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This commit is contained in:
Luis Pater
2025-09-25 10:31:02 +08:00
parent 84248b6ec2
commit 3f69254f43
222 changed files with 0 additions and 40389 deletions
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19
internal/translator/openai/claude/init.go
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package claude
import (
. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
"github.com/router-for-me/CLIProxyAPI/v6/internal/translator/translator"
)
func init() {
translator.Register(
Claude,
OpenAI,
ConvertClaudeRequestToOpenAI,
interfaces.TranslateResponse{
Stream: ConvertOpenAIResponseToClaude,
NonStream: ConvertOpenAIResponseToClaudeNonStream,
},
)
}

239
internal/translator/openai/claude/openai_claude_request.go
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// Package claude provides request translation functionality for Anthropic to OpenAI API.
// It handles parsing and transforming Anthropic API requests into OpenAI Chat Completions API format,
// extracting model information, system instructions, message contents, and tool declarations.
// The package performs JSON data transformation to ensure compatibility
// between Anthropic API format and OpenAI API's expected format.
package claude
import (
"bytes"
"encoding/json"
"strings"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
// ConvertClaudeRequestToOpenAI parses and transforms an Anthropic API request into OpenAI Chat Completions API format.
// It extracts the model name, system instruction, message contents, and tool declarations
// from the raw JSON request and returns them in the format expected by the OpenAI API.
func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream bool) []byte {
rawJSON := bytes.Clone(inputRawJSON)
// Base OpenAI Chat Completions API template
out := `{"model":"","messages":[]}`
root := gjson.ParseBytes(rawJSON)
// Model mapping
out, _ = sjson.Set(out, "model", modelName)
// Max tokens
if maxTokens := root.Get("max_tokens"); maxTokens.Exists() {
out, _ = sjson.Set(out, "max_tokens", maxTokens.Int())
}
// Temperature
if temp := root.Get("temperature"); temp.Exists() {
out, _ = sjson.Set(out, "temperature", temp.Float())
}
// Top P
if topP := root.Get("top_p"); topP.Exists() {
out, _ = sjson.Set(out, "top_p", topP.Float())
}
// Stop sequences -> stop
if stopSequences := root.Get("stop_sequences"); stopSequences.Exists() {
if stopSequences.IsArray() {
var stops []string
stopSequences.ForEach(func(_, value gjson.Result) bool {
stops = append(stops, value.String())
return true
})
if len(stops) > 0 {
if len(stops) == 1 {
out, _ = sjson.Set(out, "stop", stops[0])
} else {
out, _ = sjson.Set(out, "stop", stops)
}
}
}
}
// Stream
out, _ = sjson.Set(out, "stream", stream)
// Process messages and system
var messagesJSON = "[]"
// Handle system message first
systemMsgJSON := `{"role":"system","content":[{"type":"text","text":"Use ANY tool, the parameters MUST accord with RFC 8259 (The JavaScript Object Notation (JSON) Data Interchange Format), the keys and value MUST be enclosed in double quotes."}]}`
if system := root.Get("system"); system.Exists() {
if system.Type == gjson.String {
if system.String() != "" {
oldSystem := `{"type":"text","text":""}`
oldSystem, _ = sjson.Set(oldSystem, "text", system.String())
systemMsgJSON, _ = sjson.SetRaw(systemMsgJSON, "content.-1", oldSystem)
}
} else if system.Type == gjson.JSON {
if system.IsArray() {
systemResults := system.Array()
for i := 0; i < len(systemResults); i++ {
systemMsgJSON, _ = sjson.SetRaw(systemMsgJSON, "content.-1", systemResults[i].Raw)
}
}
}
}
messagesJSON, _ = sjson.SetRaw(messagesJSON, "-1", systemMsgJSON)
// Process Anthropic messages
if messages := root.Get("messages"); messages.Exists() && messages.IsArray() {
messages.ForEach(func(_, message gjson.Result) bool {
role := message.Get("role").String()
contentResult := message.Get("content")
// Handle content
if contentResult.Exists() && contentResult.IsArray() {
var textParts []string
var toolCalls []interface{}
contentResult.ForEach(func(_, part gjson.Result) bool {
partType := part.Get("type").String()
switch partType {
case "text":
textParts = append(textParts, part.Get("text").String())
case "image":
// Convert Anthropic image format to OpenAI format
if source := part.Get("source"); source.Exists() {
sourceType := source.Get("type").String()
if sourceType == "base64" {
mediaType := source.Get("media_type").String()
data := source.Get("data").String()
imageURL := "data:" + mediaType + ";base64," + data
// For now, add as text since OpenAI image handling is complex
// In a real implementation, you'd need to handle this properly
textParts = append(textParts, "[Image: "+imageURL+"]")
}
}
case "tool_use":
// Convert to OpenAI tool call format
toolCallJSON := `{"id":"","type":"function","function":{"name":"","arguments":""}}`
toolCallJSON, _ = sjson.Set(toolCallJSON, "id", part.Get("id").String())
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.name", part.Get("name").String())
// Convert input to arguments JSON string
if input := part.Get("input"); input.Exists() {
if inputJSON, err := json.Marshal(input.Value()); err == nil {
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", string(inputJSON))
} else {
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", "{}")
}
} else {
toolCallJSON, _ = sjson.Set(toolCallJSON, "function.arguments", "{}")
}
toolCalls = append(toolCalls, gjson.Parse(toolCallJSON).Value())
case "tool_result":
// Convert to OpenAI tool message format and add immediately to preserve order
toolResultJSON := `{"role":"tool","tool_call_id":"","content":""}`
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())
}
return true
})
// Create main message if there's text content or tool calls
if len(textParts) > 0 || len(toolCalls) > 0 {
msgJSON := `{"role":"","content":""}`
msgJSON, _ = sjson.Set(msgJSON, "role", role)
// Set content
if len(textParts) > 0 {
msgJSON, _ = sjson.Set(msgJSON, "content", strings.Join(textParts, ""))
} else {
msgJSON, _ = sjson.Set(msgJSON, "content", "")
}
// Set tool calls for assistant messages
if role == "assistant" && len(toolCalls) > 0 {
toolCallsJSON, _ := json.Marshal(toolCalls)
msgJSON, _ = sjson.SetRaw(msgJSON, "tool_calls", string(toolCallsJSON))
}
if gjson.Get(msgJSON, "content").String() != "" || len(toolCalls) != 0 {
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
}
}
} else if contentResult.Exists() && contentResult.Type == gjson.String {
// Simple string content
msgJSON := `{"role":"","content":""}`
msgJSON, _ = sjson.Set(msgJSON, "role", role)
msgJSON, _ = sjson.Set(msgJSON, "content", contentResult.String())
messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
}
return true
})
}
// Set messages
if gjson.Parse(messagesJSON).IsArray() && len(gjson.Parse(messagesJSON).Array()) > 0 {
out, _ = sjson.SetRaw(out, "messages", messagesJSON)
}
// Process tools - convert Anthropic tools to OpenAI functions
if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
var toolsJSON = "[]"
tools.ForEach(func(_, tool gjson.Result) bool {
openAIToolJSON := `{"type":"function","function":{"name":"","description":""}}`
openAIToolJSON, _ = sjson.Set(openAIToolJSON, "function.name", tool.Get("name").String())
openAIToolJSON, _ = sjson.Set(openAIToolJSON, "function.description", tool.Get("description").String())
// Convert Anthropic input_schema to OpenAI function parameters
if inputSchema := tool.Get("input_schema"); inputSchema.Exists() {
openAIToolJSON, _ = sjson.Set(openAIToolJSON, "function.parameters", inputSchema.Value())
}
toolsJSON, _ = sjson.Set(toolsJSON, "-1", gjson.Parse(openAIToolJSON).Value())
return true
})
if gjson.Parse(toolsJSON).IsArray() && len(gjson.Parse(toolsJSON).Array()) > 0 {
out, _ = sjson.SetRaw(out, "tools", toolsJSON)
}
}
// Tool choice mapping - convert Anthropic tool_choice to OpenAI format
if toolChoice := root.Get("tool_choice"); toolChoice.Exists() {
switch toolChoice.Get("type").String() {
case "auto":
out, _ = sjson.Set(out, "tool_choice", "auto")
case "any":
out, _ = sjson.Set(out, "tool_choice", "required")
case "tool":
// Specific tool choice
toolName := toolChoice.Get("name").String()
toolChoiceJSON := `{"type":"function","function":{"name":""}}`
toolChoiceJSON, _ = sjson.Set(toolChoiceJSON, "function.name", toolName)
out, _ = sjson.SetRaw(out, "tool_choice", toolChoiceJSON)
default:
// Default to auto if not specified
out, _ = sjson.Set(out, "tool_choice", "auto")
}
}
// Handle user parameter (for tracking)
if user := root.Get("user"); user.Exists() {
out, _ = sjson.Set(out, "user", user.String())
}
return []byte(out)
}

