Add OpenAI Responses API (/v1/responses) endpoint

Translate Responses API requests (input→messages, instructions→system,
max_output_tokens→max_tokens, text.format→response_format, flat tools→nested
{function:{…}}) to upstream chat/completions, then convert responses back to
Responses format (streaming SSE event lifecycle + non-streaming JSON).

Verified against OpenAI migration guide and Python SDK Response model:
- Echo back required fields parallel_tool_calls/tool_choice/tools
- Include content:[] in reasoning items, logprobs:[] in output_text parts
- Support function_call/function_call_output multi-turn input items
- Map usage fields prompt_tokens→input_tokens, completion_tokens→output_tokens

README.md

@@ -5,7 +5,7 @@
 当前实现包含：
 
 - 登录页支持插件默认的移动云手机号验证码登录：验证码校验后按插件流程调用 `/api/acepilot/zhanlu/v1/login` 获取用户资料，再通过 SM2 签名调用 `/user/api/v2/external/key/get-or-create` 换取模型 API Key，凭据自动保存到本地 JSON。
-- OpenAI 兼容接口：`/v1/models`（优先从 `/gateway/v1/model/info` 拉取模型列表）、`/v1/chat/completions`（携带 `Authorization: Bearer <apiKey>` 请求 `{modelBaseUrl}/chat/completions`）。
+- OpenAI 兼容接口：`/v1/models`（优先从 `/gateway/v1/model/info` 拉取模型列表）、`/v1/chat/completions`（携带 `Authorization: Bearer <apiKey>` 请求 `{modelBaseUrl}/chat/completions`）、`/v1/responses`（Responses API，自动转换请求/响应格式，兼容新版 SDK 与 AI 编码工具）。
 - 湛卢登录签名逻辑：RSA `authorization`、SHA-256 query hash、HMAC-SHA1 `Signature`，用于 v1.4.2 的 v1/login 认证。
 - 模型 API Key 换取签名逻辑：SM3 摘要 + SM2 签名（`X-Auth-Signature`/`X-Auth-Timestamp`/`X-Auth-Nonce`）。
 - 上游 SSE 直接透传为 OpenAI SSE；非流式请求在本地聚合为 OpenAI Chat Completion JSON。
@@ -169,6 +169,30 @@ curl -N http://127.0.0.1:8080/v1/chat/completions `
 
 请求中的 `tools`、`tool_choice` 会传给湛卢模型。流式响应返回增量 `delta.tool_calls`；非流式响应会把分片聚合为完整的 `message.tool_calls`，并保留 `finish_reason: "tool_calls"`。执行工具后，将 assistant 的 `tool_calls` 和 `role: "tool"` 结果放回 `messages` 再发起请求即可得到最终回答。
 
+### Responses API
+
+代理还兼容 OpenAI Responses API（`POST /v1/responses`），支持使用该 API 的客户端（如新版 OpenAI SDK、Cursor 等 AI 编码工具）直接对接。代理会将 Responses API 请求格式转换为上游 chat/completions 格式，再将响应转回 Responses 格式。
+
+请求中的 `input`（字符串或消息数组）、`instructions`（系统提示词）、`max_output_tokens`、`temperature`、`top_p`、`tools`、`tool_choice`、`response_format` 等参数均会翻译并透传给上游。`tools` 格式自动从 Responses 扁平结构转换为 Chat Completions 嵌套 `{function:{…}}` 结构。多轮对话中的 `function_call` 和 `function_call_output` 输入项也会自动转换为对应的 assistant `tool_calls` 和 `role: tool` 消息。
+
+非流式：
+
+```powershell
+curl http://127.0.0.1:8080/v1/responses `
+  -H "Content-Type: application/json" `
+  -d '{"model":"zhanlu/auto","input":"hello","stream":false}'
+```
+
+流式：
+
+```powershell
+curl -N http://127.0.0.1:8080/v1/responses `
+  -H "Content-Type: application/json" `
+  -d '{"model":"zhanlu/auto","input":"hello","stream":true}'
+```
+
+流式响应返回标准 Responses API SSE 事件序列（`response.created` → `response.output_item.added` → `response.output_text.delta` → `response.output_text.done` → `response.output_item.done` → `response.completed`），思考模型额外包含 `response.reasoning_summary_text.delta` 事件，工具调用包含 `response.function_call_arguments.delta` 事件。Token 统计同样记录在 SQLite 中。
+
 如果设置了本地 OpenAI 兼容 API Key，需要带 `Authorization`：
 
 ```powershell

internal/openai/responses.go

@@ -0,0 +1,347 @@
+package openai
+
+import (
+	"encoding/json"
+	"errors"
+)
+
+// --- Responses API request parsing & conversion ---
+
+// ParseResponsesRequest converts a raw OpenAI Responses API (POST /v1/responses)
+// request body into a ChatCompletionRequest suitable for the upstream gateway.
+// It translates input→messages, instructions→system message, max_output_tokens→
+// max_tokens, and reshapes tools from the Responses flat format to the Chat
+// Completions nested {function:{…}} format.
+func ParseResponsesRequest(body []byte) (ChatCompletionRequest, error) {
+	var raw map[string]json.RawMessage
+	if err := json.Unmarshal(body, &raw); err != nil {
+		return ChatCompletionRequest{}, err
+	}
+
+	var req ChatCompletionRequest
+	if v, ok := raw["model"]; ok {
+		_ = json.Unmarshal(v, &req.Model)
+	}
+	if v, ok := raw["stream"]; ok {
+		_ = json.Unmarshal(v, &req.Stream)
+	}
+
+	// Build messages from instructions + input.
+	messages := make([]map[string]any, 0, 4)
+	if v, ok := raw["instructions"]; ok {
+		var s string
+		if json.Unmarshal(v, &s) == nil && s != "" {
+			messages = append(messages, map[string]any{"role": "system", "content": s})
+		}
+	}
+	if v, ok := raw["input"]; ok {
+		msgs, err := responsesInputToMessages(v)
+		if err != nil {
+			return req, err
+		}
+		messages = append(messages, msgs...)
+	}
+	req.Messages = messages
+
+	// Extra: renamed + pass-through fields sent to upstream as-is.
+	extra := map[string]json.RawMessage{}
+	if v, ok := raw["max_output_tokens"]; ok {
+		extra["max_tokens"] = v
+	}
+	for _, key := range []string{
+		"temperature", "top_p", "top_k", "frequency_penalty",
+		"presence_penalty", "stop", "seed", "user",
+	} {
+		if v, ok := raw[key]; ok {
+			extra[key] = v
+		}
+	}
+	if v, ok := raw["tools"]; ok {
+		if translated, err := translateResponsesTools(v); err == nil {
+			extra["tools"] = translated
+		} else {
+			extra["tools"] = v // fall back to pass-through
+		}
+	}
+	if v, ok := raw["tool_choice"]; ok {
+		extra["tool_choice"] = v
+	}
+	// Structured Outputs: Responses API uses text.format instead of
+	// response_format. Translate text.format → response_format for the
+	// upstream Chat Completions endpoint.
+	if v, ok := raw["text"]; ok {
+		if rf, err := translateTextFormat(v); err == nil {
+			extra["response_format"] = rf
+		}
+	}
+	req.Extra = extra
+	return req, nil
+}
+
+// translateTextFormat converts the Responses API "text" field (containing a
+// "format" sub-object) into a Chat Completions response_format value.
