feat(openai): add /v1/messages endpoint and API compatibility layer

Add Anthropic Messages API support for OpenAI platform groups, enabling
clients using Claude-style /v1/messages format to access OpenAI accounts
through automatic protocol conversion.

- Add apicompat package with type definitions and bidirectional converters
  (Anthropic ↔ Chat, Chat ↔ Responses, Anthropic ↔ Responses)
- Implement /v1/messages endpoint for OpenAI gateway with streaming support
- Add model mapping UI for OpenAI OAuth accounts (whitelist + mapping modes)
- Support prompt caching fields and codex OAuth transforms
- Fix tool call ID conversion for Responses API (fc_ prefix)
- Ensure function_call_output has non-empty output field

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
alfadb
2026-03-06 14:29:22 +08:00
parent cac230206d
commit ff1f114989
11 changed files with 2818 additions and 5 deletions

View File

@@ -424,6 +424,262 @@ func (h *OpenAIGatewayHandler) logOpenAIRemoteCompactOutcome(c *gin.Context, sta
log.Warn("codex.remote_compact.failed") log.Warn("codex.remote_compact.failed")
} }
// Messages handles Anthropic Messages API requests routed to OpenAI platform.
// POST /v1/messages (when group platform is OpenAI)
func (h *OpenAIGatewayHandler) Messages(c *gin.Context) {
streamStarted := false
defer h.recoverResponsesPanic(c, &streamStarted)
requestStart := time.Now()
apiKey, ok := middleware2.GetAPIKeyFromContext(c)
if !ok {
h.anthropicErrorResponse(c, http.StatusUnauthorized, "authentication_error", "Invalid API key")
return
}
subject, ok := middleware2.GetAuthSubjectFromContext(c)
if !ok {
h.anthropicErrorResponse(c, http.StatusInternalServerError, "api_error", "User context not found")
return
}
reqLog := requestLogger(
c,
"handler.openai_gateway.messages",
zap.Int64("user_id", subject.UserID),
zap.Int64("api_key_id", apiKey.ID),
zap.Any("group_id", apiKey.GroupID),
)
if !h.ensureResponsesDependencies(c, reqLog) {
return
}
body, err := pkghttputil.ReadRequestBodyWithPrealloc(c.Request)
if err != nil {
if maxErr, ok := extractMaxBytesError(err); ok {
h.anthropicErrorResponse(c, http.StatusRequestEntityTooLarge, "invalid_request_error", buildBodyTooLargeMessage(maxErr.Limit))
return
}
h.anthropicErrorResponse(c, http.StatusBadRequest, "invalid_request_error", "Failed to read request body")
return
}
if len(body) == 0 {
h.anthropicErrorResponse(c, http.StatusBadRequest, "invalid_request_error", "Request body is empty")
return
}
if !gjson.ValidBytes(body) {
h.anthropicErrorResponse(c, http.StatusBadRequest, "invalid_request_error", "Failed to parse request body")
return
}
modelResult := gjson.GetBytes(body, "model")
if !modelResult.Exists() || modelResult.Type != gjson.String || modelResult.String() == "" {
h.anthropicErrorResponse(c, http.StatusBadRequest, "invalid_request_error", "model is required")
return
}
reqModel := modelResult.String()
reqStream := gjson.GetBytes(body, "stream").Bool()
reqLog = reqLog.With(zap.String("model", reqModel), zap.Bool("stream", reqStream))
setOpsRequestContext(c, reqModel, reqStream, body)
subscription, _ := middleware2.GetSubscriptionFromContext(c)
service.SetOpsLatencyMs(c, service.OpsAuthLatencyMsKey, time.Since(requestStart).Milliseconds())
routingStart := time.Now()
userReleaseFunc, acquired := h.acquireResponsesUserSlot(c, subject.UserID, subject.Concurrency, reqStream, &streamStarted, reqLog)
if !acquired {
return
}
if userReleaseFunc != nil {
defer userReleaseFunc()
}
if err := h.billingCacheService.CheckBillingEligibility(c.Request.Context(), apiKey.User, apiKey, apiKey.Group, subscription); err != nil {
reqLog.Info("openai_messages.billing_eligibility_check_failed", zap.Error(err))
status, code, message := billingErrorDetails(err)
h.anthropicStreamingAwareError(c, status, code, message, streamStarted)
return
}
sessionHash := h.gatewayService.GenerateSessionHash(c, body)
promptCacheKey := h.gatewayService.ExtractSessionID(c, body)
maxAccountSwitches := h.maxAccountSwitches
switchCount := 0
failedAccountIDs := make(map[int64]struct{})
var lastFailoverErr *service.UpstreamFailoverError
for {
reqLog.Debug("openai_messages.account_selecting", zap.Int("excluded_account_count", len(failedAccountIDs)))
selection, scheduleDecision, err := h.gatewayService.SelectAccountWithScheduler(
c.Request.Context(),
apiKey.GroupID,
"", // no previous_response_id
sessionHash,
reqModel,
failedAccountIDs,
service.OpenAIUpstreamTransportAny,
)
if err != nil {
reqLog.Warn("openai_messages.account_select_failed",
zap.Error(err),
zap.Int("excluded_account_count", len(failedAccountIDs)),
)
if len(failedAccountIDs) == 0 {
h.anthropicStreamingAwareError(c, http.StatusServiceUnavailable, "api_error", "Service temporarily unavailable", streamStarted)
return
}
if lastFailoverErr != nil {
h.handleAnthropicFailoverExhausted(c, lastFailoverErr, streamStarted)
} else {
h.anthropicStreamingAwareError(c, http.StatusBadGateway, "api_error", "Upstream request failed", streamStarted)
}
return
}
if selection == nil || selection.Account == nil {
h.anthropicStreamingAwareError(c, http.StatusServiceUnavailable, "api_error", "No available accounts", streamStarted)
return
}
account := selection.Account
reqLog.Debug("openai_messages.account_selected", zap.Int64("account_id", account.ID), zap.String("account_name", account.Name))
_ = scheduleDecision
setOpsSelectedAccount(c, account.ID, account.Platform)
accountReleaseFunc, acquired := h.acquireResponsesAccountSlot(c, apiKey.GroupID, sessionHash, selection, reqStream, &streamStarted, reqLog)
if !acquired {
return
}
service.SetOpsLatencyMs(c, service.OpsRoutingLatencyMsKey, time.Since(routingStart).Milliseconds())
forwardStart := time.Now()
result, err := h.gatewayService.ForwardAsAnthropic(c.Request.Context(), c, account, body, promptCacheKey)
forwardDurationMs := time.Since(forwardStart).Milliseconds()
if accountReleaseFunc != nil {
accountReleaseFunc()
}
upstreamLatencyMs, _ := getContextInt64(c, service.OpsUpstreamLatencyMsKey)
responseLatencyMs := forwardDurationMs
if upstreamLatencyMs > 0 && forwardDurationMs > upstreamLatencyMs {
responseLatencyMs = forwardDurationMs - upstreamLatencyMs
}
service.SetOpsLatencyMs(c, service.OpsResponseLatencyMsKey, responseLatencyMs)
if err == nil && result != nil && result.FirstTokenMs != nil {
service.SetOpsLatencyMs(c, service.OpsTimeToFirstTokenMsKey, int64(*result.FirstTokenMs))
}
if err != nil {
var failoverErr *service.UpstreamFailoverError
if errors.As(err, &failoverErr) {
h.gatewayService.ReportOpenAIAccountScheduleResult(account.ID, false, nil)
h.gatewayService.RecordOpenAIAccountSwitch()
failedAccountIDs[account.ID] = struct{}{}
lastFailoverErr = failoverErr
if switchCount >= maxAccountSwitches {
h.handleAnthropicFailoverExhausted(c, failoverErr, streamStarted)
return
}
switchCount++
reqLog.Warn("openai_messages.upstream_failover_switching",
zap.Int64("account_id", account.ID),
zap.Int("upstream_status", failoverErr.StatusCode),
zap.Int("switch_count", switchCount),
zap.Int("max_switches", maxAccountSwitches),
)
continue
}
h.gatewayService.ReportOpenAIAccountScheduleResult(account.ID, false, nil)
wroteFallback := h.ensureAnthropicErrorResponse(c, streamStarted)
reqLog.Warn("openai_messages.forward_failed",
zap.Int64("account_id", account.ID),
zap.Bool("fallback_error_response_written", wroteFallback),
zap.Error(err),
)
return
}
if result != nil {
h.gatewayService.ReportOpenAIAccountScheduleResult(account.ID, true, result.FirstTokenMs)
} else {
h.gatewayService.ReportOpenAIAccountScheduleResult(account.ID, true, nil)
}
userAgent := c.GetHeader("User-Agent")
clientIP := ip.GetClientIP(c)
h.submitUsageRecordTask(func(ctx context.Context) {
if err := h.gatewayService.RecordUsage(ctx, &service.OpenAIRecordUsageInput{
Result: result,
APIKey: apiKey,
User: apiKey.User,
Account: account,
Subscription: subscription,
UserAgent: userAgent,
IPAddress: clientIP,
APIKeyService: h.apiKeyService,
}); err != nil {
logger.L().With(
zap.String("component", "handler.openai_gateway.messages"),
zap.Int64("user_id", subject.UserID),
zap.Int64("api_key_id", apiKey.ID),
zap.Any("group_id", apiKey.GroupID),
zap.String("model", reqModel),
zap.Int64("account_id", account.ID),
).Error("openai_messages.record_usage_failed", zap.Error(err))
}
})
reqLog.Debug("openai_messages.request_completed",
zap.Int64("account_id", account.ID),
zap.Int("switch_count", switchCount),
)
return
}
}
// anthropicErrorResponse writes an error in Anthropic Messages API format.
func (h *OpenAIGatewayHandler) anthropicErrorResponse(c *gin.Context, status int, errType, message string) {
c.JSON(status, gin.H{
"type": "error",
"error": gin.H{
"type": errType,
"message": message,
},
})
}
// anthropicStreamingAwareError handles errors that may occur during streaming,
// using Anthropic SSE error format.
func (h *OpenAIGatewayHandler) anthropicStreamingAwareError(c *gin.Context, status int, errType, message string, streamStarted bool) {
if streamStarted {
flusher, ok := c.Writer.(http.Flusher)
if ok {
errorEvent := "event: error\ndata: " + `{"type":"error","error":{"type":` + strconv.Quote(errType) + `,"message":` + strconv.Quote(message) + `}}` + "\n\n"
fmt.Fprint(c.Writer, errorEvent) //nolint:errcheck
flusher.Flush()
}
return
}
h.anthropicErrorResponse(c, status, errType, message)
}
// handleAnthropicFailoverExhausted maps upstream failover errors to Anthropic format.
func (h *OpenAIGatewayHandler) handleAnthropicFailoverExhausted(c *gin.Context, failoverErr *service.UpstreamFailoverError, streamStarted bool) {
status, errType, errMsg := h.mapUpstreamError(failoverErr.StatusCode)
h.anthropicStreamingAwareError(c, status, errType, errMsg, streamStarted)
}
// ensureAnthropicErrorResponse writes a fallback Anthropic error if no response was written.
func (h *OpenAIGatewayHandler) ensureAnthropicErrorResponse(c *gin.Context, streamStarted bool) bool {
if c == nil || c.Writer == nil || c.Writer.Written() {
return false
}
h.anthropicStreamingAwareError(c, http.StatusBadGateway, "api_error", "Upstream request failed", streamStarted)
return true
}
func (h *OpenAIGatewayHandler) validateFunctionCallOutputRequest(c *gin.Context, body []byte, reqLog *zap.Logger) bool { func (h *OpenAIGatewayHandler) validateFunctionCallOutputRequest(c *gin.Context, body []byte, reqLog *zap.Logger) bool {
if !gjson.GetBytes(body, `input.#(type=="function_call_output")`).Exists() { if !gjson.GetBytes(body, `input.#(type=="function_call_output")`).Exists() {
return true return true