627
internal/translator/openai/claude/openai_claude_response.go
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@@ -1,627 +0,0 @@
// Package claude provides response translation functionality for OpenAI to Anthropic API.
// This package handles the conversion of OpenAI Chat Completions API responses into Anthropic API-compatible
// JSON format, transforming streaming events and non-streaming responses into the format
// expected by Anthropic API clients. It supports both streaming and non-streaming modes,
// handling text content, tool calls, and usage metadata appropriately.
package claude
import (
"bytes"
"context"
"encoding/json"
"strings"
"github.com/router-for-me/CLIProxyAPI/v6/internal/util"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
var (
dataTag = []byte("data:")
)
// ConvertOpenAIResponseToAnthropicParams holds parameters for response conversion
type ConvertOpenAIResponseToAnthropicParams struct {
MessageID string
Model string
CreatedAt int64
// Content accumulator for streaming
ContentAccumulator strings.Builder
// Tool calls accumulator for streaming
ToolCallsAccumulator map[int]*ToolCallAccumulator
// Track if text content block has been started
TextContentBlockStarted bool
// Track finish reason for later use
FinishReason string
// Track if content blocks have been stopped
ContentBlocksStopped bool
// Track if message_delta has been sent
MessageDeltaSent bool
}
// ToolCallAccumulator holds the state for accumulating tool call data
type ToolCallAccumulator struct {
ID string
Name string
Arguments strings.Builder
}
// ConvertOpenAIResponseToClaude converts OpenAI streaming response format to Anthropic API format.
// This function processes OpenAI streaming chunks and transforms them into Anthropic-compatible JSON responses.
// It handles text content, tool calls, and usage metadata, outputting responses that match the Anthropic API format.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - []string: A slice of strings, each containing an Anthropic-compatible JSON response.
func ConvertOpenAIResponseToClaude(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) []string {
if *param == nil {
*param = &ConvertOpenAIResponseToAnthropicParams{
MessageID: "",
Model: "",
CreatedAt: 0,
ContentAccumulator: strings.Builder{},
ToolCallsAccumulator: nil,
TextContentBlockStarted: false,
FinishReason: "",
ContentBlocksStopped: false,
MessageDeltaSent: false,
}
}
if !bytes.HasPrefix(rawJSON, dataTag) {
return []string{}
}
rawJSON = bytes.TrimSpace(rawJSON[5:])
// Check if this is the [DONE] marker
rawStr := strings.TrimSpace(string(rawJSON))
if rawStr == "[DONE]" {
return convertOpenAIDoneToAnthropic((*param).(*ConvertOpenAIResponseToAnthropicParams))
}
root := gjson.ParseBytes(rawJSON)
// Check if this is a streaming chunk or non-streaming response
objectType := root.Get("object").String()
if objectType == "chat.completion.chunk" {
// Handle streaming response
return convertOpenAIStreamingChunkToAnthropic(rawJSON, (*param).(*ConvertOpenAIResponseToAnthropicParams))
} else if objectType == "chat.completion" {
// Handle non-streaming response
return convertOpenAINonStreamingToAnthropic(rawJSON)
}
return []string{}
}
// convertOpenAIStreamingChunkToAnthropic converts OpenAI streaming chunk to Anthropic streaming events
func convertOpenAIStreamingChunkToAnthropic(rawJSON []byte, param *ConvertOpenAIResponseToAnthropicParams) []string {
root := gjson.ParseBytes(rawJSON)
var results []string
// Initialize parameters if needed
if param.MessageID == "" {
param.MessageID = root.Get("id").String()
}
if param.Model == "" {
param.Model = root.Get("model").String()
}
if param.CreatedAt == 0 {
param.CreatedAt = root.Get("created").Int()
}
// Check if this is the first chunk (has role)
if delta := root.Get("choices.0.delta"); delta.Exists() {
if role := delta.Get("role"); role.Exists() && role.String() == "assistant" {
// Send message_start event
messageStart := map[string]interface{}{
"type": "message_start",
"message": map[string]interface{}{
"id": param.MessageID,
"type": "message",
"role": "assistant",
"model": param.Model,
"content": []interface{}{},
"stop_reason": nil,
"stop_sequence": nil,
"usage": map[string]interface{}{
"input_tokens": 0,
"output_tokens": 0,
},
},
}
messageStartJSON, _ := json.Marshal(messageStart)
results = append(results, "event: message_start\ndata: "+string(messageStartJSON)+"\n\n")
// Don't send content_block_start for text here - wait for actual content
}
// Handle content delta
if content := delta.Get("content"); content.Exists() && content.String() != "" {
// Send content_block_start for text if not already sent
if !param.TextContentBlockStarted {
contentBlockStart := map[string]interface{}{
"type": "content_block_start",
"index": 0,
"content_block": map[string]interface{}{
"type": "text",
"text": "",
},
}
contentBlockStartJSON, _ := json.Marshal(contentBlockStart)
results = append(results, "event: content_block_start\ndata: "+string(contentBlockStartJSON)+"\n\n")
param.TextContentBlockStarted = true
}
contentDelta := map[string]interface{}{
"type": "content_block_delta",
"index": 0,
"delta": map[string]interface{}{
"type": "text_delta",
"text": content.String(),
},
}
contentDeltaJSON, _ := json.Marshal(contentDelta)
results = append(results, "event: content_block_delta\ndata: "+string(contentDeltaJSON)+"\n\n")
// Accumulate content
param.ContentAccumulator.WriteString(content.String())
}
// Handle tool calls
if toolCalls := delta.Get("tool_calls"); toolCalls.Exists() && toolCalls.IsArray() {
if param.ToolCallsAccumulator == nil {
param.ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
}
toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
index := int(toolCall.Get("index").Int())
// Initialize accumulator if needed
if _, exists := param.ToolCallsAccumulator[index]; !exists {
param.ToolCallsAccumulator[index] = &ToolCallAccumulator{}
}
accumulator := param.ToolCallsAccumulator[index]
// Handle tool call ID
if id := toolCall.Get("id"); id.Exists() {
accumulator.ID = id.String()
}
// Handle function name
if function := toolCall.Get("function"); function.Exists() {
if name := function.Get("name"); name.Exists() {
accumulator.Name = name.String()
if param.TextContentBlockStarted {
param.TextContentBlockStarted = false
contentBlockStop := map[string]interface{}{
"type": "content_block_stop",
"index": index,
}
contentBlockStopJSON, _ := json.Marshal(contentBlockStop)
results = append(results, "event: content_block_stop\ndata: "+string(contentBlockStopJSON)+"\n\n")
}
// Send content_block_start for tool_use
contentBlockStart := map[string]interface{}{
"type": "content_block_start",
"index": index + 1, // Offset by 1 since text is at index 0
"content_block": map[string]interface{}{
"type": "tool_use",
"id": accumulator.ID,
"name": accumulator.Name,
"input": map[string]interface{}{},
},
}
contentBlockStartJSON, _ := json.Marshal(contentBlockStart)
results = append(results, "event: content_block_start\ndata: "+string(contentBlockStartJSON)+"\n\n")
}
// Handle function arguments
if args := function.Get("arguments"); args.Exists() {
argsText := args.String()
if argsText != "" {
accumulator.Arguments.WriteString(argsText)
}
}
}
return true
})
}
}
// Handle finish_reason (but don't send message_delta/message_stop yet)
if finishReason := root.Get("choices.0.finish_reason"); finishReason.Exists() && finishReason.String() != "" {
reason := finishReason.String()
param.FinishReason = reason
// Send content_block_stop for text if text content block was started
if param.TextContentBlockStarted && !param.ContentBlocksStopped {
contentBlockStop := map[string]interface{}{
"type": "content_block_stop",
"index": 0,
}
contentBlockStopJSON, _ := json.Marshal(contentBlockStop)
results = append(results, "event: content_block_stop\ndata: "+string(contentBlockStopJSON)+"\n\n")
}
// Send content_block_stop for any tool calls
if !param.ContentBlocksStopped {
for index := range param.ToolCallsAccumulator {
accumulator := param.ToolCallsAccumulator[index]
// Send complete input_json_delta with all accumulated arguments
if accumulator.Arguments.Len() > 0 {
inputDelta := map[string]interface{}{
"type": "content_block_delta",
"index": index + 1,
"delta": map[string]interface{}{
"type": "input_json_delta",
"partial_json": util.FixJSON(accumulator.Arguments.String()),
},
}
inputDeltaJSON, _ := json.Marshal(inputDelta)
results = append(results, "event: content_block_delta\ndata: "+string(inputDeltaJSON)+"\n\n")
}
contentBlockStop := map[string]interface{}{
"type": "content_block_stop",
"index": index + 1,
}
contentBlockStopJSON, _ := json.Marshal(contentBlockStop)
results = append(results, "event: content_block_stop\ndata: "+string(contentBlockStopJSON)+"\n\n")
}
param.ContentBlocksStopped = true
}
// Don't send message_delta here - wait for usage info or [DONE]
}
// Handle usage information separately (this comes in a later chunk)
// Only process if usage has actual values (not null)
if usage := root.Get("usage"); usage.Exists() && usage.Type != gjson.Null && param.FinishReason != "" {
// Check if usage has actual token counts
promptTokens := usage.Get("prompt_tokens")
completionTokens := usage.Get("completion_tokens")
if promptTokens.Exists() && completionTokens.Exists() {
// Send message_delta with usage
messageDelta := map[string]interface{}{
"type": "message_delta",
"delta": map[string]interface{}{
"stop_reason": mapOpenAIFinishReasonToAnthropic(param.FinishReason),
"stop_sequence": nil,
},
"usage": map[string]interface{}{
"input_tokens": promptTokens.Int(),
"output_tokens": completionTokens.Int(),
},
}
messageDeltaJSON, _ := json.Marshal(messageDelta)
results = append(results, "event: message_delta\ndata: "+string(messageDeltaJSON)+"\n\n")
param.MessageDeltaSent = true
}
}
return results
}
// convertOpenAIDoneToAnthropic handles the [DONE] marker and sends final events
func convertOpenAIDoneToAnthropic(param *ConvertOpenAIResponseToAnthropicParams) []string {
var results []string
// If we haven't sent message_delta yet (no usage info was received), send it now
if param.FinishReason != "" && !param.MessageDeltaSent {
messageDelta := map[string]interface{}{
"type": "message_delta",
"delta": map[string]interface{}{
"stop_reason": mapOpenAIFinishReasonToAnthropic(param.FinishReason),
"stop_sequence": nil,
},
}
messageDeltaJSON, _ := json.Marshal(messageDelta)
results = append(results, "event: message_delta\ndata: "+string(messageDeltaJSON)+"\n\n")
param.MessageDeltaSent = true
}
// Send message_stop
results = append(results, "event: message_stop\ndata: {\"type\":\"message_stop\"}\n\n")
return results
}
// convertOpenAINonStreamingToAnthropic converts OpenAI non-streaming response to Anthropic format
func convertOpenAINonStreamingToAnthropic(rawJSON []byte) []string {
root := gjson.ParseBytes(rawJSON)
// Build Anthropic response
response := map[string]interface{}{
"id": root.Get("id").String(),
"type": "message",
"role": "assistant",
"model": root.Get("model").String(),
"content": []interface{}{},
"stop_reason": nil,
"stop_sequence": nil,
"usage": map[string]interface{}{
"input_tokens": 0,
"output_tokens": 0,
},
}
// Process message content and tool calls
var contentBlocks []interface{}
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
choice := choices.Array()[0] // Take first choice
// Handle text content
if content := choice.Get("message.content"); content.Exists() && content.String() != "" {
textBlock := map[string]interface{}{
"type": "text",
"text": content.String(),
}
contentBlocks = append(contentBlocks, textBlock)
}
// Handle tool calls
if toolCalls := choice.Get("message.tool_calls"); toolCalls.Exists() && toolCalls.IsArray() {
toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
toolUseBlock := map[string]interface{}{
"type": "tool_use",
"id": toolCall.Get("id").String(),
"name": toolCall.Get("function.name").String(),
}
// Parse arguments
argsStr := toolCall.Get("function.arguments").String()
argsStr = util.FixJSON(argsStr)
if argsStr != "" {
var args interface{}
if err := json.Unmarshal([]byte(argsStr), &args); err == nil {
toolUseBlock["input"] = args
} else {
toolUseBlock["input"] = map[string]interface{}{}
}
} else {
toolUseBlock["input"] = map[string]interface{}{}
}
contentBlocks = append(contentBlocks, toolUseBlock)
return true
})
}
// Set stop reason
if finishReason := choice.Get("finish_reason"); finishReason.Exists() {
response["stop_reason"] = mapOpenAIFinishReasonToAnthropic(finishReason.String())
}
}
response["content"] = contentBlocks
// Set usage information
if usage := root.Get("usage"); usage.Exists() {
response["usage"] = map[string]interface{}{
"input_tokens": usage.Get("prompt_tokens").Int(),
"output_tokens": usage.Get("completion_tokens").Int(),
}
}
responseJSON, _ := json.Marshal(response)
return []string{string(responseJSON)}
}
// mapOpenAIFinishReasonToAnthropic maps OpenAI finish reasons to Anthropic equivalents
func mapOpenAIFinishReasonToAnthropic(openAIReason string) string {
switch openAIReason {
case "stop":
return "end_turn"
case "length":
return "max_tokens"
case "tool_calls":
return "tool_use"
case "content_filter":
return "end_turn" // Anthropic doesn't have direct equivalent
case "function_call": // Legacy OpenAI
return "tool_use"
default:
return "end_turn"
}
}
// ConvertOpenAIResponseToClaudeNonStream converts a non-streaming OpenAI response to a non-streaming Anthropic response.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - string: An Anthropic-compatible JSON response.
func ConvertOpenAIResponseToClaudeNonStream(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, _ *any) string {
_ = originalRequestRawJSON
_ = requestRawJSON
root := gjson.ParseBytes(rawJSON)
response := map[string]interface{}{
"id": root.Get("id").String(),
"type": "message",
"role": "assistant",
"model": root.Get("model").String(),
"content": []interface{}{},
"stop_reason": nil,
"stop_sequence": nil,
"usage": map[string]interface{}{
"input_tokens": 0,
"output_tokens": 0,
},
}
var contentBlocks []interface{}
hasToolCall := false
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() && len(choices.Array()) > 0 {
choice := choices.Array()[0]
if finishReason := choice.Get("finish_reason"); finishReason.Exists() {
response["stop_reason"] = mapOpenAIFinishReasonToAnthropic(finishReason.String())
}
if message := choice.Get("message"); message.Exists() {
if contentArray := message.Get("content"); contentArray.Exists() && contentArray.IsArray() {
var textBuilder strings.Builder
var thinkingBuilder strings.Builder
flushText := func() {
if textBuilder.Len() == 0 {
return
}
contentBlocks = append(contentBlocks, map[string]interface{}{
"type": "text",
"text": textBuilder.String(),
})
textBuilder.Reset()
}
flushThinking := func() {
if thinkingBuilder.Len() == 0 {
return
}
contentBlocks = append(contentBlocks, map[string]interface{}{
"type": "thinking",
"thinking": thinkingBuilder.String(),
})
thinkingBuilder.Reset()
}
for _, item := range contentArray.Array() {
typeStr := item.Get("type").String()
switch typeStr {
case "text":
flushThinking()
textBuilder.WriteString(item.Get("text").String())
case "tool_calls":
flushThinking()
flushText()
toolCalls := item.Get("tool_calls")
if toolCalls.IsArray() {
toolCalls.ForEach(func(_, tc gjson.Result) bool {
hasToolCall = true
toolUse := map[string]interface{}{
"type": "tool_use",
"id": tc.Get("id").String(),
"name": tc.Get("function.name").String(),
}
argsStr := util.FixJSON(tc.Get("function.arguments").String())
if argsStr != "" {
var parsed interface{}
if err := json.Unmarshal([]byte(argsStr), &parsed); err == nil {
toolUse["input"] = parsed
} else {
toolUse["input"] = map[string]interface{}{}
}
} else {
toolUse["input"] = map[string]interface{}{}
}
contentBlocks = append(contentBlocks, toolUse)
return true
})
}
case "reasoning":
flushText()
if thinking := item.Get("text"); thinking.Exists() {
thinkingBuilder.WriteString(thinking.String())
}
default:
flushThinking()
flushText()
}
}
flushThinking()
flushText()
}
if toolCalls := message.Get("tool_calls"); toolCalls.Exists() && toolCalls.IsArray() {
toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
hasToolCall = true
toolUseBlock := map[string]interface{}{
"type": "tool_use",
"id": toolCall.Get("id").String(),
"name": toolCall.Get("function.name").String(),
}
argsStr := toolCall.Get("function.arguments").String()
argsStr = util.FixJSON(argsStr)
if argsStr != "" {
var args interface{}
if err := json.Unmarshal([]byte(argsStr), &args); err == nil {
toolUseBlock["input"] = args
} else {
toolUseBlock["input"] = map[string]interface{}{}
}
} else {
toolUseBlock["input"] = map[string]interface{}{}
}
contentBlocks = append(contentBlocks, toolUseBlock)
return true
})
}
}
}
response["content"] = contentBlocks
if respUsage := root.Get("usage"); respUsage.Exists() {
usageJSON := `{}`
usageJSON, _ = sjson.Set(usageJSON, "input_tokens", respUsage.Get("prompt_tokens").Int())
usageJSON, _ = sjson.Set(usageJSON, "output_tokens", respUsage.Get("completion_tokens").Int())
parsedUsage := gjson.Parse(usageJSON).Value().(map[string]interface{})
response["usage"] = parsedUsage
}
if response["stop_reason"] == nil {
if hasToolCall {
response["stop_reason"] = "tool_use"
} else {
response["stop_reason"] = "end_turn"
}
}
if !hasToolCall {
if toolBlocks := response["content"].([]interface{}); len(toolBlocks) > 0 {
for _, block := range toolBlocks {
if m, ok := block.(map[string]interface{}); ok && m["type"] == "tool_use" {
hasToolCall = true
break
}
}
}
if hasToolCall {
response["stop_reason"] = "tool_use"
}
}
responseJSON, err := json.Marshal(response)
if err != nil {
return ""
}
return string(responseJSON)
}