+//   - {text:{format:{type:"json_object"}}}        → {type:"json_object"}
+//   - {text:{format:{type:"json_schema",name,schema,strict}}} →
+//     {type:"json_schema",json_schema:{name,schema,strict}}
+func translateTextFormat(textRaw json.RawMessage) (json.RawMessage, error) {
+	var text struct {
+		Format map[string]any `json:"format"`
+	}
+	if err := json.Unmarshal(textRaw, &text); err != nil {
+		return nil, err
+	}
+	if len(text.Format) == 0 {
+		return nil, errors.New("empty text.format")
+	}
+	t, _ := text.Format["type"].(string)
+	switch t {
+	case "json_object":
+		return json.Marshal(map[string]any{"type": "json_object"})
+	case "json_schema":
+		js := map[string]any{}
+		for _, k := range []string{"name", "schema", "strict"} {
+			if v, ok := text.Format[k]; ok {
+				js[k] = v
+			}
+		}
+		return json.Marshal(map[string]any{"type": "json_schema", "json_schema": js})
+	default:
+		return json.Marshal(text.Format) // pass through unknown types
+	}
+}
+
+// ResponsesMeta holds fields from the Responses API request that should be
+// echoed back in the response object (the OpenAI SDK requires them).
+type ResponsesMeta struct {
+	ParallelToolCalls any
+	ToolChoice        any
+	Tools             any
+	Temperature       any
+	TopP              any
+	MaxOutputTokens   any
+}
+
+// ParseResponsesMeta extracts echo-back fields from the raw request body.
+func ParseResponsesMeta(body []byte) ResponsesMeta {
+	var m map[string]any
+	_ = json.Unmarshal(body, &m)
+	meta := ResponsesMeta{
+		ParallelToolCalls: false,
+		ToolChoice:        "auto",
+		Tools:             []any{},
+	}
+	if v, ok := m["parallel_tool_calls"]; ok {
+		meta.ParallelToolCalls = v
+	}
+	if v, ok := m["tool_choice"]; ok {
+		meta.ToolChoice = v
+	}
+	// Tools are echoed back in the Responses API flat format (not the
+	// translated Chat Completions format).
+	if v, ok := m["tools"]; ok {
+		meta.Tools = v
+	} else {
+		meta.Tools = []any{}
+	}
+	if v, ok := m["temperature"]; ok {
+		meta.Temperature = v
+	}
+	if v, ok := m["top_p"]; ok {
+		meta.TopP = v
+	}
+	if v, ok := m["max_output_tokens"]; ok {
+		meta.MaxOutputTokens = v
+	}
+	return meta
+}
+
+// responsesInputToMessages converts the Responses API "input" field (which may
+// be a plain string or an array of input items) into Chat Completions messages.
+func responsesInputToMessages(input json.RawMessage) ([]map[string]any, error) {
+	// Case 1: input is a plain string.
+	var s string
+	if json.Unmarshal(input, &s) == nil {
+		return []map[string]any{{"role": "user", "content": s}}, nil
+	}
+
+	// Case 2: input is an array of items.
+	var items []map[string]json.RawMessage
+	if err := json.Unmarshal(input, &items); err != nil {
+		return nil, err
+	}
+
+	messages := make([]map[string]any, 0, len(items))
+	for _, item := range items {
+		// Determine the type — most items are message-like with a role.
+		var role string
+		if v, ok := item["role"]; ok {
+			_ = json.Unmarshal(v, &role)
+		}
+		var itemType string
+		if v, ok := item["type"]; ok {
+			_ = json.Unmarshal(v, &itemType)
+		}
+
+		switch {
+		case itemType == "function_call":
+			// An assistant tool call from a previous turn.
+			msg := map[string]any{"role": "assistant"}
+			tc := map[string]any{"type": "function"}
+			inner := map[string]any{}
+			if v, ok := item["name"]; ok {
+				var name string
+				_ = json.Unmarshal(v, &name)
+				inner["name"] = name
+			}
+			if v, ok := item["arguments"]; ok {
+				var args string
+				_ = json.Unmarshal(v, &args)
+				inner["arguments"] = args
+			}
+			if v, ok := item["call_id"]; ok {
+				var id string
+				_ = json.Unmarshal(v, &id)
+				tc["id"] = id
+			}
+			tc["function"] = inner
+			msg["tool_calls"] = []any{tc}
+			messages = append(messages, msg)
+		case itemType == "function_call_output":
+			// A tool result from a previous turn.
+			msg := map[string]any{"role": "tool"}
+			if v, ok := item["call_id"]; ok {
+				var id string
+				_ = json.Unmarshal(v, &id)
+				msg["tool_call_id"] = id
+			}
+			if v, ok := item["output"]; ok {
+				var out string
+				_ = json.Unmarshal(v, &out)
+				msg["content"] = out
+			}
+			messages = append(messages, msg)
+		default:
+			// Standard message item with role + content.
+			if role == "" {
+				role = "user"
+			}
+			// "developer" maps to "system" for broad upstream compatibility.
+			if role == "developer" {
+				role = "system"
+			}
+			msg := map[string]any{"role": role}
+			if v, ok := item["content"]; ok {
+				msg["content"] = convertContentParts(v)
+			} else {
+				msg["content"] = ""
+			}
+			messages = append(messages, msg)
+		}
+	}
+	return messages, nil
+}
+
+// convertContentParts converts a Responses API content field (string or array
+// of content parts) into the Chat Completions content format.
+func convertContentParts(raw json.RawMessage) any {
+	// Content is a plain string.
+	var s string
+	if json.Unmarshal(raw, &s) == nil {
+		return s
+	}
+	// Content is an array of parts.
+	var parts []map[string]any
+	if json.Unmarshal(raw, &parts) != nil {
+		return string(raw) // fallback
+	}
+	result := make([]map[string]any, 0, len(parts))
+	for _, p := range parts {
+		pt, _ := p["type"].(string)
+		switch pt {
+		case "input_text", "output_text", "text":
+			result = append(result, map[string]any{"type": "text", "text": p["text"]})
+		case "input_image":
+			img := map[string]any{"type": "image_url"}
+			if url, ok := p["image_url"]; ok {
+				img["image_url"] = map[string]any{"url": url}
+			} else if d, ok := p["image"]; ok {
+				img["image_url"] = map[string]any{"url": d}
+			}
+			result = append(result, img)
+		default:
+			// Pass through unknown part types as-is.
+			result = append(result, p)
+		}
+	}
+	if len(result) == 0 {
+		return ""
+	}
+	return result
+}
+
+// translateResponsesTools converts tools from the Responses API flat format
+// to the Chat Completions nested {type:"function",function:{…}} format.
+func translateResponsesTools(raw json.RawMessage) (json.RawMessage, error) {
+	var tools []map[string]any
+	if err := json.Unmarshal(raw, &tools); err != nil {
+		return nil, err
+	}
+	out := make([]map[string]any, 0, len(tools))
+	for _, t := range tools {
+		tt, _ := t["type"].(string)
+		if tt != "function" && tt != "" {
+			// Non-function tool types (web_search, file_search, etc.) —
+			// pass through as-is; upstream may or may not support them.
+			out = append(out, t)
+			continue
+		}
+		fn := map[string]any{}
+		for _, key := range []string{"name", "description", "parameters", "strict"} {
+			if v, ok := t[key]; ok {
+				fn[key] = v
+			}
+		}
+		out = append(out, map[string]any{"type": "function", "function": fn})
+	}
+	return json.Marshal(out)
+}
+
+// --- Responses API response building ---
+
+// UsageToResponses converts a Chat Completions usage value (as decoded by
+// json.Unmarshal into any) to the Responses API usage field names
+// (input_tokens / output_tokens instead of prompt_tokens / completion_tokens).