View File

@@ -0,0 +1,534 @@
package apicompat
import (
"encoding/json"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
// ---------------------------------------------------------------------------
// AnthropicToResponses tests
// ---------------------------------------------------------------------------
func TestAnthropicToResponses_BasicText(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 1024,
Stream: true,
Messages: []AnthropicMessage{
{Role: "user", Content: json.RawMessage(`"Hello"`)},
},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
assert.Equal(t, "gpt-5.2", resp.Model)
assert.True(t, resp.Stream)
assert.Equal(t, 1024, *resp.MaxOutputTokens)
assert.False(t, *resp.Store)
var items []ResponsesInputItem
require.NoError(t, json.Unmarshal(resp.Input, &items))
require.Len(t, items, 1)
assert.Equal(t, "user", items[0].Role)
}
func TestAnthropicToResponses_SystemPrompt(t *testing.T) {
t.Run("string", func(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 100,
System: json.RawMessage(`"You are helpful."`),
Messages: []AnthropicMessage{{Role: "user", Content: json.RawMessage(`"Hi"`)}},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
var items []ResponsesInputItem
require.NoError(t, json.Unmarshal(resp.Input, &items))
require.Len(t, items, 2)
assert.Equal(t, "system", items[0].Role)
})
t.Run("array", func(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 100,
System: json.RawMessage(`[{"type":"text","text":"Part 1"},{"type":"text","text":"Part 2"}]`),
Messages: []AnthropicMessage{{Role: "user", Content: json.RawMessage(`"Hi"`)}},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
var items []ResponsesInputItem
require.NoError(t, json.Unmarshal(resp.Input, &items))
require.Len(t, items, 2)
assert.Equal(t, "system", items[0].Role)
// System text should be joined with double newline.
var text string
require.NoError(t, json.Unmarshal(items[0].Content, &text))
assert.Equal(t, "Part 1\n\nPart 2", text)
})
}
func TestAnthropicToResponses_ToolUse(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 1024,
Messages: []AnthropicMessage{
{Role: "user", Content: json.RawMessage(`"What is the weather?"`)},
{Role: "assistant", Content: json.RawMessage(`[{"type":"text","text":"Let me check."},{"type":"tool_use","id":"call_1","name":"get_weather","input":{"city":"NYC"}}]`)},
{Role: "user", Content: json.RawMessage(`[{"type":"tool_result","tool_use_id":"call_1","content":"Sunny, 72°F"}]`)},
},
Tools: []AnthropicTool{
{Name: "get_weather", Description: "Get weather", InputSchema: json.RawMessage(`{"type":"object","properties":{"city":{"type":"string"}}}`)},
},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
// Check tools
require.Len(t, resp.Tools, 1)
assert.Equal(t, "function", resp.Tools[0].Type)
assert.Equal(t, "get_weather", resp.Tools[0].Name)
// Check input items
var items []ResponsesInputItem
require.NoError(t, json.Unmarshal(resp.Input, &items))
// user + assistant + function_call + function_call_output = 4
require.Len(t, items, 4)
assert.Equal(t, "user", items[0].Role)
assert.Equal(t, "assistant", items[1].Role)
assert.Equal(t, "function_call", items[2].Type)
assert.Equal(t, "fc_call_1", items[2].CallID)
assert.Equal(t, "function_call_output", items[3].Type)
assert.Equal(t, "fc_call_1", items[3].CallID)
assert.Equal(t, "Sunny, 72°F", items[3].Output)
}
func TestAnthropicToResponses_ThinkingIgnored(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 1024,
Messages: []AnthropicMessage{
{Role: "user", Content: json.RawMessage(`"Hello"`)},
{Role: "assistant", Content: json.RawMessage(`[{"type":"thinking","thinking":"deep thought"},{"type":"text","text":"Hi!"}]`)},
{Role: "user", Content: json.RawMessage(`"More"`)},
},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
var items []ResponsesInputItem
require.NoError(t, json.Unmarshal(resp.Input, &items))
// user + assistant(text only, thinking ignored) + user = 3
require.Len(t, items, 3)
assert.Equal(t, "assistant", items[1].Role)
// Assistant content should only have text, not thinking.
var parts []ResponsesContentPart
require.NoError(t, json.Unmarshal(items[1].Content, &parts))
require.Len(t, parts, 1)
assert.Equal(t, "output_text", parts[0].Type)
assert.Equal(t, "Hi!", parts[0].Text)
}
func TestAnthropicToResponses_MaxTokensFloor(t *testing.T) {
req := &AnthropicRequest{
Model: "gpt-5.2",
MaxTokens: 10, // below minMaxOutputTokens (128)
Messages: []AnthropicMessage{{Role: "user", Content: json.RawMessage(`"Hi"`)}},
}
resp, err := AnthropicToResponses(req)
require.NoError(t, err)
assert.Equal(t, 128, *resp.MaxOutputTokens)
}
// ---------------------------------------------------------------------------
// ResponsesToAnthropic (non-streaming) tests
// ---------------------------------------------------------------------------
func TestResponsesToAnthropic_TextOnly(t *testing.T) {
resp := &ResponsesResponse{
ID: "resp_123",
Model: "gpt-5.2",
Status: "completed",
Output: []ResponsesOutput{
{
Type: "message",
Content: []ResponsesContentPart{
{Type: "output_text", Text: "Hello there!"},
},
},
},
Usage: &ResponsesUsage{InputTokens: 10, OutputTokens: 5, TotalTokens: 15},
}
anth := ResponsesToAnthropic(resp, "claude-opus-4-6")
assert.Equal(t, "resp_123", anth.ID)
assert.Equal(t, "claude-opus-4-6", anth.Model)
assert.Equal(t, "end_turn", anth.StopReason)
require.Len(t, anth.Content, 1)
assert.Equal(t, "text", anth.Content[0].Type)
assert.Equal(t, "Hello there!", anth.Content[0].Text)
assert.Equal(t, 10, anth.Usage.InputTokens)
assert.Equal(t, 5, anth.Usage.OutputTokens)
}
func TestResponsesToAnthropic_ToolUse(t *testing.T) {
resp := &ResponsesResponse{
ID: "resp_456",
Model: "gpt-5.2",
Status: "completed",
Output: []ResponsesOutput{
{
Type: "message",
Content: []ResponsesContentPart{
{Type: "output_text", Text: "Let me check."},
},
},
{
Type: "function_call",
CallID: "call_1",
Name: "get_weather",
Arguments: `{"city":"NYC"}`,
},
},
}
anth := ResponsesToAnthropic(resp, "claude-opus-4-6")
assert.Equal(t, "tool_use", anth.StopReason)
require.Len(t, anth.Content, 2)
assert.Equal(t, "text", anth.Content[0].Type)
assert.Equal(t, "tool_use", anth.Content[1].Type)
assert.Equal(t, "call_1", anth.Content[1].ID)
assert.Equal(t, "get_weather", anth.Content[1].Name)
}
func TestResponsesToAnthropic_Reasoning(t *testing.T) {
resp := &ResponsesResponse{
ID: "resp_789",
Model: "gpt-5.2",
Status: "completed",
Output: []ResponsesOutput{
{
Type: "reasoning",
Summary: []ResponsesSummary{
{Type: "summary_text", Text: "Thinking about the answer..."},
},
},
{
Type: "message",
Content: []ResponsesContentPart{
{Type: "output_text", Text: "42"},
},
},
},
}
anth := ResponsesToAnthropic(resp, "claude-opus-4-6")
require.Len(t, anth.Content, 2)
assert.Equal(t, "thinking", anth.Content[0].Type)
assert.Equal(t, "Thinking about the answer...", anth.Content[0].Thinking)
assert.Equal(t, "text", anth.Content[1].Type)
assert.Equal(t, "42", anth.Content[1].Text)
}
func TestResponsesToAnthropic_Incomplete(t *testing.T) {
resp := &ResponsesResponse{
ID: "resp_inc",
Model: "gpt-5.2",
Status: "incomplete",
IncompleteDetails: &ResponsesIncompleteDetails{
Reason: "max_output_tokens",
},
Output: []ResponsesOutput{
{
Type: "message",
Content: []ResponsesContentPart{{Type: "output_text", Text: "Partial..."}},
},
},
}
anth := ResponsesToAnthropic(resp, "claude-opus-4-6")
assert.Equal(t, "max_tokens", anth.StopReason)
}
func TestResponsesToAnthropic_EmptyOutput(t *testing.T) {
resp := &ResponsesResponse{
ID: "resp_empty",
Model: "gpt-5.2",
Status: "completed",
Output: []ResponsesOutput{},
}
anth := ResponsesToAnthropic(resp, "claude-opus-4-6")
require.Len(t, anth.Content, 1)
assert.Equal(t, "text", anth.Content[0].Type)
assert.Equal(t, "", anth.Content[0].Text)
}
// ---------------------------------------------------------------------------
// Streaming: ResponsesEventToAnthropicEvents tests
// ---------------------------------------------------------------------------
func TestStreamingTextOnly(t *testing.T) {
state := NewResponsesEventToAnthropicState()
// 1. response.created
events := ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{
ID: "resp_1",
Model: "gpt-5.2",
},
}, state)
require.Len(t, events, 1)
assert.Equal(t, "message_start", events[0].Type)
// 2. output_item.added (message)
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_item.added",
OutputIndex: 0,
Item: &ResponsesOutput{Type: "message"},
}, state)
assert.Len(t, events, 0) // message item doesn't emit events
// 3. text delta
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_text.delta",
Delta: "Hello",
}, state)
require.Len(t, events, 2) // content_block_start + content_block_delta
assert.Equal(t, "content_block_start", events[0].Type)
assert.Equal(t, "text", events[0].ContentBlock.Type)
assert.Equal(t, "content_block_delta", events[1].Type)
assert.Equal(t, "text_delta", events[1].Delta.Type)
assert.Equal(t, "Hello", events[1].Delta.Text)
// 4. more text
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_text.delta",
Delta: " world",
}, state)
require.Len(t, events, 1) // only delta, no new block start
assert.Equal(t, "content_block_delta", events[0].Type)
// 5. text done
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_text.done",
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_stop", events[0].Type)
// 6. completed
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.completed",
Response: &ResponsesResponse{
Status: "completed",
Usage: &ResponsesUsage{InputTokens: 10, OutputTokens: 5},
},
}, state)
require.Len(t, events, 2) // message_delta + message_stop
assert.Equal(t, "message_delta", events[0].Type)
assert.Equal(t, "end_turn", events[0].Delta.StopReason)
assert.Equal(t, 10, events[0].Usage.InputTokens)
assert.Equal(t, 5, events[0].Usage.OutputTokens)
assert.Equal(t, "message_stop", events[1].Type)
}
func TestStreamingToolCall(t *testing.T) {
state := NewResponsesEventToAnthropicState()
// 1. response.created
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{ID: "resp_2", Model: "gpt-5.2"},
}, state)
// 2. function_call added
events := ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_item.added",
OutputIndex: 0,
Item: &ResponsesOutput{Type: "function_call", CallID: "call_1", Name: "get_weather"},
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_start", events[0].Type)
assert.Equal(t, "tool_use", events[0].ContentBlock.Type)
assert.Equal(t, "call_1", events[0].ContentBlock.ID)
// 3. arguments delta
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.function_call_arguments.delta",
OutputIndex: 0,
Delta: `{"city":`,
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_delta", events[0].Type)
assert.Equal(t, "input_json_delta", events[0].Delta.Type)
assert.Equal(t, `{"city":`, events[0].Delta.PartialJSON)
// 4. arguments done
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.function_call_arguments.done",
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_stop", events[0].Type)
// 5. completed with tool_calls
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.completed",
Response: &ResponsesResponse{
Status: "completed",
Usage: &ResponsesUsage{InputTokens: 20, OutputTokens: 10},
},
}, state)
require.Len(t, events, 2)
assert.Equal(t, "tool_use", events[0].Delta.StopReason)
}
func TestStreamingReasoning(t *testing.T) {
state := NewResponsesEventToAnthropicState()
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{ID: "resp_3", Model: "gpt-5.2"},
}, state)
// reasoning item added
events := ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_item.added",
OutputIndex: 0,
Item: &ResponsesOutput{Type: "reasoning"},
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_start", events[0].Type)
assert.Equal(t, "thinking", events[0].ContentBlock.Type)
// reasoning text delta
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.reasoning_summary_text.delta",
OutputIndex: 0,
Delta: "Let me think...",
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_delta", events[0].Type)
assert.Equal(t, "thinking_delta", events[0].Delta.Type)
assert.Equal(t, "Let me think...", events[0].Delta.Thinking)
// reasoning done
events = ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.reasoning_summary_text.done",
}, state)
require.Len(t, events, 1)
assert.Equal(t, "content_block_stop", events[0].Type)
}
func TestStreamingIncomplete(t *testing.T) {
state := NewResponsesEventToAnthropicState()
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{ID: "resp_4", Model: "gpt-5.2"},
}, state)
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_text.delta",
Delta: "Partial output...",
}, state)
events := ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.incomplete",
Response: &ResponsesResponse{
Status: "incomplete",
IncompleteDetails: &ResponsesIncompleteDetails{Reason: "max_output_tokens"},
Usage: &ResponsesUsage{InputTokens: 100, OutputTokens: 4096},
},
}, state)
// Should close the text block + message_delta + message_stop
require.Len(t, events, 3)
assert.Equal(t, "content_block_stop", events[0].Type)
assert.Equal(t, "message_delta", events[1].Type)
assert.Equal(t, "max_tokens", events[1].Delta.StopReason)
assert.Equal(t, "message_stop", events[2].Type)
}
func TestFinalizeStream_NeverStarted(t *testing.T) {
state := NewResponsesEventToAnthropicState()
events := FinalizeResponsesAnthropicStream(state)
assert.Nil(t, events)
}
func TestFinalizeStream_AlreadyCompleted(t *testing.T) {
state := NewResponsesEventToAnthropicState()
state.MessageStartSent = true
state.MessageStopSent = true
events := FinalizeResponsesAnthropicStream(state)
assert.Nil(t, events)
}
func TestFinalizeStream_AbnormalTermination(t *testing.T) {
state := NewResponsesEventToAnthropicState()
// Simulate a stream that started but never completed
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{ID: "resp_5", Model: "gpt-5.2"},
}, state)
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.output_text.delta",
Delta: "Interrupted...",
}, state)
// Stream ends without response.completed
events := FinalizeResponsesAnthropicStream(state)
require.Len(t, events, 3) // content_block_stop + message_delta + message_stop
assert.Equal(t, "content_block_stop", events[0].Type)
assert.Equal(t, "message_delta", events[1].Type)
assert.Equal(t, "end_turn", events[1].Delta.StopReason)
assert.Equal(t, "message_stop", events[2].Type)
}
func TestStreamingEmptyResponse(t *testing.T) {
state := NewResponsesEventToAnthropicState()
ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.created",
Response: &ResponsesResponse{ID: "resp_6", Model: "gpt-5.2"},
}, state)
events := ResponsesEventToAnthropicEvents(&ResponsesStreamEvent{
Type: "response.completed",
Response: &ResponsesResponse{
Status: "completed",
Usage: &ResponsesUsage{InputTokens: 5, OutputTokens: 0},
},
}, state)
require.Len(t, events, 2) // message_delta + message_stop
assert.Equal(t, "message_delta", events[0].Type)
assert.Equal(t, "end_turn", events[0].Delta.StopReason)
}
func TestResponsesAnthropicEventToSSE(t *testing.T) {
evt := AnthropicStreamEvent{
Type: "message_start",
Message: &AnthropicResponse{
ID: "resp_1",
Type: "message",
Role: "assistant",
},
}
sse, err := ResponsesAnthropicEventToSSE(evt)
require.NoError(t, err)
assert.Contains(t, sse, "event: message_start\n")
assert.Contains(t, sse, "data: ")
assert.Contains(t, sse, `"resp_1"`)
}