19
internal/translator/openai/gemini-cli/init.go
View File

@@ -1,19 +0,0 @@
package geminiCLI
import (
. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
"github.com/router-for-me/CLIProxyAPI/v6/internal/translator/translator"
)
func init() {
translator.Register(
GeminiCLI,
OpenAI,
ConvertGeminiCLIRequestToOpenAI,
interfaces.TranslateResponse{
Stream: ConvertOpenAIResponseToGeminiCLI,
NonStream: ConvertOpenAIResponseToGeminiCLINonStream,
},
)
}

29
internal/translator/openai/gemini-cli/openai_gemini_request.go
View File

@@ -1,29 +0,0 @@
// Package geminiCLI provides request translation functionality for Gemini to OpenAI API.
// It handles parsing and transforming Gemini API requests into OpenAI Chat Completions API format,
// extracting model information, generation config, message contents, and tool declarations.
// The package performs JSON data transformation to ensure compatibility
// between Gemini API format and OpenAI API's expected format.
package geminiCLI
import (
"bytes"
. "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/openai/gemini"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
// ConvertGeminiCLIRequestToOpenAI parses and transforms a Gemini API request into OpenAI Chat Completions API format.
// It extracts the model name, generation config, message contents, and tool declarations
// from the raw JSON request and returns them in the format expected by the OpenAI API.
func ConvertGeminiCLIRequestToOpenAI(modelName string, inputRawJSON []byte, stream bool) []byte {
rawJSON := bytes.Clone(inputRawJSON)
rawJSON = []byte(gjson.GetBytes(rawJSON, "request").Raw)
rawJSON, _ = sjson.SetBytes(rawJSON, "model", modelName)
if gjson.GetBytes(rawJSON, "systemInstruction").Exists() {
rawJSON, _ = sjson.SetRawBytes(rawJSON, "system_instruction", []byte(gjson.GetBytes(rawJSON, "systemInstruction").Raw))
rawJSON, _ = sjson.DeleteBytes(rawJSON, "systemInstruction")
}
return ConvertGeminiRequestToOpenAI(modelName, rawJSON, stream)
}

53
internal/translator/openai/gemini-cli/openai_gemini_response.go
View File

@@ -1,53 +0,0 @@
// Package geminiCLI provides response translation functionality for OpenAI to Gemini API.
// This package handles the conversion of OpenAI Chat Completions API responses into Gemini API-compatible
// JSON format, transforming streaming events and non-streaming responses into the format
// expected by Gemini API clients. It supports both streaming and non-streaming modes,
// handling text content, tool calls, and usage metadata appropriately.
package geminiCLI
import (
"context"
. "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/openai/gemini"
"github.com/tidwall/sjson"
)
// ConvertOpenAIResponseToGeminiCLI converts OpenAI Chat Completions streaming response format to Gemini API format.
// This function processes OpenAI streaming chunks and transforms them into Gemini-compatible JSON responses.
// It handles text content, tool calls, and usage metadata, outputting responses that match the Gemini API format.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - []string: A slice of strings, each containing a Gemini-compatible JSON response.
func ConvertOpenAIResponseToGeminiCLI(ctx context.Context, modelName string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) []string {
outputs := ConvertOpenAIResponseToGemini(ctx, modelName, originalRequestRawJSON, requestRawJSON, rawJSON, param)
newOutputs := make([]string, 0)
for i := 0; i < len(outputs); i++ {
json := `{"response": {}}`
output, _ := sjson.SetRaw(json, "response", outputs[i])
newOutputs = append(newOutputs, output)
}
return newOutputs
}
// ConvertOpenAIResponseToGeminiCLINonStream converts a non-streaming OpenAI response to a non-streaming Gemini CLI response.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - string: A Gemini-compatible JSON response.
func ConvertOpenAIResponseToGeminiCLINonStream(ctx context.Context, modelName string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) string {
strJSON := ConvertOpenAIResponseToGeminiNonStream(ctx, modelName, originalRequestRawJSON, requestRawJSON, rawJSON, param)
json := `{"response": {}}`
strJSON, _ = sjson.SetRaw(json, "response", strJSON)
return strJSON
}

19
internal/translator/openai/gemini/init.go
View File

@@ -1,19 +0,0 @@
package gemini
import (
. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
"github.com/router-for-me/CLIProxyAPI/v6/internal/translator/translator"
)
func init() {
translator.Register(
Gemini,
OpenAI,
ConvertGeminiRequestToOpenAI,
interfaces.TranslateResponse{
Stream: ConvertOpenAIResponseToGemini,
NonStream: ConvertOpenAIResponseToGeminiNonStream,
},
)
}

356
internal/translator/openai/gemini/openai_gemini_request.go
View File

@@ -1,356 +0,0 @@
// Package gemini provides request translation functionality for Gemini to OpenAI API.
// It handles parsing and transforming Gemini API requests into OpenAI Chat Completions API format,
// extracting model information, generation config, message contents, and tool declarations.
// The package performs JSON data transformation to ensure compatibility
// between Gemini API format and OpenAI API's expected format.
package gemini
import (
"bytes"
"crypto/rand"
"encoding/json"
"math/big"
"strings"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
// ConvertGeminiRequestToOpenAI parses and transforms a Gemini API request into OpenAI Chat Completions API format.
// It extracts the model name, generation config, message contents, and tool declarations
// from the raw JSON request and returns them in the format expected by the OpenAI API.
func ConvertGeminiRequestToOpenAI(modelName string, inputRawJSON []byte, stream bool) []byte {
rawJSON := bytes.Clone(inputRawJSON)
// Base OpenAI Chat Completions API template
out := `{"model":"","messages":[]}`
root := gjson.ParseBytes(rawJSON)
// Helper for generating tool call IDs in the form: call_<alphanum>
genToolCallID := func() string {
const letters = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
var b strings.Builder
// 24 chars random suffix
for i := 0; i < 24; i++ {
n, _ := rand.Int(rand.Reader, big.NewInt(int64(len(letters))))
b.WriteByte(letters[n.Int64()])
}
return "call_" + b.String()
}
// Model mapping
out, _ = sjson.Set(out, "model", modelName)
// Generation config mapping
if genConfig := root.Get("generationConfig"); genConfig.Exists() {
// Temperature
if temp := genConfig.Get("temperature"); temp.Exists() {
out, _ = sjson.Set(out, "temperature", temp.Float())
}
// Max tokens
if maxTokens := genConfig.Get("maxOutputTokens"); maxTokens.Exists() {
out, _ = sjson.Set(out, "max_tokens", maxTokens.Int())
}
// Top P
if topP := genConfig.Get("topP"); topP.Exists() {
out, _ = sjson.Set(out, "top_p", topP.Float())
}
// Top K (OpenAI doesn't have direct equivalent, but we can map it)
if topK := genConfig.Get("topK"); topK.Exists() {
// Store as custom parameter for potential use
out, _ = sjson.Set(out, "top_k", topK.Int())
}
// Stop sequences
if stopSequences := genConfig.Get("stopSequences"); stopSequences.Exists() && stopSequences.IsArray() {
var stops []string
stopSequences.ForEach(func(_, value gjson.Result) bool {
stops = append(stops, value.String())
return true
})
if len(stops) > 0 {
out, _ = sjson.Set(out, "stop", stops)
}
}
}
// Stream parameter
out, _ = sjson.Set(out, "stream", stream)
// Process contents (Gemini messages) -> OpenAI messages
var openAIMessages []interface{}
var toolCallIDs []string // Track tool call IDs for matching with tool results
if contents := root.Get("contents"); contents.Exists() && contents.IsArray() {
contents.ForEach(func(_, content gjson.Result) bool {
role := content.Get("role").String()
parts := content.Get("parts")
// Convert role: model -> assistant
if role == "model" {
role = "assistant"
}
// Create OpenAI message
msg := map[string]interface{}{
"role": role,
"content": "",
}
var contentParts []string
var toolCalls []interface{}
if parts.Exists() && parts.IsArray() {
parts.ForEach(func(_, part gjson.Result) bool {
// Handle text parts
if text := part.Get("text"); text.Exists() {
contentParts = append(contentParts, text.String())
}
// Handle function calls (Gemini) -> tool calls (OpenAI)
if functionCall := part.Get("functionCall"); functionCall.Exists() {
toolCallID := genToolCallID()
toolCallIDs = append(toolCallIDs, toolCallID)
toolCall := map[string]interface{}{
"id": toolCallID,
"type": "function",
"function": map[string]interface{}{
"name": functionCall.Get("name").String(),
},
}
// Convert args to arguments JSON string
if args := functionCall.Get("args"); args.Exists() {
argsJSON, _ := json.Marshal(args.Value())
toolCall["function"].(map[string]interface{})["arguments"] = string(argsJSON)
} else {
toolCall["function"].(map[string]interface{})["arguments"] = "{}"
}
toolCalls = append(toolCalls, toolCall)
}
// Handle function responses (Gemini) -> tool role messages (OpenAI)
if functionResponse := part.Get("functionResponse"); functionResponse.Exists() {
// Create tool message for function response
toolMsg := map[string]interface{}{
"role": "tool",
"tool_call_id": "", // Will be set based on context
"content": "",
}
// Convert response.content to JSON string
if response := functionResponse.Get("response"); response.Exists() {
if content = response.Get("content"); content.Exists() {
// Use the content field from the response
contentJSON, _ := json.Marshal(content.Value())
toolMsg["content"] = string(contentJSON)
} else {
// Fallback to entire response
responseJSON, _ := json.Marshal(response.Value())
toolMsg["content"] = string(responseJSON)
}
}
// Try to match with previous tool call ID
_ = functionResponse.Get("name").String() // functionName not used for now
if len(toolCallIDs) > 0 {
// Use the last tool call ID (simple matching by function name)
// In a real implementation, you might want more sophisticated matching
toolMsg["tool_call_id"] = toolCallIDs[len(toolCallIDs)-1]
} else {
// Generate a tool call ID if none available
toolMsg["tool_call_id"] = genToolCallID()
}
openAIMessages = append(openAIMessages, toolMsg)
}
return true
})
}
// Set content
if len(contentParts) > 0 {
msg["content"] = strings.Join(contentParts, "")
}
// Set tool calls if any
if len(toolCalls) > 0 {
msg["tool_calls"] = toolCalls
}
openAIMessages = append(openAIMessages, msg)
// switch role {
// case "user", "model":
// // Convert role: model -> assistant
// if role == "model" {
// role = "assistant"
// }
//
// // Create OpenAI message
// msg := map[string]interface{}{
// "role": role,
// "content": "",
// }
//
// var contentParts []string
// var toolCalls []interface{}
//
// if parts.Exists() && parts.IsArray() {
// parts.ForEach(func(_, part gjson.Result) bool {
// // Handle text parts
// if text := part.Get("text"); text.Exists() {
// contentParts = append(contentParts, text.String())
// }
//
// // Handle function calls (Gemini) -> tool calls (OpenAI)
// if functionCall := part.Get("functionCall"); functionCall.Exists() {
// toolCallID := genToolCallID()
// toolCallIDs = append(toolCallIDs, toolCallID)
//
// toolCall := map[string]interface{}{
// "id": toolCallID,
// "type": "function",
// "function": map[string]interface{}{
// "name": functionCall.Get("name").String(),
// },
// }
//
// // Convert args to arguments JSON string
// if args := functionCall.Get("args"); args.Exists() {
// argsJSON, _ := json.Marshal(args.Value())
// toolCall["function"].(map[string]interface{})["arguments"] = string(argsJSON)
// } else {
// toolCall["function"].(map[string]interface{})["arguments"] = "{}"
// }
//
// toolCalls = append(toolCalls, toolCall)
// }
//
// return true
// })
// }
//
// // Set content
// if len(contentParts) > 0 {
// msg["content"] = strings.Join(contentParts, "")
// }
//
// // Set tool calls if any
// if len(toolCalls) > 0 {
// msg["tool_calls"] = toolCalls
// }
//
// openAIMessages = append(openAIMessages, msg)
//
// case "function":
// // Handle Gemini function role -> OpenAI tool role
// if parts.Exists() && parts.IsArray() {
// parts.ForEach(func(_, part gjson.Result) bool {
// // Handle function responses (Gemini) -> tool role messages (OpenAI)
// if functionResponse := part.Get("functionResponse"); functionResponse.Exists() {
// // Create tool message for function response
// toolMsg := map[string]interface{}{
// "role": "tool",
// "tool_call_id": "", // Will be set based on context
// "content": "",
// }
//
// // Convert response.content to JSON string
// if response := functionResponse.Get("response"); response.Exists() {
// if content = response.Get("content"); content.Exists() {
// // Use the content field from the response
// contentJSON, _ := json.Marshal(content.Value())
// toolMsg["content"] = string(contentJSON)
// } else {
// // Fallback to entire response
// responseJSON, _ := json.Marshal(response.Value())
// toolMsg["content"] = string(responseJSON)
// }
// }
//
// // Try to match with previous tool call ID
// _ = functionResponse.Get("name").String() // functionName not used for now
// if len(toolCallIDs) > 0 {
// // Use the last tool call ID (simple matching by function name)
// // In a real implementation, you might want more sophisticated matching
// toolMsg["tool_call_id"] = toolCallIDs[len(toolCallIDs)-1]
// } else {
// // Generate a tool call ID if none available
// toolMsg["tool_call_id"] = genToolCallID()
// }
//
// openAIMessages = append(openAIMessages, toolMsg)
// }
//
// return true
// })
// }
// }
return true
})
}
// Set messages
if len(openAIMessages) > 0 {
messagesJSON, _ := json.Marshal(openAIMessages)
out, _ = sjson.SetRaw(out, "messages", string(messagesJSON))
}
// Tools mapping: Gemini tools -> OpenAI tools
if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
var openAITools []interface{}
tools.ForEach(func(_, tool gjson.Result) bool {
if functionDeclarations := tool.Get("functionDeclarations"); functionDeclarations.Exists() && functionDeclarations.IsArray() {
functionDeclarations.ForEach(func(_, funcDecl gjson.Result) bool {
openAITool := map[string]interface{}{
"type": "function",
"function": map[string]interface{}{
"name": funcDecl.Get("name").String(),
"description": funcDecl.Get("description").String(),
},
}
// Convert parameters schema
if parameters := funcDecl.Get("parameters"); parameters.Exists() {
openAITool["function"].(map[string]interface{})["parameters"] = parameters.Value()
} else if parameters = funcDecl.Get("parametersJsonSchema"); parameters.Exists() {
openAITool["function"].(map[string]interface{})["parameters"] = parameters.Value()
}
openAITools = append(openAITools, openAITool)
return true
})
}
return true
})
if len(openAITools) > 0 {
toolsJSON, _ := json.Marshal(openAITools)
out, _ = sjson.SetRaw(out, "tools", string(toolsJSON))
}
}
// Tool choice mapping (Gemini doesn't have direct equivalent, but we can handle it)
if toolConfig := root.Get("toolConfig"); toolConfig.Exists() {
if functionCallingConfig := toolConfig.Get("functionCallingConfig"); functionCallingConfig.Exists() {
mode := functionCallingConfig.Get("mode").String()
switch mode {
case "NONE":
out, _ = sjson.Set(out, "tool_choice", "none")
case "AUTO":
out, _ = sjson.Set(out, "tool_choice", "auto")
case "ANY":
out, _ = sjson.Set(out, "tool_choice", "required")
}
}
}
return []byte(out)
}

