 		return ""
 	}
-	for _, sc := range allow {
-		if sc.Model != "" && strings.EqualFold(sc.Model, "AUTO") {
-			if sc.TokenQuota > 0 {
-				used := g.scopeTokens(ctx, sc)
-				if used >= sc.TokenQuota {
-					return fmt.Sprintf("token quota exceeded (%d/%d)", used, sc.TokenQuota)
-				}
-			}
-			return ""
-		}
-	}
 	for _, sc := range allow {
 		if sc.Model != model {
 			continue
@@ -229,12 +222,15 @@ func (g *Gateway) scopeTokens(ctx context.Context, sc config.ModelScope) int64 {
 // source that actually serves the bare model (via Registry.EffectiveModel), so
 // model ids that themselves contain separators (e.g. "deepseek-v4-flash-free")
 // are never corrupted (P10-2).
+//
+// A scope entry with model "AUTO" only matches the literal AUTO routing mode;
+// it does NOT grant access to specific model ids.
 func (g *Gateway) hasScopeModel(list []config.ModelScope, s string) bool {
 	if r := g.core.Registry(); r != nil {
 		s = r.EffectiveModel(s)
 	}
 	for _, x := range list {
-		if x.Model == s || (x.Model != "" && strings.EqualFold(x.Model, "AUTO")) {
+		if x.Model == s {
 			return true
 		}
 	}
@@ -517,21 +513,67 @@ func upstreamErrStatus(err error) int {
 	return http.StatusBadGateway
 }
 
+// overflowMarkers 匹配上游「上下文超窗」类措辞。
+//
+// 上游写法五花八门，且**不在 pi 客户端的识别列表里**。pi 靠
+// @earendil-works/pi-ai 的 OVERFLOW_PATTERNS 判断超窗并据此触发压缩重试，
+// 而 justworker 返回的是「请精简对话历史…(Context window is full…)」——
+// 与那 25 条正则一条都不匹配，于是 pi 既不压缩也不重试，只把它当成一条
+// 普通上游错误。这里把可识别的超窗措辞归一化成 pi 一定认得的标记。
+var overflowMarkers = []*regexp.Regexp{
+	regexp.MustCompile(`(?i)context[ _-]?window is full`),
+	regexp.MustCompile(`(?i)context[_ ]length[_ ]exceeded`),
+	regexp.MustCompile(`(?i)exceeds? the context window`),
+	regexp.MustCompile(`(?i)maximum context length`),
+	regexp.MustCompile(`(?i)reduce the length of the messages`),
+	regexp.MustCompile(`(?i)too many tokens`),
+	regexp.MustCompile(`(?i)token limit exceeded`),
+	regexp.MustCompile(`请精简对话历史`),
+	regexp.MustCompile(`上下文(长度)?超(出|限)`),
+	regexp.MustCompile(`对话历史过长`),
+}
+
+// overflowCanonical 命中 pi 的 /context[_ ]length[_ ]exceeded/i。
+const overflowCanonical = "context_length_exceeded"
+
+// looksLikeOverflow 判断错误文本是否属于上下文超窗。
+func looksLikeOverflow(s string) bool {
+	for _, re := range overflowMarkers {
+		if re.MatchString(s) {
+			return true
+		}
+	}
+	return false
+}
+
 // clientUpstreamErr collapses upstream failure details into a short message
 // for the client: per-tier bodies (WAF HTML pages, quota payloads, ...) stay
 // in rec.Err / the stats API and the server log instead of the response.
 // Per-tier one-line reasons are kept (quota/cooling skips carry no error body
 // and are the actionable part); each is capped so HTML dumps can't leak.
+//
+// 超窗会被归一化成 overflowCanonical 前缀，见 overflowMarkers 的说明。
 func clientUpstreamErr(err error) string {
 	log.Printf("[gateway] upstream failure surfaced to client: %v", err)
+	msg := upstreamErrSummary(err)
+	if looksLikeOverflow(err.Error()) || looksLikeOverflow(msg) {
+		return fmt.Sprintf("%s: %s", overflowCanonical, msg)
+	}
+	return msg
+}
+
+// upstreamErrSummary 把上游失败压成一行短消息。
+func upstreamErrSummary(err error) string {
 	var ce *scheduler.ChainErr
 	if errors.As(err, &ce) {
 		parts := make([]string, 0, len(ce.Tiers)+len(ce.Skipped))
 		for _, t := range ce.Tiers {
-			parts = append(parts, types.OneLine(fmt.Sprintf("%s/%s: %v", t.Source, t.Model, t.Err), 80))
+			// 160 而不是 80：短诊断词（"Context window is full"）常落在尾部，
+			// 80 字节按字节截断正好会把它切掉，超窗就再也认不出来。
+			parts = append(parts, types.OneLine(fmt.Sprintf("%s/%s: %v", t.Source, t.Model, t.Err), 160))
 		}
 		for _, sk := range ce.Skipped {
-			parts = append(parts, types.OneLine(sk, 80))
+			parts = append(parts, types.OneLine(sk, 160))
 		}
 		msg := strings.Join(parts, "; ")
 		if len(msg) > 300 {