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package apicompat
import (
"encoding/json"
"strings"
)
// AnthropicToResponses converts an Anthropic Messages request directly into
// a Responses API request. This preserves fields that would be lost in a
// Chat Completions intermediary round-trip (e.g. thinking, cache_control,
// structured system prompts).
func AnthropicToResponses(req *AnthropicRequest) (*ResponsesRequest, error) {
input, err := convertAnthropicToResponsesInput(req.System, req.Messages)
if err != nil {
return nil, err
}
inputJSON, err := json.Marshal(input)
if err != nil {
return nil, err
}
out := &ResponsesRequest{
Model: req.Model,
Input: inputJSON,
Temperature: req.Temperature,
TopP: req.TopP,
Stream: req.Stream,
Include: []string{"reasoning.encrypted_content"},
}
storeFalse := false
out.Store = &storeFalse
if req.MaxTokens > 0 {
v := req.MaxTokens
if v < minMaxOutputTokens {
v = minMaxOutputTokens
}
out.MaxOutputTokens = &v
}
if len(req.Tools) > 0 {
out.Tools = convertAnthropicToolsToResponses(req.Tools)
}
return out, nil
}
// convertAnthropicToResponsesInput builds the Responses API input items array
// from the Anthropic system field and message list.
func convertAnthropicToResponsesInput(system json.RawMessage, msgs []AnthropicMessage) ([]ResponsesInputItem, error) {
var out []ResponsesInputItem
// System prompt → system role input item.
if len(system) > 0 {
sysText, err := parseAnthropicSystemPrompt(system)
if err != nil {
return nil, err
}
if sysText != "" {
content, _ := json.Marshal(sysText)
out = append(out, ResponsesInputItem{
Role: "system",
Content: content,
})
}
}
for _, m := range msgs {
items, err := anthropicMsgToResponsesItems(m)
if err != nil {
return nil, err
}
out = append(out, items...)
}
return out, nil
}
// parseAnthropicSystemPrompt handles the Anthropic system field which can be
// a plain string or an array of text blocks.
func parseAnthropicSystemPrompt(raw json.RawMessage) (string, error) {
var s string
if err := json.Unmarshal(raw, &s); err == nil {
return s, nil
}
var blocks []AnthropicContentBlock
if err := json.Unmarshal(raw, &blocks); err != nil {
return "", err
}
var parts []string
for _, b := range blocks {
if b.Type == "text" && b.Text != "" {
parts = append(parts, b.Text)
}
}
return strings.Join(parts, "\n\n"), nil
}
// anthropicMsgToResponsesItems converts a single Anthropic message into one
// or more Responses API input items.
func anthropicMsgToResponsesItems(m AnthropicMessage) ([]ResponsesInputItem, error) {
switch m.Role {
case "user":
return anthropicUserToResponses(m.Content)
case "assistant":
return anthropicAssistantToResponses(m.Content)
default:
return anthropicUserToResponses(m.Content)
}
}
// anthropicUserToResponses handles an Anthropic user message. Content can be a
// plain string or an array of blocks. tool_result blocks are extracted into
// function_call_output items.
func anthropicUserToResponses(raw json.RawMessage) ([]ResponsesInputItem, error) {
// Try plain string.
var s string
if err := json.Unmarshal(raw, &s); err == nil {
content, _ := json.Marshal(s)
return []ResponsesInputItem{{Role: "user", Content: content}}, nil
}
var blocks []AnthropicContentBlock
if err := json.Unmarshal(raw, &blocks); err != nil {
return nil, err
}
var out []ResponsesInputItem
// Extract tool_result blocks → function_call_output items.
for _, b := range blocks {
if b.Type != "tool_result" {
continue
}
text := extractAnthropicToolResultText(b)
if text == "" {
// OpenAI Responses API requires "output" field; use placeholder for empty results.
text = "(empty)"
}
out = append(out, ResponsesInputItem{
Type: "function_call_output",
CallID: toResponsesCallID(b.ToolUseID),
Output: text,
})
}
// Remaining text blocks → user message.
text := extractAnthropicTextFromBlocks(blocks)
if text != "" {
content, _ := json.Marshal(text)
out = append(out, ResponsesInputItem{Role: "user", Content: content})
}
return out, nil
}
// anthropicAssistantToResponses handles an Anthropic assistant message.
// Text content → assistant message with output_text parts.
// tool_use blocks → function_call items.
// thinking blocks → ignored (OpenAI doesn't accept them as input).
func anthropicAssistantToResponses(raw json.RawMessage) ([]ResponsesInputItem, error) {
// Try plain string.
var s string
if err := json.Unmarshal(raw, &s); err == nil {
parts := []ResponsesContentPart{{Type: "output_text", Text: s}}
partsJSON, err := json.Marshal(parts)
if err != nil {
return nil, err
}
return []ResponsesInputItem{{Role: "assistant", Content: partsJSON}}, nil
}
var blocks []AnthropicContentBlock
if err := json.Unmarshal(raw, &blocks); err != nil {
return nil, err
}
var items []ResponsesInputItem
// Text content → assistant message with output_text content parts.
text := extractAnthropicTextFromBlocks(blocks)
if text != "" {
parts := []ResponsesContentPart{{Type: "output_text", Text: text}}
partsJSON, err := json.Marshal(parts)
if err != nil {
return nil, err
}
items = append(items, ResponsesInputItem{Role: "assistant", Content: partsJSON})
}
// tool_use → function_call items.
for _, b := range blocks {
if b.Type != "tool_use" {
continue
}
args := "{}"
if len(b.Input) > 0 {
args = string(b.Input)
}
fcID := toResponsesCallID(b.ID)
items = append(items, ResponsesInputItem{
Type: "function_call",
CallID: fcID,
Name: b.Name,
Arguments: args,
ID: fcID,
})
}
return items, nil
}
// toResponsesCallID converts an Anthropic tool ID (toolu_xxx / call_xxx) to a
// Responses API function_call ID that starts with "fc_".
func toResponsesCallID(id string) string {
if strings.HasPrefix(id, "fc_") {
return id
}
return "fc_" + id
}
// fromResponsesCallID reverses toResponsesCallID, stripping the "fc_" prefix
// that was added during request conversion.
func fromResponsesCallID(id string) string {
if after, ok := strings.CutPrefix(id, "fc_"); ok {
// Only strip if the remainder doesn't look like it was already "fc_" prefixed.
// E.g. "fc_toolu_xxx" → "toolu_xxx", "fc_call_xxx" → "call_xxx"
if strings.HasPrefix(after, "toolu_") || strings.HasPrefix(after, "call_") {
return after
}
}
return id
}
// extractAnthropicToolResultText gets the text content from a tool_result block.
func extractAnthropicToolResultText(b AnthropicContentBlock) string {
if len(b.Content) == 0 {
return ""
}
var s string
if err := json.Unmarshal(b.Content, &s); err == nil {
return s
}
var inner []AnthropicContentBlock
if err := json.Unmarshal(b.Content, &inner); err == nil {
var parts []string
for _, ib := range inner {
if ib.Type == "text" && ib.Text != "" {
parts = append(parts, ib.Text)
}
}
return strings.Join(parts, "\n\n")
}
return ""
}
// extractAnthropicTextFromBlocks joins all text blocks, ignoring thinking/
// tool_use/tool_result blocks.
func extractAnthropicTextFromBlocks(blocks []AnthropicContentBlock) string {
var parts []string
for _, b := range blocks {
if b.Type == "text" && b.Text != "" {
parts = append(parts, b.Text)
}
}
return strings.Join(parts, "\n\n")
}
// convertAnthropicToolsToResponses maps Anthropic tool definitions to
// Responses API function tools (input_schema → parameters).
func convertAnthropicToolsToResponses(tools []AnthropicTool) []ResponsesTool {
out := make([]ResponsesTool, len(tools))
for i, t := range tools {
out[i] = ResponsesTool{
Type: "function",
Name: t.Name,
Description: t.Description,
Parameters: t.InputSchema,
}
}
return out
}

