Merge pull request #4 from feat/chat-completions-compat

This commit is contained in:
wangbo 2026-05-19 21:31:15 +08:00
commit baffccf8f8
13 changed files with 1611 additions and 85 deletions

View File

@ -7281,6 +7281,11 @@
"type": "string",
"example": "A watercolor robot reading a book"
},
"reasoning_effort": {
"description": "ReasoningEffort 推理深度OpenAI-compatible 请求字段;开放字符串,取值随 provider 和模型能力而定,常见值为 none、minimal、low、medium、high、xhigh也可配置 max 等供应商自定义值。",
"type": "string",
"example": "medium"
},
"resolution": {
"type": "string",
"example": "720p"

View File

@ -587,6 +587,11 @@ definitions:
prompt:
example: A watercolor robot reading a book
type: string
reasoning_effort:
description: ReasoningEffort 推理深度OpenAI-compatible 请求字段;开放字符串,取值随 provider
和模型能力而定,常见值为 none、minimal、low、medium、high、xhigh也可配置 max 等供应商自定义值。
example: medium
type: string
resolution:
example: 720p
type: string

View File

@ -151,6 +151,187 @@ func TestOpenAIClientChatContract(t *testing.T) {
}
}
func TestOpenAIClientChatRequestNormalizesToolContext(t *testing.T) {
var captured map[string]any
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if err := json.NewDecoder(r.Body).Decode(&captured); err != nil {
t.Fatalf("decode request: %v", err)
}
_ = json.NewEncoder(w).Encode(map[string]any{
"id": "chatcmpl-normalized-request",
"object": "chat.completion",
"model": captured["model"],
"choices": []any{map[string]any{
"message": map[string]any{"role": "assistant", "content": "ok"},
}},
})
}))
defer server.Close()
_, err := (OpenAIClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "openai:gpt-4o-mini",
Body: map[string]any{
"model": "openai:gpt-4o-mini",
"messages": []any{
map[string]any{
"role": "assistant",
"functionCall": map[string]any{
"name": "lookup",
"arguments": map[string]any{"q": "weather"},
},
},
map[string]any{"role": "tool", "toolCallId": "call_0", "content": "sunny"},
map[string]any{
"role": "user",
"content": []any{
map[string]any{"type": "text", "text": "keep this"},
map[string]any{"type": "tool_result", "tool_use_id": "toolu_1", "content": map[string]any{"ok": true}},
},
},
},
},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ProviderModelName: "openai-compatible-gpt-4o-mini",
Credentials: map[string]any{"apiKey": "test-key"},
},
})
if err != nil {
t.Fatalf("run openai client: %v", err)
}
messages, _ := captured["messages"].([]any)
if len(messages) != 4 {
t.Fatalf("unexpected normalized messages: %+v", messages)
}
assistant, _ := messages[0].(map[string]any)
if _, ok := assistant["functionCall"]; ok {
t.Fatalf("functionCall should be converted away: %+v", assistant)
}
toolCalls, _ := assistant["tool_calls"].([]any)
toolCall, _ := toolCalls[0].(map[string]any)
function, _ := toolCall["function"].(map[string]any)
if function["name"] != "lookup" || function["arguments"] != `{"q":"weather"}` {
t.Fatalf("unexpected normalized tool call: %+v", assistant)
}
toolMessage, _ := messages[1].(map[string]any)
if toolMessage["tool_call_id"] != "call_0" || toolMessage["toolCallId"] != nil {
t.Fatalf("tool message was not normalized: %+v", toolMessage)
}
keptUser, _ := messages[2].(map[string]any)
convertedToolResult, _ := messages[3].(map[string]any)
if keptUser["content"] != "keep this" || convertedToolResult["role"] != "tool" || convertedToolResult["tool_call_id"] != "toolu_1" || convertedToolResult["content"] != `{"ok":true}` {
t.Fatalf("tool_result block was not restored: user=%+v tool=%+v", keptUser, convertedToolResult)
}
}
func TestOpenAIClientChatResponseNormalizesReasoning(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
_ = json.NewEncoder(w).Encode(map[string]any{
"id": "chatcmpl-reasoning",
"object": "chat.completion",
"model": "openrouter-test",
"choices": []any{map[string]any{
"message": map[string]any{
"role": "assistant",
"reasoning_details": []any{
map[string]any{"type": "reasoning.text", "text": "detail-"},
map[string]any{"type": "reasoning.summary", "summary": "summary"},
map[string]any{"type": "reasoning.encrypted", "data": "secret"},
},
"content": "<think>tagged</think>answer",
},
}},
})
}))
defer server.Close()
response, err := (OpenAIClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "OpenRouter-Test",
Body: map[string]any{"model": "OpenRouter-Test", "messages": []any{map[string]any{"role": "user", "content": "ping"}}},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ModelName: "openrouter-test",
Credentials: map[string]any{"apiKey": "test-key"},
},
})
if err != nil {
t.Fatalf("run openai client: %v", err)
}
choices, _ := response.Result["choices"].([]any)
choice, _ := choices[0].(map[string]any)
message, _ := choice["message"].(map[string]any)
if message["reasoning_content"] != "detail-summarytagged" || message["content"] != "answer" {
t.Fatalf("reasoning was not normalized: %+v", response.Result)
}
if _, ok := message["reasoning_details"]; ok {
t.Fatalf("reasoning_details should be converted away: %+v", message)
}
}
func TestOpenAIClientChatResponseNormalizesToolCallFormats(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
_ = json.NewEncoder(w).Encode(map[string]any{
"id": "chatcmpl-tools",
"object": "chat.completion",
"model": "tool-format-test",
"choices": []any{map[string]any{
"message": map[string]any{
"role": "assistant",
"content": []any{
map[string]any{"type": "text", "text": "calling tools"},
map[string]any{"type": "tool_use", "id": "toolu_1", "name": "anthropic_lookup", "input": map[string]any{"city": "Boston"}},
},
"toolCalls": []any{map[string]any{"id": "call_camel", "functionCall": map[string]any{"name": "camel_lookup", "args": map[string]any{"city": "SF"}}}},
"function_call": map[string]any{"name": "legacy_lookup", "arguments": "{\"city\":\"NYC\"}"},
},
}},
})
}))
defer server.Close()
response, err := (OpenAIClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "Tool-Format-Test",
Body: map[string]any{"model": "Tool-Format-Test", "messages": []any{map[string]any{"role": "user", "content": "ping"}}},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ModelName: "tool-format-test",
Credentials: map[string]any{"apiKey": "test-key"},
},
})
if err != nil {
t.Fatalf("run openai client: %v", err)
}
choices, _ := response.Result["choices"].([]any)
choice, _ := choices[0].(map[string]any)
message, _ := choice["message"].(map[string]any)
if message["content"] != "calling tools" {
t.Fatalf("tool_use block should be removed from content: %+v", message)
}
for _, key := range []string{"toolCalls", "function_call"} {
if _, ok := message[key]; ok {
t.Fatalf("%s should be converted away: %+v", key, message)
}
}
toolCalls, _ := message["tool_calls"].([]any)
if len(toolCalls) != 3 {
t.Fatalf("expected 3 normalized tool calls, got %+v", message)
}
assertToolCall := func(index int, id string, name string, arguments string) {
t.Helper()
toolCall, _ := toolCalls[index].(map[string]any)
function, _ := toolCall["function"].(map[string]any)
if toolCall["id"] != id || toolCall["type"] != "function" || function["name"] != name || function["arguments"] != arguments {
t.Fatalf("unexpected tool call[%d]: %+v", index, toolCall)
}
}
assertToolCall(0, "call_camel", "camel_lookup", "{\"city\":\"SF\"}")
assertToolCall(1, "call_1", "legacy_lookup", "{\"city\":\"NYC\"}")
assertToolCall(2, "toolu_1", "anthropic_lookup", "{\"city\":\"Boston\"}")
}
func TestOpenAIClientChatStreamContract(t *testing.T) {
var gotStream bool
var gotIncludeUsage bool
@ -204,6 +385,133 @@ func TestOpenAIClientChatStreamContract(t *testing.T) {
}
}
func TestOpenAIClientChatStreamPreservesStructuredDeltas(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
w.Header().Set("Content-Type", "text/event-stream")
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-structured\",\"object\":\"chat.completion.chunk\",\"model\":\"openrouter-reasoner\",\"choices\":[{\"delta\":{\"reasoning_details\":[{\"type\":\"reasoning.text\",\"text\":\"detail-\"},{\"type\":\"reasoning.summary\",\"summary\":\"summary\"},{\"type\":\"reasoning.encrypted\",\"data\":\"secret\"}]}}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-structured\",\"object\":\"chat.completion.chunk\",\"model\":\"openrouter-reasoner\",\"choices\":[{\"delta\":{\"content\":\"<think>tagged</think>answer\"}}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-structured\",\"object\":\"chat.completion.chunk\",\"model\":\"deepseek-v4\",\"choices\":[{\"delta\":{\"tool_calls\":[{\"index\":0,\"id\":\"call_1\",\"type\":\"function\",\"function\":{\"name\":\"lookup\",\"arguments\":\"{\\\"q\\\":\"}}]}}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-structured\",\"object\":\"chat.completion.chunk\",\"model\":\"deepseek-v4\",\"choices\":[{\"delta\":{\"tool_calls\":[{\"index\":0,\"function\":{\"arguments\":\"\\\"weather\\\"}\"}}]},\"finish_reason\":\"tool_calls\"}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: [DONE]\n\n"))