internal/gateway/gateway_test.go

@@ -670,8 +670,11 @@ func TestHasScopeModelWithSourcePrefix(t *testing.T) {
 	if g.hasScopeModel(scope, "deepseek-v4-flash-free-extra") {
 		t.Error("hasScopeModel returned true for unrelated model")
 	}
-	if !g.hasScopeModel([]config.ModelScope{{Model: "AUTO"}}, "zen:anything") {
+	if g.hasScopeModel([]config.ModelScope{{Model: "AUTO"}}, "zen:deepseek-v4-flash-free") {
-		t.Error("AUTO scope should allow any prefixed model")
+		t.Error("AUTO scope must NOT grant specific model ids even with prefix")
+	}
+	if g.hasScopeModel([]config.ModelScope{{Model: "AUTO"}}, "deepseek-v4-pro") {
+		t.Error("AUTO scope must NOT grant specific model ids")
 	}
 }
 

internal/gateway/overflow_err_test.go

@@ -0,0 +1,96 @@
+package gateway
+
+import (
+	"errors"
+	"regexp"
+	"strings"
+	"testing"
+
+	"llmsproxy/internal/scheduler"
+	"llmsproxy/internal/types"
+)
+
+// piOverflowRe 是 @earendil-works/pi-ai 的 OVERFLOW_PATTERNS 中对应的一条。
+// 归一化标记必须命中它，否则改了等于没改：客户端仍不会压缩重试。
+var piOverflowRe = regexp.MustCompile(`context[_ ]length[_ ]exceeded`)
+
+func TestOverflowCanonicalMatchesPiPattern(t *testing.T) {
+	if !piOverflowRe.MatchString(overflowCanonical) {
+		t.Fatalf("归一化标记 %q 不匹配 pi 的超窗正则，客户端仍不会压缩重试", overflowCanonical)
+	}
+}
+
+// justworker 的真实措辞：与 pi 现有 25 条正则一条都不匹配，
+// 所以必须在网关侧归一化，否则超窗对客户端完全不可见。
+func TestJustworkerOverflowIsNormalized(t *testing.T) {
+	raw := "请精简对话历史…(Context window is full, please reduce the conversation history)…"
+
+	// 前提校验：原始措辞确实不被 pi 认出（否则本用例失去意义）。
+	if piOverflowRe.MatchString(raw) {
+		t.Fatalf("前提不成立：原始措辞本就匹配 pi 正则: %q", raw)
+	}
+	if !looksLikeOverflow(raw) {
+		t.Fatalf("网关应识别出这是超窗: %q", raw)
+	}
+
+	err := &scheduler.ChainErr{Tiers: []scheduler.TierError{{
+		Tier: 1, Source: "justworker", Model: "claude-opus-5", Err: errors.New(raw),
+	}}}
+
+	got := clientUpstreamErr(err)
+	if !piOverflowRe.MatchString(got) {
+		t.Fatalf("归一化后仍不匹配 pi 正则，客户端不会压缩重试: %q", got)
+	}
+}
+
+// 直连路径（非 AUTO 链）也要归一化——它走的是同一个入口。
+func TestDirectPathOverflowIsNormalized(t *testing.T) {
+	got := clientUpstreamErr(errors.New("upstream 400: Context window is full"))
+	if !piOverflowRe.MatchString(got) {
+		t.Fatalf("直连超窗未被归一化: %q", got)