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@@ -0,0 +1,436 @@
package apicompat
import (
"encoding/json"
"fmt"
"time"
)
// ---------------------------------------------------------------------------
// Non-streaming: ResponsesResponse → AnthropicResponse
// ---------------------------------------------------------------------------
// ResponsesToAnthropic converts a Responses API response directly into an
// Anthropic Messages response. Reasoning output items are mapped to thinking
// blocks; function_call items become tool_use blocks.
func ResponsesToAnthropic(resp *ResponsesResponse, model string) *AnthropicResponse {
out := &AnthropicResponse{
ID: resp.ID,
Type: "message",
Role: "assistant",
Model: model,
}
var blocks []AnthropicContentBlock
for _, item := range resp.Output {
switch item.Type {
case "reasoning":
summaryText := ""
for _, s := range item.Summary {
if s.Type == "summary_text" && s.Text != "" {
summaryText += s.Text
}
}
if summaryText != "" {
blocks = append(blocks, AnthropicContentBlock{
Type: "thinking",
Thinking: summaryText,
})
}
case "message":
for _, part := range item.Content {
if part.Type == "output_text" && part.Text != "" {
blocks = append(blocks, AnthropicContentBlock{
Type: "text",
Text: part.Text,
})
}
}
case "function_call":
blocks = append(blocks, AnthropicContentBlock{
Type: "tool_use",
ID: fromResponsesCallID(item.CallID),
Name: item.Name,
Input: json.RawMessage(item.Arguments),
})
}
}
if len(blocks) == 0 {
blocks = append(blocks, AnthropicContentBlock{Type: "text", Text: ""})
}
out.Content = blocks
out.StopReason = responsesStatusToAnthropicStopReason(resp.Status, resp.IncompleteDetails, blocks)
if resp.Usage != nil {
out.Usage = AnthropicUsage{
InputTokens: resp.Usage.InputTokens,
OutputTokens: resp.Usage.OutputTokens,
}
if resp.Usage.InputTokensDetails != nil {
out.Usage.CacheReadInputTokens = resp.Usage.InputTokensDetails.CachedTokens
}
}
return out
}
func responsesStatusToAnthropicStopReason(status string, details *ResponsesIncompleteDetails, blocks []AnthropicContentBlock) string {
switch status {
case "incomplete":
if details != nil && details.Reason == "max_output_tokens" {
return "max_tokens"
}
return "end_turn"
case "completed":
if len(blocks) > 0 && blocks[len(blocks)-1].Type == "tool_use" {
return "tool_use"
}
return "end_turn"
default:
return "end_turn"
}
}
// ---------------------------------------------------------------------------
// Streaming: ResponsesStreamEvent → []AnthropicStreamEvent (stateful converter)
// ---------------------------------------------------------------------------
// ResponsesEventToAnthropicState tracks state for converting a sequence of
// Responses SSE events directly into Anthropic SSE events.
type ResponsesEventToAnthropicState struct {
MessageStartSent bool
MessageStopSent bool
ContentBlockIndex int
ContentBlockOpen bool
CurrentBlockType string // "text" | "thinking" | "tool_use"
// OutputIndexToBlockIdx maps Responses output_index → Anthropic content block index.
OutputIndexToBlockIdx map[int]int
InputTokens int
OutputTokens int
CacheReadInputTokens int
ResponseID string
Model string
Created int64
}
// NewResponsesEventToAnthropicState returns an initialised stream state.
func NewResponsesEventToAnthropicState() *ResponsesEventToAnthropicState {
return &ResponsesEventToAnthropicState{
OutputIndexToBlockIdx: make(map[int]int),
Created: time.Now().Unix(),
}
}
// ResponsesEventToAnthropicEvents converts a single Responses SSE event into
// zero or more Anthropic SSE events, updating state as it goes.
func ResponsesEventToAnthropicEvents(
evt *ResponsesStreamEvent,
state *ResponsesEventToAnthropicState,
) []AnthropicStreamEvent {
switch evt.Type {
case "response.created":
return resToAnthHandleCreated(evt, state)
case "response.output_item.added":
return resToAnthHandleOutputItemAdded(evt, state)
case "response.output_text.delta":
return resToAnthHandleTextDelta(evt, state)
case "response.output_text.done":
return resToAnthHandleBlockDone(state)
case "response.function_call_arguments.delta":
return resToAnthHandleFuncArgsDelta(evt, state)
case "response.function_call_arguments.done":
return resToAnthHandleBlockDone(state)
case "response.output_item.done":
return resToAnthHandleOutputItemDone(evt, state)
case "response.reasoning_summary_text.delta":
return resToAnthHandleReasoningDelta(evt, state)
case "response.reasoning_summary_text.done":
return resToAnthHandleBlockDone(state)
case "response.completed", "response.incomplete":
return resToAnthHandleCompleted(evt, state)
default:
return nil
}
}
// FinalizeResponsesAnthropicStream emits synthetic termination events if the
// stream ended without a proper completion event.
func FinalizeResponsesAnthropicStream(state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if !state.MessageStartSent || state.MessageStopSent {
return nil
}
var events []AnthropicStreamEvent
events = append(events, closeCurrentBlock(state)...)
events = append(events,
AnthropicStreamEvent{
Type: "message_delta",
Delta: &AnthropicDelta{
StopReason: "end_turn",
},
Usage: &AnthropicUsage{
InputTokens: state.InputTokens,
OutputTokens: state.OutputTokens,
CacheReadInputTokens: state.CacheReadInputTokens,
},
},
AnthropicStreamEvent{Type: "message_stop"},
)
state.MessageStopSent = true
return events
}
// ResponsesAnthropicEventToSSE formats an AnthropicStreamEvent as an SSE line pair.
func ResponsesAnthropicEventToSSE(evt AnthropicStreamEvent) (string, error) {
data, err := json.Marshal(evt)
if err != nil {
return "", err
}
return fmt.Sprintf("event: %s\ndata: %s\n\n", evt.Type, data), nil
}
// --- internal handlers ---
func resToAnthHandleCreated(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Response != nil {
state.ResponseID = evt.Response.ID
// Only use upstream model if no override was set (e.g. originalModel)
if state.Model == "" {
state.Model = evt.Response.Model
}
}
if state.MessageStartSent {
return nil
}
state.MessageStartSent = true
return []AnthropicStreamEvent{{
Type: "message_start",
Message: &AnthropicResponse{
ID: state.ResponseID,
Type: "message",
Role: "assistant",
Content: []AnthropicContentBlock{},
Model: state.Model,
Usage: AnthropicUsage{
InputTokens: 0,
OutputTokens: 0,
},
},
}}
}
func resToAnthHandleOutputItemAdded(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Item == nil {
return nil
}
switch evt.Item.Type {
case "function_call":
var events []AnthropicStreamEvent
events = append(events, closeCurrentBlock(state)...)
idx := state.ContentBlockIndex
state.OutputIndexToBlockIdx[evt.OutputIndex] = idx
state.ContentBlockOpen = true
state.CurrentBlockType = "tool_use"
events = append(events, AnthropicStreamEvent{
Type: "content_block_start",
Index: &idx,
ContentBlock: &AnthropicContentBlock{
Type: "tool_use",
ID: fromResponsesCallID(evt.Item.CallID),
Name: evt.Item.Name,
Input: json.RawMessage("{}"),
},
})
return events
case "reasoning":
var events []AnthropicStreamEvent
events = append(events, closeCurrentBlock(state)...)
idx := state.ContentBlockIndex
state.OutputIndexToBlockIdx[evt.OutputIndex] = idx
state.ContentBlockOpen = true
state.CurrentBlockType = "thinking"
events = append(events, AnthropicStreamEvent{
Type: "content_block_start",
Index: &idx,
ContentBlock: &AnthropicContentBlock{
Type: "thinking",
Thinking: "",
},
})
return events
case "message":
return nil
}
return nil
}
func resToAnthHandleTextDelta(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Delta == "" {
return nil
}
var events []AnthropicStreamEvent
if !state.ContentBlockOpen || state.CurrentBlockType != "text" {
events = append(events, closeCurrentBlock(state)...)
idx := state.ContentBlockIndex
state.ContentBlockOpen = true
state.CurrentBlockType = "text"
events = append(events, AnthropicStreamEvent{
Type: "content_block_start",
Index: &idx,
ContentBlock: &AnthropicContentBlock{
Type: "text",
Text: "",
},
})
}
idx := state.ContentBlockIndex
events = append(events, AnthropicStreamEvent{
Type: "content_block_delta",
Index: &idx,
Delta: &AnthropicDelta{
Type: "text_delta",
Text: evt.Delta,
},
})
return events
}
func resToAnthHandleFuncArgsDelta(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Delta == "" {
return nil
}
blockIdx, ok := state.OutputIndexToBlockIdx[evt.OutputIndex]
if !ok {
return nil
}
return []AnthropicStreamEvent{{
Type: "content_block_delta",
Index: &blockIdx,
Delta: &AnthropicDelta{
Type: "input_json_delta",
PartialJSON: evt.Delta,
},
}}
}
func resToAnthHandleReasoningDelta(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Delta == "" {
return nil
}
blockIdx, ok := state.OutputIndexToBlockIdx[evt.OutputIndex]
if !ok {
return nil
}
return []AnthropicStreamEvent{{
Type: "content_block_delta",
Index: &blockIdx,
Delta: &AnthropicDelta{
Type: "thinking_delta",
Thinking: evt.Delta,
},
}}
}
func resToAnthHandleBlockDone(state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if !state.ContentBlockOpen {
return nil
}
return closeCurrentBlock(state)
}
func resToAnthHandleOutputItemDone(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if evt.Item == nil {
return nil
}
if state.ContentBlockOpen {
return closeCurrentBlock(state)
}
return nil
}
func resToAnthHandleCompleted(evt *ResponsesStreamEvent, state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if state.MessageStopSent {
return nil
}
var events []AnthropicStreamEvent
events = append(events, closeCurrentBlock(state)...)
stopReason := "end_turn"
if evt.Response != nil {
if evt.Response.Usage != nil {
state.InputTokens = evt.Response.Usage.InputTokens
state.OutputTokens = evt.Response.Usage.OutputTokens
if evt.Response.Usage.InputTokensDetails != nil {
state.CacheReadInputTokens = evt.Response.Usage.InputTokensDetails.CachedTokens
}
}
switch evt.Response.Status {
case "incomplete":
if evt.Response.IncompleteDetails != nil && evt.Response.IncompleteDetails.Reason == "max_output_tokens" {
stopReason = "max_tokens"
}
case "completed":
if state.ContentBlockIndex > 0 && state.CurrentBlockType == "tool_use" {
stopReason = "tool_use"
}
}
}
events = append(events,
AnthropicStreamEvent{
Type: "message_delta",
Delta: &AnthropicDelta{
StopReason: stopReason,
},
Usage: &AnthropicUsage{
InputTokens: state.InputTokens,
OutputTokens: state.OutputTokens,
CacheReadInputTokens: state.CacheReadInputTokens,
},
},
AnthropicStreamEvent{Type: "message_stop"},
)
state.MessageStopSent = true
return events
}
func closeCurrentBlock(state *ResponsesEventToAnthropicState) []AnthropicStreamEvent {
if !state.ContentBlockOpen {
return nil
}
idx := state.ContentBlockIndex
state.ContentBlockOpen = false
state.ContentBlockIndex++
return []AnthropicStreamEvent{{
Type: "content_block_stop",
Index: &idx,
}}
}