}))
defer server.Close()
captured := make([]StreamDeltaEvent, 0)
response, err := (OpenAIClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "DeepSeek-V4",
Body: map[string]any{
"model": "DeepSeek-V4",
"messages": []any{map[string]any{"role": "user", "content": "ping"}},
"stream": true,
},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ModelName: "deepseek-v4",
Credentials: map[string]any{"apiKey": "test-key"},
},
StreamDelta: func(event StreamDeltaEvent) error {
captured = append(captured, event)
return nil
},
})
if err != nil {
t.Fatalf("run openai structured stream client: %v", err)
}
if len(captured) != 4 || captured[0].ReasoningContent != "detail-summary" || captured[1].ReasoningContent != "tagged" || captured[1].Text != "answer" || captured[2].Event == nil {
t.Fatalf("structured stream events were not preserved: %+v", captured)
}
firstChoices, _ := captured[0].Event["choices"].([]any)
firstChoice, _ := firstChoices[0].(map[string]any)
firstDelta, _ := firstChoice["delta"].(map[string]any)
if firstDelta["reasoning_content"] != "detail-summary" {
t.Fatalf("reasoning_details were not converted in stream event: %+v", captured[0].Event)
}
if _, ok := firstDelta["reasoning_details"]; ok {
t.Fatalf("reasoning_details should be removed from stream event: %+v", captured[0].Event)
}
choices, _ := response.Result["choices"].([]any)
choice, _ := choices[0].(map[string]any)
message, _ := choice["message"].(map[string]any)
if message["reasoning_content"] != "detail-summarytagged" || message["content"] != "answer" || choice["finish_reason"] != "tool_calls" {
t.Fatalf("reasoning or finish reason missing from aggregated result: %+v", response.Result)
}
toolCalls, _ := message["tool_calls"].([]any)
toolCall, _ := toolCalls[0].(map[string]any)
function, _ := toolCall["function"].(map[string]any)
if function["arguments"] != "{\"q\":\"weather\"}" {
t.Fatalf("tool call arguments were not aggregated: %+v", response.Result)
}
}
func TestOpenAIClientChatStreamNormalizesToolCallFormats(t *testing.T) {
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
w.Header().Set("Content-Type", "text/event-stream")
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-tools-stream\",\"object\":\"chat.completion.chunk\",\"model\":\"tool-format-test\",\"choices\":[{\"delta\":{\"function_call\":{\"name\":\"legacy_lookup\",\"arguments\":\"{\\\"city\\\":\"}}}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-tools-stream\",\"object\":\"chat.completion.chunk\",\"model\":\"tool-format-test\",\"choices\":[{\"delta\":{\"functionCall\":{\"arguments\":\"\\\"Boston\\\"}\"}}}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: {\"id\":\"chatcmpl-tools-stream\",\"object\":\"chat.completion.chunk\",\"model\":\"tool-format-test\",\"choices\":[{\"delta\":{\"toolCall\":{\"index\":1,\"id\":\"call_camel\",\"functionCall\":{\"name\":\"camel_lookup\",\"args\":{\"city\":\"SF\"}}}},\"finish_reason\":\"tool_calls\"}],\"usage\":null}\n\n"))
_, _ = w.Write([]byte("data: [DONE]\n\n"))
}))
defer server.Close()
captured := make([]StreamDeltaEvent, 0)
response, err := (OpenAIClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "Tool-Format-Test",
Body: map[string]any{
"model": "Tool-Format-Test",
"messages": []any{map[string]any{"role": "user", "content": "ping"}},
"stream": true,
},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ModelName: "tool-format-test",
Credentials: map[string]any{"apiKey": "test-key"},
},
StreamDelta: func(event StreamDeltaEvent) error {
captured = append(captured, event)
return nil
},
})
if err != nil {
t.Fatalf("run openai stream client: %v", err)
}
if len(captured) != 3 {
t.Fatalf("unexpected captured events: %+v", captured)
}
for _, event := range captured {
choices, _ := event.Event["choices"].([]any)
choice, _ := choices[0].(map[string]any)
delta, _ := choice["delta"].(map[string]any)
if _, ok := delta["function_call"]; ok {
t.Fatalf("function_call should be converted away: %+v", event.Event)
}
if _, ok := delta["functionCall"]; ok {
t.Fatalf("functionCall should be converted away: %+v", event.Event)
}
if _, ok := delta["toolCall"]; ok {
t.Fatalf("toolCall should be converted away: %+v", event.Event)
}
}
choices, _ := response.Result["choices"].([]any)
choice, _ := choices[0].(map[string]any)
message, _ := choice["message"].(map[string]any)
toolCalls, _ := message["tool_calls"].([]any)
if len(toolCalls) != 2 || choice["finish_reason"] != "tool_calls" {
t.Fatalf("unexpected normalized stream result: %+v", response.Result)
}
legacyCall, _ := toolCalls[0].(map[string]any)
legacyFunction, _ := legacyCall["function"].(map[string]any)
if legacyFunction["name"] != "legacy_lookup" || legacyFunction["arguments"] != "{\"city\":\"Boston\"}" {
t.Fatalf("legacy function_call was not aggregated: %+v", response.Result)
}
camelCall, _ := toolCalls[1].(map[string]any)
camelFunction, _ := camelCall["function"].(map[string]any)
if camelCall["id"] != "call_camel" || camelFunction["name"] != "camel_lookup" || camelFunction["arguments"] != "{\"city\":\"SF\"}" {
t.Fatalf("camel toolCall was not normalized: %+v", response.Result)
}
}
func TestGeminiClientChatContract(t *testing.T) {
var gotPath string
var gotKey string
@ -261,6 +569,92 @@ func TestGeminiClientChatContract(t *testing.T) {
}
}
func TestGeminiClientChatRestoresToolContext(t *testing.T) {
var captured map[string]any
server := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
if err := json.NewDecoder(r.Body).Decode(&captured); err != nil {
t.Fatalf("decode request: %v", err)
}
_ = json.NewEncoder(w).Encode(map[string]any{
"candidates": []any{map[string]any{
"content": map[string]any{"parts": []any{map[string]any{"text": "gemini ok"}}},
}},
})
}))
defer server.Close()
_, err := (GeminiClient{HTTPClient: server.Client()}).Run(context.Background(), Request{
Kind: "chat.completions",
Model: "gemini:gemini-2.5-flash",
Body: map[string]any{
"model": "gemini:gemini-2.5-flash",
"messages": []any{
map[string]any{"role": "user", "content": "weather?"},
map[string]any{
"role": "assistant",
"content": "checking",
"tool_calls": []any{map[string]any{
"id": "call_weather",
"type": "function",
"function": map[string]any{
"name": "get_weather",
"arguments": `{"city":"SF"}`,
},
}},
},
map[string]any{"role": "tool", "tool_call_id": "call_weather", "content": `{"temperature":"72F"}`},
},
"tools": []any{map[string]any{
"type": "function",
"function": map[string]any{
"name": "get_weather",
"description": "lookup weather",
"parameters": map[string]any{"type": "object"},
},
}},
},
Candidate: store.RuntimeModelCandidate{
BaseURL: server.URL,
ProviderModelName: "gemini-2.5-flash",
ModelType: "chat",
Credentials: map[string]any{"apiKey": "gemini-key"},
},
})
if err != nil {
t.Fatalf("run gemini client: %v", err)
}
contents, _ := captured["contents"].([]any)
if len(contents) != 3 {
t.Fatalf("unexpected Gemini contents: %+v", captured)
}
modelTurn, _ := contents[1].(map[string]any)
if modelTurn["role"] != "model" {
t.Fatalf("assistant turn should become Gemini model turn: %+v", modelTurn)
}
modelParts, _ := modelTurn["parts"].([]any)
callPart, _ := modelParts[1].(map[string]any)
functionCall, _ := callPart["functionCall"].(map[string]any)
args, _ := functionCall["args"].(map[string]any)
if functionCall["name"] != "get_weather" || args["city"] != "SF" {
t.Fatalf("tool call was not restored for Gemini: %+v", modelTurn)
}
toolTurn, _ := contents[2].(map[string]any)
toolParts, _ := toolTurn["parts"].([]any)
responsePart, _ := toolParts[0].(map[string]any)
functionResponse, _ := responsePart["functionResponse"].(map[string]any)
response, _ := functionResponse["response"].(map[string]any)
if toolTurn["role"] != "user" || functionResponse["name"] != "get_weather" || response["temperature"] != "72F" {
t.Fatalf("tool result was not restored for Gemini: %+v", toolTurn)
}
tools, _ := captured["tools"].([]any)
declarationGroup, _ := tools[0].(map[string]any)
declarations, _ := declarationGroup["functionDeclarations"].([]any)
declaration, _ := declarations[0].(map[string]any)
if declaration["name"] != "get_weather" || declaration["description"] != "lookup weather" {
t.Fatalf("tool declaration was not converted for Gemini: %+v", captured["tools"])
}
}
func TestGeminiURLAcceptsVersionedBaseURL(t *testing.T) {
got := geminiURL("https://generativelanguage.googleapis.com/v1beta", "gemini-2.5-flash", "test-key")
want := "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=test-key"

