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https://github.com/router-for-me/CLIProxyAPI.git
synced 2026-02-05 22:10:51 +08:00
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12 Commits
| Author | SHA1 | Date | |
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750b930679 | ||
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3902fd7501 | ||
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2d2f4572a7 | ||
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8f4c46f38d | ||
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b6ba51bc2a | ||
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6a66d32d37 | ||
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47b9503112 | ||
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3b9253c2be | ||
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d241359153 | ||
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f4d4249ba5 |
@@ -740,7 +740,7 @@ func GetIFlowModels() []*ModelInfo {
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{ID: "qwen3-235b-a22b-thinking-2507", DisplayName: "Qwen3-235B-A22B-Thinking", Description: "Qwen3 235B A22B Thinking (2507)", Created: 1753401600},
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{ID: "qwen3-235b-a22b-instruct", DisplayName: "Qwen3-235B-A22B-Instruct", Description: "Qwen3 235B A22B Instruct", Created: 1753401600},
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{ID: "qwen3-235b", DisplayName: "Qwen3-235B-A22B", Description: "Qwen3 235B A22B", Created: 1753401600},
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{ID: "minimax-m2", DisplayName: "MiniMax-M2", Description: "MiniMax M2", Created: 1758672000},
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{ID: "minimax-m2", DisplayName: "MiniMax-M2", Description: "MiniMax M2", Created: 1758672000, Thinking: iFlowThinkingSupport},
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{ID: "minimax-m2.1", DisplayName: "MiniMax-M2.1", Description: "MiniMax M2.1", Created: 1766448000, Thinking: iFlowThinkingSupport},
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}
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models := make([]*ModelInfo, 0, len(entries))
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@@ -625,6 +625,131 @@ func (r *ModelRegistry) GetAvailableModels(handlerType string) []map[string]any
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return models
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}
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// GetAvailableModelsByProvider returns models available for the given provider identifier.
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// Parameters:
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// - provider: Provider identifier (e.g., "codex", "gemini", "antigravity")
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//
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// Returns:
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// - []*ModelInfo: List of available models for the provider
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func (r *ModelRegistry) GetAvailableModelsByProvider(provider string) []*ModelInfo {
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provider = strings.ToLower(strings.TrimSpace(provider))
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if provider == "" {
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return nil
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}
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r.mutex.RLock()
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defer r.mutex.RUnlock()
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type providerModel struct {
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count int
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info *ModelInfo
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}
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providerModels := make(map[string]*providerModel)
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for clientID, clientProvider := range r.clientProviders {
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if clientProvider != provider {
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continue
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}
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modelIDs := r.clientModels[clientID]
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if len(modelIDs) == 0 {
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continue
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}
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clientInfos := r.clientModelInfos[clientID]
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for _, modelID := range modelIDs {
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modelID = strings.TrimSpace(modelID)
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if modelID == "" {
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continue
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}
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entry := providerModels[modelID]
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if entry == nil {
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entry = &providerModel{}
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providerModels[modelID] = entry
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}
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entry.count++
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if entry.info == nil {
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if clientInfos != nil {
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if info := clientInfos[modelID]; info != nil {
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entry.info = info
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}
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}
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if entry.info == nil {
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if reg, ok := r.models[modelID]; ok && reg != nil && reg.Info != nil {
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entry.info = reg.Info
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}
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}
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}
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}
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}
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if len(providerModels) == 0 {
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return nil
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}
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quotaExpiredDuration := 5 * time.Minute
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now := time.Now()
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result := make([]*ModelInfo, 0, len(providerModels))
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for modelID, entry := range providerModels {
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if entry == nil || entry.count <= 0 {
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continue
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}
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registration, ok := r.models[modelID]
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expiredClients := 0
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cooldownSuspended := 0
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otherSuspended := 0
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if ok && registration != nil {
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if registration.QuotaExceededClients != nil {
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for clientID, quotaTime := range registration.QuotaExceededClients {
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if clientID == "" {
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continue
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}
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if p, okProvider := r.clientProviders[clientID]; !okProvider || p != provider {
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continue
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}
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if quotaTime != nil && now.Sub(*quotaTime) < quotaExpiredDuration {
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expiredClients++
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}
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}
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}
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if registration.SuspendedClients != nil {
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for clientID, reason := range registration.SuspendedClients {
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if clientID == "" {
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continue
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}
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if p, okProvider := r.clientProviders[clientID]; !okProvider || p != provider {
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continue
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}
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if strings.EqualFold(reason, "quota") {
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cooldownSuspended++
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continue
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}
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otherSuspended++
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}
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}
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}
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availableClients := entry.count
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effectiveClients := availableClients - expiredClients - otherSuspended
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if effectiveClients < 0 {
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effectiveClients = 0
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}
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if effectiveClients > 0 || (availableClients > 0 && (expiredClients > 0 || cooldownSuspended > 0) && otherSuspended == 0) {
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if entry.info != nil {
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result = append(result, entry.info)
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continue
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}
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if ok && registration != nil && registration.Info != nil {
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result = append(result, registration.Info)
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}
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}
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}
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return result
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}
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// GetModelCount returns the number of available clients for a specific model
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// Parameters:
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// - modelID: The model ID to check
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@@ -441,21 +441,18 @@ func ensureToolsArray(body []byte) []byte {
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return updated
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}
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// preserveReasoningContentInMessages ensures reasoning_content from assistant messages in the
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// conversation history is preserved when sending to iFlow models that support thinking.