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@@ -0,0 +1,544 @@
// Package apicompat provides type definitions and conversion utilities for
// translating between Anthropic Messages, OpenAI Chat Completions, and OpenAI
// Responses API formats. It enables multi-protocol support so that clients
// using different API formats can be served through a unified gateway.
package apicompat
import "encoding/json"
// ---------------------------------------------------------------------------
// Anthropic Messages API types
// ---------------------------------------------------------------------------
// AnthropicRequest is the request body for POST /v1/messages.
type AnthropicRequest struct {
Model string `json:"model"`
MaxTokens int `json:"max_tokens"`
System json.RawMessage `json:"system,omitempty"` // string or []AnthropicContentBlock
Messages []AnthropicMessage `json:"messages"`
Tools []AnthropicTool `json:"tools,omitempty"`
Stream bool `json:"stream,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopP *float64 `json:"top_p,omitempty"`
StopSeqs []string `json:"stop_sequences,omitempty"`
}
// AnthropicMessage is a single message in the Anthropic conversation.
type AnthropicMessage struct {
Role string `json:"role"` // "user" | "assistant"
Content json.RawMessage `json:"content"`
}
// AnthropicContentBlock is one block inside a message's content array.
type AnthropicContentBlock struct {
Type string `json:"type"`
// type=text
Text string `json:"text,omitempty"`
// type=thinking
Thinking string `json:"thinking,omitempty"`
// type=tool_use
ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"`
Input json.RawMessage `json:"input,omitempty"`
// type=tool_result
ToolUseID string `json:"tool_use_id,omitempty"`
Content json.RawMessage `json:"content,omitempty"` // string or []AnthropicContentBlock
IsError bool `json:"is_error,omitempty"`
}
// AnthropicTool describes a tool available to the model.
type AnthropicTool struct {
Name string `json:"name"`
Description string `json:"description,omitempty"`
InputSchema json.RawMessage `json:"input_schema"` // JSON Schema object
}
// AnthropicResponse is the non-streaming response from POST /v1/messages.
type AnthropicResponse struct {
ID string `json:"id"`
Type string `json:"type"` // "message"
Role string `json:"role"` // "assistant"
Content []AnthropicContentBlock `json:"content"`
Model string `json:"model"`
StopReason string `json:"stop_reason"`
StopSequence *string `json:"stop_sequence,omitempty"`
Usage AnthropicUsage `json:"usage"`
}
// AnthropicUsage holds token counts in Anthropic format.
type AnthropicUsage struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
CacheCreationInputTokens int `json:"cache_creation_input_tokens"`
CacheReadInputTokens int `json:"cache_read_input_tokens"`
}
// ---------------------------------------------------------------------------
// Anthropic SSE event types
// ---------------------------------------------------------------------------
// AnthropicStreamEvent is a single SSE event in the Anthropic streaming protocol.
type AnthropicStreamEvent struct {
Type string `json:"type"`
// message_start
Message *AnthropicResponse `json:"message,omitempty"`
// content_block_start
Index *int `json:"index,omitempty"`
ContentBlock *AnthropicContentBlock `json:"content_block,omitempty"`
// content_block_delta
Delta *AnthropicDelta `json:"delta,omitempty"`
// message_delta
Usage *AnthropicUsage `json:"usage,omitempty"`
}
// AnthropicDelta carries incremental content in streaming events.
type AnthropicDelta struct {
Type string `json:"type,omitempty"` // "text_delta" | "input_json_delta" | "thinking_delta" | "signature_delta"
// text_delta
Text string `json:"text,omitempty"`
// input_json_delta
PartialJSON string `json:"partial_json,omitempty"`
// thinking_delta
Thinking string `json:"thinking,omitempty"`
// signature_delta
Signature string `json:"signature,omitempty"`
// message_delta fields
StopReason string `json:"stop_reason,omitempty"`
StopSequence *string `json:"stop_sequence,omitempty"`
}
// ---------------------------------------------------------------------------
// OpenAI Chat Completions API types
// ---------------------------------------------------------------------------
// ChatRequest is the request body for POST /v1/chat/completions.
type ChatRequest struct {
Model string `json:"model"`
Messages []ChatMessage `json:"messages"`
MaxTokens *int `json:"max_tokens,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopP *float64 `json:"top_p,omitempty"`
Stream bool `json:"stream,omitempty"`
Tools []ChatTool `json:"tools,omitempty"`
Stop json.RawMessage `json:"stop,omitempty"` // string or []string
}
// ChatMessage is a single message in the Chat Completions conversation.
type ChatMessage struct {
Role string `json:"role"` // "system" | "user" | "assistant" | "tool"
Content json.RawMessage `json:"content,omitempty"` // string or []ChatContentPart
// assistant fields
ToolCalls []ChatToolCall `json:"tool_calls,omitempty"`
// tool fields
ToolCallID string `json:"tool_call_id,omitempty"`
// Copilot-specific reasoning passthrough
ReasoningText string `json:"reasoning_text,omitempty"`
ReasoningOpaque string `json:"reasoning_opaque,omitempty"`
}
// ChatContentPart is a typed content part in a multi-part message.
type ChatContentPart struct {
Type string `json:"type"` // "text" | "image_url"
Text string `json:"text,omitempty"`
}
// ChatToolCall represents a tool invocation in an assistant message.
// In streaming deltas, Index identifies which tool call is being updated.
type ChatToolCall struct {
Index int `json:"index"`
ID string `json:"id,omitempty"`
Type string `json:"type,omitempty"` // "function"
Function ChatFunctionCall `json:"function"`
}
// ChatFunctionCall holds the function name and arguments.
type ChatFunctionCall struct {
Name string `json:"name"`
Arguments string `json:"arguments"`
}
// ChatTool describes a tool available to the model.
type ChatTool struct {
Type string `json:"type"` // "function"
Function ChatFunction `json:"function"`
}
// ChatFunction is the function definition inside a ChatTool.
type ChatFunction struct {
Name string `json:"name"`
Description string `json:"description,omitempty"`
Parameters json.RawMessage `json:"parameters,omitempty"` // JSON Schema
}
// ChatResponse is the non-streaming response from POST /v1/chat/completions.
type ChatResponse struct {
ID string `json:"id"`
Object string `json:"object"` // "chat.completion"
Created int64 `json:"created"`
Model string `json:"model"`
Choices []ChatChoice `json:"choices"`
Usage *ChatUsage `json:"usage,omitempty"`
}
// ChatChoice is one completion choice.
type ChatChoice struct {
Index int `json:"index"`
Message ChatMessage `json:"message"`
FinishReason string `json:"finish_reason"`
}
// ChatUsage holds token counts in Chat Completions format.
type ChatUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
// ---------------------------------------------------------------------------
// Chat Completions SSE types
// ---------------------------------------------------------------------------
// ChatStreamChunk is a single SSE chunk in the Chat Completions streaming protocol.
type ChatStreamChunk struct {
ID string `json:"id"`
Object string `json:"object"` // "chat.completion.chunk"
Created int64 `json:"created"`
Model string `json:"model"`
Choices []ChatStreamChoice `json:"choices"`
Usage *ChatUsage `json:"usage,omitempty"`
}
// ChatStreamChoice is one choice inside a streaming chunk.
type ChatStreamChoice struct {
Index int `json:"index"`
Delta ChatStreamDelta `json:"delta"`
FinishReason *string `json:"finish_reason"`
}
// ChatStreamDelta carries incremental content in a streaming chunk.
type ChatStreamDelta struct {
Role string `json:"role,omitempty"`
Content string `json:"content,omitempty"`
ToolCalls []ChatToolCall `json:"tool_calls,omitempty"`
// Copilot-specific reasoning passthrough (streaming)
ReasoningText string `json:"reasoning_text,omitempty"`
ReasoningOpaque string `json:"reasoning_opaque,omitempty"`
}
// ---------------------------------------------------------------------------
// OpenAI Responses API types
// ---------------------------------------------------------------------------
// ResponsesRequest is the request body for POST /v1/responses.
type ResponsesRequest struct {
Model string `json:"model"`
Input json.RawMessage `json:"input"` // string or []ResponsesInputItem
MaxOutputTokens *int `json:"max_output_tokens,omitempty"`
Temperature *float64 `json:"temperature,omitempty"`
TopP *float64 `json:"top_p,omitempty"`
Stream bool `json:"stream,omitempty"`
Tools []ResponsesTool `json:"tools,omitempty"`
Include []string `json:"include,omitempty"`
Store *bool `json:"store,omitempty"`
}
// ResponsesInputItem is one item in the Responses API input array.
// The Type field determines which other fields are populated.
type ResponsesInputItem struct {
// Common
Type string `json:"type,omitempty"` // "" for role-based messages
// Role-based messages (system/user/assistant)
Role string `json:"role,omitempty"`
Content json.RawMessage `json:"content,omitempty"` // string or []ResponsesContentPart
// type=function_call
CallID string `json:"call_id,omitempty"`
Name string `json:"name,omitempty"`
Arguments string `json:"arguments,omitempty"`
ID string `json:"id,omitempty"`
// type=function_call_output
Output string `json:"output,omitempty"`
}
// ResponsesContentPart is a typed content part in a Responses message.
type ResponsesContentPart struct {
Type string `json:"type"` // "input_text" | "output_text" | "input_image"
Text string `json:"text,omitempty"`
}
// ResponsesTool describes a tool in the Responses API.
type ResponsesTool struct {
Type string `json:"type"` // "function" | "web_search" | "local_shell" etc.
Name string `json:"name,omitempty"`
Description string `json:"description,omitempty"`
Parameters json.RawMessage `json:"parameters,omitempty"`
Strict *bool `json:"strict,omitempty"`
}
// ResponsesResponse is the non-streaming response from POST /v1/responses.
type ResponsesResponse struct {
ID string `json:"id"`
Object string `json:"object"` // "response"
Model string `json:"model"`
Status string `json:"status"` // "completed" | "incomplete" | "failed"
Output []ResponsesOutput `json:"output"`
Usage *ResponsesUsage `json:"usage,omitempty"`
// incomplete_details is present when status="incomplete"
IncompleteDetails *ResponsesIncompleteDetails `json:"incomplete_details,omitempty"`
}
// ResponsesIncompleteDetails explains why a response is incomplete.
type ResponsesIncompleteDetails struct {
Reason string `json:"reason"` // "max_output_tokens" | "content_filter"
}
// ResponsesOutput is one output item in a Responses API response.
type ResponsesOutput struct {
Type string `json:"type"` // "message" | "reasoning" | "function_call"
// type=message
ID string `json:"id,omitempty"`
Role string `json:"role,omitempty"`
Content []ResponsesContentPart `json:"content,omitempty"`
Status string `json:"status,omitempty"`
// type=reasoning
EncryptedContent string `json:"encrypted_content,omitempty"`
Summary []ResponsesSummary `json:"summary,omitempty"`
// type=function_call
CallID string `json:"call_id,omitempty"`
Name string `json:"name,omitempty"`
Arguments string `json:"arguments,omitempty"`
}
// ResponsesSummary is a summary text block inside a reasoning output.
type ResponsesSummary struct {
Type string `json:"type"` // "summary_text"
Text string `json:"text"`
}
// ResponsesUsage holds token counts in Responses API format.
type ResponsesUsage struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
TotalTokens int `json:"total_tokens"`
// Optional detailed breakdown
InputTokensDetails *ResponsesInputTokensDetails `json:"input_tokens_details,omitempty"`
OutputTokensDetails *ResponsesOutputTokensDetails `json:"output_tokens_details,omitempty"`
}
// ---------------------------------------------------------------------------
// Responses SSE event types
// ---------------------------------------------------------------------------
// ResponsesStreamEvent is a single SSE event in the Responses streaming protocol.
// The Type field corresponds to the "type" in the JSON payload.
type ResponsesStreamEvent struct {
Type string `json:"type"`
// response.created / response.completed / response.failed / response.incomplete
Response *ResponsesResponse `json:"response,omitempty"`
// response.output_item.added / response.output_item.done
Item *ResponsesOutput `json:"item,omitempty"`
// response.output_text.delta / response.output_text.done
OutputIndex int `json:"output_index,omitempty"`
ContentIndex int `json:"content_index,omitempty"`
Delta string `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
ItemID string `json:"item_id,omitempty"`
// response.function_call_arguments.delta / done
CallID string `json:"call_id,omitempty"`
Name string `json:"name,omitempty"`
Arguments string `json:"arguments,omitempty"`
// response.reasoning_summary_text.delta / done
// Reuses Text/Delta fields above, SummaryIndex identifies which summary part
SummaryIndex int `json:"summary_index,omitempty"`
// error event fields
Code string `json:"code,omitempty"`
Param string `json:"param,omitempty"`
// Sequence number for ordering events
SequenceNumber int `json:"sequence_number,omitempty"`
}
// ResponsesOutputReasoning is a reasoning output item in the Responses API.
// This type represents the "type":"reasoning" output item that contains
// extended thinking from the model.
type ResponsesOutputReasoning struct {
ID string `json:"id,omitempty"`
Type string `json:"type"` // "reasoning"
Status string `json:"status,omitempty"` // "in_progress" | "completed" | "incomplete"
EncryptedContent string `json:"encrypted_content,omitempty"`
Summary []ResponsesReasoningSummary `json:"summary,omitempty"`
}
// ResponsesReasoningSummary is a summary text block inside a reasoning output.
type ResponsesReasoningSummary struct {
Type string `json:"type"` // "summary_text"
Text string `json:"text"`
}
// ResponsesStreamState maintains the state for converting Responses streaming
// events to Chat Completions format. It tracks content blocks, tool calls,
// reasoning blocks, and other streaming artifacts.
type ResponsesStreamState struct {
// Response metadata
ID string
Model string
Created int64
// Content tracking
ContentIndex int
CurrentText string
CurrentItemID string
PendingText []string // Text to accumulate before emitting
// Tool call tracking
ToolCalls []ResponsesToolCallState
CurrentToolCall *ResponsesToolCallState
// Reasoning tracking
ReasoningBlocks []ResponsesReasoningState
CurrentReasoning *ResponsesReasoningState
// Usage tracking
InputTokens int
OutputTokens int
// Status tracking
Status string
FinishReason string
}
// ResponsesToolCallState tracks a single tool call during streaming.
type ResponsesToolCallState struct {
Index int
ItemID string
CallID string
Name string
Arguments string
Status string
IsComplete bool
}
// ResponsesReasoningState tracks a reasoning block during streaming.
type ResponsesReasoningState struct {
ItemID string
SummaryIndex int
SummaryText string
Status string
IsComplete bool
}
// ResponsesUsageDetail provides additional token usage details in Responses format.
type ResponsesUsageDetail struct {
InputTokens int `json:"input_tokens"`
OutputTokens int `json:"output_tokens"`
TotalTokens int `json:"total_tokens"`
// Optional detailed breakdown
InputTokensDetails *ResponsesInputTokensDetails `json:"input_tokens_details,omitempty"`
OutputTokensDetails *ResponsesOutputTokensDetails `json:"output_tokens_details,omitempty"`
}
// ResponsesInputTokensDetails breaks down input token usage.
type ResponsesInputTokensDetails struct {
CachedTokens int `json:"cached_tokens,omitempty"`
}
// ResponsesOutputTokensDetails breaks down output token usage.
type ResponsesOutputTokensDetails struct {
ReasoningTokens int `json:"reasoning_tokens,omitempty"`
}
// ---------------------------------------------------------------------------
// Finish reason mapping helpers
// ---------------------------------------------------------------------------
// ChatFinishToAnthropic maps a Chat Completions finish_reason to an Anthropic stop_reason.
func ChatFinishToAnthropic(reason string) string {
switch reason {
case "stop":
return "end_turn"
case "tool_calls":
return "tool_use"
case "length":
return "max_tokens"
default:
return "end_turn"
}
}
// AnthropicStopToChat maps an Anthropic stop_reason to a Chat Completions finish_reason.
func AnthropicStopToChat(reason string) string {
switch reason {
case "end_turn":
return "stop"
case "tool_use":
return "tool_calls"
case "max_tokens":
return "length"
default:
return "stop"
}
}
// ResponsesStatusToChat maps a Responses API status to a Chat Completions finish_reason.
func ResponsesStatusToChat(status string, details *ResponsesIncompleteDetails) string {
switch status {
case "completed":
return "stop"
case "incomplete":
if details != nil && details.Reason == "max_output_tokens" {
return "length"
}
return "stop"
default:
return "stop"
}
}
// ChatFinishToResponsesStatus maps a Chat Completions finish_reason to a Responses status.
func ChatFinishToResponsesStatus(reason string) string {
switch reason {
case "length":
return "incomplete"
default:
return "completed"
}
}
// ---------------------------------------------------------------------------
// Shared constants
// ---------------------------------------------------------------------------
// minMaxOutputTokens is the floor for max_output_tokens in a Responses request.
// Very small values may cause upstream API errors, so we enforce a minimum.
const minMaxOutputTokens = 128