600
internal/translator/openai/gemini/openai_gemini_response.go
View File

@@ -1,600 +0,0 @@
// Package gemini provides response translation functionality for OpenAI to Gemini API.
// This package handles the conversion of OpenAI Chat Completions API responses into Gemini API-compatible
// JSON format, transforming streaming events and non-streaming responses into the format
// expected by Gemini API clients. It supports both streaming and non-streaming modes,
// handling text content, tool calls, and usage metadata appropriately.
package gemini
import (
"bytes"
"context"
"encoding/json"
"strconv"
"strings"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
// ConvertOpenAIResponseToGeminiParams holds parameters for response conversion
type ConvertOpenAIResponseToGeminiParams struct {
// Tool calls accumulator for streaming
ToolCallsAccumulator map[int]*ToolCallAccumulator
// Content accumulator for streaming
ContentAccumulator strings.Builder
// Track if this is the first chunk
IsFirstChunk bool
}
// ToolCallAccumulator holds the state for accumulating tool call data
type ToolCallAccumulator struct {
ID string
Name string
Arguments strings.Builder
}
// ConvertOpenAIResponseToGemini converts OpenAI Chat Completions streaming response format to Gemini API format.
// This function processes OpenAI streaming chunks and transforms them into Gemini-compatible JSON responses.
// It handles text content, tool calls, and usage metadata, outputting responses that match the Gemini API format.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - []string: A slice of strings, each containing a Gemini-compatible JSON response.
func ConvertOpenAIResponseToGemini(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) []string {
if *param == nil {
*param = &ConvertOpenAIResponseToGeminiParams{
ToolCallsAccumulator: nil,
ContentAccumulator: strings.Builder{},
IsFirstChunk: false,
}
}
// Handle [DONE] marker
if strings.TrimSpace(string(rawJSON)) == "[DONE]" {
return []string{}
}
if bytes.HasPrefix(rawJSON, []byte("data:")) {
rawJSON = bytes.TrimSpace(rawJSON[5:])
}
root := gjson.ParseBytes(rawJSON)
// Initialize accumulators if needed
if (*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator == nil {
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
}
// Process choices
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
// Handle empty choices array (usage-only chunk)
if len(choices.Array()) == 0 {
// This is a usage-only chunk, handle usage and return
if usage := root.Get("usage"); usage.Exists() {
template := `{"candidates":[],"usageMetadata":{}}`
// Set model if available
if model := root.Get("model"); model.Exists() {
template, _ = sjson.Set(template, "model", model.String())
}
usageObj := map[string]interface{}{
"promptTokenCount": usage.Get("prompt_tokens").Int(),
"candidatesTokenCount": usage.Get("completion_tokens").Int(),
"totalTokenCount": usage.Get("total_tokens").Int(),
}
template, _ = sjson.Set(template, "usageMetadata", usageObj)
return []string{template}
}
return []string{}
}
var results []string
choices.ForEach(func(choiceIndex, choice gjson.Result) bool {
// Base Gemini response template
template := `{"candidates":[{"content":{"parts":[],"role":"model"},"finishReason":"STOP","index":0}]}`
// Set model if available
if model := root.Get("model"); model.Exists() {
template, _ = sjson.Set(template, "model", model.String())
}
_ = int(choice.Get("index").Int()) // choiceIdx not used in streaming
delta := choice.Get("delta")
// Handle role (only in first chunk)
if role := delta.Get("role"); role.Exists() && (*param).(*ConvertOpenAIResponseToGeminiParams).IsFirstChunk {
// OpenAI assistant -> Gemini model
if role.String() == "assistant" {
template, _ = sjson.Set(template, "candidates.0.content.role", "model")
}
(*param).(*ConvertOpenAIResponseToGeminiParams).IsFirstChunk = false
results = append(results, template)
return true
}
// Handle content delta
if content := delta.Get("content"); content.Exists() && content.String() != "" {
contentText := content.String()
(*param).(*ConvertOpenAIResponseToGeminiParams).ContentAccumulator.WriteString(contentText)
// Create text part for this delta
parts := []interface{}{
map[string]interface{}{
"text": contentText,
},
}
template, _ = sjson.Set(template, "candidates.0.content.parts", parts)
results = append(results, template)
return true
}
// Handle tool calls delta
if toolCalls := delta.Get("tool_calls"); toolCalls.Exists() && toolCalls.IsArray() {
toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
toolIndex := int(toolCall.Get("index").Int())
toolID := toolCall.Get("id").String()
toolType := toolCall.Get("type").String()
if toolType == "function" {
function := toolCall.Get("function")
functionName := function.Get("name").String()
functionArgs := function.Get("arguments").String()
// Initialize accumulator if needed
if _, exists := (*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator[toolIndex]; !exists {
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator[toolIndex] = &ToolCallAccumulator{
ID: toolID,
Name: functionName,
}
}
// Update ID if provided
if toolID != "" {
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator[toolIndex].ID = toolID
}
// Update name if provided
if functionName != "" {
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator[toolIndex].Name = functionName
}
// Accumulate arguments
if functionArgs != "" {
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator[toolIndex].Arguments.WriteString(functionArgs)
}
}
return true
})
// Don't output anything for tool call deltas - wait for completion
return true
}
// Handle finish reason
if finishReason := choice.Get("finish_reason"); finishReason.Exists() {
geminiFinishReason := mapOpenAIFinishReasonToGemini(finishReason.String())
template, _ = sjson.Set(template, "candidates.0.finishReason", geminiFinishReason)
// If we have accumulated tool calls, output them now
if len((*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator) > 0 {
var parts []interface{}
for _, accumulator := range (*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator {
argsStr := accumulator.Arguments.String()
var argsMap map[string]interface{}
argsMap = parseArgsToMap(argsStr)
functionCallPart := map[string]interface{}{
"functionCall": map[string]interface{}{
"name": accumulator.Name,
"args": argsMap,
},
}
parts = append(parts, functionCallPart)
}
if len(parts) > 0 {
template, _ = sjson.Set(template, "candidates.0.content.parts", parts)
}
// Clear accumulators
(*param).(*ConvertOpenAIResponseToGeminiParams).ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
}
results = append(results, template)
return true
}
// Handle usage information
if usage := root.Get("usage"); usage.Exists() {
usageObj := map[string]interface{}{
"promptTokenCount": usage.Get("prompt_tokens").Int(),
"candidatesTokenCount": usage.Get("completion_tokens").Int(),
"totalTokenCount": usage.Get("total_tokens").Int(),
}
template, _ = sjson.Set(template, "usageMetadata", usageObj)
results = append(results, template)
return true
}
return true
})
return results
}
return []string{}
}
// mapOpenAIFinishReasonToGemini maps OpenAI finish reasons to Gemini finish reasons
func mapOpenAIFinishReasonToGemini(openAIReason string) string {
switch openAIReason {
case "stop":
return "STOP"
case "length":
return "MAX_TOKENS"
case "tool_calls":
return "STOP" // Gemini doesn't have a specific tool_calls finish reason
case "content_filter":
return "SAFETY"
default:
return "STOP"
}
}
// parseArgsToMap safely parses a JSON string of function arguments into a map.
// It returns an empty map if the input is empty or cannot be parsed as a JSON object.
func parseArgsToMap(argsStr string) map[string]interface{} {
trimmed := strings.TrimSpace(argsStr)
if trimmed == "" || trimmed == "{}" {
return map[string]interface{}{}
}
// First try strict JSON
var out map[string]interface{}
if errUnmarshal := json.Unmarshal([]byte(trimmed), &out); errUnmarshal == nil {
return out
}
// Tolerant parse: handle streams where values are barewords (e.g., 北京, celsius)
tolerant := tolerantParseJSONMap(trimmed)
if len(tolerant) > 0 {
return tolerant
}
// Fallback: return empty object when parsing fails
return map[string]interface{}{}
}
// tolerantParseJSONMap attempts to parse a JSON-like object string into a map, tolerating
// bareword values (unquoted strings) commonly seen during streamed tool calls.
// Example input: {"location": 北京, "unit": celsius}
func tolerantParseJSONMap(s string) map[string]interface{} {
// Ensure we operate within the outermost braces if present
start := strings.Index(s, "{")
end := strings.LastIndex(s, "}")
if start == -1 || end == -1 || start >= end {
return map[string]interface{}{}
}
content := s[start+1 : end]
runes := []rune(content)
n := len(runes)
i := 0
result := make(map[string]interface{})
for i < n {
// Skip whitespace and commas
for i < n && (runes[i] == ' ' || runes[i] == '\n' || runes[i] == '\r' || runes[i] == '\t' || runes[i] == ',') {
i++
}
if i >= n {
break
}
// Expect quoted key
if runes[i] != '"' {
// Unable to parse this segment reliably; skip to next comma
for i < n && runes[i] != ',' {
i++
}
continue
}
// Parse JSON string for key
keyToken, nextIdx := parseJSONStringRunes(runes, i)
if nextIdx == -1 {
break
}
keyName := jsonStringTokenToRawString(keyToken)
i = nextIdx
// Skip whitespace
for i < n && (runes[i] == ' ' || runes[i] == '\n' || runes[i] == '\r' || runes[i] == '\t') {
i++
}
if i >= n || runes[i] != ':' {
break
}
i++ // skip ':'
// Skip whitespace
for i < n && (runes[i] == ' ' || runes[i] == '\n' || runes[i] == '\r' || runes[i] == '\t') {
i++
}
if i >= n {
break
}
// Parse value (string, number, object/array, bareword)
var value interface{}
switch runes[i] {
case '"':
// JSON string
valToken, ni := parseJSONStringRunes(runes, i)
if ni == -1 {
// Malformed; treat as empty string
value = ""
i = n
} else {
value = jsonStringTokenToRawString(valToken)
i = ni
}
case '{', '[':
// Bracketed value: attempt to capture balanced structure
seg, ni := captureBracketed(runes, i)
if ni == -1 {
i = n
} else {
var anyVal interface{}