View File

@ -70,15 +70,185 @@ func geminiBody(request Request) map[string]any {
return map[string]any{"contents": contents}
}
prompt := firstNonEmptyPrompt(request.Body, "")
if prompt == "" {
prompt = textFromMessages(request.Body)
if prompt != "" {
return map[string]any{
"contents": []any{map[string]any{
"role": "user",
"parts": []any{map[string]any{"text": prompt}},
}},
}
}
return map[string]any{
"contents": []any{map[string]any{
"role": "user",
"parts": []any{map[string]any{"text": prompt}},
}},
body := map[string]any{"contents": geminiContentsFromMessages(request.Body)}
if tools := geminiToolsFromOpenAITools(request.Body["tools"]); len(tools) > 0 {
body["tools"] = tools
}
contents, _ := body["contents"].([]any)
if len(contents) > 0 {
return body
}
return map[string]any{"contents": []any{map[string]any{
"role": "user",
"parts": []any{map[string]any{"text": textFromMessages(request.Body)}},
}}}
}
func geminiContentsFromMessages(body map[string]any) []any {
normalized := NormalizeChatCompletionRequestBody(body)
messages, _ := normalized["messages"].([]any)
contents := make([]any, 0, len(messages))
toolNames := map[string]string{}
for _, rawMessage := range messages {
message, _ := rawMessage.(map[string]any)
if len(message) == 0 {
continue
}
role := stringFromAny(message["role"])
if role == "tool" {
toolCallID := stringFromAny(message["tool_call_id"])
name := toolNames[toolCallID]
if name == "" {
name = toolCallID
}
if name == "" {
name = "tool"
}
contents = append(contents, map[string]any{
"role": "user",
"parts": []any{map[string]any{"functionResponse": map[string]any{
"name": name,
"response": geminiFunctionResponsePayload(message["content"]),
}}},
})
continue
}
parts := geminiTextParts(message["content"])
if role == "assistant" {
for _, rawToolCall := range toolCallsSlice(message["tool_calls"]) {
toolCall, _ := rawToolCall.(map[string]any)
function, _ := toolCall["function"].(map[string]any)
name := stringFromAny(function["name"])
if name == "" {
continue
}
if id := stringFromAny(toolCall["id"]); id != "" {
toolNames[id] = name
}
parts = append(parts, map[string]any{"functionCall": map[string]any{
"name": name,
"args": geminiFunctionArgs(function["arguments"]),
}})
}
}
if len(parts) == 0 {
continue
}
contents = append(contents, map[string]any{
"role": geminiRole(role),
"parts": parts,
})
}
return contents
}
func geminiRole(role string) string {
if role == "assistant" {
return "model"
}
return "user"
}
func geminiTextParts(content any) []any {
parts := make([]any, 0)
switch typed := content.(type) {
case string:
if strings.TrimSpace(typed) != "" {
parts = append(parts, map[string]any{"text": typed})
}
case []any:
for _, rawPart := range typed {
part, _ := rawPart.(map[string]any)
if text := stringFromAny(firstPresent(part["text"], part["content"])); strings.TrimSpace(text) != "" {
parts = append(parts, map[string]any{"text": text})
}
}
}
return parts
}
func toolCallsSlice(value any) []any {
switch typed := value.(type) {
case []any:
return typed
case map[string]any:
return []any{typed}
default:
return nil
}
}
func geminiFunctionArgs(value any) map[string]any {
if value == nil {
return map[string]any{}
}
if args, ok := value.(map[string]any); ok {
return args
}
if text, ok := value.(string); ok {
if strings.TrimSpace(text) == "" {
return map[string]any{}
}
var args map[string]any
if err := json.Unmarshal([]byte(text), &args); err == nil {
return args
}
return map[string]any{"arguments": text}
}
return map[string]any{"arguments": value}
}
func geminiFunctionResponsePayload(value any) map[string]any {
if payload, ok := value.(map[string]any); ok {
return payload
}
if text, ok := value.(string); ok {
var payload map[string]any
if err := json.Unmarshal([]byte(text), &payload); err == nil {
return payload
}
return map[string]any{"content": text}
}
if value == nil {
return map[string]any{}
}
return map[string]any{"content": value}
}
func geminiToolsFromOpenAITools(value any) []any {
tools, ok := value.([]any)
if !ok || len(tools) == 0 {
return nil
}
declarations := make([]any, 0, len(tools))
for _, rawTool := range tools {
tool, _ := rawTool.(map[string]any)
function, _ := tool["function"].(map[string]any)
name := stringFromAny(function["name"])
if name == "" {
continue
}
declaration := map[string]any{"name": name}
if description := stringFromAny(function["description"]); description != "" {
declaration["description"] = description
}
if parameters, ok := function["parameters"]; ok {
declaration["parameters"] = parameters
}
declarations = append(declarations, declaration)
}
if len(declarations) == 0 {
return nil
}
return []any{map[string]any{"functionDeclarations": declarations}}
}
func geminiResult(request Request, raw map[string]any) map[string]any {