View File

@@ -43,8 +43,28 @@ func RegisterGatewayRoutes(
gateway.Use(gin.HandlerFunc(apiKeyAuth)) gateway.Use(gin.HandlerFunc(apiKeyAuth))
gateway.Use(requireGroupAnthropic) gateway.Use(requireGroupAnthropic)
{ {
gateway.POST("/messages", h.Gateway.Messages) // /v1/messages: auto-route based on group platform
gateway.POST("/messages/count_tokens", h.Gateway.CountTokens) gateway.POST("/messages", func(c *gin.Context) {
if getGroupPlatform(c) == service.PlatformOpenAI {
h.OpenAIGateway.Messages(c)
return
}
h.Gateway.Messages(c)
})
// /v1/messages/count_tokens: OpenAI groups get 404
gateway.POST("/messages/count_tokens", func(c *gin.Context) {
if getGroupPlatform(c) == service.PlatformOpenAI {
c.JSON(http.StatusNotFound, gin.H{
"type": "error",
"error": gin.H{
"type": "not_found_error",
"message": "Token counting is not supported for this platform",
},
})
return
}
h.Gateway.CountTokens(c)
})
gateway.GET("/models", h.Gateway.Models) gateway.GET("/models", h.Gateway.Models)
gateway.GET("/usage", h.Gateway.Usage) gateway.GET("/usage", h.Gateway.Usage)
// OpenAI Responses API // OpenAI Responses API
@@ -132,3 +152,12 @@ func RegisterGatewayRoutes(
// Sora 媒体代理(签名 URL无需 API Key // Sora 媒体代理(签名 URL无需 API Key
r.GET("/sora/media-signed/*filepath", h.SoraGateway.MediaProxySigned) r.GET("/sora/media-signed/*filepath", h.SoraGateway.MediaProxySigned)
} }
// getGroupPlatform extracts the group platform from the API Key stored in context.
func getGroupPlatform(c *gin.Context) string {
apiKey, ok := middleware.GetAPIKeyFromContext(c)
if !ok || apiKey.Group == nil {
return ""
}
return apiKey.Group.Platform
}

View File

@@ -5421,6 +5421,11 @@ func extractUpstreamErrorMessage(body []byte) string {
return m return m
} }
// ChatGPT 内部 API 风格:{"detail":"..."}
if d := gjson.GetBytes(body, "detail").String(); strings.TrimSpace(d) != "" {
return d
}
// 兜底:尝试顶层 message // 兜底:尝试顶层 message
return gjson.GetBytes(body, "message").String() return gjson.GetBytes(body, "message").String()
} }