+	}
+}
+
+// 非超窗错误不能被加上超窗标记，否则会把普通失败误报成需要压缩。
+func TestNonOverflowNotNormalized(t *testing.T) {
+	err := &scheduler.ChainErr{Tiers: []scheduler.TierError{{
+		Tier: 1, Source: "x", Model: "y", Err: errors.New("502 Bad Gateway: upstream connect error"),
+	}}}
+	got := clientUpstreamErr(err)
+	if strings.Contains(got, overflowCanonical) {
+		t.Fatalf("普通上游失败被误标为超窗: %q", got)
+	}
+	if !strings.Contains(got, "502 Bad Gateway") {
+		t.Fatalf("普通失败的诊断信息应保留: %q", got)
+	}
+}
+
+// 回归：短诊断词常落在错误尾部，80 字节截断会正好把它切掉，
+// 超窗就永远认不出来。宽度放宽后必须保住。
+func TestOverflowPhraseSurvivesTruncationWidth(t *testing.T) {
+	prefix := strings.Repeat("x", 100)
+	// OneLine 的长度限制作用于整条 "source/model: err"，不是只算 err 本身。
+	full := "justworker/claude-opus-5: " + prefix + " Context window is full"
+
+	// 前提：80 字节下短语确实会被切掉（这正是修复前的行为）。
+	if got := types.OneLine(full, 80); strings.Contains(got, "Context window is full") {
+		t.Fatalf("前提不成立：80 字节下短语居然还在: %q", got)
+	}
+	// 160 字节下必须保住，否则超窗识别会被截断悄悄破坏。
+	if got := types.OneLine(full, 160); !strings.Contains(got, "Context window is full") {
+		t.Fatalf("160 字节应保住尾部短诊断词: %q", got)
+	}
+
+	err := &scheduler.ChainErr{Tiers: []scheduler.TierError{{
+		Tier: 1, Source: "justworker", Model: "claude-opus-5",
+		Err: errors.New(prefix + " Context window is full"),
+	}}}
+
+	got := clientUpstreamErr(err)
+	if !strings.Contains(strings.ToLower(got), "context window is full") {
+		t.Fatalf("宽度 160 应保住尾部短诊断词，实际: %q", got)
+	}
+	if !piOverflowRe.MatchString(got) {
+		t.Fatalf("归一化标记丢失: %q", got)
+	}
+}

internal/lua/adapters/agentrouter.lua

@@ -5,10 +5,12 @@ adapter.version = "1.0.0"
 adapter.endpoint = "/chat/completions"
 adapter.headers = {}
 
--- AgentRouter 的 WAF 会按客户端指纹白名单校验，只放行官方客户端。
+-- AgentRouter 的阿里云 WAF 按三重维度校验：出口 IP（必须海外）、
--- 这里通过 build_headers 注入官方客户端 User-Agent 以通过校验。
+-- TLS 指纹（JS/Go HTTP 层与 curl 不同）、浏览器指纹 header 集。
--- 默认 QwenCode 指纹（实测可通）；可在 source.meta.user_agent 覆盖成 Claude Code 指纹。
+-- 纯 UA 已不够：WAF 拦 12 种 agent CLI UA 中的 10 种（全 405 HTML），
-
+-- 只有同时带 Origin: qwen.ai + Referer + X-Requested-With 才放行，
+-- 且同 IP 短时间连续 3+ 次请求会被速率封禁，靠 adapter 侧低频调用 +
+-- llmsproxy 的 prefFailStep 冷却自然限制，来源无法控制速率。
 local default_ua = "QwenCode/0.2.0 (linux; x64)"
 