View File

@ -8,6 +8,7 @@ import (
"io"
"math"
"net/http"
"sort"
"strings"
"time"
)
@ -87,8 +88,11 @@ func decodeOpenAIStreamReader(reader io.Reader, onDelta StreamDelta) (map[string
scanner.Buffer(make([]byte, 0, 64*1024), 16*1024*1024)
rawLines := make([]string, 0)
parts := make([]string, 0)
reasoningParts := make([]string, 0)
var last map[string]any
var usage Usage
finishReason := ""
toolCalls := map[int]map[string]any{}
for scanner.Scan() {
rawLine := scanner.Text()
rawLines = append(rawLines, rawLine)
@ -104,13 +108,23 @@ func decodeOpenAIStreamReader(reader io.Reader, onDelta StreamDelta) (map[string
if err := json.Unmarshal([]byte(payload), &event); err != nil {
continue
}
event = NormalizeChatCompletionStreamEvent(event)
last = event
if text := streamEventText(event); text != "" {
text := streamEventText(event)
reasoningText := streamEventReasoningContent(event)
if text != "" {
parts = append(parts, text)
if onDelta != nil {
if err := onDelta(text); err != nil {
return nil, true, err
}
}
if reasoningText != "" {
reasoningParts = append(reasoningParts, reasoningText)
}
aggregateStreamToolCalls(event, toolCalls)
if reason := streamEventFinishReason(event); reason != "" {
finishReason = reason
}
if onDelta != nil {
if err := onDelta(StreamDeltaEvent{Text: text, ReasoningContent: reasoningText, Event: event}); err != nil {
return nil, true, err
}
}
if eventUsage := usageFromOpenAI(event); eventUsage.TotalTokens > 0 {
@ -131,7 +145,7 @@ func decodeOpenAIStreamReader(reader io.Reader, onDelta StreamDelta) (map[string
}
return out, true, nil
}
return buildOpenAIStreamResult(last, parts, usage), true, nil
return buildOpenAIStreamResult(last, parts, reasoningParts, toolCalls, finishReason, usage), true, nil
}
func decodeOpenAIStream(raw []byte) (map[string]any, bool) {
@ -142,22 +156,32 @@ func decodeOpenAIStream(raw []byte) (map[string]any, bool) {
return result, ok && err == nil
}
func buildOpenAIStreamResult(last map[string]any, parts []string, usage Usage) map[string]any {
if len(parts) == 0 {
func buildOpenAIStreamResult(last map[string]any, parts []string, reasoningParts []string, toolCalls map[int]map[string]any, finishReason string, usage Usage) map[string]any {
if len(parts) == 0 && len(reasoningParts) == 0 && len(toolCalls) == 0 {
return last
}
message := map[string]any{
"role": "assistant",
"content": strings.Join(parts, ""),
}
if len(reasoningParts) > 0 {
message["reasoning_content"] = strings.Join(reasoningParts, "")
}
if len(toolCalls) > 0 {
message["tool_calls"] = sortedStreamToolCalls(toolCalls)
}
if finishReason == "" {
finishReason = "stop"
}
var out map[string]any
out = map[string]any{
"id": stringFromAny(firstPresent(last["id"], "chatcmpl-stream")),
"object": "chat.completion",
"model": stringFromAny(last["model"]),
"choices": []any{map[string]any{
"index": 0,
"message": map[string]any{
"role": "assistant",
"content": strings.Join(parts, ""),
},
"finish_reason": "stop",
"index": 0,
"message": message,
"finish_reason": finishReason,
}},
}
if usage.TotalTokens > 0 {
@ -170,6 +194,571 @@ func buildOpenAIStreamResult(last map[string]any, parts []string, usage Usage) m
return out
}
// NormalizeChatCompletionRequestBody 将后续请求里的工具调用上下文还原为
// OpenAI Chat Completions 标准格式,便于再次发送给 OpenAI-compatible 上游。
func NormalizeChatCompletionRequestBody(body map[string]any) map[string]any {
if body == nil {
return nil
}
out := cloneBody(body)
messages, ok := out["messages"].([]any)
if !ok {
return out
}
normalizedMessages := make([]any, 0, len(messages))
for _, rawMessage := range messages {
message, ok := rawMessage.(map[string]any)
if !ok {
normalizedMessages = append(normalizedMessages, rawMessage)
continue
}
copied := cloneMapAny(message)
normalizeToolCallsContainer(copied, false)
normalizeToolMessageFields(copied)
toolMessages, cleanContent, changed := toolResultMessagesFromContent(copied["content"])
if changed {
if cleanContent != nil && contentHasText(cleanContent) {
copied["content"] = cleanContent
normalizedMessages = append(normalizedMessages, copied)
} else if len(copied) > 1 || copied["role"] != nil {
delete(copied, "content")
if len(copied) > 1 {
normalizedMessages = append(normalizedMessages, copied)
}
}
normalizedMessages = append(normalizedMessages, toolMessages...)
continue
}
normalizedMessages = append(normalizedMessages, copied)
}
out["messages"] = normalizedMessages
return out
}
func cloneMapAny(source map[string]any) map[string]any {
if source == nil {
return nil
}
out := make(map[string]any, len(source))
for key, value := range source {
out[key] = value
}
return out
}
// NormalizeChatCompletionResult 将供应商自定义推理字段归一化到
// message.reasoning_content并从最终回答 content 中剥离内联推理块。
// 加密推理载荷不可展示,且不应作为正文输出,因此会被忽略。
func NormalizeChatCompletionResult(result map[string]any) map[string]any {
if result == nil {
return nil
}
choices, _ := result["choices"].([]any)
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if message, ok := choice["message"].(map[string]any); ok {
normalizeToolCallsContainer(message, false)
normalizeReasoningContainer(message, false)
}
if delta, ok := choice["delta"].(map[string]any); ok {
normalizeToolCallsContainer(delta, true)
normalizeReasoningContainer(delta, true)
}
}
return result
}
// NormalizeChatCompletionStreamEvent 将供应商自定义流式推理字段
// (例如 reasoning_details 或 reasoning归一化到 delta.reasoning_content。
func NormalizeChatCompletionStreamEvent(event map[string]any) map[string]any {
if event == nil {
return nil
}
choices, _ := event["choices"].([]any)
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if delta, ok := choice["delta"].(map[string]any); ok {
normalizeToolCallsContainer(delta, true)
normalizeReasoningContainer(delta, true)
}
if message, ok := choice["message"].(map[string]any); ok {
normalizeToolCallsContainer(message, false)
normalizeReasoningContainer(message, false)
}
}
return event
}
func normalizeToolCallsContainer(container map[string]any, stream bool) {
if container == nil {
return
}
toolCalls := make([]any, 0)
for _, rawToolCall := range rawToolCallValues(container) {
for _, normalized := range normalizeRawToolCalls(rawToolCall, len(toolCalls), stream) {
toolCalls = append(toolCalls, normalized)
}
}
if contentToolCalls, cleanContent, changed := toolCallsFromContent(container["content"], len(toolCalls), stream); changed {
toolCalls = append(toolCalls, contentToolCalls...)
setNormalizedContent(container, cleanContent, stream)
}
if partToolCalls := toolCallsFromParts(container["parts"], len(toolCalls), stream); len(partToolCalls) > 0 {
toolCalls = append(toolCalls, partToolCalls...)
delete(container, "parts")
}
if len(toolCalls) > 0 {
container["tool_calls"] = toolCalls
}
for _, key := range []string{"tool_call", "toolCall", "toolCalls", "function_call", "functionCall"} {
delete(container, key)
}
}
func normalizeToolMessageFields(message map[string]any) {
if message == nil {
return
}
if id := firstNonEmptyString(message["tool_call_id"], message["toolCallId"], message["tool_use_id"], message["toolUseId"], message["call_id"], message["callId"]); id != "" {
message["tool_call_id"] = id
}
for _, key := range []string{"toolCallId", "tool_use_id", "toolUseId", "call_id", "callId"} {
delete(message, key)
}
}
func toolResultMessagesFromContent(value any) ([]any, any, bool) {
blocks, ok := value.([]any)
if !ok {
return nil, nil, false
}
toolMessages := make([]any, 0)
remaining := make([]any, 0, len(blocks))
for _, rawBlock := range blocks {
block, _ := rawBlock.(map[string]any)
if len(block) == 0 || stringFromAny(block["type"]) != "tool_result" {
remaining = append(remaining, rawBlock)
continue
}
message := map[string]any{
"role": "tool",
"tool_call_id": firstNonEmptyString(block["tool_call_id"], block["toolCallId"], block["tool_use_id"], block["toolUseId"], block["id"]),
"content": toolResultContent(block["content"]),
}
toolMessages = append(toolMessages, message)
}
if len(toolMessages) == 0 {
return nil, nil, false
}
return toolMessages, contentBlocksText(remaining), true
}
func toolResultContent(value any) any {
if text, ok := value.(string); ok {
return text
}
return jsonStringFromAny(value)
}
func contentHasText(value any) bool {
switch typed := value.(type) {
case string:
return strings.TrimSpace(typed) != ""
case []any:
return len(typed) > 0
default:
return value != nil
}
}
func rawToolCallValues(container map[string]any) []any {
values := make([]any, 0, 6)
for _, key := range []string{"tool_calls", "tool_call", "toolCalls", "toolCall", "function_call", "functionCall"} {
if value, ok := container[key]; ok {
values = append(values, value)
}
}
return values
}
func normalizeRawToolCalls(value any, startIndex int, stream bool) []any {
switch typed := value.(type) {
case []any:
out := make([]any, 0, len(typed))
for _, raw := range typed {
if toolCall := normalizeToolCall(raw, startIndex+len(out), stream); toolCall != nil {
out = append(out, toolCall)
}
}
return out
default:
if toolCall := normalizeToolCall(value, startIndex, stream); toolCall != nil {
return []any{toolCall}
}
return nil
}
}
func normalizeToolCall(value any, index int, stream bool) map[string]any {
source, _ := value.(map[string]any)
if len(source) == 0 {
return nil
}
functionSource := mapFromAny(source["function"])
if len(functionSource) == 0 {
functionSource = mapFromAny(firstPresent(source["function_call"], source["functionCall"]))
}
name := firstNonEmptyString(
functionSource["name"], source["name"], source["function_name"], source["functionName"], source["tool_name"], source["toolName"],
)
arguments, hasArguments := toolCallArguments(functionSource)
if !hasArguments {
arguments, hasArguments = toolCallArguments(source)
}
if name == "" && !hasArguments && firstNonEmptyString(source["id"], source["call_id"], source["callId"], source["tool_call_id"], source["toolCallId"]) == "" {
return nil
}
function := map[string]any{}
if name != "" {
function["name"] = name
}
if hasArguments {
function["arguments"] = arguments
}
toolCall := map[string]any{
"type": firstNonEmptyString(source["type"], "function"),
"function": function,
}
if id := firstNonEmptyString(source["id"], source["call_id"], source["callId"], source["tool_call_id"], source["toolCallId"]); id != "" {
toolCall["id"] = id
} else if !stream {
toolCall["id"] = fmt.Sprintf("call_%d", index)
}
if stream {
if rawIndex, ok := firstPresent(source["index"], source["idx"]).(float64); ok {
toolCall["index"] = int(math.Round(rawIndex))
} else if rawIndex, ok := firstPresent(source["index"], source["idx"]).(int); ok {
toolCall["index"] = rawIndex
} else {
toolCall["index"] = index
}
}
return toolCall
}
func toolCallsFromContent(value any, startIndex int, stream bool) ([]any, any, bool) {
blocks, ok := value.([]any)
if !ok {
return nil, nil, false
}
toolCalls := make([]any, 0)
remaining := make([]any, 0, len(blocks))
containsReasoning := false
for _, rawBlock := range blocks {
block, _ := rawBlock.(map[string]any)
if len(block) == 0 {