+func UsageToResponses(v any) any {
+	if v == nil {
+		return nil
+	}
+	b, err := json.Marshal(v)
+	if err != nil {
+		return v
+	}
+	var m map[string]any
+	if json.Unmarshal(b, &m) != nil {
+		return v
+	}
+	out := map[string]any{}
+	if pt, ok := m["prompt_tokens"]; ok {
+		out["input_tokens"] = pt
+	}
+	if ct, ok := m["completion_tokens"]; ok {
+		out["output_tokens"] = ct
+	}
+	if tt, ok := m["total_tokens"]; ok {
+		out["total_tokens"] = tt
+	}
+	if d, ok := m["prompt_tokens_details"]; ok {
+		out["input_tokens_details"] = d
+	} else if d, ok := m["input_tokens_details"]; ok {
+		out["input_tokens_details"] = d
+	}
+	if d, ok := m["completion_tokens_details"]; ok {
+		out["output_tokens_details"] = d
+	} else if d, ok := m["output_tokens_details"]; ok {
+		out["output_tokens_details"] = d
+	}
+	return out
+}

internal/openai/responses_test.go

@@ -0,0 +1,305 @@
+package openai
+
+import (
+	"encoding/json"
+	"testing"
+)
+
+func TestParseResponsesRequest_StringInput(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"hello world","stream":false}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if req.Model != "GLM-4.7" {
+		t.Fatalf("model = %q", req.Model)
+	}
+	if len(req.Messages) != 1 {
+		t.Fatalf("messages = %d items", len(req.Messages))
+	}
+	if req.Messages[0]["role"] != "user" {
+		t.Fatalf("role = %v", req.Messages[0]["role"])
+	}
+	if req.Messages[0]["content"] != "hello world" {
+		t.Fatalf("content = %v", req.Messages[0]["content"])
+	}
+}
+
+func TestParseResponsesRequest_Instructions(t *testing.T) {
+	body := `{"model":"GLM-4.7","instructions":"be helpful","input":"hi"}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(req.Messages) != 2 {
+		t.Fatalf("messages = %d items", len(req.Messages))
+	}
+	if req.Messages[0]["role"] != "system" {
+		t.Fatalf("first role = %v", req.Messages[0]["role"])
+	}
+	if req.Messages[0]["content"] != "be helpful" {
+		t.Fatalf("first content = %v", req.Messages[0]["content"])
+	}
+	if req.Messages[1]["role"] != "user" {
+		t.Fatalf("second role = %v", req.Messages[1]["role"])
+	}
+}
+
+func TestParseResponsesRequest_ArrayInput(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":[
+		{"role":"user","content":"hello"},
+		{"role":"assistant","content":"hi there"},
+		{"role":"user","content":"how are you?"}
+	]}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(req.Messages) != 3 {
+		t.Fatalf("messages = %d items", len(req.Messages))
+	}
+	if req.Messages[0]["role"] != "user" || req.Messages[0]["content"] != "hello" {
+		t.Fatalf("msg[0] = %v", req.Messages[0])
+	}
+	if req.Messages[1]["role"] != "assistant" || req.Messages[1]["content"] != "hi there" {
+		t.Fatalf("msg[1] = %v", req.Messages[1])
+	}
+	if req.Messages[2]["role"] != "user" || req.Messages[2]["content"] != "how are you?" {
+		t.Fatalf("msg[2] = %v", req.Messages[2])
+	}
+}
+
+func TestParseResponsesRequest_ContentParts(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":[
+		{"role":"user","content":[
+			{"type":"input_text","text":"describe this"},
+			{"type":"input_image","image_url":"data:image/png;base64,abc"}
+		]}
+	]}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(req.Messages) != 1 {
+		t.Fatalf("messages = %d items", len(req.Messages))
+	}
+	content, ok := req.Messages[0]["content"].([]map[string]any)
+	if !ok {
+		t.Fatalf("content type = %T", req.Messages[0]["content"])
+	}
+	if len(content) != 2 {
+		t.Fatalf("content parts = %d", len(content))
+	}
+	if content[0]["type"] != "text" || content[0]["text"] != "describe this" {
+		t.Fatalf("content[0] = %v", content[0])
+	}
+	if content[1]["type"] != "image_url" {
+		t.Fatalf("content[1] type = %v", content[1])
+	}
+}
+
+func TestParseResponsesRequest_MaxOutputTokens(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"hi","max_output_tokens":500}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if v, ok := req.Extra["max_tokens"]; !ok {
+		t.Fatal("max_tokens not in Extra")
+	} else {
+		var n int
+		_ = json.Unmarshal(v, &n)
+		if n != 500 {
+			t.Fatalf("max_tokens = %d", n)
+		}
+	}
+}
+
+func TestParseResponsesRequest_Tools(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"hi","tools":[
+		{"type":"function","name":"get_weather","description":"get weather","parameters":{"type":"object"}}
+	]}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	raw, ok := req.Extra["tools"]
+	if !ok {
+		t.Fatal("tools not in Extra")
+	}
+	var tools []map[string]any
+	if err := json.Unmarshal(raw, &tools); err != nil {
+		t.Fatal(err)
+	}
+	if len(tools) != 1 {
+		t.Fatalf("tools = %d", len(tools))
+	}
+	if tools[0]["type"] != "function" {
+		t.Fatalf("tool type = %v", tools[0]["type"])
+	}
+	fn, ok := tools[0]["function"].(map[string]any)
+	if !ok {
+		t.Fatalf("function type = %T", tools[0]["function"])
+	}
+	if fn["name"] != "get_weather" {
+		t.Fatalf("function name = %v", fn["name"])
+	}
+}
+
+func TestParseResponsesRequest_FunctionCallInput(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":[
+		{"role":"user","content":"what's the weather?"},
+		{"type":"function_call","call_id":"call_123","name":"get_weather","arguments":"{\"city\":\"NYC\"}"},
+		{"type":"function_call_output","call_id":"call_123","output":"sunny 72F"}
+	]}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	if len(req.Messages) != 3 {
+		t.Fatalf("messages = %d items", len(req.Messages))
+	}
+	// First message is user text
+	if req.Messages[0]["role"] != "user" {
+		t.Fatalf("msg[0] role = %v", req.Messages[0]["role"])
+	}
+	// Second message is assistant with tool_calls
+	if req.Messages[1]["role"] != "assistant" {
+		t.Fatalf("msg[1] role = %v", req.Messages[1]["role"])
+	}
+	tcs, ok := req.Messages[1]["tool_calls"].([]any)
+	if !ok || len(tcs) != 1 {
+		t.Fatalf("msg[1] tool_calls = %v", req.Messages[1]["tool_calls"])
+	}
+	tc, _ := tcs[0].(map[string]any)
+	if tc["id"] != "call_123" {
+		t.Fatalf("tool call id = %v", tc["id"])
+	}
+	fn, _ := tc["function"].(map[string]any)
+	if fn["name"] != "get_weather" {
+		t.Fatalf("function name = %v", fn["name"])
+	}
+	// Third message is tool result
+	if req.Messages[2]["role"] != "tool" {
+		t.Fatalf("msg[2] role = %v", req.Messages[2]["role"])
+	}
+	if req.Messages[2]["tool_call_id"] != "call_123" {
+		t.Fatalf("msg[2] tool_call_id = %v", req.Messages[2]["tool_call_id"])
+	}
+	if req.Messages[2]["content"] != "sunny 72F" {
+		t.Fatalf("msg[2] content = %v", req.Messages[2]["content"])
+	}
+}
+
+func TestUsageToResponses(t *testing.T) {
+	usage := map[string]any{
+		"prompt_tokens":             10,
+		"completion_tokens":         20,
+		"total_tokens":              30,
+		"prompt_tokens_details":     map[string]any{"cached_tokens": 4},
+		"completion_tokens_details": map[string]any{"reasoning_tokens": 5},