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// This is critical for multi-turn conversations where the model needs to see its previous
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// reasoning to maintain coherent thought chains across tool calls and conversation turns.
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// preserveReasoningContentInMessages checks if reasoning_content from assistant messages
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// is preserved in conversation history for iFlow models that support thinking.
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// This is helpful for multi-turn conversations where the model may benefit from seeing
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// its previous reasoning to maintain coherent thought chains.
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//
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// For GLM-4.7 and MiniMax-M2.1, the full assistant response (including reasoning) must be
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// appended back into message history before the next call.
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// For GLM-4.6/4.7 and MiniMax M2/M2.1, it is recommended to include the full assistant
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// response (including reasoning_content) in message history for better context continuity.
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func preserveReasoningContentInMessages(body []byte) []byte {
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model := strings.ToLower(gjson.GetBytes(body, "model").String())
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// Only apply to models that support thinking with history preservation
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needsPreservation := strings.HasPrefix(model, "glm-4.7") ||
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strings.HasPrefix(model, "glm-4-7") ||
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strings.HasPrefix(model, "minimax-m2.1") ||
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strings.HasPrefix(model, "minimax-m2-1")
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needsPreservation := strings.HasPrefix(model, "glm-4") || strings.HasPrefix(model, "minimax-m2")
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if !needsPreservation {
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return body
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@@ -493,45 +490,35 @@ func preserveReasoningContentInMessages(body []byte) []byte {
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// This should be called after NormalizeThinkingConfig has processed the payload.
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//
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// Model-specific handling:
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// - GLM-4.7: Uses extra_body={"thinking": {"type": "enabled"}, "clear_thinking": false}
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// - MiniMax-M2.1: Uses reasoning_split=true for OpenAI-style reasoning separation
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// - Other iFlow models: Uses chat_template_kwargs.enable_thinking (boolean)
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// - GLM-4.6/4.7: Uses chat_template_kwargs.enable_thinking (boolean) and chat_template_kwargs.clear_thinking=false
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// - MiniMax M2/M2.1: Uses reasoning_split=true for OpenAI-style reasoning separation
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func applyIFlowThinkingConfig(body []byte) []byte {
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effort := gjson.GetBytes(body, "reasoning_effort")
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model := strings.ToLower(gjson.GetBytes(body, "model").String())
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// Check if thinking should be enabled
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val := ""
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if effort.Exists() {
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val = strings.ToLower(strings.TrimSpace(effort.String()))
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if !effort.Exists() {
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return body
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}
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enableThinking := effort.Exists() && val != "none" && val != ""
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model := strings.ToLower(gjson.GetBytes(body, "model").String())
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val := strings.ToLower(strings.TrimSpace(effort.String()))
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enableThinking := val != "none" && val != ""
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// Remove reasoning_effort as we'll convert to model-specific format
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if effort.Exists() {
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body, _ = sjson.DeleteBytes(body, "reasoning_effort")
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}
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body, _ = sjson.DeleteBytes(body, "reasoning_effort")
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body, _ = sjson.DeleteBytes(body, "thinking")
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// GLM-4.7: Use extra_body with thinking config and clear_thinking: false
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if strings.HasPrefix(model, "glm-4.7") || strings.HasPrefix(model, "glm-4-7") {
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if enableThinking {
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body, _ = sjson.SetBytes(body, "extra_body.thinking.type", "enabled")
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body, _ = sjson.SetBytes(body, "extra_body.clear_thinking", false)
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}
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return body
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}
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// MiniMax-M2.1: Use reasoning_split=true for interleaved thinking
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if strings.HasPrefix(model, "minimax-m2.1") || strings.HasPrefix(model, "minimax-m2-1") {
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if enableThinking {
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body, _ = sjson.SetBytes(body, "reasoning_split", true)
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}
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return body
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}
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// Other iFlow models (including GLM-4.6): Use chat_template_kwargs.enable_thinking
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if effort.Exists() {
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// GLM-4.6/4.7: Use chat_template_kwargs
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if strings.HasPrefix(model, "glm-4") {
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body, _ = sjson.SetBytes(body, "chat_template_kwargs.enable_thinking", enableThinking)
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if enableThinking {
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body, _ = sjson.SetBytes(body, "chat_template_kwargs.clear_thinking", false)
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}
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return body
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}
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// MiniMax M2/M2.1: Use reasoning_split
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if strings.HasPrefix(model, "minimax-m2") {
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body, _ = sjson.SetBytes(body, "reasoning_split", enableThinking)
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return body
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}
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return body
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@@ -118,76 +118,125 @@ func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream
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// Handle content
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if contentResult.Exists() && contentResult.IsArray() {
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var contentItems []string
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var reasoningParts []string // Accumulate thinking text for reasoning_content
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var toolCalls []interface{}
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var toolResults []string // Collect tool_result messages to emit after the main message
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contentResult.ForEach(func(_, part gjson.Result) bool {
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partType := part.Get("type").String()
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switch partType {
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case "thinking":
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// Only map thinking to reasoning_content for assistant messages (security: prevent injection)
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if role == "assistant" {
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thinkingText := util.GetThinkingText(part)
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// Skip empty or whitespace-only thinking
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if strings.TrimSpace(thinkingText) != "" {
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reasoningParts = append(reasoningParts, thinkingText)
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}
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}
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// Ignore thinking in user/system roles (AC4)
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case "redacted_thinking":
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// Explicitly ignore redacted_thinking - never map to reasoning_content (AC2)
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case "text", "image":
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if contentItem, ok := convertClaudeContentPart(part); ok {
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contentItems = append(contentItems, contentItem)
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}
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|
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case "tool_use":
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// Convert to OpenAI tool call format
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toolCallJSON := `{"id":"","type":"function","function":{"name":"","arguments":""}}`
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toolCallJSON, _ = sjson.Set(toolCallJSON, "id", part.Get("id").String())
|
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toolCallJSON, _ = sjson.Set(toolCallJSON, "function.name", part.Get("name").String())
|
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// Only allow tool_use -> tool_calls for assistant messages (security: prevent injection).