remaining = append(remaining, rawBlock)
continue
}
switch stringFromAny(block["type"]) {
case "tool_use":
if toolCall := normalizeToolUseBlock(block, startIndex+len(toolCalls), stream); toolCall != nil {
toolCalls = append(toolCalls, toolCall)
}
case "tool_result":
remaining = append(remaining, rawBlock)
default:
if isReasoningContentBlock(block) {
containsReasoning = true
}
remaining = append(remaining, rawBlock)
}
}
if len(toolCalls) == 0 {
return nil, nil, false
}
if containsReasoning {
return toolCalls, remaining, true
}
return toolCalls, contentBlocksText(remaining), true
}
func normalizeToolUseBlock(block map[string]any, index int, stream bool) map[string]any {
toolCall := map[string]any{
"type": "function",
"function": map[string]any{
"name": stringFromAny(block["name"]),
"arguments": jsonStringFromAny(block["input"]),
},
}
if id := firstNonEmptyString(block["id"], block["tool_use_id"], block["toolUseId"]); id != "" {
toolCall["id"] = id
} else if !stream {
toolCall["id"] = fmt.Sprintf("call_%d", index)
}
if stream {
toolCall["index"] = index
}
return toolCall
}
func toolCallsFromParts(value any, startIndex int, stream bool) []any {
parts, ok := value.([]any)
if !ok {
return nil
}
out := make([]any, 0)
for _, rawPart := range parts {
part, _ := rawPart.(map[string]any)
if functionCall := mapFromAny(firstPresent(part["functionCall"], part["function_call"])); len(functionCall) > 0 {
if toolCall := normalizeGeminiFunctionCall(functionCall, startIndex+len(out), stream); toolCall != nil {
out = append(out, toolCall)
}
}
}
return out
}
func normalizeGeminiFunctionCall(functionCall map[string]any, index int, stream bool) map[string]any {
toolCall := map[string]any{
"type": "function",
"function": map[string]any{
"name": stringFromAny(functionCall["name"]),
"arguments": jsonStringFromAny(firstPresent(functionCall["args"], functionCall["arguments"])),
},
}
if id := firstNonEmptyString(functionCall["id"], functionCall["call_id"], functionCall["callId"]); id != "" {
toolCall["id"] = id
} else if !stream {
toolCall["id"] = fmt.Sprintf("call_%d", index)
}
if stream {
toolCall["index"] = index
}
return toolCall
}
func setNormalizedContent(container map[string]any, value any, stream bool) {
if text, ok := value.(string); ok && text == "" {
if stream {
delete(container, "content")
return
}
container["content"] = nil
return
}
container["content"] = value
}
func isReasoningContentBlock(block map[string]any) bool {
switch stringFromAny(block["type"]) {
case "thinking", "redacted_thinking", "reasoning.text", "reasoning.summary", "reasoning.encrypted":
return true
default:
return false
}
}
func contentBlocksText(blocks []any) string {
parts := make([]string, 0, len(blocks))
for _, rawBlock := range blocks {
switch block := rawBlock.(type) {
case string:
parts = append(parts, block)
case map[string]any:
if text := stringFromAny(firstPresent(block["text"], block["content"])); text != "" {
parts = append(parts, text)
}
}
}
return strings.Join(parts, "")
}
func toolCallArguments(source map[string]any) (string, bool) {
for _, key := range []string{"arguments", "args", "input", "parameters"} {
if value, ok := source[key]; ok {
return jsonStringFromAny(value), true
}
}
return "", false
}
func jsonStringFromAny(value any) string {
if value == nil {
return ""
}
if text, ok := value.(string); ok {
return text
}
encoded, err := json.Marshal(value)
if err != nil {
return ""
}
return string(encoded)
}
func normalizeReasoningContainer(container map[string]any, deleteEmptyContent bool) {
if container == nil {
return
}
reasoningParts := make([]string, 0, 3)
if reasoning := reasoningDetailsText(container["reasoning_details"]); reasoning != "" {
reasoningParts = append(reasoningParts, reasoning)
} else if reasoning := stringFromAny(container["reasoning_content"]); reasoning != "" {
reasoningParts = append(reasoningParts, reasoning)
} else if reasoning := stringFromAny(container["reasoning"]); reasoning != "" {
reasoningParts = append(reasoningParts, reasoning)
}
if content, ok := container["content"]; ok {
cleanContent, contentReasoning, changed := normalizeReasoningContentValue(content)
if changed {
if deleteEmptyContent {
if text, ok := cleanContent.(string); ok && text == "" {
delete(container, "content")
} else {
container["content"] = cleanContent
}
} else {
container["content"] = cleanContent
}
}
if contentReasoning != "" {
reasoningParts = append(reasoningParts, contentReasoning)
}
}
if len(reasoningParts) > 0 {
container["reasoning_content"] = strings.Join(reasoningParts, "")
}
delete(container, "reasoning_details")
delete(container, "reasoning")
}
func reasoningDetailsText(value any) string {
rawItems, ok := value.([]any)
if !ok {
return ""
}
parts := make([]string, 0, len(rawItems))
for _, rawItem := range rawItems {
item, _ := rawItem.(map[string]any)
switch stringFromAny(item["type"]) {
case "reasoning.text":
if text := stringFromAny(item["text"]); text != "" {
parts = append(parts, text)
}
case "reasoning.summary":
if summary := stringFromAny(item["summary"]); summary != "" {
parts = append(parts, summary)
}
}
}
return strings.Join(parts, "")
}
func normalizeReasoningContentValue(value any) (any, string, bool) {
switch typed := value.(type) {
case string:
cleanContent, reasoning, changed := splitTaggedReasoningText(typed)
return cleanContent, reasoning, changed
case []any:
contentParts := make([]string, 0, len(typed))
reasoningParts := make([]string, 0)
changed := false
for _, rawItem := range typed {
switch item := rawItem.(type) {
case string:
contentParts = append(contentParts, item)
case map[string]any:
switch stringFromAny(item["type"]) {
case "thinking":
if thinking := stringFromAny(item["thinking"]); thinking != "" {
reasoningParts = append(reasoningParts, thinking)
}
changed = true
case "redacted_thinking", "reasoning.encrypted":
changed = true
case "reasoning.text":
if text := stringFromAny(item["text"]); text != "" {
reasoningParts = append(reasoningParts, text)
}
changed = true
case "reasoning.summary":
if summary := stringFromAny(item["summary"]); summary != "" {
reasoningParts = append(reasoningParts, summary)
}
changed = true
case "text", "output_text":
if text := stringFromAny(firstPresent(item["text"], item["content"])); text != "" {
cleanText, reasoning, tagged := splitTaggedReasoningText(text)
contentParts = append(contentParts, cleanText)
if reasoning != "" {
reasoningParts = append(reasoningParts, reasoning)
}
changed = changed || tagged
}
default:
if text := stringFromAny(firstPresent(item["text"], item["content"])); text != "" {
contentParts = append(contentParts, text)
}
}
}
}
if !changed {
return value, "", false
}
return strings.Join(contentParts, ""), strings.Join(reasoningParts, ""), true
default:
return value, "", false
}
}
func splitTaggedReasoningText(text string) (string, string, bool) {
lower := strings.ToLower(text)
clean := strings.Builder{}
reasoning := strings.Builder{}
changed := false
for offset := 0; offset < len(text); {
start, tag := nextReasoningOpenTag(lower, offset)
if start < 0 {
clean.WriteString(text[offset:])
break
}
clean.WriteString(text[offset:start])
openEnd := start + len("<"+tag+">")
closeToken := "</" + tag + ">"
closeStart := strings.Index(lower[openEnd:], closeToken)
if closeStart < 0 {
reasoning.WriteString(text[openEnd:])
offset = len(text)
changed = true
break
}
closeStart += openEnd
reasoning.WriteString(text[openEnd:closeStart])
offset = closeStart + len(closeToken)
changed = true
}
return clean.String(), reasoning.String(), changed
}
func nextReasoningOpenTag(lower string, offset int) (int, string) {
bestStart := -1
bestTag := ""
for _, tag := range []string{"think", "reasoning", "analysis"} {
needle := "<" + tag + ">"
idx := strings.Index(lower[offset:], needle)
if idx < 0 {
continue
}
absolute := offset + idx
if bestStart < 0 || absolute < bestStart {
bestStart = absolute
bestTag = tag
}
}
return bestStart, bestTag
}
func streamEventText(event map[string]any) string {
if choices, ok := event["choices"].([]any); ok {
for _, rawChoice := range choices {
@ -195,6 +784,91 @@ func streamEventText(event map[string]any) string {
return ""
}
func streamEventReasoningContent(event map[string]any) string {
if choices, ok := event["choices"].([]any); ok {
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if delta, ok := choice["delta"].(map[string]any); ok {
if content, ok := delta["reasoning_content"].(string); ok {
return content
}
if content, ok := delta["reasoning"].(string); ok {
return content
}
}
if message, ok := choice["message"].(map[string]any); ok {
if content, ok := message["reasoning_content"].(string); ok {
return content
}
}
}
}
return ""
}
func streamEventFinishReason(event map[string]any) string {
if choices, ok := event["choices"].([]any); ok {
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if reason, ok := choice["finish_reason"].(string); ok && reason != "" {
return reason
}
}
}
return ""
}
func aggregateStreamToolCalls(event map[string]any, toolCalls map[int]map[string]any) {
choices, _ := event["choices"].([]any)
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
delta, _ := choice["delta"].(map[string]any)
rawToolCalls, _ := delta["tool_calls"].([]any)
for _, rawToolCall := range rawToolCalls {
incoming, _ := rawToolCall.(map[string]any)
index := intFromAny(incoming["index"])
current := toolCalls[index]
if current == nil {
current = map[string]any{}
toolCalls[index] = current
}
for _, key := range []string{"id", "type"} {
if value, ok := incoming[key].(string); ok && value != "" {
current[key] = value
}
}
incomingFn, _ := incoming["function"].(map[string]any)
if len(incomingFn) == 0 {
continue
}
currentFn, _ := current["function"].(map[string]any)
if currentFn == nil {
currentFn = map[string]any{}
current["function"] = currentFn
}
if name, ok := incomingFn["name"].(string); ok && name != "" {
currentFn["name"] = stringFromAny(currentFn["name"]) + name
}
if arguments, ok := incomingFn["arguments"].(string); ok && arguments != "" {
currentFn["arguments"] = stringFromAny(currentFn["arguments"]) + arguments
}
}
}
}
func sortedStreamToolCalls(toolCalls map[int]map[string]any) []any {
indices := make([]int, 0, len(toolCalls))
for index := range toolCalls {
indices = append(indices, index)
}
sort.Ints(indices)
out := make([]any, 0, len(indices))
for _, index := range indices {
out = append(out, toolCalls[index])
}
return out
}
func usageFromOpenAI(result map[string]any) Usage {
usage, _ := result["usage"].(map[string]any)
input := intFromAny(firstPresent(usage["prompt_tokens"], usage["input_tokens"]))
@ -254,6 +928,15 @@ func stringFromAny(value any) string {
return ""
}
func firstNonEmptyString(values ...any) string {
for _, value := range values {
if text := strings.TrimSpace(stringFromAny(value)); text != "" {
return text
}
}
return ""
}
func firstPresent(values ...any) any {
for _, value := range values {
if value != nil {