+	}
+	result := UsageToResponses(usage)
+	m, ok := result.(map[string]any)
+	if !ok {
+		t.Fatalf("result type = %T", result)
+	}
+	if m["input_tokens"] != float64(10) {
+		t.Fatalf("input_tokens = %v", m["input_tokens"])
+	}
+	if m["output_tokens"] != float64(20) {
+		t.Fatalf("output_tokens = %v", m["output_tokens"])
+	}
+	if m["total_tokens"] != float64(30) {
+		t.Fatalf("total_tokens = %v", m["total_tokens"])
+	}
+	if d, ok := m["input_tokens_details"].(map[string]any); !ok || d["cached_tokens"] != float64(4) {
+		t.Fatalf("input_tokens_details = %v", m["input_tokens_details"])
+	}
+	if d, ok := m["output_tokens_details"].(map[string]any); !ok || d["reasoning_tokens"] != float64(5) {
+		t.Fatalf("output_tokens_details = %v", m["output_tokens_details"])
+	}
+}
+
+func TestParseResponsesRequest_TextFormat(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"Jane, 54","text":{"format":{"type":"json_schema","name":"person","strict":true,"schema":{"type":"object"}}}}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	rf, ok := req.Extra["response_format"]
+	if !ok {
+		t.Fatal("response_format not in Extra")
+	}
+	var m map[string]any
+	if err := json.Unmarshal(rf, &m); err != nil {
+		t.Fatal(err)
+	}
+	if m["type"] != "json_schema" {
+		t.Fatalf("type = %v", m["type"])
+	}
+	js, ok := m["json_schema"].(map[string]any)
+	if !ok {
+		t.Fatalf("json_schema = %v", m["json_schema"])
+	}
+	if js["name"] != "person" {
+		t.Fatalf("name = %v", js["name"])
+	}
+	if js["strict"] != true {
+		t.Fatalf("strict = %v", js["strict"])
+	}
+}
+
+func TestParseResponsesRequest_TextFormatJsonObject(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"hi","text":{"format":{"type":"json_object"}}}`
+	req, err := ParseResponsesRequest([]byte(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	rf, ok := req.Extra["response_format"]
+	if !ok {
+		t.Fatal("response_format not in Extra")
+	}
+	var m map[string]any
+	if err := json.Unmarshal(rf, &m); err != nil {
+		t.Fatal(err)
+	}
+	if m["type"] != "json_object" {
+		t.Fatalf("type = %v", m["type"])
+	}
+}
+
+func TestParseResponsesMeta_Defaults(t *testing.T) {
+	meta := ParseResponsesMeta([]byte(`{"model":"GLM-4.7","input":"hi"}`))
+	if meta.ParallelToolCalls != false {
+		t.Fatalf("parallel_tool_calls = %v", meta.ParallelToolCalls)
+	}
+	if meta.ToolChoice != "auto" {
+		t.Fatalf("tool_choice = %v", meta.ToolChoice)
+	}
+	tools, ok := meta.Tools.([]any)
+	if !ok || len(tools) != 0 {
+		t.Fatalf("tools = %v", meta.Tools)
+	}
+}
+
+func TestParseResponsesMeta_EchoBack(t *testing.T) {
+	body := `{"model":"GLM-4.7","input":"hi","parallel_tool_calls":true,"tool_choice":"required","tools":[{"type":"function","name":"get_weather"}],"temperature":0.7,"max_output_tokens":500}`
+	meta := ParseResponsesMeta([]byte(body))
+	if meta.ParallelToolCalls != true {
+		t.Fatalf("parallel_tool_calls = %v", meta.ParallelToolCalls)
+	}
+	if meta.ToolChoice != "required" {
+		t.Fatalf("tool_choice = %v", meta.ToolChoice)
+	}
+	tools, ok := meta.Tools.([]any)
+	if !ok || len(tools) != 1 {
+		t.Fatalf("tools = %v", meta.Tools)
+	}
+	if meta.Temperature != 0.7 {
+		t.Fatalf("temperature = %v", meta.Temperature)
+	}
+	if meta.MaxOutputTokens != float64(500) {
+		t.Fatalf("max_output_tokens = %v", meta.MaxOutputTokens)
+	}
+}

internal/server/responses.go

@@ -0,0 +1,591 @@
+package server
+
+import (
+	"bufio"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"time"
+
+	"git.misaka.ren/M1saka/zhanlu_proxy/internal/openai"
+)
+
+// responses handles POST /v1/responses — the OpenAI Responses API. It
+// translates the request to a chat-completions request for the upstream
+// gateway, then translates the response back into the Responses format.
+func (s *Server) responses(w http.ResponseWriter, r *http.Request) {
+	creds, err := s.currentCredentials()
+	if err != nil {
+		writeOpenAIError(w, http.StatusUnauthorized, "zhanlu credentials are not configured; open /login first", "auth_error", "missing_credentials")
+		return
+	}
+
+	body, err := io.ReadAll(r.Body)
+	if err != nil {
+		writeOpenAIError(w, http.StatusBadRequest, err.Error(), "invalid_request_error", "bad_body")
+		return
+	}
+
+	chatReq, err := openai.ParseResponsesRequest(body)
+	if err != nil {
+		writeOpenAIError(w, http.StatusBadRequest, err.Error(), "invalid_request_error", "bad_json")
+		return
+	}
+	meta := openai.ParseResponsesMeta(body)
+	if chatReq.Model == "" {
+		chatReq.Model = "zhanlu/auto"
+	}
+
+	start := time.Now()
+	clientWantsStream := chatReq.Stream
+	chatReq.Stream = true // upstream always streams
+	upstreamBody, err := chatReq.MarshalForUpstream()
+	if err != nil {
+		writeOpenAIError(w, http.StatusBadRequest, err.Error(), "invalid_request_error", "bad_body")
+		return
+	}
+
+	if !creds.HasAPIKey() {
+		creds, err = s.provisionCredentials(r.Context(), creds)
+		if err != nil {
+			writeOpenAIError(w, http.StatusBadGateway, "zhanlu api key provisioning failed: "+err.Error(), "auth_error", "zhanlu_provision_failed")
+			return
+		}
+		s.cfg.Credentials = creds
+		_ = s.st.SaveCredentials(creds)
+	}
+	modelBaseURL := firstNonEmpty(creds.ModelBaseURL, s.cfg.MobileModelBaseURL)
+	client, err := s.zhanluClientWithBase(modelBaseURL)
+	if err != nil {
+		writeOpenAIError(w, http.StatusInternalServerError, err.Error(), "sign_error", "signer_init_failed")
+		return
+	}
+	resp, err := client.ChatCompletions(r.Context(), creds.APIKey, upstreamBody)
+	if err != nil {
+		msg := "zhanlu upstream request failed"
+		if s.cfg.Debug {
+			msg = redactSensitive(err.Error())
+		}
+		writeOpenAIError(w, http.StatusBadGateway, msg, "upstream_error", "zhanlu_request_failed")
+		s.record(chatReq.Model, clientWantsStream, nil, "upstream_error", start)
+		return
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode < 200 || resp.StatusCode >= 300 {
+		b, _ := io.ReadAll(io.LimitReader(resp.Body, 4096))
+		msg := fmt.Sprintf("zhanlu upstream returned %d", resp.StatusCode)
+		if s.cfg.Debug && len(b) > 0 {
+			msg += ": " + string(b)
+		}
+		writeOpenAIError(w, http.StatusBadGateway, msg, "upstream_error", "zhanlu_bad_status")
+		s.record(chatReq.Model, clientWantsStream, nil, "upstream_error", start)
+		return
+	}
+
+	if clientWantsStream {
+		usage, status := s.proxyResponsesStream(w, resp, chatReq.Model, meta)
+		s.record(chatReq.Model, true, usage, status, start)
+		return
+	}
+	usage, status := s.aggregateResponsesStream(w, resp, chatReq.Model, meta)
+	s.record(chatReq.Model, false, usage, status, start)
+}
+
+// ---------------------------------------------------------------- non-streaming
+
+// aggregateResponsesStream reads the upstream SSE, aggregates it (same logic
+// as aggregateStream), then emits a Responses API JSON object.