if errUnmarshal := json.Unmarshal([]byte(seg), &anyVal); errUnmarshal == nil {
value = anyVal
} else {
value = seg
}
i = ni
}
default:
// Bare token until next comma or end
j := i
for j < n && runes[j] != ',' {
j++
}
token := strings.TrimSpace(string(runes[i:j]))
// Interpret common JSON atoms and numbers; otherwise treat as string
if token == "true" {
value = true
} else if token == "false" {
value = false
} else if token == "null" {
value = nil
} else if numVal, ok := tryParseNumber(token); ok {
value = numVal
} else {
value = token
}
i = j
}
result[keyName] = value
// Skip trailing whitespace and optional comma before next pair
for i < n && (runes[i] == ' ' || runes[i] == '\n' || runes[i] == '\r' || runes[i] == '\t') {
i++
}
if i < n && runes[i] == ',' {
i++
}
}
return result
}
// parseJSONStringRunes returns the JSON string token (including quotes) and the index just after it.
func parseJSONStringRunes(runes []rune, start int) (string, int) {
if start >= len(runes) || runes[start] != '"' {
return "", -1
}
i := start + 1
escaped := false
for i < len(runes) {
r := runes[i]
if r == '\\' && !escaped {
escaped = true
i++
continue
}
if r == '"' && !escaped {
return string(runes[start : i+1]), i + 1
}
escaped = false
i++
}
return string(runes[start:]), -1
}
// jsonStringTokenToRawString converts a JSON string token (including quotes) to a raw Go string value.
func jsonStringTokenToRawString(token string) string {
var s string
if errUnmarshal := json.Unmarshal([]byte(token), &s); errUnmarshal == nil {
return s
}
// Fallback: strip surrounding quotes if present
if len(token) >= 2 && token[0] == '"' && token[len(token)-1] == '"' {
return token[1 : len(token)-1]
}
return token
}
// captureBracketed captures a balanced JSON object/array starting at index i.
// Returns the segment string and the index just after it; -1 if malformed.
func captureBracketed(runes []rune, i int) (string, int) {
if i >= len(runes) {
return "", -1
}
startRune := runes[i]
var endRune rune
if startRune == '{' {
endRune = '}'
} else if startRune == '[' {
endRune = ']'
} else {
return "", -1
}
depth := 0
j := i
inStr := false
escaped := false
for j < len(runes) {
r := runes[j]
if inStr {
if r == '\\' && !escaped {
escaped = true
j++
continue
}
if r == '"' && !escaped {
inStr = false
} else {
escaped = false
}
j++
continue
}
if r == '"' {
inStr = true
j++
continue
}
if r == startRune {
depth++
} else if r == endRune {
depth--
if depth == 0 {
return string(runes[i : j+1]), j + 1
}
}
j++
}
return string(runes[i:]), -1
}
// tryParseNumber attempts to parse a string as an int or float.
func tryParseNumber(s string) (interface{}, bool) {
if s == "" {
return nil, false
}
// Try integer
if i64, errParseInt := strconv.ParseInt(s, 10, 64); errParseInt == nil {
return i64, true
}
if u64, errParseUInt := strconv.ParseUint(s, 10, 64); errParseUInt == nil {
return u64, true
}
if f64, errParseFloat := strconv.ParseFloat(s, 64); errParseFloat == nil {
return f64, true
}
return nil, false
}
// ConvertOpenAIResponseToGeminiNonStream converts a non-streaming OpenAI response to a non-streaming Gemini response.
//
// Parameters:
// - ctx: The context for the request.
// - modelName: The name of the model.
// - rawJSON: The raw JSON response from the OpenAI API.
// - param: A pointer to a parameter object for the conversion.
//
// Returns:
// - string: A Gemini-compatible JSON response.
func ConvertOpenAIResponseToGeminiNonStream(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, _ *any) string {
root := gjson.ParseBytes(rawJSON)
// Base Gemini response template
out := `{"candidates":[{"content":{"parts":[],"role":"model"},"finishReason":"STOP","index":0}]}`
// Set model if available
if model := root.Get("model"); model.Exists() {
out, _ = sjson.Set(out, "model", model.String())
}
// Process choices
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
choices.ForEach(func(choiceIndex, choice gjson.Result) bool {
choiceIdx := int(choice.Get("index").Int())
message := choice.Get("message")
// Set role
if role := message.Get("role"); role.Exists() {
if role.String() == "assistant" {
out, _ = sjson.Set(out, "candidates.0.content.role", "model")
}
}
var parts []interface{}
// Handle content first
if content := message.Get("content"); content.Exists() && content.String() != "" {
parts = append(parts, map[string]interface{}{
"text": content.String(),
})
}
// Handle tool calls
if toolCalls := message.Get("tool_calls"); toolCalls.Exists() && toolCalls.IsArray() {
toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
if toolCall.Get("type").String() == "function" {
function := toolCall.Get("function")
functionName := function.Get("name").String()
functionArgs := function.Get("arguments").String()
// Parse arguments
var argsMap map[string]interface{}
argsMap = parseArgsToMap(functionArgs)
functionCallPart := map[string]interface{}{
"functionCall": map[string]interface{}{
"name": functionName,
"args": argsMap,
},
}
parts = append(parts, functionCallPart)
}
return true
})
}
// Set parts
if len(parts) > 0 {
out, _ = sjson.Set(out, "candidates.0.content.parts", parts)
}
// Handle finish reason
if finishReason := choice.Get("finish_reason"); finishReason.Exists() {
geminiFinishReason := mapOpenAIFinishReasonToGemini(finishReason.String())
out, _ = sjson.Set(out, "candidates.0.finishReason", geminiFinishReason)
}
// Set index
out, _ = sjson.Set(out, "candidates.0.index", choiceIdx)
return true
})
}
// Handle usage information
if usage := root.Get("usage"); usage.Exists() {
usageObj := map[string]interface{}{
"promptTokenCount": usage.Get("prompt_tokens").Int(),
"candidatesTokenCount": usage.Get("completion_tokens").Int(),
"totalTokenCount": usage.Get("total_tokens").Int(),
}
out, _ = sjson.Set(out, "usageMetadata", usageObj)
}
return out
}

19
internal/translator/openai/openai/chat-completions/init.go
View File

@@ -1,19 +0,0 @@
package chat_completions
import (
. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
"github.com/router-for-me/CLIProxyAPI/v6/internal/translator/translator"
)
func init() {
translator.Register(
OpenAI,
OpenAI,
ConvertOpenAIRequestToOpenAI,
interfaces.TranslateResponse{
Stream: ConvertOpenAIResponseToOpenAI,
NonStream: ConvertOpenAIResponseToOpenAINonStream,
},
)
}

21
internal/translator/openai/openai/chat-completions/openai_openai_request.go
View File

@@ -1,21 +0,0 @@
// Package openai provides request translation functionality for OpenAI to Gemini CLI API compatibility.
// It converts OpenAI Chat Completions requests into Gemini CLI compatible JSON using gjson/sjson only.
package chat_completions
import (
"bytes"
)
// ConvertOpenAIRequestToOpenAI converts an OpenAI Chat Completions request (raw JSON)
// into a complete Gemini CLI request JSON. All JSON construction uses sjson and lookups use gjson.
//
// Parameters:
// - modelName: The name of the model to use for the request
// - rawJSON: The raw JSON request data from the OpenAI API
// - stream: A boolean indicating if the request is for a streaming response (unused in current implementation)
//
// Returns:
// - []byte: The transformed request data in Gemini CLI API format
func ConvertOpenAIRequestToOpenAI(modelName string, inputRawJSON []byte, _ bool) []byte {
return bytes.Clone(inputRawJSON)
}

52
internal/translator/openai/openai/chat-completions/openai_openai_response.go
View File

@@ -1,52 +0,0 @@
// Package openai provides response translation functionality for Gemini CLI to OpenAI API compatibility.
// This package handles the conversion of Gemini CLI API responses into OpenAI Chat Completions-compatible
// JSON format, transforming streaming events and non-streaming responses into the format
// expected by OpenAI API clients. It supports both streaming and non-streaming modes,
// handling text content, tool calls, reasoning content, and usage metadata appropriately.
package chat_completions
import (
"bytes"
"context"
)
// ConvertOpenAIResponseToOpenAI translates a single chunk of a streaming response from the
// Gemini CLI API format to the OpenAI Chat Completions streaming format.
// It processes various Gemini CLI event types and transforms them into OpenAI-compatible JSON responses.
// The function handles text content, tool calls, reasoning content, and usage metadata, outputting
// responses that match the OpenAI API format. It supports incremental updates for streaming responses.
//
// Parameters:
// - ctx: The context for the request, used for cancellation and timeout handling
// - modelName: The name of the model being used for the response (unused in current implementation)
// - rawJSON: The raw JSON response from the Gemini CLI API
// - param: A pointer to a parameter object for maintaining state between calls
//
// Returns:
// - []string: A slice of strings, each containing an OpenAI-compatible JSON response
func ConvertOpenAIResponseToOpenAI(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) []string {
if bytes.HasPrefix(rawJSON, []byte("data:")) {
rawJSON = bytes.TrimSpace(rawJSON[5:])
}
if bytes.Equal(rawJSON, []byte("[DONE]")) {
return []string{}
}
return []string{string(rawJSON)}
}
// ConvertOpenAIResponseToOpenAINonStream converts a non-streaming Gemini CLI response to a non-streaming OpenAI response.
// This function processes the complete Gemini CLI response and transforms it into a single OpenAI-compatible
// JSON response. It handles message content, tool calls, reasoning content, and usage metadata, combining all
// the information into a single response that matches the OpenAI API format.
//
// Parameters:
// - ctx: The context for the request, used for cancellation and timeout handling
// - modelName: The name of the model being used for the response
// - rawJSON: The raw JSON response from the Gemini CLI API
// - param: A pointer to a parameter object for the conversion
//
// Returns:
// - string: An OpenAI-compatible JSON response containing all message content and metadata
func ConvertOpenAIResponseToOpenAINonStream(ctx context.Context, modelName string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) string {
return string(rawJSON)
}