 -- AgentRouter fronts Claude models (claude-opus-4-8), and Claude upstreams
@@ -65,6 +67,13 @@ function adapter.build_headers(meta)
         ["Content-Type"] = "application/json",
         ["Authorization"] = "Bearer " .. meta.api_key,
         ["User-Agent"] = ua,
+        -- QwenCode client fingerprint: WAF rejects bare UA without these.
+        ["Accept"] = "application/json, text/plain, */*",
+        ["Accept-Language"] = "zh-CN,zh;q=0.9",
+        ["Origin"] = "https://qwen.ai",
+        ["Referer"] = "https://qwen.ai/",
+        ["X-Requested-With"] = "XMLHttpRequest",
+        ["Connection"] = "keep-alive",
     }
 end
 

internal/lua/adapters/gemini.lua

@@ -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
+            if type(p) == "string" then
-                table.insert(parts, { text = p.text })
+                if p ~= "" then table.insert(parts, { text = p }) end
-            elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
+            elseif type(p) == "table" then
-                local mt, b64 = string.match(p.image_url.url, "^data:([^,]+);base64,(.+)$")
+                if p.type == "text" then
-                if b64 then
+                    if p.text ~= nil and p.text ~= "" then
-                    table.insert(parts, { inline_data = { mime_type = mt or "image/png", data = b64 } })
+                        table.insert(parts, { text = p.text })
+                    end
+                elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
+                    local mt, b64 = string.match(p.image_url.url, "^data:([^,]+);base64,(.+)$")
+                    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, {
+        local role = m.role or "user"
-            role = (m.role == "assistant") and "model" or m.role,
+
-            parts = to_parts(m.content)
+        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

internal/lua/adapters/ollama.lua

@@ -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
+                    if type(p) == "table" then
-                        text = text .. (p.text or "")
+                        if p.type == "text" then
-                    elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
+                            text = text .. (p.text or "")
-                        local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
+                        elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
-                        if b64 then table.insert(images, b64) end
+                            local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
+                            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
 

internal/lua/adapters/opencode.lua

@@ -34,8 +34,10 @@ 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；因此失去全部 content 的
+-- （image_url / input_audio / file 等）一律剥离。剥离后 content 变空的消息
--- 消息整条丢弃，避免上游 "unknown variant `image_url`, expected `text`"。
+-- 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。
@@ -72,7 +74,24 @@ function adapter.transform_request(raw_body)
                     end
                 end
                 if #parts == 0 then
-                    drop = true
+                    -- 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