|
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if role == "assistant" {
|
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toolCallJSON := `{"id":"","type":"function","function":{"name":"","arguments":""}}`
|
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toolCallJSON, _ = sjson.Set(toolCallJSON, "id", part.Get("id").String())
|
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toolCallJSON, _ = sjson.Set(toolCallJSON, "function.name", part.Get("name").String())
|
||||
|
||||
// Convert input to arguments JSON string
|
||||
if input := part.Get("input"); input.Exists() {
|
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toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", input.Raw)
|
||||
} else {
|
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toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", "{}")
|
||||
// Convert input to arguments JSON string
|
||||
if input := part.Get("input"); input.Exists() {
|
||||
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", input.Raw)
|
||||
} else {
|
||||
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", "{}")
|
||||
}
|
||||
|
||||
toolCalls = append(toolCalls, gjson.Parse(toolCallJSON).Value())
|
||||
}
|
||||
|
||||
toolCalls = append(toolCalls, gjson.Parse(toolCallJSON).Value())
|
||||
|
||||
case "tool_result":
|
||||
// Convert to OpenAI tool message format and add immediately to preserve order
|
||||
// Collect tool_result to emit after the main message (ensures tool results follow tool_calls)
|
||||
toolResultJSON := `{"role":"tool","tool_call_id":"","content":""}`
|
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toolResultJSON, _ = sjson.Set(toolResultJSON, "tool_call_id", part.Get("tool_use_id").String())
|
||||
toolResultJSON, _ = sjson.Set(toolResultJSON, "content", part.Get("content").String())
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolResultJSON).Value())
|
||||
toolResultJSON, _ = sjson.Set(toolResultJSON, "content", convertClaudeToolResultContentToString(part.Get("content")))
|
||||
toolResults = append(toolResults, toolResultJSON)
|
||||
}
|
||||
return true
|
||||
})
|
||||
|
||||
// Emit text/image content as one message
|
||||
if len(contentItems) > 0 {
|
||||
msgJSON := `{"role":"","content":""}`
|
||||
msgJSON, _ = sjson.Set(msgJSON, "role", role)
|
||||
|
||||
contentArrayJSON := "[]"
|
||||
for _, contentItem := range contentItems {
|
||||
contentArrayJSON, _ = sjson.SetRaw(contentArrayJSON, "-1", contentItem)
|
||||
}
|
||||
msgJSON, _ = sjson.SetRaw(msgJSON, "content", contentArrayJSON)
|
||||
|
||||
contentValue := gjson.Get(msgJSON, "content")
|
||||
hasContent := false
|
||||
switch {
|
||||
case !contentValue.Exists():
|
||||
hasContent = false
|
||||
case contentValue.Type == gjson.String:
|
||||
hasContent = contentValue.String() != ""
|
||||
case contentValue.IsArray():
|
||||
hasContent = len(contentValue.Array()) > 0
|
||||
default:
|
||||
hasContent = contentValue.Raw != "" && contentValue.Raw != "null"
|
||||
}
|
||||
|
||||
if hasContent {
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
|
||||
}
|
||||
// Build reasoning content string
|
||||
reasoningContent := ""
|
||||
if len(reasoningParts) > 0 {
|
||||
reasoningContent = strings.Join(reasoningParts, "\n\n")
|
||||
}
|
||||
|
||||
// Emit tool calls in a separate assistant message
|
||||
if role == "assistant" && len(toolCalls) > 0 {
|
||||
toolCallMsgJSON := `{"role":"assistant","tool_calls":[]}`
|
||||
toolCallMsgJSON, _ = sjson.Set(toolCallMsgJSON, "tool_calls", toolCalls)
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolCallMsgJSON).Value())
|
||||
hasContent := len(contentItems) > 0
|
||||
hasReasoning := reasoningContent != ""
|
||||
hasToolCalls := len(toolCalls) > 0
|
||||
hasToolResults := len(toolResults) > 0
|
||||
|
||||
// OpenAI requires: tool messages MUST immediately follow the assistant message with tool_calls.
|
||||
// Therefore, we emit tool_result messages FIRST (they respond to the previous assistant's tool_calls),
|
||||
// then emit the current message's content.