19
internal/translator/openai/openai/responses/init.go
View File

@@ -1,19 +0,0 @@
package responses
import (
. "github.com/router-for-me/CLIProxyAPI/v6/internal/constant"
"github.com/router-for-me/CLIProxyAPI/v6/internal/interfaces"
"github.com/router-for-me/CLIProxyAPI/v6/internal/translator/translator"
)
func init() {
translator.Register(
OpenaiResponse,
OpenAI,
ConvertOpenAIResponsesRequestToOpenAIChatCompletions,
interfaces.TranslateResponse{
Stream: ConvertOpenAIChatCompletionsResponseToOpenAIResponses,
NonStream: ConvertOpenAIChatCompletionsResponseToOpenAIResponsesNonStream,
},
)
}

210
internal/translator/openai/openai/responses/openai_openai-responses_request.go
View File

@@ -1,210 +0,0 @@
package responses
import (
"bytes"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
// ConvertOpenAIResponsesRequestToOpenAIChatCompletions converts OpenAI responses format to OpenAI chat completions format.
// It transforms the OpenAI responses API format (with instructions and input array) into the standard
// OpenAI chat completions format (with messages array and system content).
//
// The conversion handles:
// 1. Model name and streaming configuration
// 2. Instructions to system message conversion
// 3. Input array to messages array transformation
// 4. Tool definitions and tool choice conversion
// 5. Function calls and function results handling
// 6. Generation parameters mapping (max_tokens, reasoning, etc.)
//
// Parameters:
// - modelName: The name of the model to use for the request
// - rawJSON: The raw JSON request data in OpenAI responses format
// - stream: A boolean indicating if the request is for a streaming response
//
// Returns:
// - []byte: The transformed request data in OpenAI chat completions format
func ConvertOpenAIResponsesRequestToOpenAIChatCompletions(modelName string, inputRawJSON []byte, stream bool) []byte {
rawJSON := bytes.Clone(inputRawJSON)
// Base OpenAI chat completions template with default values
out := `{"model":"","messages":[],"stream":false}`
root := gjson.ParseBytes(rawJSON)
// Set model name
out, _ = sjson.Set(out, "model", modelName)
// Set stream configuration
out, _ = sjson.Set(out, "stream", stream)
// Map generation parameters from responses format to chat completions format
if maxTokens := root.Get("max_output_tokens"); maxTokens.Exists() {
out, _ = sjson.Set(out, "max_tokens", maxTokens.Int())
}
if parallelToolCalls := root.Get("parallel_tool_calls"); parallelToolCalls.Exists() {
out, _ = sjson.Set(out, "parallel_tool_calls", parallelToolCalls.Bool())
}
// Convert instructions to system message
if instructions := root.Get("instructions"); instructions.Exists() {
systemMessage := `{"role":"system","content":""}`
systemMessage, _ = sjson.Set(systemMessage, "content", instructions.String())
out, _ = sjson.SetRaw(out, "messages.-1", systemMessage)
}
// Convert input array to messages
if input := root.Get("input"); input.Exists() && input.IsArray() {
input.ForEach(func(_, item gjson.Result) bool {
itemType := item.Get("type").String()
if itemType == "" && item.Get("role").String() != "" {
itemType = "message"
}
switch itemType {
case "message":
// Handle regular message conversion
role := item.Get("role").String()
message := `{"role":"","content":""}`
message, _ = sjson.Set(message, "role", role)
if content := item.Get("content"); content.Exists() && content.IsArray() {
var messageContent string
var toolCalls []interface{}
content.ForEach(func(_, contentItem gjson.Result) bool {
contentType := contentItem.Get("type").String()
if contentType == "" {
contentType = "input_text"
}
switch contentType {
case "input_text":
text := contentItem.Get("text").String()
if messageContent != "" {
messageContent += "\n" + text
} else {
messageContent = text
}
case "output_text":
text := contentItem.Get("text").String()
if messageContent != "" {
messageContent += "\n" + text
} else {
messageContent = text
}
}
return true
})
if messageContent != "" {
message, _ = sjson.Set(message, "content", messageContent)
}
if len(toolCalls) > 0 {
message, _ = sjson.Set(message, "tool_calls", toolCalls)
}
}
out, _ = sjson.SetRaw(out, "messages.-1", message)
case "function_call":
// Handle function call conversion to assistant message with tool_calls
assistantMessage := `{"role":"assistant","tool_calls":[]}`
toolCall := `{"id":"","type":"function","function":{"name":"","arguments":""}}`
if callId := item.Get("call_id"); callId.Exists() {
toolCall, _ = sjson.Set(toolCall, "id", callId.String())
}
if name := item.Get("name"); name.Exists() {
toolCall, _ = sjson.Set(toolCall, "function.name", name.String())
}
if arguments := item.Get("arguments"); arguments.Exists() {
toolCall, _ = sjson.Set(toolCall, "function.arguments", arguments.String())
}
assistantMessage, _ = sjson.SetRaw(assistantMessage, "tool_calls.0", toolCall)
out, _ = sjson.SetRaw(out, "messages.-1", assistantMessage)
case "function_call_output":
// Handle function call output conversion to tool message
toolMessage := `{"role":"tool","tool_call_id":"","content":""}`
if callId := item.Get("call_id"); callId.Exists() {
toolMessage, _ = sjson.Set(toolMessage, "tool_call_id", callId.String())
}
if output := item.Get("output"); output.Exists() {
toolMessage, _ = sjson.Set(toolMessage, "content", output.String())
}
out, _ = sjson.SetRaw(out, "messages.-1", toolMessage)
}
return true
})
}
// Convert tools from responses format to chat completions format
if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
var chatCompletionsTools []interface{}
tools.ForEach(func(_, tool gjson.Result) bool {
chatTool := `{"type":"function","function":{}}`
// Convert tool structure from responses format to chat completions format
function := `{"name":"","description":"","parameters":{}}`
if name := tool.Get("name"); name.Exists() {
function, _ = sjson.Set(function, "name", name.String())
}
if description := tool.Get("description"); description.Exists() {
function, _ = sjson.Set(function, "description", description.String())
}
if parameters := tool.Get("parameters"); parameters.Exists() {
function, _ = sjson.SetRaw(function, "parameters", parameters.Raw)
}
chatTool, _ = sjson.SetRaw(chatTool, "function", function)
chatCompletionsTools = append(chatCompletionsTools, gjson.Parse(chatTool).Value())
return true
})
if len(chatCompletionsTools) > 0 {
out, _ = sjson.Set(out, "tools", chatCompletionsTools)
}
}
if reasoningEffort := root.Get("reasoning.effort"); reasoningEffort.Exists() {
switch reasoningEffort.String() {
case "none":
out, _ = sjson.Set(out, "reasoning_effort", "none")
case "auto":
out, _ = sjson.Set(out, "reasoning_effort", "auto")
case "minimal":
out, _ = sjson.Set(out, "reasoning_effort", "low")
case "low":
out, _ = sjson.Set(out, "reasoning_effort", "low")
case "medium":
out, _ = sjson.Set(out, "reasoning_effort", "medium")
case "high":
out, _ = sjson.Set(out, "reasoning_effort", "high")
default:
out, _ = sjson.Set(out, "reasoning_effort", "auto")
}
}
// Convert tool_choice if present
if toolChoice := root.Get("tool_choice"); toolChoice.Exists() {
out, _ = sjson.Set(out, "tool_choice", toolChoice.String())
}
return []byte(out)
}

709
internal/translator/openai/openai/responses/openai_openai-responses_response.go
View File