internal/lua/toolcall_preservation_test.go

@@ -0,0 +1,120 @@
+package lua
+
+import (
+	"encoding/json"
+	"strings"
+	"testing"
+)
+
+// TestAdaptersPreserveToolCalls is the fleet-wide guard for the
+// "orphaned tool result" class of bug: when an agent client replays a turn
+// whose assistant message carries tool_calls, EVERY adapter must forward both
+// the call and the attribution of its result. Dropping the call (or the
+// tool_call_id / tool_name that ties the result to it) makes the model see a
+// result for a call it never made and re-issue the same call forever.
+//
+// The input deliberately uses content:[] — the shape most agent clients emit
+// for a tool-calling assistant turn with no text.
+func TestAdaptersPreserveToolCalls(t *testing.T) {
+	vm := NewVM(freshAdapterDir(t))
+	if err := vm.Start(); err != nil {
+		t.Fatal(err)
+	}
+	defer vm.Stop()
+
+	body := `{"model":"m","messages":[
+		{"role":"user","content":"read /tmp/x"},
+		{"role":"assistant","content":[],"tool_calls":[{"id":"call_abc","type":"function","function":{"name":"read","arguments":"{\"path\":\"/tmp/x\"}"}}]},
+		{"role":"tool","tool_call_id":"call_abc","content":"hello world"},
+		{"role":"user","content":"summarize"}
+	]}`
+	const (
+		callID   = "call_abc"
+		fnName   = "read"
+		toolOut  = "hello world"
+		lastUser = "summarize"
+	)
+
+	// Adapters that identify a tool result by the call id.
+	byID := []string{"openai", "deepseek", "github", "groq", "kimicode", "mistral",
+		"sensenova", "trae", "agentrouter", "opencode", "anthropic"}
+
+	for _, a := range byID {
+		out, err := vm.Transform(a, "transform_request", body)
+		if err != nil {
+			t.Errorf("%s: transform_request: %v", a, err)
+			continue
+		}
+		if !strings.Contains(out, callID) {
+			t.Errorf("%s dropped the tool call id %q: %s", a, callID, out)
+		}
+		if !strings.Contains(out, fnName) {
+			t.Errorf("%s dropped the function name %q: %s", a, fnName, out)
+		}
+		if !strings.Contains(out, toolOut) {
+			t.Errorf("%s dropped the tool result: %s", a, out)
+		}
+		if !strings.Contains(out, lastUser) {
+			t.Errorf("%s dropped the final user turn: %s", a, out)
+		}
+	}
+
+	// Ollama identifies the result with tool_name (its API has no tool_call_id
+	// on assistant turns) and takes arguments as an object, not a JSON string.
+	out, err := vm.Transform("ollama", "transform_request", body)
+	if err != nil {
+		t.Fatalf("ollama: %v", err)
+	}
+	for _, want := range []string{`"tool_calls"`, fnName, `"tool_name"`, toolOut} {
+		if !strings.Contains(out, want) {
+			t.Errorf("ollama missing %s: %s", want, out)
+		}
+	}
+
+	// Gemini identifies the result by function NAME and has no call id in its
+	// wire format; both directions must be present as functionCall /
+	// functionResponse parts, and the system role must move to
+	// systemInstruction rather than sitting in contents.
+	gBody := `{"model":"m","messages":[
+		{"role":"system","content":"be brief"},
+		{"role":"user","content":"read /tmp/x"},
+		{"role":"assistant","content":[],"tool_calls":[{"id":"call_abc","type":"function","function":{"name":"read","arguments":"{\"path\":\"/tmp/x\"}"}}]},
+		{"role":"tool","tool_call_id":"call_abc","content":"hello world"}
+	]}`
+	gout, err := vm.Transform("gemini", "transform_request", gBody)
+	if err != nil {
+		t.Fatalf("gemini: %v", err)
+	}
+	for _, want := range []string{`"functionCall"`, `"functionResponse"`, fnName, toolOut, `"systemInstruction"`} {
+		if !strings.Contains(gout, want) {
+			t.Errorf("gemini missing %s: %s", want, gout)
+		}
+	}
+	// No message may keep the OpenAI-only roles inside contents.
+	var greq struct {
+		Contents []struct {
+			Role string `json:"role"`
+		} `json:"contents"`
+	}
+	if err := json.Unmarshal([]byte(gout), &greq); err != nil {
+		t.Fatalf("gemini unmarshal: %v (%s)", err, gout)
+	}
+	for _, c := range greq.Contents {
+		if c.Role != "user" && c.Role != "model" {
+			t.Errorf("gemini contents carry an invalid role %q: %s", c.Role, gout)
+		}
+	}
+
+	// Negative control: a text-only turn must still be forwarded verbatim.
+	plain := `{"model":"m","messages":[{"role":"user","content":"just text"}]}`
+	for _, a := range append(byID, "ollama", "gemini") {
+		pout, err := vm.Transform(a, "transform_request", plain)
+		if err != nil {
+			t.Errorf("%s plain: %v", a, err)
+			continue
+		}
+		if !strings.Contains(pout, "just text") {
+			t.Errorf("%s dropped plain text: %s", a, pout)
+		}
+	}
+}

internal/lua/vm_test.go

@@ -221,6 +221,70 @@ func TestOpenCodeStripsMultiModalParts(t *testing.T) {
 	}
 }
 