|
||||
for _, toolResultJSON := range toolResults {
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolResultJSON).Value())
|
||||
}
|
||||
|
||||
// For assistant messages: emit a single unified message with content, tool_calls, and reasoning_content
|
||||
// This avoids splitting into multiple assistant messages which breaks OpenAI tool-call adjacency
|
||||
if role == "assistant" {
|
||||
if hasContent || hasReasoning || hasToolCalls {
|
||||
msgJSON := `{"role":"assistant"}`
|
||||
|
||||
// Add content (as array if we have items, empty string if reasoning-only)
|
||||
if hasContent {
|
||||
contentArrayJSON := "[]"
|
||||
for _, contentItem := range contentItems {
|
||||
contentArrayJSON, _ = sjson.SetRaw(contentArrayJSON, "-1", contentItem)
|
||||
}
|
||||
msgJSON, _ = sjson.SetRaw(msgJSON, "content", contentArrayJSON)
|
||||
} else {
|
||||
// Ensure content field exists for OpenAI compatibility
|
||||
msgJSON, _ = sjson.Set(msgJSON, "content", "")
|
||||
}
|
||||
|
||||
// Add reasoning_content if present
|
||||
if hasReasoning {
|
||||
msgJSON, _ = sjson.Set(msgJSON, "reasoning_content", reasoningContent)
|
||||
}
|
||||
|
||||
// Add tool_calls if present (in same message as content)
|
||||
if hasToolCalls {
|
||||
msgJSON, _ = sjson.Set(msgJSON, "tool_calls", toolCalls)
|
||||
}
|
||||
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
|
||||
}
|
||||
} else {
|
||||
// For non-assistant roles: emit content message if we have content
|
||||
// If the message only contains tool_results (no text/image), we still processed them above
|
||||
if hasContent {
|
||||
msgJSON := `{"role":""}`
|
||||
msgJSON, _ = sjson.Set(msgJSON, "role", role)
|
||||
|
||||
contentArrayJSON := "[]"
|
||||
for _, contentItem := range contentItems {
|
||||
contentArrayJSON, _ = sjson.SetRaw(contentArrayJSON, "-1", contentItem)
|
||||
}
|
||||
msgJSON, _ = sjson.SetRaw(msgJSON, "content", contentArrayJSON)
|
||||
|
||||
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
|
||||
} else if hasToolResults && !hasContent {
|
||||
// tool_results already emitted above, no additional user message needed
|
||||
}
|
||||
}
|
||||
|
||||
} else if contentResult.Exists() && contentResult.Type == gjson.String {
|
||||
@@ -307,3 +356,43 @@ func convertClaudeContentPart(part gjson.Result) (string, bool) {
|
||||
return "", false
|
||||
}
|
||||
}
|
||||
|
||||
func convertClaudeToolResultContentToString(content gjson.Result) string {
|
||||
if !content.Exists() {
|
||||
return ""
|
||||
}
|
||||
|
||||
if content.Type == gjson.String {
|
||||
return content.String()
|
||||
}
|
||||
|
||||
if content.IsArray() {
|
||||
var parts []string
|
||||
content.ForEach(func(_, item gjson.Result) bool {
|
||||
switch {
|
||||
case item.Type == gjson.String:
|
||||
parts = append(parts, item.String())
|
||||
case item.IsObject() && item.Get("text").Exists() && item.Get("text").Type == gjson.String:
|
||||
parts = append(parts, item.Get("text").String())
|
||||
default:
|
||||
parts = append(parts, item.Raw)
|
||||
}
|
||||
return true
|
||||
})
|
||||
|
||||
joined := strings.Join(parts, "\n\n")
|
||||
if strings.TrimSpace(joined) != "" {
|
||||
return joined
|
||||
}
|
||||
return content.Raw
|
||||
}
|
||||
|
||||
if content.IsObject() {
|
||||
if text := content.Get("text"); text.Exists() && text.Type == gjson.String {
|
||||
return text.String()
|
||||
}
|
||||
return content.Raw
|
||||
}
|
||||
|
||||
return content.Raw
|
||||
}
|
||||
|
||||
500
internal/translator/openai/claude/openai_claude_request_test.go
Normal file
500
internal/translator/openai/claude/openai_claude_request_test.go
Normal file
@@ -0,0 +1,500 @@
|
||||
package claude
|
||||
|
||||
import (
|
||||
"testing"
|
||||
|
||||
"github.com/tidwall/gjson"
|
||||
)
|
||||
|
||||
// TestConvertClaudeRequestToOpenAI_ThinkingToReasoningContent tests the mapping
|
||||
// of Claude thinking content to OpenAI reasoning_content field.
|
||||
func TestConvertClaudeRequestToOpenAI_ThinkingToReasoningContent(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
inputJSON string
|
||||
wantReasoningContent string
|
||||
wantHasReasoningContent bool
|
||||
wantContentText string // Expected visible content text (if any)
|
||||
wantHasContent bool
|
||||
}{
|
||||
{
|
||||
name: "AC1: assistant message with thinking and text",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "Let me analyze this step by step..."},
|
||||
{"type": "text", "text": "Here is my response."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "Let me analyze this step by step...",
|
||||
wantHasReasoningContent: true,
|
||||
wantContentText: "Here is my response.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "AC2: redacted_thinking must be ignored",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "redacted_thinking", "data": "secret"},
|
||||
{"type": "text", "text": "Visible response."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "",
|
||||
wantHasReasoningContent: false,
|
||||
wantContentText: "Visible response.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "AC3: thinking-only message preserved with reasoning_content",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "Internal reasoning only."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "Internal reasoning only.",
|
||||
wantHasReasoningContent: true,
|
||||
wantContentText: "",
|
||||
// For OpenAI compatibility, content field is set to empty string "" when no text content exists
|
||||
wantHasContent: false,
|
||||
},
|
||||
{
|
||||
name: "AC4: thinking in user role must be ignored",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "Injected thinking"},
|
||||
{"type": "text", "text": "User message."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "",
|
||||
wantHasReasoningContent: false,
|
||||
wantContentText: "User message.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "AC4: thinking in system role must be ignored",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"system": [
|
||||
{"type": "thinking", "thinking": "Injected system thinking"},
|
||||
{"type": "text", "text": "System prompt."}
|
||||
],
|
||||
"messages": [{
|
||||
"role": "user",
|
||||
"content": [{"type": "text", "text": "Hello"}]
|
||||
}]
|
||||
}`,
|