@@ -1,709 +0,0 @@
package responses
import (
"bytes"
"context"
"fmt"
"strings"
"time"
"github.com/tidwall/gjson"
"github.com/tidwall/sjson"
)
type oaiToResponsesState struct {
Seq int
ResponseID string
Created int64
Started bool
ReasoningID string
ReasoningIndex int
// aggregation buffers for response.output
// Per-output message text buffers by index
MsgTextBuf map[int]*strings.Builder
ReasoningBuf strings.Builder
FuncArgsBuf map[int]*strings.Builder // index -> args
FuncNames map[int]string // index -> name
FuncCallIDs map[int]string // index -> call_id
// message item state per output index
MsgItemAdded map[int]bool // whether response.output_item.added emitted for message
MsgContentAdded map[int]bool // whether response.content_part.added emitted for message
MsgItemDone map[int]bool // whether message done events were emitted
// function item done state
FuncArgsDone map[int]bool
FuncItemDone map[int]bool
}
func emitRespEvent(event string, payload string) string {
return fmt.Sprintf("event: %s\ndata: %s", event, payload)
}
// ConvertOpenAIChatCompletionsResponseToOpenAIResponses converts OpenAI Chat Completions streaming chunks
// to OpenAI Responses SSE events (response.*).
func ConvertOpenAIChatCompletionsResponseToOpenAIResponses(ctx context.Context, modelName string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, param *any) []string {
if *param == nil {
*param = &oaiToResponsesState{
FuncArgsBuf: make(map[int]*strings.Builder),
FuncNames: make(map[int]string),
FuncCallIDs: make(map[int]string),
MsgTextBuf: make(map[int]*strings.Builder),
MsgItemAdded: make(map[int]bool),
MsgContentAdded: make(map[int]bool),
MsgItemDone: make(map[int]bool),
FuncArgsDone: make(map[int]bool),
FuncItemDone: make(map[int]bool),
}
}
st := (*param).(*oaiToResponsesState)
if bytes.HasPrefix(rawJSON, []byte("data:")) {
rawJSON = bytes.TrimSpace(rawJSON[5:])
}
root := gjson.ParseBytes(rawJSON)
obj := root.Get("object").String()
if obj != "chat.completion.chunk" {
return []string{}
}
nextSeq := func() int { st.Seq++; return st.Seq }
var out []string
if !st.Started {
st.ResponseID = root.Get("id").String()
st.Created = root.Get("created").Int()
// reset aggregation state for a new streaming response
st.MsgTextBuf = make(map[int]*strings.Builder)
st.ReasoningBuf.Reset()
st.ReasoningID = ""
st.ReasoningIndex = 0
st.FuncArgsBuf = make(map[int]*strings.Builder)
st.FuncNames = make(map[int]string)
st.FuncCallIDs = make(map[int]string)
st.MsgItemAdded = make(map[int]bool)
st.MsgContentAdded = make(map[int]bool)
st.MsgItemDone = make(map[int]bool)
st.FuncArgsDone = make(map[int]bool)
st.FuncItemDone = make(map[int]bool)
// response.created
created := `{"type":"response.created","sequence_number":0,"response":{"id":"","object":"response","created_at":0,"status":"in_progress","background":false,"error":null}}`
created, _ = sjson.Set(created, "sequence_number", nextSeq())
created, _ = sjson.Set(created, "response.id", st.ResponseID)
created, _ = sjson.Set(created, "response.created_at", st.Created)
out = append(out, emitRespEvent("response.created", created))
inprog := `{"type":"response.in_progress","sequence_number":0,"response":{"id":"","object":"response","created_at":0,"status":"in_progress"}}`
inprog, _ = sjson.Set(inprog, "sequence_number", nextSeq())
inprog, _ = sjson.Set(inprog, "response.id", st.ResponseID)
inprog, _ = sjson.Set(inprog, "response.created_at", st.Created)
out = append(out, emitRespEvent("response.in_progress", inprog))
st.Started = true
}
// choices[].delta content / tool_calls / reasoning_content
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
choices.ForEach(func(_, choice gjson.Result) bool {
idx := int(choice.Get("index").Int())
delta := choice.Get("delta")
if delta.Exists() {
if c := delta.Get("content"); c.Exists() && c.String() != "" {
// Ensure the message item and its first content part are announced before any text deltas
if !st.MsgItemAdded[idx] {
item := `{"type":"response.output_item.added","sequence_number":0,"output_index":0,"item":{"id":"","type":"message","status":"in_progress","content":[],"role":"assistant"}}`
item, _ = sjson.Set(item, "sequence_number", nextSeq())
item, _ = sjson.Set(item, "output_index", idx)
item, _ = sjson.Set(item, "item.id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
out = append(out, emitRespEvent("response.output_item.added", item))
st.MsgItemAdded[idx] = true
}
if !st.MsgContentAdded[idx] {
part := `{"type":"response.content_part.added","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}`
part, _ = sjson.Set(part, "sequence_number", nextSeq())
part, _ = sjson.Set(part, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
part, _ = sjson.Set(part, "output_index", idx)
part, _ = sjson.Set(part, "content_index", 0)
out = append(out, emitRespEvent("response.content_part.added", part))
st.MsgContentAdded[idx] = true
}
msg := `{"type":"response.output_text.delta","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"delta":"","logprobs":[]}`
msg, _ = sjson.Set(msg, "sequence_number", nextSeq())
msg, _ = sjson.Set(msg, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
msg, _ = sjson.Set(msg, "output_index", idx)
msg, _ = sjson.Set(msg, "content_index", 0)
msg, _ = sjson.Set(msg, "delta", c.String())
out = append(out, emitRespEvent("response.output_text.delta", msg))
// aggregate for response.output
if st.MsgTextBuf[idx] == nil {
st.MsgTextBuf[idx] = &strings.Builder{}
}
st.MsgTextBuf[idx].WriteString(c.String())
}
// reasoning_content (OpenAI reasoning incremental text)
if rc := delta.Get("reasoning_content"); rc.Exists() && rc.String() != "" {
// On first appearance, add reasoning item and part
if st.ReasoningID == "" {
st.ReasoningID = fmt.Sprintf("rs_%s_%d", st.ResponseID, idx)
st.ReasoningIndex = idx
item := `{"type":"response.output_item.added","sequence_number":0,"output_index":0,"item":{"id":"","type":"reasoning","status":"in_progress","summary":[]}}`
item, _ = sjson.Set(item, "sequence_number", nextSeq())
item, _ = sjson.Set(item, "output_index", idx)
item, _ = sjson.Set(item, "item.id", st.ReasoningID)
out = append(out, emitRespEvent("response.output_item.added", item))
part := `{"type":"response.reasoning_summary_part.added","sequence_number":0,"item_id":"","output_index":0,"summary_index":0,"part":{"type":"summary_text","text":""}}`
part, _ = sjson.Set(part, "sequence_number", nextSeq())
part, _ = sjson.Set(part, "item_id", st.ReasoningID)
part, _ = sjson.Set(part, "output_index", st.ReasoningIndex)
out = append(out, emitRespEvent("response.reasoning_summary_part.added", part))
}
// Append incremental text to reasoning buffer
st.ReasoningBuf.WriteString(rc.String())
msg := `{"type":"response.reasoning_summary_text.delta","sequence_number":0,"item_id":"","output_index":0,"summary_index":0,"text":""}`
msg, _ = sjson.Set(msg, "sequence_number", nextSeq())
msg, _ = sjson.Set(msg, "item_id", st.ReasoningID)
msg, _ = sjson.Set(msg, "output_index", st.ReasoningIndex)
msg, _ = sjson.Set(msg, "text", rc.String())
out = append(out, emitRespEvent("response.reasoning_summary_text.delta", msg))
}
// tool calls
if tcs := delta.Get("tool_calls"); tcs.Exists() && tcs.IsArray() {
// Before emitting any function events, if a message is open for this index,
// close its text/content to match Codex expected ordering.
if st.MsgItemAdded[idx] && !st.MsgItemDone[idx] {
fullText := ""
if b := st.MsgTextBuf[idx]; b != nil {
fullText = b.String()
}
done := `{"type":"response.output_text.done","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"text":"","logprobs":[]}`
done, _ = sjson.Set(done, "sequence_number", nextSeq())
done, _ = sjson.Set(done, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
done, _ = sjson.Set(done, "output_index", idx)
done, _ = sjson.Set(done, "content_index", 0)
done, _ = sjson.Set(done, "text", fullText)
out = append(out, emitRespEvent("response.output_text.done", done))
partDone := `{"type":"response.content_part.done","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}`
partDone, _ = sjson.Set(partDone, "sequence_number", nextSeq())
partDone, _ = sjson.Set(partDone, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
partDone, _ = sjson.Set(partDone, "output_index", idx)
partDone, _ = sjson.Set(partDone, "content_index", 0)
partDone, _ = sjson.Set(partDone, "part.text", fullText)
out = append(out, emitRespEvent("response.content_part.done", partDone))
itemDone := `{"type":"response.output_item.done","sequence_number":0,"output_index":0,"item":{"id":"","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":""}],"role":"assistant"}}`
itemDone, _ = sjson.Set(itemDone, "sequence_number", nextSeq())
itemDone, _ = sjson.Set(itemDone, "output_index", idx)
itemDone, _ = sjson.Set(itemDone, "item.id", fmt.Sprintf("msg_%s_%d", st.ResponseID, idx))
itemDone, _ = sjson.Set(itemDone, "item.content.0.text", fullText)
out = append(out, emitRespEvent("response.output_item.done", itemDone))
st.MsgItemDone[idx] = true
}
// Only emit item.added once per tool call and preserve call_id across chunks.
newCallID := tcs.Get("0.id").String()
nameChunk := tcs.Get("0.function.name").String()
if nameChunk != "" {
st.FuncNames[idx] = nameChunk
}
existingCallID := st.FuncCallIDs[idx]
effectiveCallID := existingCallID
shouldEmitItem := false
if existingCallID == "" && newCallID != "" {
// First time seeing a valid call_id for this index
effectiveCallID = newCallID
st.FuncCallIDs[idx] = newCallID
shouldEmitItem = true
}
if shouldEmitItem && effectiveCallID != "" {
o := `{"type":"response.output_item.added","sequence_number":0,"output_index":0,"item":{"id":"","type":"function_call","status":"in_progress","arguments":"","call_id":"","name":""}}`
o, _ = sjson.Set(o, "sequence_number", nextSeq())
o, _ = sjson.Set(o, "output_index", idx)
o, _ = sjson.Set(o, "item.id", fmt.Sprintf("fc_%s", effectiveCallID))
o, _ = sjson.Set(o, "item.call_id", effectiveCallID)
name := st.FuncNames[idx]
o, _ = sjson.Set(o, "item.name", name)
out = append(out, emitRespEvent("response.output_item.added", o))
}
// Ensure args buffer exists for this index
if st.FuncArgsBuf[idx] == nil {
st.FuncArgsBuf[idx] = &strings.Builder{}
}
// Append arguments delta if available and we have a valid call_id to reference
if args := tcs.Get("0.function.arguments"); args.Exists() && args.String() != "" {
// Prefer an already known call_id; fall back to newCallID if first time
refCallID := st.FuncCallIDs[idx]
if refCallID == "" {
refCallID = newCallID
}
if refCallID != "" {
ad := `{"type":"response.function_call_arguments.delta","sequence_number":0,"item_id":"","output_index":0,"delta":""}`
ad, _ = sjson.Set(ad, "sequence_number", nextSeq())
ad, _ = sjson.Set(ad, "item_id", fmt.Sprintf("fc_%s", refCallID))
ad, _ = sjson.Set(ad, "output_index", idx)
ad, _ = sjson.Set(ad, "delta", args.String())
out = append(out, emitRespEvent("response.function_call_arguments.delta", ad))
}
st.FuncArgsBuf[idx].WriteString(args.String())
}
}
}
// finish_reason triggers finalization, including text done/content done/item done,
// reasoning done/part.done, function args done/item done, and completed
if fr := choice.Get("finish_reason"); fr.Exists() && fr.String() != "" {
// Emit message done events for all indices that started a message
if len(st.MsgItemAdded) > 0 {
// sort indices for deterministic order
idxs := make([]int, 0, len(st.MsgItemAdded))
for i := range st.MsgItemAdded {
idxs = append(idxs, i)
}
for i := 0; i < len(idxs); i++ {
for j := i + 1; j < len(idxs); j++ {
if idxs[j] < idxs[i] {
idxs[i], idxs[j] = idxs[j], idxs[i]
}
}
}
for _, i := range idxs {
if st.MsgItemAdded[i] && !st.MsgItemDone[i] {
fullText := ""
if b := st.MsgTextBuf[i]; b != nil {
fullText = b.String()
}
done := `{"type":"response.output_text.done","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"text":"","logprobs":[]}`
done, _ = sjson.Set(done, "sequence_number", nextSeq())
done, _ = sjson.Set(done, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, i))
done, _ = sjson.Set(done, "output_index", i)
done, _ = sjson.Set(done, "content_index", 0)
done, _ = sjson.Set(done, "text", fullText)
out = append(out, emitRespEvent("response.output_text.done", done))
partDone := `{"type":"response.content_part.done","sequence_number":0,"item_id":"","output_index":0,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}`
partDone, _ = sjson.Set(partDone, "sequence_number", nextSeq())
partDone, _ = sjson.Set(partDone, "item_id", fmt.Sprintf("msg_%s_%d", st.ResponseID, i))
partDone, _ = sjson.Set(partDone, "output_index", i)
partDone, _ = sjson.Set(partDone, "content_index", 0)
partDone, _ = sjson.Set(partDone, "part.text", fullText)
out = append(out, emitRespEvent("response.content_part.done", partDone))
itemDone := `{"type":"response.output_item.done","sequence_number":0,"output_index":0,"item":{"id":"","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":""}],"role":"assistant"}}`
itemDone, _ = sjson.Set(itemDone, "sequence_number", nextSeq())
itemDone, _ = sjson.Set(itemDone, "output_index", i)
itemDone, _ = sjson.Set(itemDone, "item.id", fmt.Sprintf("msg_%s_%d", st.ResponseID, i))
itemDone, _ = sjson.Set(itemDone, "item.content.0.text", fullText)
out = append(out, emitRespEvent("response.output_item.done", itemDone))
st.MsgItemDone[i] = true
}
}
}
if st.ReasoningID != "" {
// Emit reasoning done events
textDone := `{"type":"response.reasoning_summary_text.done","sequence_number":0,"item_id":"","output_index":0,"summary_index":0,"text":""}`
textDone, _ = sjson.Set(textDone, "sequence_number", nextSeq())