View File

@ -23,6 +23,9 @@ func (c OpenAIClient) Run(ctx context.Context, request Request) (Response, error
return Response{}, &ClientError{Code: "unsupported_kind", Message: "unsupported openai request kind", Retryable: false}
}
body := cloneBody(request.Body)
if request.Kind == "chat.completions" {
body = NormalizeChatCompletionRequestBody(body)
}
body["model"] = upstreamModelName(request.Candidate)
stream := request.Stream || boolValue(body, "stream")
ensureOpenAIStreamUsage(body, request.Kind, stream)
@ -40,6 +43,9 @@ func (c OpenAIClient) Run(ctx context.Context, request Request) (Response, error
}
requestID := requestIDFromHTTPResponse(resp)
result, err := decodeOpenAIResponse(resp, stream, request.StreamDelta)
if err == nil && request.Kind == "chat.completions" {
result = NormalizeChatCompletionResult(result)
}
responseFinishedAt := time.Now()
if err != nil {
return Response{}, annotateResponseError(err, requestID, responseStartedAt, responseFinishedAt)

View File

@ -48,7 +48,13 @@ type Progress struct {
Payload map[string]any
}
type StreamDelta func(text string) error
type StreamDeltaEvent struct {
Text string
ReasoningContent string
Event map[string]any
}
type StreamDelta func(event StreamDeltaEvent) error
type Client interface {
Run(ctx context.Context, request Request) (Response, error)

View File

@ -50,7 +50,7 @@ func TestWriteCompatibleTaskResponseReturnsJSONWhenStreamIsFalse(t *testing.T) {
req := httptest.NewRequest(http.MethodPost, "/api/v1/chat/completions", nil)
recorder := httptest.NewRecorder()
writeCompatibleTaskResponse(context.Background(), recorder, req, executor, "chat.completions", "gpt-test", store.GatewayTask{ID: "task-test"}, &auth.User{}, false)
writeCompatibleTaskResponse(context.Background(), recorder, req, executor, "chat.completions", "gpt-test", store.GatewayTask{ID: "task-test"}, &auth.User{}, false, false)
if recorder.Code != http.StatusOK {
t.Fatalf("status=%d want=%d body=%s", recorder.Code, http.StatusOK, recorder.Body.String())
@ -69,13 +69,13 @@ func TestWriteCompatibleTaskResponseReturnsJSONWhenStreamIsFalse(t *testing.T) {
func TestWriteCompatibleTaskResponseReturnsSSEWhenStreamIsTrue(t *testing.T) {
executor := &fakeTaskExecutor{
deltas: []string{"hel", "lo"},
output: map[string]any{"id": "chatcmpl-test", "object": "chat.completion"},
deltas: []clients.StreamDeltaEvent{{Text: "hel"}, {Text: "lo"}},
output: map[string]any{"id": "chatcmpl-test", "object": "chat.completion", "usage": map[string]any{"prompt_tokens": 1, "completion_tokens": 2, "total_tokens": 3}},
}
req := httptest.NewRequest(http.MethodPost, "/api/v1/chat/completions", nil)
recorder := httptest.NewRecorder()
writeCompatibleTaskResponse(context.Background(), recorder, req, executor, "chat.completions", "gpt-test", store.GatewayTask{ID: "task-test"}, &auth.User{}, true)
writeCompatibleTaskResponse(context.Background(), recorder, req, executor, "chat.completions", "gpt-test", store.GatewayTask{ID: "task-test"}, &auth.User{}, true, true)
if executor.executeCalls != 0 || executor.streamCalls != 1 {
t.Fatalf("expected stream execute only, got execute=%d stream=%d", executor.executeCalls, executor.streamCalls)
@ -84,17 +84,53 @@ func TestWriteCompatibleTaskResponseReturnsSSEWhenStreamIsTrue(t *testing.T) {
t.Fatalf("Content-Type=%q want text/event-stream", contentType)
}
body := recorder.Body.String()
for _, want := range []string{"event: message", `"content":"hel"`, `"content":"lo"`, `"finish_reason":"stop"`} {
for _, want := range []string{`data: {`, `"role":"assistant"`, `"created":`, `"system_fingerprint":`, `"content":"hel"`, `"content":"lo"`, `"finish_reason":"stop"`, `"usage":{"completion_tokens":2,"prompt_tokens":1,"total_tokens":3}`, "data: [DONE]"} {
if !strings.Contains(body, want) {
t.Fatalf("SSE body missing %s: %s", want, body)
}
}
if strings.Contains(body, "event: message") {
t.Fatalf("chat completions stream should use OpenAI data-only SSE frames: %s", body)
}
}
func TestWriteCompatibleTaskResponseStreamsStructuredToolAndReasoningDeltas(t *testing.T) {
executor := &fakeTaskExecutor{
deltas: []clients.StreamDeltaEvent{
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "system_fingerprint": "fp-test", "choices": []any{map[string]any{"index": float64(0), "delta": map[string]any{"reasoning_details": []any{map[string]any{"type": "reasoning.text", "text": "detail-"}, map[string]any{"type": "reasoning.summary", "summary": "summary"}, map[string]any{"type": "reasoning.encrypted", "data": "secret"}}}, "finish_reason": nil}}}},
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "system_fingerprint": "fp-test", "choices": []any{map[string]any{"index": float64(0), "delta": map[string]any{"content": "<think>tagged</think>answer"}, "finish_reason": nil}}}},
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "system_fingerprint": "fp-test", "choices": []any{map[string]any{"index": float64(0), "delta": map[string]any{"functionCall": map[string]any{"name": "legacy_lookup", "arguments": "{\"city\":\"Boston\"}"}}, "finish_reason": nil}}}},
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "system_fingerprint": "fp-test", "choices": []any{map[string]any{"index": float64(0), "delta": map[string]any{"tool_calls": []any{map[string]any{"index": float64(0), "id": "call_1", "type": "function", "function": map[string]any{"name": "lookup", "arguments": "{\"q\":"}}}}, "finish_reason": nil}}}},
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "system_fingerprint": "fp-test", "choices": []any{map[string]any{"index": float64(0), "delta": map[string]any{"tool_calls": []any{map[string]any{"index": float64(0), "function": map[string]any{"arguments": "\"weather\"}"}}}}, "finish_reason": "tool_calls"}}}},
{Event: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion.chunk", "created": float64(1710000000), "model": "deepseek-v4", "choices": []any{}, "usage": map[string]any{"prompt_tokens": float64(4), "completion_tokens": float64(5), "total_tokens": float64(9)}}},
},
output: map[string]any{"id": "chatcmpl-upstream", "object": "chat.completion", "model": "deepseek-v4"},
}
req := httptest.NewRequest(http.MethodPost, "/api/v1/chat/completions", nil)
recorder := httptest.NewRecorder()
writeCompatibleTaskResponse(context.Background(), recorder, req, executor, "chat.completions", "gpt-test", store.GatewayTask{ID: "task-test"}, &auth.User{}, true, true)
body := recorder.Body.String()
roleIndex := strings.Index(body, `"role":"assistant"`)
reasoningIndex := strings.Index(body, `"reasoning_content":"detail-summary"`)
if roleIndex < 0 || reasoningIndex < 0 || roleIndex > reasoningIndex {
t.Fatalf("assistant role should be emitted before structured deltas: %s", body)
}
for _, want := range []string{`"system_fingerprint":"fp-test"`, `"created":1710000000`, `"reasoning_content":"tagged"`, `"content":"answer"`, `"tool_calls":[{"function":{"arguments":"{\"city\":\"Boston\"}","name":"legacy_lookup"}`, `"tool_calls":[{"function":{"arguments":"{\"q\":"`, `"finish_reason":"tool_calls"`, `"choices":[],"created":1710000000`, `"usage":{"completion_tokens":5,"prompt_tokens":4,"total_tokens":9}`, "data: [DONE]"} {
if !strings.Contains(body, want) {
t.Fatalf("SSE body missing %s: %s", want, body)
}
}
if strings.Contains(body, "reasoning_details") || strings.Contains(body, "<think>") || strings.Contains(body, "functionCall") {
t.Fatalf("provider-specific reasoning/tool fields should be converted away: %s", body)
}
}
type fakeTaskExecutor struct {
executeCalls int
streamCalls int
deltas []string
deltas []clients.StreamDeltaEvent
output map[string]any
}