+func (s *Server) aggregateResponsesStream(w http.ResponseWriter, resp *http.Response, model string, meta openai.ResponsesMeta) (any, string) {
+	var content, reasoning, id string
+	var usage any
+	finishReason := "stop"
+	type toolCall struct {
+		ID       string `json:"id"`
+		Type     string `json:"type"`
+		Function struct {
+			Name      string `json:"name"`
+			Arguments string `json:"arguments"`
+		} `json:"function"`
+	}
+	toolCalls := map[int]*toolCall{}
+	err := forEachSSEChunk(resp.Body, func(chunk []byte) error {
+		var event struct {
+			ID      string `json:"id"`
+			Choices []struct {
+				Delta struct {
+					Content          string `json:"content"`
+					ReasoningContent string `json:"reasoning_content"`
+					Reasoning        string `json:"reasoning"`
+					ToolCalls        []struct {
+						Index    int    `json:"index"`
+						ID       string `json:"id"`
+						Type     string `json:"type"`
+						Function struct {
+							Name      string `json:"name"`
+							Arguments string `json:"arguments"`
+						} `json:"function"`
+					} `json:"tool_calls"`
+				} `json:"delta"`
+				FinishReason *string `json:"finish_reason"`
+			} `json:"choices"`
+			Usage any `json:"usage"`
+		}
+		if err := json.Unmarshal(chunk, &event); err != nil {
+			return err
+		}
+		if event.ID != "" {
+			id = event.ID
+		}
+		if event.Usage != nil {
+			usage = event.Usage
+		}
+		if len(event.Choices) > 0 {
+			content += event.Choices[0].Delta.Content
+			reasoning += event.Choices[0].Delta.ReasoningContent + event.Choices[0].Delta.Reasoning
+			for _, part := range event.Choices[0].Delta.ToolCalls {
+				call := toolCalls[part.Index]
+				if call == nil {
+					call = &toolCall{Type: "function"}
+					toolCalls[part.Index] = call
+				}
+				if part.ID != "" {
+					call.ID = part.ID
+				}
+				if part.Type != "" {
+					call.Type = part.Type
+				}
+				call.Function.Name += part.Function.Name
+				call.Function.Arguments += part.Function.Arguments
+			}
+			if event.Choices[0].FinishReason != nil {
+				finishReason = *event.Choices[0].FinishReason
+			}
+		}
+		return nil
+	})
+	if err != nil {
+		writeOpenAIError(w, http.StatusBadGateway, err.Error(), "upstream_error", "zhanlu_stream_error")
+		return nil, "upstream_error"
+	}
+
+	_ = id
+	_ = finishReason
+	respID := "resp_" + randomRequestID()
+	output := []any{}
+
+	if reasoning != "" {
+		output = append(output, map[string]any{
+			"type": "reasoning", "id": "rs_" + randomRequestID(), "status": "completed",
+			"content": []any{},
+			"summary": []map[string]any{{"type": "summary_text", "text": reasoning}},
+		})
+	}
+
+	// Message output item — included when there is text content.
+	if content != "" {
+		output = append(output, map[string]any{
+			"type": "message", "id": "msg_" + randomRequestID(), "status": "completed",
+			"role": "assistant",
+			"content": []map[string]any{{
+				"type": "output_text", "text": content,
+				"annotations": []any{}, "logprobs": []any{},
+			}},
+		})
+	}
+
+	if len(toolCalls) > 0 {
+		ordered := make([]*toolCall, 0, len(toolCalls))
+		for i := 0; i < len(toolCalls); i++ {
+			if call := toolCalls[i]; call != nil {
+				ordered = append(ordered, call)
+			}
+		}
+		for _, tc := range ordered {
+			output = append(output, map[string]any{
+				"type": "function_call", "id": "fc_" + randomRequestID(),
+				"call_id": tc.ID, "name": tc.Function.Name,
+				"arguments": tc.Function.Arguments, "status": "completed",
+			})
+		}
+	}
+
+	// If there was no content and no tool calls, still emit an empty message
+	// so the response always has at least one output item.
+	if len(output) == 0 {
+		output = append(output, map[string]any{
+			"type": "message", "id": "msg_" + randomRequestID(), "status": "completed",
+			"role": "assistant", "content": []map[string]any{},
+		})
+	}
+
+	result := map[string]any{
+		"id": respID, "object": "response", "created_at": time.Now().Unix(),
+		"model": model, "status": "completed", "output": output,
+		"parallel_tool_calls": meta.ParallelToolCalls,
+		"tool_choice":         meta.ToolChoice,
+		"tools":               meta.Tools,
+	}
+	if usage != nil {
+		result["usage"] = openai.UsageToResponses(usage)
+	}
+	writeJSON(w, http.StatusOK, result)
+	return usage, "success"
+}
+
+// ------------------------------------------------------------------- streaming
+
+// responsesStreamState tracks the lifecycle of output items while converting
+// Chat Completions SSE into Responses API SSE events.
+type responsesStreamState struct {
+	w       http.ResponseWriter
+	flusher http.Flusher
+	respID  string
+	msgID   string
+	rsID    string
+	meta    openai.ResponsesMeta
+
+	outputIdx     int
+	reasoningOn   bool
+	reasonPartOn  bool
+	messageOn     bool
+	partOn        bool
+	fullContent   string
+	fullReasoning string
+	usage         any
+	status        string
+
+	// tool call tracking
+	tools     map[int]*streamToolCall
+	toolOrder []int
+}
+
+type streamToolCall struct {
+	itemID  string
+	callID  string
+	name    string
+	args    string
+	started bool
+	doneIdx int // assigned output index when started
+}
+
+func newResponsesStreamState(w http.ResponseWriter, model string, meta openai.ResponsesMeta) *responsesStreamState {
+	flusher, _ := w.(http.Flusher)
+	w.Header().Set("Content-Type", "text/event-stream; charset=utf-8")
+	w.Header().Set("Cache-Control", "no-cache")
+	w.Header().Set("Connection", "keep-alive")
+	w.Header().Set("X-Accel-Buffering", "no")
+	w.WriteHeader(http.StatusOK)
+	st := &responsesStreamState{
+		w:       w,
+		flusher: flusher,
+		respID:  "resp_" + randomRequestID(),
+		msgID:   "msg_" + randomRequestID(),
+		rsID:    "rs_" + randomRequestID(),
+		meta:    meta,
+		tools:   map[int]*streamToolCall{},
+		status:  "success",
+	}
+	baseResp := func(st2 string) map[string]any {
+		return map[string]any{
+			"id": st.respID, "object": "response", "created_at": time.Now().Unix(),
+			"model": model, "status": st2, "output": []any{},
+			"parallel_tool_calls": meta.ParallelToolCalls,
+			"tool_choice":         meta.ToolChoice,
+			"tools":               meta.Tools,
+		}
+	}
+	st.emit("response.created", map[string]any{"type": "response.created", "response": baseResp("in_progress")})
+	st.emit("response.in_progress", map[string]any{"type": "response.in_progress", "response": baseResp("in_progress")})
+	return st
+}
+
+func (st *responsesStreamState) emit(event string, data any) {
+	b, _ := json.Marshal(data)
+	fmt.Fprintf(st.w, "event: %s\ndata: %s\n\n", event, b)
+	if st.flusher != nil {
+		st.flusher.Flush()
+	}
+}
+
+// closeReasoning closes the reasoning output item if it is open.