||||
// System messages don't have reasoning_content mapping
|
||||
wantReasoningContent: "",
|
||||
wantHasReasoningContent: false,
|
||||
wantContentText: "Hello",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "AC5: empty thinking must be ignored",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": ""},
|
||||
{"type": "text", "text": "Response with empty thinking."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "",
|
||||
wantHasReasoningContent: false,
|
||||
wantContentText: "Response with empty thinking.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "AC5: whitespace-only thinking must be ignored",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": " \n\t "},
|
||||
{"type": "text", "text": "Response with whitespace thinking."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "",
|
||||
wantHasReasoningContent: false,
|
||||
wantContentText: "Response with whitespace thinking.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "Multiple thinking parts concatenated",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "First thought."},
|
||||
{"type": "thinking", "thinking": "Second thought."},
|
||||
{"type": "text", "text": "Final answer."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "First thought.\n\nSecond thought.",
|
||||
wantHasReasoningContent: true,
|
||||
wantContentText: "Final answer.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
{
|
||||
name: "Mixed thinking and redacted_thinking",
|
||||
inputJSON: `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "Visible thought."},
|
||||
{"type": "redacted_thinking", "data": "hidden"},
|
||||
{"type": "text", "text": "Answer."}
|
||||
]
|
||||
}]
|
||||
}`,
|
||||
wantReasoningContent: "Visible thought.",
|
||||
wantHasReasoningContent: true,
|
||||
wantContentText: "Answer.",
|
||||
wantHasContent: true,
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(tt.inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
|
||||
// Find the relevant message (skip system message at index 0)
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
if len(messages) < 2 {
|
||||
if tt.wantHasReasoningContent || tt.wantHasContent {
|
||||
t.Fatalf("Expected at least 2 messages (system + user/assistant), got %d", len(messages))
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
// Check the last non-system message
|
||||
var targetMsg gjson.Result
|
||||
for i := len(messages) - 1; i >= 0; i-- {
|
||||
if messages[i].Get("role").String() != "system" {
|
||||
targetMsg = messages[i]
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
// Check reasoning_content
|
||||
gotReasoningContent := targetMsg.Get("reasoning_content").String()
|
||||
gotHasReasoningContent := targetMsg.Get("reasoning_content").Exists()
|
||||
|
||||
if gotHasReasoningContent != tt.wantHasReasoningContent {
|
||||
t.Errorf("reasoning_content existence = %v, want %v", gotHasReasoningContent, tt.wantHasReasoningContent)
|
||||
}
|
||||
|
||||
if gotReasoningContent != tt.wantReasoningContent {
|
||||
t.Errorf("reasoning_content = %q, want %q", gotReasoningContent, tt.wantReasoningContent)
|
||||
}
|
||||
|
||||
// Check content
|
||||
content := targetMsg.Get("content")
|
||||
// content has meaningful content if it's a non-empty array, or a non-empty string
|
||||
var gotHasContent bool
|
||||
switch {
|
||||
case content.IsArray():
|
||||
gotHasContent = len(content.Array()) > 0
|
||||
case content.Type == gjson.String:
|
||||
gotHasContent = content.String() != ""
|
||||
default:
|
||||
gotHasContent = false
|
||||
}
|
||||
|
||||
if gotHasContent != tt.wantHasContent {
|
||||
t.Errorf("content existence = %v, want %v", gotHasContent, tt.wantHasContent)
|
||||
}
|
||||
|
||||
if tt.wantHasContent && tt.wantContentText != "" {
|
||||
// Find text content
|
||||
var foundText string
|
||||
content.ForEach(func(_, v gjson.Result) bool {
|
||||
if v.Get("type").String() == "text" {
|
||||
foundText = v.Get("text").String()
|
||||
return false
|
||||
}
|
||||
return true
|
||||
})
|
||||
if foundText != tt.wantContentText {
|
||||
t.Errorf("content text = %q, want %q", foundText, tt.wantContentText)
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// TestConvertClaudeRequestToOpenAI_ThinkingOnlyMessagePreserved tests AC3:
|
||||
// that a message with only thinking content is preserved (not dropped).
|
||||
func TestConvertClaudeRequestToOpenAI_ThinkingOnlyMessagePreserved(t *testing.T) {
|
||||
inputJSON := `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [{"type": "text", "text": "What is 2+2?"}]
|
||||
},
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [{"type": "thinking", "thinking": "Let me calculate: 2+2=4"}]
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [{"type": "text", "text": "Thanks"}]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
|
||||
// Should have: system (auto-added) + user + assistant (thinking-only) + user = 4 messages
|
||||
if len(messages) != 4 {
|
||||
t.Fatalf("Expected 4 messages, got %d. Messages: %v", len(messages), resultJSON.Get("messages").Raw)
|
||||
}
|
||||
|
||||
// Check the assistant message (index 2) has reasoning_content
|
||||
assistantMsg := messages[2]
|
||||
if assistantMsg.Get("role").String() != "assistant" {
|
||||
t.Errorf("Expected message[2] to be assistant, got %s", assistantMsg.Get("role").String())
|
||||
}
|
||||
|
||||
if !assistantMsg.Get("reasoning_content").Exists() {
|
||||
t.Error("Expected assistant message to have reasoning_content")
|
||||
}
|
||||
|
||||
if assistantMsg.Get("reasoning_content").String() != "Let me calculate: 2+2=4" {
|
||||
t.Errorf("Unexpected reasoning_content: %s", assistantMsg.Get("reasoning_content").String())
|
||||
}
|
||||
}
|
||||
|
||||
func TestConvertClaudeRequestToOpenAI_ToolResultOrderAndContent(t *testing.T) {
|
||||
inputJSON := `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}}
|
||||
]
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "text", "text": "before"},
|
||||
{"type": "tool_result", "tool_use_id": "call_1", "content": [{"type":"text","text":"tool ok"}]},
|
||||
{"type": "text", "text": "after"}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
|
||||
// OpenAI requires: tool messages MUST immediately follow assistant(tool_calls).