View File

@ -934,7 +934,7 @@ func (s *Server) createTask(kind string, compatible bool) http.Handler {
runCtx, cancelRun := s.requestExecutionContext(r)
defer cancelRun()
if responsePlan.compatibleMode {
writeCompatibleTaskResponse(runCtx, w, r, s.runner, kind, model, task, user, responsePlan.streamMode)
writeCompatibleTaskResponse(runCtx, w, r, s.runner, kind, model, task, user, responsePlan.streamMode, streamIncludeUsage(body))
return
}
result, runErr := s.runner.Execute(runCtx, task, user)
@ -1002,14 +1002,15 @@ type taskExecutor interface {
ExecuteStream(context.Context, store.GatewayTask, *auth.User, clients.StreamDelta) (runner.Result, error)
}
func writeCompatibleTaskResponse(runCtx context.Context, w http.ResponseWriter, r *http.Request, executor taskExecutor, kind string, model string, task store.GatewayTask, user *auth.User, streamMode bool) {
func writeCompatibleTaskResponse(runCtx context.Context, w http.ResponseWriter, r *http.Request, executor taskExecutor, kind string, model string, task store.GatewayTask, user *auth.User, streamMode bool, includeUsage bool) {
if streamMode {
flusher := prepareCompatibleStream(w)
result, runErr := executor.ExecuteStream(runCtx, task, user, func(delta string) error {
streamWriter := newCompatibleStreamWriter(kind, model, includeUsage)
result, runErr := executor.ExecuteStream(runCtx, task, user, func(delta clients.StreamDeltaEvent) error {
if !requestStillConnected(r) {
return nil
}
writeCompatibleDelta(w, kind, model, delta)
streamWriter.writeDelta(w, delta)
if flusher != nil {
flusher.Flush()
}
@ -1043,7 +1044,7 @@ func writeCompatibleTaskResponse(runCtx context.Context, w http.ResponseWriter,
if !requestStillConnected(r) {
return
}
writeCompatibleDone(w, kind, model, result.Output)
streamWriter.writeDone(w, result.Output)
if flusher != nil {
flusher.Flush()
}
@ -1064,6 +1065,12 @@ func writeCompatibleTaskResponse(runCtx context.Context, w http.ResponseWriter,
writeJSON(w, http.StatusOK, result.Output)
}
func streamIncludeUsage(body map[string]any) bool {
streamOptions, _ := body["stream_options"].(map[string]any)
includeUsage, _ := streamOptions["include_usage"].(bool)
return includeUsage
}
func asyncRequest(r *http.Request) bool {
value := strings.TrimSpace(strings.ToLower(r.Header.Get("x-async")))
return value == "1" || value == "true" || value == "yes" || value == "on"

View File

@ -172,16 +172,18 @@ type PricingEstimateResponse struct {
}
type TaskRequest struct {
Model string `json:"model" example:"gpt-4o-mini"`
Messages []ChatMessage `json:"messages,omitempty"`
Input string `json:"input,omitempty" example:"Tell me a short story"`
Prompt string `json:"prompt,omitempty" example:"A watercolor robot reading a book"`
Stream bool `json:"stream,omitempty" example:"false"`
RunMode string `json:"runMode,omitempty" example:"simulation"`
MaxTokens int `json:"max_tokens,omitempty" example:"512"`
Size string `json:"size,omitempty" example:"1024x1024"`
Duration int `json:"duration,omitempty" example:"5"`
Resolution string `json:"resolution,omitempty" example:"720p"`
Model string `json:"model" example:"gpt-4o-mini"`
Messages []ChatMessage `json:"messages,omitempty"`
Input string `json:"input,omitempty" example:"Tell me a short story"`
Prompt string `json:"prompt,omitempty" example:"A watercolor robot reading a book"`
Stream bool `json:"stream,omitempty" example:"false"`
RunMode string `json:"runMode,omitempty" example:"simulation"`
MaxTokens int `json:"max_tokens,omitempty" example:"512"`
// ReasoningEffort 推理深度OpenAI-compatible 请求字段;开放字符串,取值随 provider 和模型能力而定,常见值为 none、minimal、low、medium、high、xhigh也可配置 max 等供应商自定义值。
ReasoningEffort string `json:"reasoning_effort,omitempty" example:"medium"`
Size string `json:"size,omitempty" example:"1024x1024"`
Duration int `json:"duration,omitempty" example:"5"`
Resolution string `json:"resolution,omitempty" example:"720p"`
}
type ChatCompletionRequest struct {
@ -189,8 +191,10 @@ type ChatCompletionRequest struct {
Messages []ChatMessage `json:"messages"`
Temperature float64 `json:"temperature,omitempty" example:"0.7"`
MaxTokens int `json:"max_tokens,omitempty" example:"512"`
Stream bool `json:"stream,omitempty" example:"false"`
RunMode string `json:"runMode,omitempty" example:"simulation"`
// ReasoningEffort 推理深度OpenAI-compatible 请求字段;开放字符串,取值随 provider 和模型能力而定,常见值为 none、minimal、low、medium、high、xhigh也可配置 max 等供应商自定义值。
ReasoningEffort string `json:"reasoning_effort,omitempty" example:"medium"`
Stream bool `json:"stream,omitempty" example:"false"`
RunMode string `json:"runMode,omitempty" example:"simulation"`
}
type ChatMessage struct {