+func (st *responsesStreamState) closeReasoning() {
+	if !st.reasoningOn {
+		return
+	}
+	if st.reasonPartOn {
+		st.emit("response.reasoning_summary_text.done", map[string]any{
+			"type": "response.reasoning_summary_text.done", "item_id": st.rsID,
+			"output_index": st.outputIdx, "summary_index": 0, "text": st.fullReasoning,
+		})
+		st.emit("response.reasoning_summary_part.done", map[string]any{
+			"type": "response.reasoning_summary_part.done", "item_id": st.rsID,
+			"output_index": st.outputIdx, "summary_index": 0,
+			"part": map[string]any{"type": "summary_text", "text": st.fullReasoning},
+		})
+		st.reasonPartOn = false
+	}
+	st.emit("response.output_item.done", map[string]any{
+		"type": "response.output_item.done", "output_index": st.outputIdx,
+		"item": map[string]any{
+			"type": "reasoning", "id": st.rsID, "status": "completed",
+			"content": []any{},
+			"summary": []map[string]any{{"type": "summary_text", "text": st.fullReasoning}},
+		},
+	})
+	st.reasoningOn = false
+	st.outputIdx++
+}
+
+// closeMessage closes the message output item if it is open.
+func (st *responsesStreamState) closeMessage() {
+	if !st.messageOn {
+		return
+	}
+	if st.partOn {
+		st.emit("response.output_text.done", map[string]any{
+			"type": "response.output_text.done", "item_id": st.msgID,
+			"output_index": st.outputIdx, "content_index": 0, "text": st.fullContent,
+		})
+		st.emit("response.content_part.done", map[string]any{
+			"type": "response.content_part.done", "item_id": st.msgID,
+			"output_index": st.outputIdx, "content_index": 0,
+			"part": map[string]any{"type": "output_text", "text": st.fullContent, "annotations": []any{}, "logprobs": []any{}},
+		})
+		st.partOn = false
+	}
+	st.emit("response.output_item.done", map[string]any{
+		"type": "response.output_item.done", "output_index": st.outputIdx,
+		"item": map[string]any{
+			"type": "message", "id": st.msgID, "status": "completed", "role": "assistant",
+			"content": []map[string]any{{"type": "output_text", "text": st.fullContent, "annotations": []any{}, "logprobs": []any{}}},
+		},
+	})
+	st.messageOn = false
+	st.outputIdx++
+}
+
+// handleReasoning processes a reasoning content delta.
+func (st *responsesStreamState) handleReasoning(delta string) {
+	if !st.reasoningOn {
+		st.reasoningOn = true
+		st.emit("response.output_item.added", map[string]any{
+			"type": "response.output_item.added", "output_index": st.outputIdx,
+			"item": map[string]any{
+				"type": "reasoning", "id": st.rsID, "status": "in_progress",
+				"content": []any{}, "summary": []any{},
+			},
+		})
+		st.emit("response.reasoning_summary_part.added", map[string]any{
+			"type": "response.reasoning_summary_part.added", "item_id": st.rsID,
+			"output_index": st.outputIdx, "summary_index": 0,
+			"part": map[string]any{"type": "summary_text", "text": ""},
+		})
+		st.reasonPartOn = true
+	}
+	st.fullReasoning += delta
+	st.emit("response.reasoning_summary_text.delta", map[string]any{
+		"type": "response.reasoning_summary_text.delta", "item_id": st.rsID,
+		"output_index": st.outputIdx, "summary_index": 0, "delta": delta,
+	})
+}
+
+// handleContent processes a text content delta.
+func (st *responsesStreamState) handleContent(delta string) {
+	// Close reasoning if open — text content comes after reasoning.
+	st.closeReasoning()
+	if !st.messageOn {
+		st.messageOn = true
+		st.emit("response.output_item.added", map[string]any{
+			"type": "response.output_item.added", "output_index": st.outputIdx,
+			"item": map[string]any{
+				"type": "message", "id": st.msgID, "status": "in_progress", "role": "assistant", "content": []any{},
+			},
+		})
+		st.emit("response.content_part.added", map[string]any{
+			"type": "response.content_part.added", "item_id": st.msgID,
+			"output_index": st.outputIdx, "content_index": 0,
+			"part": map[string]any{"type": "output_text", "text": "", "annotations": []any{}, "logprobs": []any{}},
+		})
+		st.partOn = true
+	}
+	st.fullContent += delta
+	st.emit("response.output_text.delta", map[string]any{
+		"type": "response.output_text.delta", "item_id": st.msgID,
+		"output_index": st.outputIdx, "content_index": 0, "delta": delta,
+	})
+}
+
+// handleToolCall processes a tool call delta from the chat completion stream.
+func (st *responsesStreamState) handleToolCall(index int, id, name, args string) {
+	// Close reasoning/message if open — tool calls are separate output items.
+	st.closeReasoning()
+	st.closeMessage()
+
+	call := st.tools[index]
+	if call == nil {
+		call = &streamToolCall{itemID: "fc_" + randomRequestID()}
+		st.tools[index] = call
+		st.toolOrder = append(st.toolOrder, index)
+	}
+	if id != "" {
+		call.callID = id
+	}
+	if name != "" {
+		call.name += name
+	}
+	if !call.started {
+		call.started = true
+		call.doneIdx = st.outputIdx
+		st.emit("response.output_item.added", map[string]any{
+			"type": "response.output_item.added", "output_index": st.outputIdx,
+			"item": map[string]any{
+				"type": "function_call", "id": call.itemID, "call_id": call.callID,
+				"name": call.name, "arguments": "", "status": "in_progress",
+			},
+		})
+		st.outputIdx++
+	}
+	if args != "" {
+		call.args += args
+		st.emit("response.function_call_arguments.delta", map[string]any{
+			"type": "response.function_call_arguments.delta", "item_id": call.itemID,
+			"output_index": call.doneIdx, "delta": args,
+		})
+	}
+}
+
+// finish closes all open items and sends the response.completed event.
+func (st *responsesStreamState) finish(model string) {
+	st.closeReasoning()
+	st.closeMessage()
+	for _, idx := range st.toolOrder {
+		call := st.tools[idx]
+		st.emit("response.function_call_arguments.done", map[string]any{
+			"type": "response.function_call_arguments.done", "item_id": call.itemID,
+			"output_index": call.doneIdx, "arguments": call.args,
+		})
+		st.emit("response.output_item.done", map[string]any{
+			"type": "response.output_item.done", "output_index": call.doneIdx,
+			"item": map[string]any{
+				"type": "function_call", "id": call.itemID, "call_id": call.callID,
+				"name": call.name, "arguments": call.args, "status": "completed",
+			},
+		})
+	}
+
+	// Build the final output array for the completed event.
+	finalOutput := []any{}
+	if st.fullReasoning != "" {
+		finalOutput = append(finalOutput, map[string]any{
+			"type": "reasoning", "id": st.rsID, "status": "completed",
+			"content": []any{},
+			"summary": []map[string]any{{"type": "summary_text", "text": st.fullReasoning}},
+		})
+	}
+	if st.fullContent != "" {
+		finalOutput = append(finalOutput, map[string]any{
+			"type": "message", "id": st.msgID, "status": "completed", "role": "assistant",
+			"content": []map[string]any{{"type": "output_text", "text": st.fullContent, "annotations": []any{}, "logprobs": []any{}}},
+		})
+	}
+	for _, idx := range st.toolOrder {
+		call := st.tools[idx]
+		finalOutput = append(finalOutput, map[string]any{
+			"type": "function_call", "id": call.itemID, "call_id": call.callID,
+			"name": call.name, "arguments": call.args, "status": "completed",
+		})
+	}
+	// Ensure at least one output item exists.
+	if len(finalOutput) == 0 {
+		finalOutput = append(finalOutput, map[string]any{
+			"type": "message", "id": st.msgID, "status": "completed", "role": "assistant",
+			"content": []map[string]any{},
+		})
+	}
+
+	completedResp := map[string]any{
+		"id": st.respID, "object": "response", "created_at": time.Now().Unix(),
+		"model": model, "status": "completed", "output": finalOutput,
+		"parallel_tool_calls": st.meta.ParallelToolCalls,
+		"tool_choice":         st.meta.ToolChoice,
+		"tools":               st.meta.Tools,
+	}
+	if st.usage != nil {
+		completedResp["usage"] = openai.UsageToResponses(st.usage)
+	}
+	st.emit("response.completed", map[string]any{"type": "response.completed", "response": completedResp})
+}
+
+// proxyResponsesStream reads the upstream Chat Completions SSE and emits
+// Responses API SSE events via a responsesStreamState state machine.