|
||||
// Correct order: system + assistant(tool_calls) + tool(result) + user(before+after)
|
||||
if len(messages) != 4 {
|
||||
t.Fatalf("Expected 4 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
|
||||
}
|
||||
|
||||
if messages[0].Get("role").String() != "system" {
|
||||
t.Fatalf("Expected messages[0] to be system, got %s", messages[0].Get("role").String())
|
||||
}
|
||||
|
||||
if messages[1].Get("role").String() != "assistant" || !messages[1].Get("tool_calls").Exists() {
|
||||
t.Fatalf("Expected messages[1] to be assistant tool_calls, got %s: %s", messages[1].Get("role").String(), messages[1].Raw)
|
||||
}
|
||||
|
||||
// tool message MUST immediately follow assistant(tool_calls) per OpenAI spec
|
||||
if messages[2].Get("role").String() != "tool" {
|
||||
t.Fatalf("Expected messages[2] to be tool (must follow tool_calls), got %s", messages[2].Get("role").String())
|
||||
}
|
||||
if got := messages[2].Get("tool_call_id").String(); got != "call_1" {
|
||||
t.Fatalf("Expected tool_call_id %q, got %q", "call_1", got)
|
||||
}
|
||||
if got := messages[2].Get("content").String(); got != "tool ok" {
|
||||
t.Fatalf("Expected tool content %q, got %q", "tool ok", got)
|
||||
}
|
||||
|
||||
// User message comes after tool message
|
||||
if messages[3].Get("role").String() != "user" {
|
||||
t.Fatalf("Expected messages[3] to be user, got %s", messages[3].Get("role").String())
|
||||
}
|
||||
// User message should contain both "before" and "after" text
|
||||
if got := messages[3].Get("content.0.text").String(); got != "before" {
|
||||
t.Fatalf("Expected user text[0] %q, got %q", "before", got)
|
||||
}
|
||||
if got := messages[3].Get("content.1.text").String(); got != "after" {
|
||||
t.Fatalf("Expected user text[1] %q, got %q", "after", got)
|
||||
}
|
||||
}
|
||||
|
||||
func TestConvertClaudeRequestToOpenAI_ToolResultObjectContent(t *testing.T) {
|
||||
inputJSON := `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}}
|
||||
]
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "tool_result", "tool_use_id": "call_1", "content": {"foo": "bar"}}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
|
||||
// system + assistant(tool_calls) + tool(result)
|
||||
if len(messages) != 3 {
|
||||
t.Fatalf("Expected 3 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
|
||||
}
|
||||
|
||||
if messages[2].Get("role").String() != "tool" {
|
||||
t.Fatalf("Expected messages[2] to be tool, got %s", messages[2].Get("role").String())
|
||||
}
|
||||
|
||||
toolContent := messages[2].Get("content").String()
|
||||
parsed := gjson.Parse(toolContent)
|
||||
if parsed.Get("foo").String() != "bar" {
|
||||
t.Fatalf("Expected tool content JSON foo=bar, got %q", toolContent)
|
||||
}
|
||||
}
|
||||
|
||||
func TestConvertClaudeRequestToOpenAI_AssistantTextToolUseTextOrder(t *testing.T) {
|
||||
inputJSON := `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "text", "text": "pre"},
|
||||
{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}},
|
||||
{"type": "text", "text": "post"}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
|
||||
// New behavior: content + tool_calls unified in single assistant message
|
||||
// Expect: system + assistant(content[pre,post] + tool_calls)
|
||||
if len(messages) != 2 {
|
||||
t.Fatalf("Expected 2 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
|
||||
}
|
||||
|
||||
if messages[0].Get("role").String() != "system" {
|
||||
t.Fatalf("Expected messages[0] to be system, got %s", messages[0].Get("role").String())
|
||||
}
|
||||
|
||||
assistantMsg := messages[1]
|
||||
if assistantMsg.Get("role").String() != "assistant" {
|
||||
t.Fatalf("Expected messages[1] to be assistant, got %s", assistantMsg.Get("role").String())
|
||||
}
|
||||
|
||||
// Should have both content and tool_calls in same message
|
||||
if !assistantMsg.Get("tool_calls").Exists() {
|
||||
t.Fatalf("Expected assistant message to have tool_calls")
|
||||
}
|
||||