View File

@ -1,6 +1,13 @@
package httpapi
import "net/http"
import (
"encoding/json"
"fmt"
"net/http"
"time"
"github.com/easyai/easyai-ai-gateway/apps/api/internal/clients"
)
func prepareCompatibleStream(w http.ResponseWriter) http.Flusher {
w.Header().Set("Content-Type", "text/event-stream")
@ -10,55 +17,180 @@ func prepareCompatibleStream(w http.ResponseWriter) http.Flusher {
return flusher
}
func writeCompatibleDelta(w http.ResponseWriter, kind string, model string, content string) {
if kind == "responses" {
sendSSE(w, "response.output_text.delta", map[string]any{"type": "response.output_text.delta", "delta": content})
return
}
sendSSE(w, "message", map[string]any{
"id": "chatcmpl-stream",
"object": "chat.completion.chunk",
"model": model,
"choices": []any{map[string]any{"index": 0, "delta": map[string]any{"content": content}, "finish_reason": nil}},
})
type compatibleStreamWriter struct {
kind string
model string
includeUsage bool
id string
created int64
systemFingerprint any
sentRole bool
sentFinish bool
sentUsage bool
}
func writeCompatibleDone(w http.ResponseWriter, kind string, model string, output map[string]any) {
if kind == "responses" {
func newCompatibleStreamWriter(kind string, model string, includeUsage bool) *compatibleStreamWriter {
return &compatibleStreamWriter{
kind: kind,
model: model,
includeUsage: includeUsage,
id: "chatcmpl-stream",
created: time.Now().Unix(),
}
}
func (s *compatibleStreamWriter) writeDelta(w http.ResponseWriter, event clients.StreamDeltaEvent) {
if s.kind == "responses" {
if event.Text != "" {
sendSSE(w, "response.output_text.delta", map[string]any{"type": "response.output_text.delta", "delta": event.Text})
}
return
}
if event.Event != nil && isChatCompletionChunk(event.Event) {
s.writeChatChunk(w, event.Event)
return
}
if event.Text == "" && event.ReasoningContent == "" {
return
}
s.ensureRoleChunk(w)
if event.ReasoningContent != "" {
s.writeChatData(w, s.chatChunk([]any{map[string]any{"index": 0, "delta": map[string]any{"reasoning_content": event.ReasoningContent}, "finish_reason": nil}}, nil))
}
if event.Text != "" {
s.writeChatData(w, s.chatChunk([]any{map[string]any{"index": 0, "delta": map[string]any{"content": event.Text}, "finish_reason": nil}}, nil))
}
}
func (s *compatibleStreamWriter) writeDone(w http.ResponseWriter, output map[string]any) {
if s.kind == "responses" {
sendSSE(w, "response.completed", map[string]any{"type": "response.completed", "response": output})
return
}
sendSSE(w, "message", map[string]any{
"id": firstString(output["id"], "chatcmpl-stream"),
"object": "chat.completion.chunk",
"model": model,
"choices": []any{map[string]any{"index": 0, "delta": map[string]any{}, "finish_reason": "stop"}},
})
s.captureOutputMetadata(output)
if !s.sentRole {
s.ensureRoleChunk(w)
}
if !s.sentFinish {
s.writeChatData(w, s.chatChunk([]any{map[string]any{"index": 0, "delta": map[string]any{}, "finish_reason": finishReasonFromOutput(output)}}, nil))
s.sentFinish = true
}
if s.includeUsage && !s.sentUsage {
if usage, ok := output["usage"].(map[string]any); ok && len(usage) > 0 {
s.writeChatData(w, s.chatChunk([]any{}, usage))
s.sentUsage = true
}
}
s.writeDoneMarker(w)
}
func (s *compatibleStreamWriter) writeChatChunk(w http.ResponseWriter, chunk map[string]any) {
chunk = clients.NormalizeChatCompletionStreamEvent(chunk)
s.captureChunkMetadata(chunk)
choices, _ := chunk["choices"].([]any)
usage, hasUsage := chunk["usage"].(map[string]any)
if len(choices) == 0 && hasUsage {
if !s.includeUsage {
return
}
s.writeChatData(w, s.chatChunk([]any{}, usage))
s.sentUsage = true
return
}
if len(choices) > 0 && !chunkHasRole(choices) && !s.sentRole {
s.ensureRoleChunk(w)
}
if chunkHasRole(choices) {
s.sentRole = true
}
if chunkHasFinishReason(choices) {
s.sentFinish = true
}
normalized := cloneMap(chunk)
normalized["id"] = s.id
normalized["object"] = "chat.completion.chunk"
normalized["created"] = s.created
normalized["model"] = firstString(normalized["model"], s.model)
normalized["system_fingerprint"] = s.systemFingerprint
s.writeChatData(w, normalized)
}
func (s *compatibleStreamWriter) ensureRoleChunk(w http.ResponseWriter) {
if s.sentRole {
return
}
s.writeChatData(w, s.chatChunk([]any{map[string]any{"index": 0, "delta": map[string]any{"role": "assistant"}, "finish_reason": nil}}, nil))
s.sentRole = true
}
func (s *compatibleStreamWriter) chatChunk(choices []any, usage map[string]any) map[string]any {
chunk := map[string]any{
"id": s.id,
"object": "chat.completion.chunk",
"created": s.created,
"model": s.model,
"system_fingerprint": s.systemFingerprint,
"choices": choices,
}
if usage != nil {
chunk["usage"] = usage
} else {
chunk["usage"] = nil
}
return chunk
}
func (s *compatibleStreamWriter) writeChatData(w http.ResponseWriter, payload map[string]any) {
bytes, _ := json.Marshal(payload)
_, _ = fmt.Fprintf(w, "data: %s\n\n", bytes)
}
func (s *compatibleStreamWriter) writeDoneMarker(w http.ResponseWriter) {
_, _ = fmt.Fprint(w, "data: [DONE]\n\n")
}
func (s *compatibleStreamWriter) captureChunkMetadata(chunk map[string]any) {
if id := firstString(chunk["id"], ""); id != "" {
s.id = id
}
if model := firstString(chunk["model"], ""); model != "" {
s.model = model
}
if created := int64FromAny(chunk["created"]); created > 0 {
s.created = created
}
if value, ok := chunk["system_fingerprint"]; ok {
s.systemFingerprint = value
}
}
func (s *compatibleStreamWriter) captureOutputMetadata(output map[string]any) {
if id := firstString(output["id"], ""); id != "" {
s.id = id
}
if model := firstString(output["model"], ""); model != "" {
s.model = model
}
if created := int64FromAny(output["created"]); created > 0 {
s.created = created
}
if value, ok := output["system_fingerprint"]; ok {
s.systemFingerprint = value
}
}
func writeCompatibleStream(w http.ResponseWriter, kind string, model string, output map[string]any) {
prepareCompatibleStream(w)
writer := newCompatibleStreamWriter(kind, model, true)
content := extractOutputText(output)
if content == "" {
content = "done"
}
if kind == "responses" {
sendSSE(w, "response.output_text.delta", map[string]any{"type": "response.output_text.delta", "delta": content})
sendSSE(w, "response.completed", map[string]any{"type": "response.completed", "response": output})
return
}
sendSSE(w, "message", map[string]any{
"id": output["id"],
"object": "chat.completion.chunk",
"model": model,
"choices": []any{map[string]any{"index": 0, "delta": map[string]any{"content": content}, "finish_reason": nil}},
})
sendSSE(w, "message", map[string]any{
"id": output["id"],
"object": "chat.completion.chunk",
"model": model,
"choices": []any{map[string]any{"index": 0, "delta": map[string]any{}, "finish_reason": "stop"}},
})
writer.writeDelta(w, clients.StreamDeltaEvent{Text: content})
writer.writeDone(w, output)
}
func firstString(value any, fallback string) string {
@ -68,6 +200,68 @@ func firstString(value any, fallback string) string {
return fallback
}
func int64FromAny(value any) int64 {
switch typed := value.(type) {
case int64:
return typed
case int:
return int64(typed)
case float64:
return int64(typed)
default:
return 0
}
}
func isChatCompletionChunk(event map[string]any) bool {
object, _ := event["object"].(string)
if object == "chat.completion.chunk" {
return true
}
_, hasChoices := event["choices"].([]any)
return hasChoices
}
func chunkHasRole(choices []any) bool {
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
delta, _ := choice["delta"].(map[string]any)
if role, ok := delta["role"].(string); ok && role != "" {
return true
}
}
return false
}
func chunkHasFinishReason(choices []any) bool {
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if reason, ok := choice["finish_reason"].(string); ok && reason != "" {
return true
}
}
return false
}
func finishReasonFromOutput(output map[string]any) string {
choices, _ := output["choices"].([]any)
for _, rawChoice := range choices {
choice, _ := rawChoice.(map[string]any)
if reason, ok := choice["finish_reason"].(string); ok && reason != "" {
return reason
}
}
return "stop"
}
func cloneMap(value map[string]any) map[string]any {
out := map[string]any{}
for key, item := range value {
out[key] = item
}
return out
}
func extractOutputText(output map[string]any) string {
if text, ok := output["output_text"].(string); ok {
return text

View File

@ -40,14 +40,14 @@ type ValueOption = { label: string; value: string };
const textFields: FieldDefinition[] = [
{ key: 'supportTool', label: '工具调用', hint: 'function calling / tools', type: 'boolean' },
{ key: 'supportStructuredOutput', label: '结构化输出', hint: 'JSON Schema 等输出', type: 'boolean' },
{ key: 'supportThinking', label: '思考能力', hint: '支持 thinking 参数', type: 'boolean' },
{ key: 'supportThinking', label: '推理能力', hint: '支持 reasoning / thinking 参数', type: 'boolean' },
{ key: 'supportThinkingModeSwitch', label: '思考开关', hint: '可按请求切换', type: 'boolean' },
{ key: 'supportWebSearch', label: '联网搜索', type: 'boolean' },
{ key: 'max_context_tokens', label: '上下文 Token', placeholder: '128000', type: 'number' },
{ key: 'max_input_tokens', label: '最大输入 Token', placeholder: '64000', type: 'number' },
{ key: 'max_output_tokens', label: '最大输出 Token', placeholder: '8192', type: 'number' },
{ key: 'max_thinking_tokens', label: '最大思考 Token', placeholder: '32768', type: 'number' },
{ key: 'thinkingEffortLevels', label: '思考强度', placeholder: 'minimal, low, medium, high', type: 'list' },
{ key: 'thinkingEffortLevels', label: '推理深度', hint: '声明模型支持的 reasoning_effort 取值,可填写 max 等供应商自定义值', placeholder: 'none, minimal, low, medium, high, xhigh, max', type: 'list' },
];
const embeddingFields: FieldDefinition[] = [
@ -535,7 +535,7 @@ const imageAspectRatioOptions = [
'7:4',
'4:7',
];
const thinkingEffortOptions = ['minimal', 'low', 'medium', 'high'];
const thinkingEffortOptions = ['none', 'minimal', 'low', 'medium', 'high', 'xhigh', 'max'];
const omniVideoModeOptions = ['text_to_video', 'image_reference', 'element_reference', 'first_last_frame', 'video_reference', 'video_edit', 'multi_shot'];
const durationOptionValues = ['1', '2', '3', '4', '5', '6', '8', '10', '15', '20', '25', '30'];
const exclusiveCapabilityFields: Record<string, string> = {

View File

@ -1505,6 +1505,22 @@ type ModelClient interface {
- progress event snapshot确保前端进度面板兼容。
- billing snapshot确保预估扣费和最终 billings 语义一致。
OpenAI-compatible 文本请求中的推理深度统一使用 `reasoning_effort` 表达。该字段是请求参数,不是响应中的推理内容;模型能力中用 `thinkingEffortLevels` 声明该模型支持的可选取值。`reasoning_effort` 必须按开放字符串处理,不在网关层写死枚举;实际可用集合必须以 provider 和模型能力为准。常见取值定义如下:
| 值 | 含义 |
| --- | --- |
| `none` | 不启用额外推理,适用于不需要思考链路的低延迟请求。 |
| `minimal` | 最小推理预算,优先降低延迟和成本。 |
| `low` | 较低推理预算,用于简单推理任务。 |
| `medium` | 默认/均衡推理深度,在质量、延迟和成本之间折中。 |
| `high` | 较高推理预算,用于复杂规划、代码和多步推理。 |
| `xhigh` | 最高推理预算,仅在模型和 provider 明确支持时使用,通常成本和延迟最高。 |
| `max` | 供应商自定义最高档示例,例如 DeepSeek V4 类模型可能使用该值;语义以 provider 文档为准。 |
除上表外,`thinkingEffortLevels` 可以保存任意供应商自定义值,例如 `max`、`ultra` 或后续模型新增档位。管理端只提供常见值作为快捷选项,不应阻止自定义输入;请求透传时按模型能力校验或直接交由上游 provider 返回错误。
`reasoning_content`、推理过程 delta 或思考摘要在 Chat Completions 中不是 OpenAI 标准必需字段;如需兼容 DeepSeek、Qwen 等供应商扩展,应在 adapter 层作为可选扩展透传,并避免把 hidden reasoning 默认暴露给普通兼容客户端。
## 11. 队列持久化、恢复与限流执行
### 11.1 持久化队列原则