+func (s *Server) proxyResponsesStream(w http.ResponseWriter, resp *http.Response, model string, meta openai.ResponsesMeta) (any, string) {
+	st := newResponsesStreamState(w, model, meta)
+
+	reader := bufio.NewReader(resp.Body)
+	for {
+		line, err := reader.ReadString('\n')
+		if line != "" {
+			payload := sseDataPayload(line)
+			if payload != "" && payload != "[DONE]" {
+				var evt struct {
+					State        string `json:"state"`
+					ErrorMessage string `json:"errorMessage"`
+					Usage        any    `json:"usage"`
+					Choices      []struct {
+						Delta struct {
+							Content          string `json:"content"`
+							ReasoningContent string `json:"reasoning_content"`
+							Reasoning        string `json:"reasoning"`
+							ToolCalls        []struct {
+								Index    int    `json:"index"`
+								ID       string `json:"id"`
+								Function struct {
+									Name      string `json:"name"`
+									Arguments string `json:"arguments"`
+								} `json:"function"`
+							} `json:"tool_calls"`
+						} `json:"delta"`
+					} `json:"choices"`
+				}
+				if jErr := json.Unmarshal([]byte(payload), &evt); jErr == nil {
+					if evt.State == "ERROR" {
+						st.status = "upstream_error"
+					}
+					if evt.Usage != nil {
+						st.usage = evt.Usage
+					}
+					if len(evt.Choices) > 0 {
+						delta := evt.Choices[0].Delta
+						reasoningDelta := delta.ReasoningContent + delta.Reasoning
+						if reasoningDelta != "" {
+							st.handleReasoning(reasoningDelta)
+						}
+						if delta.Content != "" {
+							st.handleContent(delta.Content)
+						}
+						for _, tc := range delta.ToolCalls {
+							st.handleToolCall(tc.Index, tc.ID, tc.Function.Name, tc.Function.Arguments)
+						}
+					}
+				}
+			}
+		}
+		if err != nil {
+			if err != io.EOF {
+				b, _ := json.Marshal(map[string]any{
+					"message": err.Error(), "type": "upstream_error", "code": "zhanlu_stream_error",
+				})
+				fmt.Fprintf(w, "data: %s\n\n", b)
+				if st.flusher != nil {
+					st.flusher.Flush()
+				}
+				st.status = "upstream_error"
+			}
+			break
+		}
+	}
+
+	st.finish(model)
+	return st.usage, st.status
+}

internal/server/responses_test.go

@@ -0,0 +1,304 @@
+package server
+
+import (
+	"encoding/json"
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"path/filepath"
+	"strings"
+	"testing"
+
+	"git.misaka.ren/M1saka/zhanlu_proxy/internal/auth"
+	"git.misaka.ren/M1saka/zhanlu_proxy/internal/config"
+	"git.misaka.ren/M1saka/zhanlu_proxy/internal/store"
+)
+
+// TestResponsesNonStreaming verifies POST /v1/responses with stream:false
+// returns a properly formatted Responses API JSON object.
+func TestResponsesNonStreaming(t *testing.T) {
+	upstream, proxy, st := setupTestServer(t)
+	defer upstream.Close()
+	defer proxy.Close()
+
+	creds := auth.Credentials{
+		AccessKey: "AK", SecretKey: "SK", Token: "TOKEN",
+		APIKey: "sk-test-456", ModelBaseURL: upstream.URL, Email: "[email protected]",
+	}
+	if err := st.SaveCredentials(creds); err != nil {
+		t.Fatal(err)
+	}
+
+	body := `{"model":"GLM-4.7","input":"hi","stream":false}`
+	resp, err := http.Post(proxy.URL+"/v1/responses", "application/json", strings.NewReader(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode != 200 {
+		b, _ := io.ReadAll(resp.Body)
+		t.Fatalf("status %d: %s", resp.StatusCode, string(b))
+	}
+	var result map[string]any
+	if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
+		t.Fatal(err)
+	}
+	if result["object"] != "response" {
+		t.Fatalf("object = %v", result["object"])
+	}
+	if result["status"] != "completed" {
+		t.Fatalf("status = %v", result["status"])
+	}
+	output, ok := result["output"].([]any)
+	if !ok || len(output) == 0 {
+		t.Fatalf("output = %v", result["output"])
+	}
+	msg, ok := output[0].(map[string]any)
+	if !ok {
+		t.Fatalf("output[0] type = %T", output[0])
+	}
+	if msg["type"] != "message" {
+		t.Fatalf("output[0] type = %v", msg["type"])
+	}
+	if msg["role"] != "assistant" {
+		t.Fatalf("output[0] role = %v", msg["role"])
+	}
+	content, ok := msg["content"].([]any)
+	if !ok || len(content) == 0 {
+		t.Fatalf("content = %v", msg["content"])
+	}
+	part, ok := content[0].(map[string]any)
+	if !ok {
+		t.Fatalf("content[0] type = %T", content[0])
+	}
+	if part["type"] != "output_text" {
+		t.Fatalf("content[0] type = %v", part["type"])
+	}
+	if part["text"] != "hello" {
+		t.Fatalf("content[0] text = %v", part["text"])
+	}
+	// Verify required SDK fields are present.
+	if _, ok := result["parallel_tool_calls"]; !ok {
+		t.Fatal("missing parallel_tool_calls in response")
+	}
+	if _, ok := result["tool_choice"]; !ok {
+		t.Fatal("missing tool_choice in response")
+	}
+	if _, ok := result["tools"]; !ok {
+		t.Fatal("missing tools in response")
+	}
+	// Verify output_text has logprobs field.
+	if _, ok := part["logprobs"]; !ok {
+		t.Fatal("missing logprobs in output_text content part")
+	}
+	usage, ok := result["usage"].(map[string]any)
+	if !ok {
+		t.Fatalf("usage = %v", result["usage"])
+	}
+	if totNum(usage["input_tokens"]) != 10 {
+		t.Fatalf("input_tokens = %v", usage["input_tokens"])
+	}
+	if totNum(usage["output_tokens"]) != 20 {
+		t.Fatalf("output_tokens = %v", usage["output_tokens"])
+	}
+	if totNum(usage["total_tokens"]) != 30 {
+		t.Fatalf("total_tokens = %v", usage["total_tokens"])
+	}
+}
+
+// TestResponsesStreaming verifies POST /v1/responses with stream:true
+// emits proper Responses API SSE events.
+func TestResponsesStreaming(t *testing.T) {
+	upstream, proxy, st := setupTestServer(t)
+	defer upstream.Close()
+	defer proxy.Close()
+
+	creds := auth.Credentials{
+		AccessKey: "AK", SecretKey: "SK", Token: "TOKEN",
+		APIKey: "sk-test-456", ModelBaseURL: upstream.URL, Email: "[email protected]",
+	}
+	if err := st.SaveCredentials(creds); err != nil {
+		t.Fatal(err)
+	}
+
+	body := `{"model":"GLM-4.7","input":"hi","stream":true}`
+	resp, err := http.Post(proxy.URL+"/v1/responses", "application/json", strings.NewReader(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer resp.Body.Close()
+	if resp.StatusCode != 200 {
+		b, _ := io.ReadAll(resp.Body)
+		t.Fatalf("status %d: %s", resp.StatusCode, string(b))
+	}
+	raw, _ := io.ReadAll(resp.Body)
+	s := string(raw)
+
+	// Check key lifecycle events are present.