if got := assistantMsg.Get("tool_calls.0.id").String(); got != "call_1" {
|
||||
t.Fatalf("Expected tool_call id %q, got %q", "call_1", got)
|
||||
}
|
||||
if got := assistantMsg.Get("tool_calls.0.function.name").String(); got != "do_work" {
|
||||
t.Fatalf("Expected tool_call name %q, got %q", "do_work", got)
|
||||
}
|
||||
|
||||
// Content should have both pre and post text
|
||||
if got := assistantMsg.Get("content.0.text").String(); got != "pre" {
|
||||
t.Fatalf("Expected content[0] text %q, got %q", "pre", got)
|
||||
}
|
||||
if got := assistantMsg.Get("content.1.text").String(); got != "post" {
|
||||
t.Fatalf("Expected content[1] text %q, got %q", "post", got)
|
||||
}
|
||||
}
|
||||
|
||||
func TestConvertClaudeRequestToOpenAI_AssistantThinkingToolUseThinkingSplit(t *testing.T) {
|
||||
inputJSON := `{
|
||||
"model": "claude-3-opus",
|
||||
"messages": [
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "t1"},
|
||||
{"type": "text", "text": "pre"},
|
||||
{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}},
|
||||
{"type": "thinking", "thinking": "t2"},
|
||||
{"type": "text", "text": "post"}
|
||||
]
|
||||
}
|
||||
]
|
||||
}`
|
||||
|
||||
result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
|
||||
resultJSON := gjson.ParseBytes(result)
|
||||
messages := resultJSON.Get("messages").Array()
|
||||
|
||||
// New behavior: all content, thinking, and tool_calls unified in single assistant message
|
||||
// Expect: system + assistant(content[pre,post] + tool_calls + reasoning_content[t1+t2])
|
||||
if len(messages) != 2 {
|
||||
t.Fatalf("Expected 2 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
|
||||
}
|
||||
|
||||
assistantMsg := messages[1]
|
||||
if assistantMsg.Get("role").String() != "assistant" {
|
||||
t.Fatalf("Expected messages[1] to be assistant, got %s", assistantMsg.Get("role").String())
|
||||
}
|
||||
|
||||
// Should have content with both pre and post
|
||||
if got := assistantMsg.Get("content.0.text").String(); got != "pre" {
|
||||
t.Fatalf("Expected content[0] text %q, got %q", "pre", got)
|
||||
}
|
||||
if got := assistantMsg.Get("content.1.text").String(); got != "post" {
|
||||
t.Fatalf("Expected content[1] text %q, got %q", "post", got)
|
||||
}
|
||||
|
||||
// Should have tool_calls
|
||||
if !assistantMsg.Get("tool_calls").Exists() {
|
||||
t.Fatalf("Expected assistant message to have tool_calls")
|
||||
}
|
||||
|
||||
// Should have combined reasoning_content from both thinking blocks
|
||||
if got := assistantMsg.Get("reasoning_content").String(); got != "t1\n\nt2" {
|
||||
t.Fatalf("Expected reasoning_content %q, got %q", "t1\n\nt2", got)
|
||||
}
|
||||
}
|
||||
@@ -480,15 +480,15 @@ func collectOpenAIReasoningTexts(node gjson.Result) []string {
|
||||
|
||||
switch node.Type {
|
||||
case gjson.String:
|
||||
if text := strings.TrimSpace(node.String()); text != "" {
|
||||
if text := node.String(); text != "" {
|
||||
texts = append(texts, text)
|
||||
}
|
||||
case gjson.JSON:
|
||||
if text := node.Get("text"); text.Exists() {
|
||||
if trimmed := strings.TrimSpace(text.String()); trimmed != "" {
|
||||
texts = append(texts, trimmed)
|
||||
if textStr := text.String(); textStr != "" {
|
||||
texts = append(texts, textStr)
|
||||
}
|
||||
} else if raw := strings.TrimSpace(node.Raw); raw != "" && !strings.HasPrefix(raw, "{") && !strings.HasPrefix(raw, "[") {
|
||||
} else if raw := node.Raw; raw != "" && !strings.HasPrefix(raw, "{") && !strings.HasPrefix(raw, "[") {
|
||||
texts = append(texts, raw)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -390,6 +390,11 @@ func addEmptySchemaPlaceholder(jsonStr string) string {
|
||||
|
||||
// If schema has properties but none are required, add a minimal placeholder.
|
||||
if propsVal.IsObject() && !hasRequiredProperties {
|
||||
// DO NOT add placeholder if it's a top-level schema (parentPath is empty)
|
||||
// or if we've already added a placeholder reason above.