View File

@@ -0,0 +1,376 @@
package service
import (
"bufio"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"net/http"
"strings"
"time"
"github.com/Wei-Shaw/sub2api/internal/pkg/apicompat"
"github.com/Wei-Shaw/sub2api/internal/pkg/logger"
"github.com/Wei-Shaw/sub2api/internal/util/responseheaders"
"github.com/gin-gonic/gin"
"go.uber.org/zap"
)
// ForwardAsAnthropic accepts an Anthropic Messages request body, converts it
// to OpenAI Responses API format, forwards to the OpenAI upstream, and converts
// the response back to Anthropic Messages format. This enables Claude Code
// clients to access OpenAI models through the standard /v1/messages endpoint.
func (s *OpenAIGatewayService) ForwardAsAnthropic(
ctx context.Context,
c *gin.Context,
account *Account,
body []byte,
promptCacheKey string,
) (*OpenAIForwardResult, error) {
startTime := time.Now()
// 1. Parse Anthropic request
var anthropicReq apicompat.AnthropicRequest
if err := json.Unmarshal(body, &anthropicReq); err != nil {
return nil, fmt.Errorf("parse anthropic request: %w", err)
}
originalModel := anthropicReq.Model
isStream := anthropicReq.Stream
// 2. Convert Anthropic → Responses
responsesReq, err := apicompat.AnthropicToResponses(&anthropicReq)
if err != nil {
return nil, fmt.Errorf("convert anthropic to responses: %w", err)
}
// 3. Model mapping
mappedModel := account.GetMappedModel(originalModel)
responsesReq.Model = mappedModel
logger.L().Info("openai messages: model mapping applied",
zap.Int64("account_id", account.ID),
zap.String("original_model", originalModel),
zap.String("mapped_model", mappedModel),
zap.Bool("stream", isStream),
)
// 4. Marshal Responses request body, then apply OAuth codex transform
responsesBody, err := json.Marshal(responsesReq)
if err != nil {
return nil, fmt.Errorf("marshal responses request: %w", err)
}
if account.Type == AccountTypeOAuth {
var reqBody map[string]any
if err := json.Unmarshal(responsesBody, &reqBody); err != nil {
return nil, fmt.Errorf("unmarshal for codex transform: %w", err)
}
applyCodexOAuthTransform(reqBody, false)
// OAuth codex transform forces stream=true upstream, so always use
// the streaming response handler regardless of what the client asked.
isStream = true
responsesBody, err = json.Marshal(reqBody)
if err != nil {
return nil, fmt.Errorf("remarshal after codex transform: %w", err)
}
}
// 5. Get access token
token, _, err := s.GetAccessToken(ctx, account)
if err != nil {
return nil, fmt.Errorf("get access token: %w", err)
}
// 6. Build upstream request
upstreamReq, err := s.buildUpstreamRequest(ctx, c, account, responsesBody, token, isStream, promptCacheKey, false)
if err != nil {
return nil, fmt.Errorf("build upstream request: %w", err)
}
// 7. Send request
proxyURL := ""
if account.Proxy != nil {
proxyURL = account.Proxy.URL()
}
resp, err := s.httpUpstream.Do(upstreamReq, proxyURL, account.ID, account.Concurrency)
if err != nil {
safeErr := sanitizeUpstreamErrorMessage(err.Error())
setOpsUpstreamError(c, 0, safeErr, "")
appendOpsUpstreamError(c, OpsUpstreamErrorEvent{
Platform: account.Platform,
AccountID: account.ID,
AccountName: account.Name,
UpstreamStatusCode: 0,
Kind: "request_error",
Message: safeErr,
})
writeAnthropicError(c, http.StatusBadGateway, "api_error", "Upstream request failed")
return nil, fmt.Errorf("upstream request failed: %s", safeErr)
}
defer func() { _ = resp.Body.Close() }()
// 8. Handle error response with failover
if resp.StatusCode >= 400 {
if s.shouldFailoverUpstreamError(resp.StatusCode) {
respBody, _ := io.ReadAll(io.LimitReader(resp.Body, 2<<20))
_ = resp.Body.Close()
upstreamMsg := strings.TrimSpace(extractUpstreamErrorMessage(respBody))
upstreamMsg = sanitizeUpstreamErrorMessage(upstreamMsg)
upstreamDetail := ""
if s.cfg != nil && s.cfg.Gateway.LogUpstreamErrorBody {
maxBytes := s.cfg.Gateway.LogUpstreamErrorBodyMaxBytes
if maxBytes <= 0 {
maxBytes = 2048
}
upstreamDetail = truncateString(string(respBody), maxBytes)
}
appendOpsUpstreamError(c, OpsUpstreamErrorEvent{
Platform: account.Platform,
AccountID: account.ID,
AccountName: account.Name,
UpstreamStatusCode: resp.StatusCode,
UpstreamRequestID: resp.Header.Get("x-request-id"),
Kind: "failover",
Message: upstreamMsg,
Detail: upstreamDetail,
})
s.rateLimitService.HandleUpstreamError(ctx, account, resp.StatusCode, resp.Header, respBody)
return nil, &UpstreamFailoverError{StatusCode: resp.StatusCode, ResponseBody: respBody}
}
// Non-failover error: return Anthropic-formatted error to client
return s.handleAnthropicErrorResponse(resp, c)
}
// 9. Handle normal response
if isStream {
return s.handleAnthropicStreamingResponse(resp, c, originalModel, startTime)
}
return s.handleAnthropicNonStreamingResponse(resp, c, originalModel, startTime)
}
// handleAnthropicErrorResponse reads an upstream error and returns it in
// Anthropic error format.
func (s *OpenAIGatewayService) handleAnthropicErrorResponse(
resp *http.Response,
c *gin.Context,
) (*OpenAIForwardResult, error) {
body, _ := io.ReadAll(io.LimitReader(resp.Body, 2<<20))
upstreamMsg := strings.TrimSpace(extractUpstreamErrorMessage(body))
if upstreamMsg == "" {
upstreamMsg = fmt.Sprintf("Upstream error: %d", resp.StatusCode)
}
upstreamMsg = sanitizeUpstreamErrorMessage(upstreamMsg)
// Record upstream error details for ops logging
upstreamDetail := ""
if s.cfg != nil && s.cfg.Gateway.LogUpstreamErrorBody {
maxBytes := s.cfg.Gateway.LogUpstreamErrorBodyMaxBytes
if maxBytes <= 0 {
maxBytes = 2048
}
upstreamDetail = truncateString(string(body), maxBytes)
}
setOpsUpstreamError(c, resp.StatusCode, upstreamMsg, upstreamDetail)
errType := "api_error"
switch {
case resp.StatusCode == 400:
errType = "invalid_request_error"
case resp.StatusCode == 404:
errType = "not_found_error"
case resp.StatusCode == 429:
errType = "rate_limit_error"
case resp.StatusCode >= 500:
errType = "api_error"
}
writeAnthropicError(c, resp.StatusCode, errType, upstreamMsg)
return nil, fmt.Errorf("upstream error: %d %s", resp.StatusCode, upstreamMsg)
}
// handleAnthropicNonStreamingResponse reads a Responses API JSON response,
// converts it to Anthropic Messages format, and writes it to the client.
func (s *OpenAIGatewayService) handleAnthropicNonStreamingResponse(
resp *http.Response,
c *gin.Context,
originalModel string,
startTime time.Time,
) (*OpenAIForwardResult, error) {
requestID := resp.Header.Get("x-request-id")
respBody, err := io.ReadAll(resp.Body)
if err != nil {
return nil, fmt.Errorf("read upstream response: %w", err)
}
var responsesResp apicompat.ResponsesResponse
if err := json.Unmarshal(respBody, &responsesResp); err != nil {
return nil, fmt.Errorf("parse responses response: %w", err)
}
anthropicResp := apicompat.ResponsesToAnthropic(&responsesResp, originalModel)
var usage OpenAIUsage
if responsesResp.Usage != nil {
usage = OpenAIUsage{
InputTokens: responsesResp.Usage.InputTokens,
OutputTokens: responsesResp.Usage.OutputTokens,
}
if responsesResp.Usage.InputTokensDetails != nil {
usage.CacheReadInputTokens = responsesResp.Usage.InputTokensDetails.CachedTokens
}
}
if s.responseHeaderFilter != nil {
responseheaders.WriteFilteredHeaders(c.Writer.Header(), resp.Header, s.responseHeaderFilter)
}
c.JSON(http.StatusOK, anthropicResp)
return &OpenAIForwardResult{
RequestID: requestID,
Usage: usage,
Model: originalModel,
Stream: false,
Duration: time.Since(startTime),
}, nil
}
// handleAnthropicStreamingResponse reads Responses SSE events from upstream,
// converts each to Anthropic SSE events, and writes them to the client.
func (s *OpenAIGatewayService) handleAnthropicStreamingResponse(
resp *http.Response,
c *gin.Context,
originalModel string,
startTime time.Time,
) (*OpenAIForwardResult, error) {
requestID := resp.Header.Get("x-request-id")
if s.responseHeaderFilter != nil {
responseheaders.WriteFilteredHeaders(c.Writer.Header(), resp.Header, s.responseHeaderFilter)
}
c.Writer.Header().Set("Content-Type", "text/event-stream")
c.Writer.Header().Set("Cache-Control", "no-cache")
c.Writer.Header().Set("Connection", "keep-alive")
c.Writer.WriteHeader(http.StatusOK)
state := apicompat.NewResponsesEventToAnthropicState()
state.Model = originalModel
var usage OpenAIUsage
var firstTokenMs *int
firstChunk := true
scanner := bufio.NewScanner(resp.Body)
scanner.Buffer(make([]byte, 0, 64*1024), 1024*1024)
for scanner.Scan() {
line := scanner.Text()
if !strings.HasPrefix(line, "data: ") || line == "data: [DONE]" {
continue
}
payload := line[6:]
if firstChunk {
firstChunk = false
ms := int(time.Since(startTime).Milliseconds())
firstTokenMs = &ms
}
// Parse the Responses SSE event
var event apicompat.ResponsesStreamEvent
if err := json.Unmarshal([]byte(payload), &event); err != nil {
logger.L().Warn("openai messages stream: failed to parse event",
zap.Error(err),
zap.String("request_id", requestID),
)
continue
}
// Extract usage from completion events
if (event.Type == "response.completed" || event.Type == "response.incomplete") &&
event.Response != nil && event.Response.Usage != nil {
usage = OpenAIUsage{
InputTokens: event.Response.Usage.InputTokens,
OutputTokens: event.Response.Usage.OutputTokens,
}
if event.Response.Usage.InputTokensDetails != nil {
usage.CacheReadInputTokens = event.Response.Usage.InputTokensDetails.CachedTokens
}
}
// Convert to Anthropic events
events := apicompat.ResponsesEventToAnthropicEvents(&event, state)
for _, evt := range events {
sse, err := apicompat.ResponsesAnthropicEventToSSE(evt)
if err != nil {
logger.L().Warn("openai messages stream: failed to marshal event",
zap.Error(err),
zap.String("request_id", requestID),
)
continue
}
if _, err := fmt.Fprint(c.Writer, sse); err != nil {
// Client disconnected — return collected usage
logger.L().Info("openai messages stream: client disconnected",
zap.String("request_id", requestID),
)
return &OpenAIForwardResult{
RequestID: requestID,
Usage: usage,
Model: originalModel,
Stream: true,
Duration: time.Since(startTime),
FirstTokenMs: firstTokenMs,
}, nil
}
}
if len(events) > 0 {
c.Writer.Flush()
}
}
if err := scanner.Err(); err != nil {
if !errors.Is(err, context.Canceled) && !errors.Is(err, context.DeadlineExceeded) {
logger.L().Warn("openai messages stream: read error",
zap.Error(err),
zap.String("request_id", requestID),
)
}
}
// Ensure the Anthropic stream is properly terminated
if finalEvents := apicompat.FinalizeResponsesAnthropicStream(state); len(finalEvents) > 0 {
for _, evt := range finalEvents {
sse, err := apicompat.ResponsesAnthropicEventToSSE(evt)
if err != nil {
continue
}
fmt.Fprint(c.Writer, sse) //nolint:errcheck
}
c.Writer.Flush()
}
return &OpenAIForwardResult{
RequestID: requestID,
Usage: usage,
Model: originalModel,
Stream: true,
Duration: time.Since(startTime),
FirstTokenMs: firstTokenMs,
}, nil
}
// writeAnthropicError writes an error response in Anthropic Messages API format.
func writeAnthropicError(c *gin.Context, statusCode int, errType, message string) {
c.JSON(statusCode, gin.H{
"type": "error",
"error": gin.H{
"type": errType,
"message": message,
},
})
}

View File

@@ -888,6 +888,22 @@ func isOpenAIInstructionsRequiredError(upstreamStatusCode int, upstreamMsg strin
return false return false
} }
// ExtractSessionID extracts the raw session ID from headers or body without hashing.
// Used by ForwardAsAnthropic to pass as prompt_cache_key for upstream cache.
func (s *OpenAIGatewayService) ExtractSessionID(c *gin.Context, body []byte) string {
if c == nil {
return ""
}
sessionID := strings.TrimSpace(c.GetHeader("session_id"))
if sessionID == "" {
sessionID = strings.TrimSpace(c.GetHeader("conversation_id"))
}
if sessionID == "" && len(body) > 0 {
sessionID = strings.TrimSpace(gjson.GetBytes(body, "prompt_cache_key").String())
}
return sessionID
}
// GenerateSessionHash generates a sticky-session hash for OpenAI requests. // GenerateSessionHash generates a sticky-session hash for OpenAI requests.
// //
// Priority: // Priority:

View File

@@ -1230,6 +1230,142 @@
<!-- API Key 账号配额限制 --> <!-- API Key 账号配额限制 -->
<QuotaLimitCard v-if="form.type === 'apikey'" v-model="editQuotaLimit" /> <QuotaLimitCard v-if="form.type === 'apikey'" v-model="editQuotaLimit" />
<!-- OpenAI OAuth Model Mapping (OAuth 类型没有 apikey 容器需要独立的模型映射区域) -->
<div
v-if="form.platform === 'openai' && accountCategory === 'oauth-based'"
class="border-t border-gray-200 pt-4 dark:border-dark-600"
>
<label class="input-label">{{ t('admin.accounts.modelRestriction') }}</label>
<div
v-if="isOpenAIModelRestrictionDisabled"
class="mb-3 rounded-lg bg-amber-50 p-3 dark:bg-amber-900/20"
>
<p class="text-xs text-amber-700 dark:text-amber-400">
{{ t('admin.accounts.openai.modelRestrictionDisabledByPassthrough') }}
</p>
</div>
<template v-else>
<!-- Mode Toggle -->
<div class="mb-4 flex gap-2">
<button
type="button"
@click="modelRestrictionMode = 'whitelist'"
:class="[
'flex-1 rounded-lg px-4 py-2 text-sm font-medium transition-all',
modelRestrictionMode === 'whitelist'
? 'bg-primary-100 text-primary-700 dark:bg-primary-900/30 dark:text-primary-400'
: 'bg-gray-100 text-gray-600 hover:bg-gray-200 dark:bg-dark-600 dark:text-gray-400 dark:hover:bg-dark-500'
]"
>
{{ t('admin.accounts.modelWhitelist') }}
</button>
<button
type="button"
@click="modelRestrictionMode = 'mapping'"
:class="[
'flex-1 rounded-lg px-4 py-2 text-sm font-medium transition-all',
modelRestrictionMode === 'mapping'
? 'bg-purple-100 text-purple-700 dark:bg-purple-900/30 dark:text-purple-400'
: 'bg-gray-100 text-gray-600 hover:bg-gray-200 dark:bg-dark-600 dark:text-gray-400 dark:hover:bg-dark-500'
]"
>
{{ t('admin.accounts.modelMapping') }}
</button>
</div>
<!-- Whitelist Mode -->
<div v-if="modelRestrictionMode === 'whitelist'">
<ModelWhitelistSelector v-model="allowedModels" :platform="form.platform" />
<p class="text-xs text-gray-500 dark:text-gray-400">
{{ t('admin.accounts.selectedModels', { count: allowedModels.length }) }}
<span v-if="allowedModels.length === 0">{{
t('admin.accounts.supportsAllModels')
}}</span>
</p>
</div>
<!-- Mapping Mode -->
<div v-else>
<div class="mb-3 rounded-lg bg-purple-50 p-3 dark:bg-purple-900/20">
<p class="text-xs text-purple-700 dark:text-purple-400">
{{ t('admin.accounts.mapRequestModels') }}
</p>
</div>
<div v-if="modelMappings.length > 0" class="mb-3 space-y-2">
<div
v-for="(mapping, index) in modelMappings"
:key="'oauth-' + getModelMappingKey(mapping)"
class="flex items-center gap-2"
>
<input
v-model="mapping.from"
type="text"
class="input flex-1"
:placeholder="t('admin.accounts.requestModel')"
/>
<svg
class="h-4 w-4 flex-shrink-0 text-gray-400"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
stroke-width="2"
d="M14 5l7 7m0 0l-7 7m7-7H3"
/>
</svg>
<input
v-model="mapping.to"
type="text"
class="input flex-1"
:placeholder="t('admin.accounts.actualModel')"
/>
<button
type="button"
@click="removeModelMapping(index)"
class="rounded-lg p-2 text-red-500 transition-colors hover:bg-red-50 hover:text-red-600 dark:hover:bg-red-900/20"
>
<svg class="h-4 w-4" fill="none" viewBox="0 0 24 24" stroke="currentColor">
<path
stroke-linecap="round"
stroke-linejoin="round"
stroke-width="2"
d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"
/>
</svg>
</button>
</div>
</div>
<button
type="button"
@click="addModelMapping"
class="mb-3 w-full rounded-lg border-2 border-dashed border-gray-300 px-4 py-2 text-gray-600 transition-colors hover:border-gray-400 hover:text-gray-700 dark:border-dark-500 dark:text-gray-400 dark:hover:border-dark-400 dark:hover:text-gray-300"
>
+ {{ t('admin.accounts.addMapping') }}
</button>
<!-- Quick Add Buttons -->
<div class="flex flex-wrap gap-2">
<button
v-for="preset in presetMappings"
:key="'oauth-' + preset.label"
type="button"
@click="addPresetMapping(preset.from, preset.to)"
:class="['rounded-lg px-3 py-1 text-xs transition-colors', preset.color]"
>
+ {{ preset.label }}
</button>
</div>
</div>
</template>
</div>
<!-- Temp Unschedulable Rules --> <!-- Temp Unschedulable Rules -->
<div class="border-t border-gray-200 pt-4 dark:border-dark-600 space-y-4"> <div class="border-t border-gray-200 pt-4 dark:border-dark-600 space-y-4">
<div class="mb-3 flex items-center justify-between"> <div class="mb-3 flex items-center justify-between">
@@ -3603,6 +3739,14 @@ const handleOpenAIExchange = async (authCode: string) => {
const shouldCreateOpenAI = form.platform === 'openai' const shouldCreateOpenAI = form.platform === 'openai'
const shouldCreateSora = form.platform === 'sora' const shouldCreateSora = form.platform === 'sora'
// Add model mapping for OpenAI OAuth accounts透传模式下不应用
if (shouldCreateOpenAI && !isOpenAIModelRestrictionDisabled.value) {
const modelMapping = buildModelMappingObject(modelRestrictionMode.value, allowedModels.value, modelMappings.value)
if (modelMapping) {
credentials.model_mapping = modelMapping
}
}
// 应用临时不可调度配置 // 应用临时不可调度配置
if (!applyTempUnschedConfig(credentials)) { if (!applyTempUnschedConfig(credentials)) {
return return
@@ -3713,6 +3857,14 @@ const handleOpenAIValidateRT = async (refreshTokenInput: string) => {
const oauthExtra = oauthClient.buildExtraInfo(tokenInfo) as Record<string, unknown> | undefined const oauthExtra = oauthClient.buildExtraInfo(tokenInfo) as Record<string, unknown> | undefined
const extra = buildOpenAIExtra(oauthExtra) const extra = buildOpenAIExtra(oauthExtra)
// Add model mapping for OpenAI OAuth accounts透传模式下不应用
if (shouldCreateOpenAI && !isOpenAIModelRestrictionDisabled.value) {
const modelMapping = buildModelMappingObject(modelRestrictionMode.value, allowedModels.value, modelMappings.value)
if (modelMapping) {
credentials.model_mapping = modelMapping
}
}
// Generate account name with index for batch // Generate account name with index for batch
const accountName = refreshTokens.length > 1 ? `${form.name} #${i + 1}` : form.name const accountName = refreshTokens.length > 1 ? `${form.name} #${i + 1}` : form.name

View File

@@ -351,6 +351,142 @@
</div> </div>
<!-- OpenAI OAuth Model Mapping (OAuth 类型没有 apikey 容器需要独立的模型映射区域) -->
<div
v-if="account.platform === 'openai' && account.type === 'oauth'"
class="border-t border-gray-200 pt-4 dark:border-dark-600"
>
<label class="input-label">{{ t('admin.accounts.modelRestriction') }}</label>
<div
v-if="isOpenAIModelRestrictionDisabled"
class="mb-3 rounded-lg bg-amber-50 p-3 dark:bg-amber-900/20"
>
<p class="text-xs text-amber-700 dark:text-amber-400">
{{ t('admin.accounts.openai.modelRestrictionDisabledByPassthrough') }}
</p>
</div>
<template v-else>
<!-- Mode Toggle -->
<div class="mb-4 flex gap-2">
<button
type="button"
@click="modelRestrictionMode = 'whitelist'"
:class="[
'flex-1 rounded-lg px-4 py-2 text-sm font-medium transition-all',
modelRestrictionMode === 'whitelist'
? 'bg-primary-100 text-primary-700 dark:bg-primary-900/30 dark:text-primary-400'
: 'bg-gray-100 text-gray-600 hover:bg-gray-200 dark:bg-dark-600 dark:text-gray-400 dark:hover:bg-dark-500'
]"
>
{{ t('admin.accounts.modelWhitelist') }}
</button>
<button
type="button"
@click="modelRestrictionMode = 'mapping'"
:class="[
'flex-1 rounded-lg px-4 py-2 text-sm font-medium transition-all',
modelRestrictionMode === 'mapping'
? 'bg-purple-100 text-purple-700 dark:bg-purple-900/30 dark:text-purple-400'
: 'bg-gray-100 text-gray-600 hover:bg-gray-200 dark:bg-dark-600 dark:text-gray-400 dark:hover:bg-dark-500'
]"
>
{{ t('admin.accounts.modelMapping') }}
</button>
</div>
<!-- Whitelist Mode -->
<div v-if="modelRestrictionMode === 'whitelist'">
<ModelWhitelistSelector v-model="allowedModels" :platform="account?.platform || 'anthropic'" />
<p class="text-xs text-gray-500 dark:text-gray-400">
{{ t('admin.accounts.selectedModels', { count: allowedModels.length }) }}
<span v-if="allowedModels.length === 0">{{
t('admin.accounts.supportsAllModels')
}}</span>
</p>
</div>
<!-- Mapping Mode -->
<div v-else>
<div class="mb-3 rounded-lg bg-purple-50 p-3 dark:bg-purple-900/20">
<p class="text-xs text-purple-700 dark:text-purple-400">
{{ t('admin.accounts.mapRequestModels') }}
</p>
</div>
<div v-if="modelMappings.length > 0" class="mb-3 space-y-2">
<div
v-for="(mapping, index) in modelMappings"
:key="'oauth-' + getModelMappingKey(mapping)"
class="flex items-center gap-2"
>
<input
v-model="mapping.from"
type="text"
class="input flex-1"
:placeholder="t('admin.accounts.requestModel')"
/>
<svg
class="h-4 w-4 flex-shrink-0 text-gray-400"
fill="none"
viewBox="0 0 24 24"
stroke="currentColor"
>
<path
stroke-linecap="round"
stroke-linejoin="round"
stroke-width="2"
d="M14 5l7 7m0 0l-7 7m7-7H3"
/>
</svg>
<input
v-model="mapping.to"
type="text"
class="input flex-1"
:placeholder="t('admin.accounts.actualModel')"
/>
<button
type="button"
@click="removeModelMapping(index)"
class="rounded-lg p-2 text-red-500 transition-colors hover:bg-red-50 hover:text-red-600 dark:hover:bg-red-900/20"
>
<svg class="h-4 w-4" fill="none" viewBox="0 0 24 24" stroke="currentColor">
<path
stroke-linecap="round"
stroke-linejoin="round"
stroke-width="2"
d="M19 7l-.867 12.142A2 2 0 0116.138 21H7.862a2 2 0 01-1.995-1.858L5 7m5 4v6m4-6v6m1-10V4a1 1 0 00-1-1h-4a1 1 0 00-1 1v3M4 7h16"
/>
</svg>
</button>
</div>
</div>
<button
type="button"
@click="addModelMapping"
class="mb-3 w-full rounded-lg border-2 border-dashed border-gray-300 px-4 py-2 text-gray-600 transition-colors hover:border-gray-400 hover:text-gray-700 dark:border-dark-500 dark:text-gray-400 dark:hover:border-dark-400 dark:hover:text-gray-300"
>
+ {{ t('admin.accounts.addMapping') }}
</button>
<!-- Quick Add Buttons -->
<div class="flex flex-wrap gap-2">
<button
v-for="preset in presetMappings"
:key="'oauth-' + preset.label"
type="button"
@click="addPresetMapping(preset.from, preset.to)"
:class="['rounded-lg px-3 py-1 text-xs transition-colors', preset.color]"
>
+ {{ preset.label }}
</button>
</div>
</div>
</template>
</div>
<!-- Upstream fields (only for upstream type) --> <!-- Upstream fields (only for upstream type) -->
<div v-if="account.type === 'upstream'" class="space-y-4"> <div v-if="account.type === 'upstream'" class="space-y-4">
<div> <div>
@@ -1659,9 +1795,33 @@ watch(
? 'https://generativelanguage.googleapis.com' ? 'https://generativelanguage.googleapis.com'
: 'https://api.anthropic.com' : 'https://api.anthropic.com'
editBaseUrl.value = platformDefaultUrl editBaseUrl.value = platformDefaultUrl
modelRestrictionMode.value = 'whitelist'
modelMappings.value = [] // Load model mappings for OpenAI OAuth accounts
allowedModels.value = [] if (newAccount.platform === 'openai' && newAccount.credentials) {
const oauthCredentials = newAccount.credentials as Record<string, unknown>
const existingMappings = oauthCredentials.model_mapping as Record<string, string> | undefined
if (existingMappings && typeof existingMappings === 'object') {
const entries = Object.entries(existingMappings)
const isWhitelistMode = entries.length > 0 && entries.every(([from, to]) => from === to)
if (isWhitelistMode) {
modelRestrictionMode.value = 'whitelist'
allowedModels.value = entries.map(([from]) => from)
modelMappings.value = []
} else {
modelRestrictionMode.value = 'mapping'
modelMappings.value = entries.map(([from, to]) => ({ from, to }))
allowedModels.value = []
}
} else {
modelRestrictionMode.value = 'whitelist'
modelMappings.value = []
allowedModels.value = []
}
} else {
modelRestrictionMode.value = 'whitelist'
modelMappings.value = []
allowedModels.value = []
}
customErrorCodesEnabled.value = false customErrorCodesEnabled.value = false
selectedErrorCodes.value = [] selectedErrorCodes.value = []
} }
@@ -2163,6 +2323,28 @@ const handleSubmit = async () => {
updatePayload.credentials = newCredentials updatePayload.credentials = newCredentials
} }
// OpenAI OAuth: persist model mapping to credentials
if (props.account.platform === 'openai' && props.account.type === 'oauth') {
const currentCredentials = (updatePayload.credentials as Record<string, unknown>) ||
((props.account.credentials as Record<string, unknown>) || {})
const newCredentials: Record<string, unknown> = { ...currentCredentials }
const shouldApplyModelMapping = !openaiPassthroughEnabled.value
if (shouldApplyModelMapping) {
const modelMapping = buildModelMappingObject(modelRestrictionMode.value, allowedModels.value, modelMappings.value)
if (modelMapping) {
newCredentials.model_mapping = modelMapping
} else {
delete newCredentials.model_mapping
}
} else if (currentCredentials.model_mapping) {
// 透传模式保留现有映射
newCredentials.model_mapping = currentCredentials.model_mapping
}
updatePayload.credentials = newCredentials
}
// Antigravity: persist model mapping to credentials (applies to all antigravity types) // Antigravity: persist model mapping to credentials (applies to all antigravity types)
// Antigravity 只支持映射模式 // Antigravity 只支持映射模式
if (props.account.platform === 'antigravity') { if (props.account.platform === 'antigravity') {