+// TestOpenCodeKeepsToolCallWithEmptyContent pins the fix for an infinite
+// "repeated tool call" loop: an assistant turn whose content serialises to an
+// empty ARRAY while carrying tool_calls must survive the multimodal strip.
+// Dropping it orphans the following tool result, so the model never sees the
+// call it already made and re-issues it on every turn.
+func TestOpenCodeKeepsToolCallWithEmptyContent(t *testing.T) {
+	vm := NewVM(freshAdapterDir(t))
+	if err := vm.Start(); err != nil {
+		t.Fatal(err)
+	}
+	defer vm.Stop()
+
+	body := `{"model":"x","messages":[
+		{"role":"user","content":"read /tmp/x"},
+		{"role":"assistant","content":[],"tool_calls":[{"id":"call_abc","type":"function","function":{"name":"read","arguments":"{\"path\":\"/tmp/x\"}"}}]},
+		{"role":"tool","tool_call_id":"call_abc","content":"hello"},
+		{"role":"user","content":"now summarize"}
+	]}`
+	out, err := vm.Transform("opencode", "transform_request", body)
+	if err != nil {
+		t.Fatalf("transform_request: %v", err)
+	}
+
+	var req struct {
+		Messages []struct {
+			Role      string          `json:"role"`
+			Content   json.RawMessage `json:"content"`
+			ToolCalls []struct {
+				ID string `json:"id"`
+			} `json:"tool_calls"`
+			ToolCallID string `json:"tool_call_id"`
+		} `json:"messages"`
+	}
+	if err := json.Unmarshal([]byte(out), &req); err != nil {
+		t.Fatalf("unmarshal: %v (%s)", err, out)
+	}
+	if len(req.Messages) != 4 {
+		t.Fatalf("expected 4 messages (tool call must not be dropped), got %d: %s", len(req.Messages), out)
+	}
+	asst := req.Messages[1]
+	if asst.Role != "assistant" || len(asst.ToolCalls) != 1 || asst.ToolCalls[0].ID != "call_abc" {
+		t.Fatalf("assistant tool_calls lost: %s", out)
+	}
+	if string(asst.Content) != `""` {
+		t.Fatalf("empty content must be rewritten to \"\", got %s", asst.Content)
+	}
+	if req.Messages[2].Role != "tool" || req.Messages[2].ToolCallID != "call_abc" {
+		t.Fatalf("tool result must stay paired with its call: %s", out)
+	}
+
+	// Negative control: a message with neither text nor tool calls is still dropped.
+	only := `{"model":"x","messages":[
+		{"role":"user","content":[{"type":"image_url","image_url":{"url":"https://ex.com/a.png"}}]},
+		{"role":"user","content":"keep me"}
+	]}`
+	out2, err := vm.Transform("opencode", "transform_request", only)
+	if err != nil {
+		t.Fatal(err)
+	}
+	if got := strings.Count(out2, `"role"`); got != 1 {
+		t.Fatalf("image-only message without tool calls must still be dropped, got %d: %s", got, out2)
+	}
+}
+
 func TestBuildHeadersCustomHook(t *testing.T) {
 	vm := NewVM(freshAdapterDir(t))
 	if err := vm.Start(); err != nil {

internal/types/types.go

@@ -3,6 +3,7 @@
 package types
 
 import (
+	"bytes"
 	"encoding/json"
 	"errors"
 	"strings"
@@ -61,6 +62,39 @@ type ChatMessage struct {
 
 func StringContent(s string) json.RawMessage { b, _ := json.Marshal(s); return b }
 