|
||||
if parentPath == "" {
|
||||
continue
|
||||
}
|
||||
placeholderPath := joinPath(propsPath, "_")
|
||||
if !gjson.Get(jsonStr, placeholderPath).Exists() {
|
||||
jsonStr, _ = sjson.Set(jsonStr, placeholderPath+".type", "boolean")
|
||||
|
||||
@@ -127,8 +127,10 @@ func TestCleanJSONSchemaForAntigravity_AnyOfFlattening_SmartSelection(t *testing
|
||||
"type": "object",
|
||||
"description": "Accepts: null | object",
|
||||
"properties": {
|
||||
"_": { "type": "boolean" },
|
||||
"kind": { "type": "string" }
|
||||
}
|
||||
},
|
||||
"required": ["_"]
|
||||
}
|
||||
}
|
||||
}`
|
||||
|
||||
56
internal/util/sanitize_test.go
Normal file
56
internal/util/sanitize_test.go
Normal file
@@ -0,0 +1,56 @@
|
||||
package util
|
||||
|
||||
import (
|
||||
"testing"
|
||||
)
|
||||
|
||||
func TestSanitizeFunctionName(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
input string
|
||||
expected string
|
||||
}{
|
||||
{"Normal", "valid_name", "valid_name"},
|
||||
{"With Dots", "name.with.dots", "name.with.dots"},
|
||||
{"With Colons", "name:with:colons", "name:with:colons"},
|
||||
{"With Dashes", "name-with-dashes", "name-with-dashes"},
|
||||
{"Mixed Allowed", "name.with_dots:colons-dashes", "name.with_dots:colons-dashes"},
|
||||
{"Invalid Characters", "name!with@invalid#chars", "name_with_invalid_chars"},
|
||||
{"Spaces", "name with spaces", "name_with_spaces"},
|
||||
{"Non-ASCII", "name_with_你好_chars", "name_with____chars"},
|
||||
{"Starts with digit", "123name", "_123name"},
|
||||
{"Starts with dot", ".name", "_.name"},
|
||||
{"Starts with colon", ":name", "_:name"},
|
||||
{"Starts with dash", "-name", "_-name"},
|
||||
{"Starts with invalid char", "!name", "_name"},
|
||||
{"Exactly 64 chars", "this_is_a_very_long_name_that_exactly_reaches_sixty_four_charact", "this_is_a_very_long_name_that_exactly_reaches_sixty_four_charact"},
|
||||
{"Too long (65 chars)", "this_is_a_very_long_name_that_exactly_reaches_sixty_four_charactX", "this_is_a_very_long_name_that_exactly_reaches_sixty_four_charact"},
|
||||
{"Very long", "this_is_a_very_long_name_that_exceeds_the_sixty_four_character_limit_for_function_names", "this_is_a_very_long_name_that_exceeds_the_sixty_four_character_l"},
|
||||
{"Starts with digit (64 chars total)", "1234567890123456789012345678901234567890123456789012345678901234", "_123456789012345678901234567890123456789012345678901234567890123"},
|
||||
{"Starts with invalid char (64 chars total)", "!234567890123456789012345678901234567890123456789012345678901234", "_234567890123456789012345678901234567890123456789012345678901234"},
|
||||
{"Empty", "", ""},
|
||||
{"Single character invalid", "@", "_"},
|
||||
{"Single character valid", "a", "a"},
|
||||
{"Single character digit", "1", "_1"},
|
||||
{"Single character underscore", "_", "_"},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
got := SanitizeFunctionName(tt.input)
|
||||
if got != tt.expected {
|
||||
t.Errorf("SanitizeFunctionName(%q) = %v, want %v", tt.input, got, tt.expected)
|
||||
}
|
||||
// Verify Gemini compliance
|
||||
if len(got) > 64 {
|
||||
t.Errorf("SanitizeFunctionName(%q) result too long: %d", tt.input, len(got))
|
||||
}
|
||||
if len(got) > 0 {
|
||||
first := got[0]
|
||||
if !((first >= 'a' && first <= 'z') || (first >= 'A' && first <= 'Z') || first == '_') {
|
||||
t.Errorf("SanitizeFunctionName(%q) result starts with invalid char: %c", tt.input, first)
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
@@ -8,12 +8,52 @@ import (
|
||||
"io/fs"
|
||||
"os"
|
||||
"path/filepath"
|
||||
"regexp"
|
||||
"strings"
|
||||
|
||||
"github.com/router-for-me/CLIProxyAPI/v6/internal/config"
|
||||
log "github.com/sirupsen/logrus"
|
||||
)
|
||||
|
||||
var functionNameSanitizer = regexp.MustCompile(`[^a-zA-Z0-9_.:-]`)
|
||||
|
||||
// SanitizeFunctionName ensures a function name matches the requirements for Gemini/Vertex AI.
|
||||
// It replaces invalid characters with underscores, ensures it starts with a letter or underscore,
|
||||
// and truncates it to 64 characters if necessary.
|
||||
// Regex Rule: [^a-zA-Z0-9_.:-] replaced with _.
|
||||
func SanitizeFunctionName(name string) string {
|
||||
if name == "" {
|
||||
return ""
|
||||
}
|
||||
|
||||
// Replace invalid characters with underscore
|
||||
sanitized := functionNameSanitizer.ReplaceAllString(name, "_")
|
||||
|
||||
// Ensure it starts with a letter or underscore
|
||||
// Re-reading requirements: Must start with a letter or an underscore.
|
||||
if len(sanitized) > 0 {
|
||||
first := sanitized[0]
|
||||
if !((first >= 'a' && first <= 'z') || (first >= 'A' && first <= 'Z') || first == '_') {
|
||||
// If it starts with an allowed character but not allowed at the beginning (digit, dot, colon, dash),
|
||||
// we must prepend an underscore.
|
||||
|
||||
// To stay within the 64-character limit while prepending, we must truncate first.
|
||||
if len(sanitized) >= 64 {
|
||||
sanitized = sanitized[:63]
|
||||
}
|
||||
sanitized = "_" + sanitized
|
||||
}
|
||||
} else {
|
||||
sanitized = "_"
|
||||
}
|
||||
|
||||
// Truncate to 64 characters
|
||||
if len(sanitized) > 64 {
|
||||
sanitized = sanitized[:64]
|
||||
}
|
||||
return sanitized
|
||||
}
|
||||
|
||||
// SetLogLevel configures the logrus log level based on the configuration.
|
||||
// It sets the log level to DebugLevel if debug mode is enabled, otherwise to InfoLevel.
|
||||
func SetLogLevel(cfg *config.Config) {
|
||||
|
||||
@@ -13,6 +13,7 @@ type ModelRegistry interface {
|
||||
ClearModelQuotaExceeded(clientID, modelID string)
|
||||
ClientSupportsModel(clientID, modelID string) bool
|
||||
GetAvailableModels(handlerType string) []map[string]any
|
||||
GetAvailableModelsByProvider(provider string) []*ModelInfo
|
||||
}
|
||||
|
||||
// GlobalModelRegistry returns the shared registry instance.
|
||||
|
||||
Reference in New Issue
Block a user