textDone, _ = sjson.Set(textDone, "item_id", st.ReasoningID)
textDone, _ = sjson.Set(textDone, "output_index", st.ReasoningIndex)
out = append(out, emitRespEvent("response.reasoning_summary_text.done", textDone))
partDone := `{"type":"response.reasoning_summary_part.done","sequence_number":0,"item_id":"","output_index":0,"summary_index":0,"part":{"type":"summary_text","text":""}}`
partDone, _ = sjson.Set(partDone, "sequence_number", nextSeq())
partDone, _ = sjson.Set(partDone, "item_id", st.ReasoningID)
partDone, _ = sjson.Set(partDone, "output_index", st.ReasoningIndex)
out = append(out, emitRespEvent("response.reasoning_summary_part.done", partDone))
}
// Emit function call done events for any active function calls
if len(st.FuncCallIDs) > 0 {
idxs := make([]int, 0, len(st.FuncCallIDs))
for i := range st.FuncCallIDs {
idxs = append(idxs, i)
}
for i := 0; i < len(idxs); i++ {
for j := i + 1; j < len(idxs); j++ {
if idxs[j] < idxs[i] {
idxs[i], idxs[j] = idxs[j], idxs[i]
}
}
}
for _, i := range idxs {
callID := st.FuncCallIDs[i]
if callID == "" || st.FuncItemDone[i] {
continue
}
args := "{}"
if b := st.FuncArgsBuf[i]; b != nil && b.Len() > 0 {
args = b.String()
}
fcDone := `{"type":"response.function_call_arguments.done","sequence_number":0,"item_id":"","output_index":0,"arguments":""}`
fcDone, _ = sjson.Set(fcDone, "sequence_number", nextSeq())
fcDone, _ = sjson.Set(fcDone, "item_id", fmt.Sprintf("fc_%s", callID))
fcDone, _ = sjson.Set(fcDone, "output_index", i)
fcDone, _ = sjson.Set(fcDone, "arguments", args)
out = append(out, emitRespEvent("response.function_call_arguments.done", fcDone))
itemDone := `{"type":"response.output_item.done","sequence_number":0,"output_index":0,"item":{"id":"","type":"function_call","status":"completed","arguments":"","call_id":"","name":""}}`
itemDone, _ = sjson.Set(itemDone, "sequence_number", nextSeq())
itemDone, _ = sjson.Set(itemDone, "output_index", i)
itemDone, _ = sjson.Set(itemDone, "item.id", fmt.Sprintf("fc_%s", callID))
itemDone, _ = sjson.Set(itemDone, "item.arguments", args)
itemDone, _ = sjson.Set(itemDone, "item.call_id", callID)
itemDone, _ = sjson.Set(itemDone, "item.name", st.FuncNames[i])
out = append(out, emitRespEvent("response.output_item.done", itemDone))
st.FuncItemDone[i] = true
st.FuncArgsDone[i] = true
}
}
completed := `{"type":"response.completed","sequence_number":0,"response":{"id":"","object":"response","created_at":0,"status":"completed","background":false,"error":null}}`
completed, _ = sjson.Set(completed, "sequence_number", nextSeq())
completed, _ = sjson.Set(completed, "response.id", st.ResponseID)
completed, _ = sjson.Set(completed, "response.created_at", st.Created)
// Inject original request fields into response as per docs/response.completed.json
if requestRawJSON != nil {
req := gjson.ParseBytes(requestRawJSON)
if v := req.Get("instructions"); v.Exists() {
completed, _ = sjson.Set(completed, "response.instructions", v.String())
}
if v := req.Get("max_output_tokens"); v.Exists() {
completed, _ = sjson.Set(completed, "response.max_output_tokens", v.Int())
}
if v := req.Get("max_tool_calls"); v.Exists() {
completed, _ = sjson.Set(completed, "response.max_tool_calls", v.Int())
}
if v := req.Get("model"); v.Exists() {
completed, _ = sjson.Set(completed, "response.model", v.String())
}
if v := req.Get("parallel_tool_calls"); v.Exists() {
completed, _ = sjson.Set(completed, "response.parallel_tool_calls", v.Bool())
}
if v := req.Get("previous_response_id"); v.Exists() {
completed, _ = sjson.Set(completed, "response.previous_response_id", v.String())
}
if v := req.Get("prompt_cache_key"); v.Exists() {
completed, _ = sjson.Set(completed, "response.prompt_cache_key", v.String())
}
if v := req.Get("reasoning"); v.Exists() {
completed, _ = sjson.Set(completed, "response.reasoning", v.Value())
}
if v := req.Get("safety_identifier"); v.Exists() {
completed, _ = sjson.Set(completed, "response.safety_identifier", v.String())
}
if v := req.Get("service_tier"); v.Exists() {
completed, _ = sjson.Set(completed, "response.service_tier", v.String())
}
if v := req.Get("store"); v.Exists() {
completed, _ = sjson.Set(completed, "response.store", v.Bool())
}
if v := req.Get("temperature"); v.Exists() {
completed, _ = sjson.Set(completed, "response.temperature", v.Float())
}
if v := req.Get("text"); v.Exists() {
completed, _ = sjson.Set(completed, "response.text", v.Value())
}
if v := req.Get("tool_choice"); v.Exists() {
completed, _ = sjson.Set(completed, "response.tool_choice", v.Value())
}
if v := req.Get("tools"); v.Exists() {
completed, _ = sjson.Set(completed, "response.tools", v.Value())
}
if v := req.Get("top_logprobs"); v.Exists() {
completed, _ = sjson.Set(completed, "response.top_logprobs", v.Int())
}
if v := req.Get("top_p"); v.Exists() {
completed, _ = sjson.Set(completed, "response.top_p", v.Float())
}
if v := req.Get("truncation"); v.Exists() {
completed, _ = sjson.Set(completed, "response.truncation", v.String())
}
if v := req.Get("user"); v.Exists() {
completed, _ = sjson.Set(completed, "response.user", v.Value())
}
if v := req.Get("metadata"); v.Exists() {
completed, _ = sjson.Set(completed, "response.metadata", v.Value())
}
}
// Build response.output using aggregated buffers
var outputs []interface{}
if st.ReasoningBuf.Len() > 0 {
outputs = append(outputs, map[string]interface{}{
"id": st.ReasoningID,
"type": "reasoning",
"summary": []interface{}{map[string]interface{}{
"type": "summary_text",
"text": st.ReasoningBuf.String(),
}},
})
}
// Append message items in ascending index order
if len(st.MsgItemAdded) > 0 {
midxs := make([]int, 0, len(st.MsgItemAdded))
for i := range st.MsgItemAdded {
midxs = append(midxs, i)
}
for i := 0; i < len(midxs); i++ {
for j := i + 1; j < len(midxs); j++ {
if midxs[j] < midxs[i] {
midxs[i], midxs[j] = midxs[j], midxs[i]
}
}
}
for _, i := range midxs {
txt := ""
if b := st.MsgTextBuf[i]; b != nil {
txt = b.String()
}
outputs = append(outputs, map[string]interface{}{
"id": fmt.Sprintf("msg_%s_%d", st.ResponseID, i),
"type": "message",
"status": "completed",
"content": []interface{}{map[string]interface{}{
"type": "output_text",
"annotations": []interface{}{},
"logprobs": []interface{}{},
"text": txt,
}},
"role": "assistant",
})
}
}
if len(st.FuncArgsBuf) > 0 {
idxs := make([]int, 0, len(st.FuncArgsBuf))
for i := range st.FuncArgsBuf {
idxs = append(idxs, i)
}
// small-N sort without extra imports
for i := 0; i < len(idxs); i++ {
for j := i + 1; j < len(idxs); j++ {
if idxs[j] < idxs[i] {
idxs[i], idxs[j] = idxs[j], idxs[i]
}
}
}
for _, i := range idxs {
args := ""
if b := st.FuncArgsBuf[i]; b != nil {
args = b.String()
}
callID := st.FuncCallIDs[i]
name := st.FuncNames[i]
outputs = append(outputs, map[string]interface{}{
"id": fmt.Sprintf("fc_%s", callID),
"type": "function_call",
"status": "completed",
"arguments": args,
"call_id": callID,
"name": name,
})
}
}
if len(outputs) > 0 {
completed, _ = sjson.Set(completed, "response.output", outputs)
}
out = append(out, emitRespEvent("response.completed", completed))
}
return true
})
}
return out
}
// ConvertOpenAIChatCompletionsResponseToOpenAIResponsesNonStream builds a single Responses JSON
// from a non-streaming OpenAI Chat Completions response.
func ConvertOpenAIChatCompletionsResponseToOpenAIResponsesNonStream(_ context.Context, _ string, originalRequestRawJSON, requestRawJSON, rawJSON []byte, _ *any) string {
root := gjson.ParseBytes(rawJSON)
// Basic response scaffold
resp := `{"id":"","object":"response","created_at":0,"status":"completed","background":false,"error":null,"incomplete_details":null}`
// id: use provider id if present, otherwise synthesize
id := root.Get("id").String()
if id == "" {
id = fmt.Sprintf("resp_%x", time.Now().UnixNano())
}
resp, _ = sjson.Set(resp, "id", id)
// created_at: map from chat.completion created
created := root.Get("created").Int()
if created == 0 {
created = time.Now().Unix()
}
resp, _ = sjson.Set(resp, "created_at", created)
// Echo request fields when available (aligns with streaming path behavior)
if len(requestRawJSON) > 0 {
req := gjson.ParseBytes(requestRawJSON)
if v := req.Get("instructions"); v.Exists() {
resp, _ = sjson.Set(resp, "instructions", v.String())
}
if v := req.Get("max_output_tokens"); v.Exists() {
resp, _ = sjson.Set(resp, "max_output_tokens", v.Int())
} else {
// Also support max_tokens from chat completion style
if v = req.Get("max_tokens"); v.Exists() {
resp, _ = sjson.Set(resp, "max_output_tokens", v.Int())
}
}
if v := req.Get("max_tool_calls"); v.Exists() {
resp, _ = sjson.Set(resp, "max_tool_calls", v.Int())
}
if v := req.Get("model"); v.Exists() {
resp, _ = sjson.Set(resp, "model", v.String())
} else if v = root.Get("model"); v.Exists() {
resp, _ = sjson.Set(resp, "model", v.String())
}
if v := req.Get("parallel_tool_calls"); v.Exists() {
resp, _ = sjson.Set(resp, "parallel_tool_calls", v.Bool())
}
if v := req.Get("previous_response_id"); v.Exists() {
resp, _ = sjson.Set(resp, "previous_response_id", v.String())
}
if v := req.Get("prompt_cache_key"); v.Exists() {
resp, _ = sjson.Set(resp, "prompt_cache_key", v.String())
}
if v := req.Get("reasoning"); v.Exists() {
resp, _ = sjson.Set(resp, "reasoning", v.Value())
}
if v := req.Get("safety_identifier"); v.Exists() {
resp, _ = sjson.Set(resp, "safety_identifier", v.String())
}
if v := req.Get("service_tier"); v.Exists() {
resp, _ = sjson.Set(resp, "service_tier", v.String())
}
if v := req.Get("store"); v.Exists() {
resp, _ = sjson.Set(resp, "store", v.Bool())
}
if v := req.Get("temperature"); v.Exists() {
resp, _ = sjson.Set(resp, "temperature", v.Float())
}
if v := req.Get("text"); v.Exists() {
resp, _ = sjson.Set(resp, "text", v.Value())
}
if v := req.Get("tool_choice"); v.Exists() {
resp, _ = sjson.Set(resp, "tool_choice", v.Value())
}
if v := req.Get("tools"); v.Exists() {
resp, _ = sjson.Set(resp, "tools", v.Value())
}
if v := req.Get("top_logprobs"); v.Exists() {
resp, _ = sjson.Set(resp, "top_logprobs", v.Int())
}
if v := req.Get("top_p"); v.Exists() {
resp, _ = sjson.Set(resp, "top_p", v.Float())
}
if v := req.Get("truncation"); v.Exists() {
resp, _ = sjson.Set(resp, "truncation", v.String())
}
if v := req.Get("user"); v.Exists() {
resp, _ = sjson.Set(resp, "user", v.Value())
}
if v := req.Get("metadata"); v.Exists() {
resp, _ = sjson.Set(resp, "metadata", v.Value())
}
} else if v := root.Get("model"); v.Exists() {
// Fallback model from response
resp, _ = sjson.Set(resp, "model", v.String())
}
// Build output list from choices[...]
var outputs []interface{}
// Detect and capture reasoning content if present
rcText := gjson.GetBytes(rawJSON, "choices.0.message.reasoning_content").String()
includeReasoning := rcText != ""
if !includeReasoning && len(requestRawJSON) > 0 {
includeReasoning = gjson.GetBytes(requestRawJSON, "reasoning").Exists()
}
if includeReasoning {
rid := id
if strings.HasPrefix(rid, "resp_") {
rid = strings.TrimPrefix(rid, "resp_")
}
reasoningItem := map[string]interface{}{
"id": fmt.Sprintf("rs_%s", rid),
"type": "reasoning",
"encrypted_content": "",
}
// Prefer summary_text from reasoning_content; encrypted_content is optional
var summaries []interface{}
if rcText != "" {
summaries = append(summaries, map[string]interface{}{
"type": "summary_text",
"text": rcText,
})
}
reasoningItem["summary"] = summaries
outputs = append(outputs, reasoningItem)
}
if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
choices.ForEach(func(_, choice gjson.Result) bool {
msg := choice.Get("message")
if msg.Exists() {
// Text message part
if c := msg.Get("content"); c.Exists() && c.String() != "" {
outputs = append(outputs, map[string]interface{}{
"id": fmt.Sprintf("msg_%s_%d", id, int(choice.Get("index").Int())),
"type": "message",
"status": "completed",
"content": []interface{}{map[string]interface{}{
"type": "output_text",
"annotations": []interface{}{},
"logprobs": []interface{}{},
"text": c.String(),
}},
"role": "assistant",
})
}
// Function/tool calls
if tcs := msg.Get("tool_calls"); tcs.Exists() && tcs.IsArray() {
tcs.ForEach(func(_, tc gjson.Result) bool {
callID := tc.Get("id").String()
name := tc.Get("function.name").String()
args := tc.Get("function.arguments").String()
outputs = append(outputs, map[string]interface{}{
"id": fmt.Sprintf("fc_%s", callID),
"type": "function_call",
"status": "completed",
"arguments": args,
"call_id": callID,
"name": name,
})
return true
})
}
}
return true
})
}
if len(outputs) > 0 {
resp, _ = sjson.Set(resp, "output", outputs)
}
// usage mapping
if usage := root.Get("usage"); usage.Exists() {
// Map common tokens
if usage.Get("prompt_tokens").Exists() || usage.Get("completion_tokens").Exists() || usage.Get("total_tokens").Exists() {
resp, _ = sjson.Set(resp, "usage.input_tokens", usage.Get("prompt_tokens").Int())
if d := usage.Get("prompt_tokens_details.cached_tokens"); d.Exists() {
resp, _ = sjson.Set(resp, "usage.input_tokens_details.cached_tokens", d.Int())
}
resp, _ = sjson.Set(resp, "usage.output_tokens", usage.Get("completion_tokens").Int())
// Reasoning tokens not available in Chat Completions; set only if present under output_tokens_details
if d := usage.Get("output_tokens_details.reasoning_tokens"); d.Exists() {
resp, _ = sjson.Set(resp, "usage.output_tokens_details.reasoning_tokens", d.Int())
}
resp, _ = sjson.Set(resp, "usage.total_tokens", usage.Get("total_tokens").Int())
} else {
// Fallback to raw usage object if structure differs
resp, _ = sjson.Set(resp, "usage", usage.Value())
}
}
return resp
}