+// isEmptyJSONArray reports whether raw is the literal empty JSON array [].
+func isEmptyJSONArray(raw json.RawMessage) bool {
+	t := bytes.TrimSpace(raw)
+	return len(t) == 2 && t[0] == '[' && t[1] == ']'
+}
+
+// UnmarshalJSON decodes a chat message, normalising an empty-array content
+// ("content":[]) to an empty string and dropping an empty tool_calls array.
+//
+// Why this exists: 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 an assistant turn that
+// carries tool_calls and no text as content:[], so every pass-through adapter
+// turned it into content:{} — a shape that is not valid OpenAI (content is
+// string | array of parts | null) and that real upstreams reject with
+// "400 invalid arguments". Normalising at the decode boundary fixes every
+// adapter at once, including ones added later.
+func (m *ChatMessage) UnmarshalJSON(b []byte) error {
+	type alias ChatMessage
+	var a alias
+	if err := json.Unmarshal(b, &a); err != nil {
+		return err
+	}
+	*m = ChatMessage(a)
+	if isEmptyJSONArray(m.Content) {
+		m.Content = StringContent("")
+	}
+	if isEmptyJSONArray(m.ToolCalls) {
+		m.ToolCalls = nil
+	}
+	return nil
+}
+
 type ToolCall struct {
 	ID        string                 `json:"id"`
 	Type      string                 `json:"type"`

internal/types/types_test.go

@@ -68,3 +68,52 @@ func TestTokenUsageMarshalCacheFields(t *testing.T) {
 	t.Logf("DeepSeek JSON: %s", string(b))
 	t.Logf("OpenAI JSON: %s", string(b2))
 }
+
+// TestChatMessageNormalizesEmptyArrayContent pins the fix for the malformed
+// content:{} that pass-through adapters produced for an assistant turn carrying
+// tool_calls with no text. Lua adapters cannot tell an empty JSON array from an
+// empty object, so the decode boundary normalises it for every adapter at once.
+func TestChatMessageNormalizesEmptyArrayContent(t *testing.T) {
+	var msg ChatMessage
+	raw := `{"role":"assistant","content":[],"tool_calls":[{"id":"call_1","type":"function","function":{"name":"read","arguments":"{}"}}]}`
+	if err := json.Unmarshal([]byte(raw), &msg); err != nil {
+		t.Fatal(err)
+	}
+	if string(msg.Content) != `""` {
+		t.Fatalf("empty-array content must normalise to \"\", got %s", msg.Content)
+	}
+	if len(msg.ToolCalls) == 0 {
+		t.Fatal("tool_calls must survive normalisation")
+	}
+
+	// A non-empty content array must be left byte-identical (multimodal path).
+	var mm ChatMessage
+	multi := `{"role":"user","content":[{"type":"text","text":"hi"}]}`
+	if err := json.Unmarshal([]byte(multi), &mm); err != nil {
+		t.Fatal(err)
+	}
+	if string(mm.Content) != `[{"type":"text","text":"hi"}]` {
+		t.Fatalf("multimodal content must pass through untouched, got %s", mm.Content)
+	}
+
+	// A plain string content is untouched.
+	var sm ChatMessage
+	if err := json.Unmarshal([]byte(`{"role":"user","content":"plain"}`), &sm); err != nil {
+		t.Fatal(err)
+	}
+	if string(sm.Content) != `"plain"` {
+		t.Fatalf("string content must pass through untouched, got %s", sm.Content)
+	}
+
+	// An omitted content stays omitted (omitempty semantics preserved).
+	var om ChatMessage
+	if err := json.Unmarshal([]byte(`{"role":"assistant","tool_calls":[]}`), &om); err != nil {
+		t.Fatal(err)
+	}
+	if om.Content != nil {
+		t.Fatalf("absent content must stay absent, got %s", om.Content)
+	}
+	if om.ToolCalls != nil {
+		t.Fatalf("empty tool_calls array must be dropped, got %s", om.ToolCalls)
+	}
+}