+	checks := []string{
+		"event: response.created",
+		"event: response.in_progress",
+		"event: response.output_item.added",
+		"event: response.content_part.added",
+		"event: response.output_text.delta",
+		"event: response.output_text.done",
+		"event: response.content_part.done",
+		"event: response.output_item.done",
+		"event: response.completed",
+	}
+	for _, c := range checks {
+		if !strings.Contains(s, c) {
+			t.Fatalf("missing %q in SSE body:\n%s", c, s)
+		}
+	}
+
+	// Verify the text delta contains "hello".
+	if !strings.Contains(s, `"delta":"hello"`) {
+		t.Fatalf("text delta missing 'hello' in SSE body:\n%s", s)
+	}
+
+	// Verify required SDK fields are present in completed event.
+	if !strings.Contains(s, `"parallel_tool_calls"`) {
+		t.Fatalf("missing parallel_tool_calls in SSE body:\n%s", s)
+	}
+	if !strings.Contains(s, `"tool_choice"`) {
+		t.Fatalf("missing tool_choice in SSE body:\n%s", s)
+	}
+	// Verify logprobs field in output_text.
+	if !strings.Contains(s, `"logprobs"`) {
+		t.Fatalf("missing logprobs in SSE body:\n%s", s)
+	}
+
+	// Verify usage in the completed event has input_tokens.
+	if !strings.Contains(s, `"input_tokens":`) {
+		t.Fatalf("usage missing input_tokens in SSE body:\n%s", s)
+	}
+}
+
+// TestResponsesStringInput verifies the proxy correctly translates a string
+// "input" to a chat-completions "messages" array before forwarding upstream.
+func TestResponsesStringInput(t *testing.T) {
+	var capturedBody []byte
+	upstream := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		if r.URL.Path == "/chat/completions" {
+			capturedBody, _ = io.ReadAll(r.Body)
+			w.Header().Set("Content-Type", "text/event-stream")
+			_, _ = w.Write([]byte("data: {\"id\":\"x\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"ok\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"x\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"stop\"}]}\n\ndata: [DONE]\n\n"))
+			return
+		}
+		http.NotFound(w, r)
+	}))
+	defer upstream.Close()
+
+	st, err := store.Open(filepath.Join(t.TempDir(), "test.db"))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer st.Close()
+
+	cfg := config.Config{
+		MobileLoginBaseURL: upstream.URL,
+		MobileModelBaseURL: upstream.URL,
+		UpstreamPath:       "/chat/completions",
+		DBPath:             filepath.Join(t.TempDir(), "zhanlu.db"),
+		PublicKeyPEM:       defaultTestPublicKey,
+		PhonePublicKeyPEM:  defaultTestPublicKey,
+		SM2PrivateKey:      testSM2Key,
+		PluginVersion:      "1.4.2",
+	}
+	h := New(cfg, st)
+	proxy := httptest.NewServer(h)
+	defer proxy.Close()
+
+	creds := auth.Credentials{
+		APIKey: "sk-test-456", ModelBaseURL: upstream.URL, Email: "[email protected]",
+	}
+	_ = st.SaveCredentials(creds)
+
+	body := `{"model":"GLM-4.7","input":"hello world","stream":false}`
+	resp, err := http.Post(proxy.URL+"/v1/responses", "application/json", strings.NewReader(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer resp.Body.Close()
+	io.Copy(io.Discard, resp.Body)
+
+	if len(capturedBody) == 0 {
+		t.Fatal("no upstream request body captured")
+	}
+	var upstreamReq map[string]any
+	if err := json.Unmarshal(capturedBody, &upstreamReq); err != nil {
+		t.Fatal(err)
+	}
+	messages, ok := upstreamReq["messages"].([]any)
+	if !ok || len(messages) != 1 {
+		t.Fatalf("messages = %v", upstreamReq["messages"])
+	}
+	msg, _ := messages[0].(map[string]any)
+	if msg["role"] != "user" || msg["content"] != "hello world" {
+		t.Fatalf("upstream message = %v", msg)
+	}
+}
+
+// TestResponsesInstructions verifies instructions are prepended as a system
+// message in the upstream request.
+func TestResponsesInstructions(t *testing.T) {
+	var capturedBody []byte
+	upstream := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		if r.URL.Path == "/chat/completions" {
+			capturedBody, _ = io.ReadAll(r.Body)
+			w.Header().Set("Content-Type", "text/event-stream")
+			_, _ = w.Write([]byte("data: {\"id\":\"x\",\"choices\":[{\"index\":0,\"delta\":{\"content\":\"ok\"},\"finish_reason\":null}]}\n\ndata: {\"id\":\"x\",\"choices\":[{\"index\":0,\"delta\":{},\"finish_reason\":\"stop\"}]}\n\ndata: [DONE]\n\n"))
+			return
+		}
+		http.NotFound(w, r)
+	}))
+	defer upstream.Close()
+
+	st, err := store.Open(filepath.Join(t.TempDir(), "test.db"))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer st.Close()
+
+	cfg := config.Config{
+		MobileLoginBaseURL: upstream.URL,
+		MobileModelBaseURL: upstream.URL,
+		UpstreamPath:       "/chat/completions",
+		DBPath:             filepath.Join(t.TempDir(), "zhanlu.db"),
+		PublicKeyPEM:       defaultTestPublicKey,
+		PhonePublicKeyPEM:  defaultTestPublicKey,
+		SM2PrivateKey:      testSM2Key,
+		PluginVersion:      "1.4.2",
+	}
+	h := New(cfg, st)
+	proxy := httptest.NewServer(h)
+	defer proxy.Close()
+
+	creds := auth.Credentials{
+		APIKey: "sk-test-456", ModelBaseURL: upstream.URL, Email: "[email protected]",
+	}
+	_ = st.SaveCredentials(creds)
+
+	body := `{"model":"GLM-4.7","instructions":"be concise","input":"hello","stream":false}`
+	resp, err := http.Post(proxy.URL+"/v1/responses", "application/json", strings.NewReader(body))
+	if err != nil {
+		t.Fatal(err)
+	}
+	defer resp.Body.Close()
+	io.Copy(io.Discard, resp.Body)
+
+	if len(capturedBody) == 0 {
+		t.Fatal("no upstream request body captured")
+	}
+	var upstreamReq map[string]any
+	_ = json.Unmarshal(capturedBody, &upstreamReq)
+	messages, _ := upstreamReq["messages"].([]any)
+	if len(messages) != 2 {
+		t.Fatalf("messages = %d items", len(messages))
+	}
+	sys, _ := messages[0].(map[string]any)
+	if sys["role"] != "system" || sys["content"] != "be concise" {
+		t.Fatalf("system message = %v", sys)
+	}
+}

internal/server/server.go

@@ -65,6 +65,7 @@ func (s *Server) routes() {
 	s.mux.HandleFunc("POST /api/models/test", s.withLoginSession(s.testModel))
 	s.mux.HandleFunc("GET /v1/models", s.withAPIKey(s.models))
 	s.mux.HandleFunc("POST /v1/chat/completions", s.withAPIKey(s.chatCompletions))
+	s.mux.HandleFunc("POST /v1/responses", s.withAPIKey(s.responses))
 }
 
 func (s *Server) healthz(w http.ResponseWriter, r *http.Request) {
@@ -704,9 +705,9 @@ func (s *Server) testModel(w http.ResponseWriter, r *http.Request) {
 			payload := sseDataPayload(line)
 			if payload != "" && payload != "[DONE]" {
 				var evt struct {
-					State         string `json:"state"`
+					State        string `json:"state"`
-					ErrorMessage  string `json:"errorMessage"`
+					ErrorMessage string `json:"errorMessage"`
-					Choices       []struct {
+					Choices      []struct {
 						Delta struct {
 							Content string `json:"content"`
 						} `json:"delta"`