mirror of
https://github.com/router-for-me/CLIProxyAPI.git
synced 2026-02-18 20:30:51 +08:00
Add Qwen support
This commit is contained in:
Luis Pater
359
internal/translator/openai/gemini/openai_gemini_request.go
Normal file
359
internal/translator/openai/gemini/openai_gemini_request.go
Normal file
@@ -0,0 +1,359 @@
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// Package gemini provides request translation functionality for Gemini to OpenAI API.
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// It handles parsing and transforming Gemini API requests into OpenAI Chat Completions API format,
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// extracting model information, generation config, message contents, and tool declarations.
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// The package performs JSON data transformation to ensure compatibility
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// between Gemini API format and OpenAI API's expected format.
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package gemini
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import (
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"crypto/rand"
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"encoding/json"
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"math/big"
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"strings"
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"github.com/tidwall/gjson"
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"github.com/tidwall/sjson"
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)
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// ConvertGeminiRequestToOpenAI parses and transforms a Gemini API request into OpenAI Chat Completions API format.
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// It extracts the model name, generation config, message contents, and tool declarations
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// from the raw JSON request and returns them in the format expected by the OpenAI API.
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func ConvertGeminiRequestToOpenAI(rawJSON []byte) string {
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// Base OpenAI Chat Completions API template
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out := `{"model":"","messages":[]}`
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root := gjson.ParseBytes(rawJSON)
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// Helper for generating tool call IDs in the form: call_<alphanum>
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genToolCallID := func() string {
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const letters = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
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var b strings.Builder
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// 24 chars random suffix
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for i := 0; i < 24; i++ {
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n, _ := rand.Int(rand.Reader, big.NewInt(int64(len(letters))))
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b.WriteByte(letters[n.Int64()])
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}
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return "call_" + b.String()
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}
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// Model mapping
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if model := root.Get("model"); model.Exists() {
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modelStr := model.String()
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out, _ = sjson.Set(out, "model", modelStr)
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}
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// Generation config mapping
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if genConfig := root.Get("generationConfig"); genConfig.Exists() {
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// Temperature
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if temp := genConfig.Get("temperature"); temp.Exists() {
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out, _ = sjson.Set(out, "temperature", temp.Float())
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}
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// Max tokens
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if maxTokens := genConfig.Get("maxOutputTokens"); maxTokens.Exists() {
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out, _ = sjson.Set(out, "max_tokens", maxTokens.Int())
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}
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// Top P
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if topP := genConfig.Get("topP"); topP.Exists() {
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out, _ = sjson.Set(out, "top_p", topP.Float())
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}
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// Top K (OpenAI doesn't have direct equivalent, but we can map it)
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if topK := genConfig.Get("topK"); topK.Exists() {
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// Store as custom parameter for potential use
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out, _ = sjson.Set(out, "top_k", topK.Int())
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}
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// Stop sequences
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if stopSequences := genConfig.Get("stopSequences"); stopSequences.Exists() && stopSequences.IsArray() {
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var stops []string
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stopSequences.ForEach(func(_, value gjson.Result) bool {
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stops = append(stops, value.String())
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return true
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})
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if len(stops) > 0 {
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out, _ = sjson.Set(out, "stop", stops)
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}
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}
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}
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// Stream parameter
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if stream := root.Get("stream"); stream.Exists() {
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out, _ = sjson.Set(out, "stream", stream.Bool())
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}
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// Process contents (Gemini messages) -> OpenAI messages
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var openAIMessages []interface{}
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var toolCallIDs []string // Track tool call IDs for matching with tool results
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if contents := root.Get("contents"); contents.Exists() && contents.IsArray() {
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contents.ForEach(func(_, content gjson.Result) bool {
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role := content.Get("role").String()
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parts := content.Get("parts")
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// Convert role: model -> assistant
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if role == "model" {
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role = "assistant"
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}
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// Create OpenAI message
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msg := map[string]interface{}{
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"role": role,
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"content": "",
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}
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var contentParts []string
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var toolCalls []interface{}
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if parts.Exists() && parts.IsArray() {
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parts.ForEach(func(_, part gjson.Result) bool {
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// Handle text parts
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if text := part.Get("text"); text.Exists() {
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contentParts = append(contentParts, text.String())
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}
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// Handle function calls (Gemini) -> tool calls (OpenAI)
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if functionCall := part.Get("functionCall"); functionCall.Exists() {
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toolCallID := genToolCallID()
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toolCallIDs = append(toolCallIDs, toolCallID)
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toolCall := map[string]interface{}{
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"id": toolCallID,
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"type": "function",
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"function": map[string]interface{}{
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"name": functionCall.Get("name").String(),
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},
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}
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// Convert args to arguments JSON string
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if args := functionCall.Get("args"); args.Exists() {
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argsJSON, _ := json.Marshal(args.Value())
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toolCall["function"].(map[string]interface{})["arguments"] = string(argsJSON)
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} else {
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toolCall["function"].(map[string]interface{})["arguments"] = "{}"
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}
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toolCalls = append(toolCalls, toolCall)
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}
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// Handle function responses (Gemini) -> tool role messages (OpenAI)
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if functionResponse := part.Get("functionResponse"); functionResponse.Exists() {
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// Create tool message for function response
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toolMsg := map[string]interface{}{
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"role": "tool",
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"tool_call_id": "", // Will be set based on context
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"content": "",
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}
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// Convert response.content to JSON string
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if response := functionResponse.Get("response"); response.Exists() {
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if content = response.Get("content"); content.Exists() {
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// Use the content field from the response
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contentJSON, _ := json.Marshal(content.Value())
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toolMsg["content"] = string(contentJSON)
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} else {
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// Fallback to entire response
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responseJSON, _ := json.Marshal(response.Value())
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toolMsg["content"] = string(responseJSON)
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}
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}
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// Try to match with previous tool call ID
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_ = functionResponse.Get("name").String() // functionName not used for now
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if len(toolCallIDs) > 0 {
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// Use the last tool call ID (simple matching by function name)
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// In a real implementation, you might want more sophisticated matching
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toolMsg["tool_call_id"] = toolCallIDs[len(toolCallIDs)-1]
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} else {
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// Generate a tool call ID if none available
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toolMsg["tool_call_id"] = genToolCallID()
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}
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openAIMessages = append(openAIMessages, toolMsg)
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}
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return true
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})
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}
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// Set content
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if len(contentParts) > 0 {
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msg["content"] = strings.Join(contentParts, "")
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}
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// Set tool calls if any
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if len(toolCalls) > 0 {
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msg["tool_calls"] = toolCalls
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}
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openAIMessages = append(openAIMessages, msg)
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// switch role {
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// case "user", "model":
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// // Convert role: model -> assistant
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// if role == "model" {
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// role = "assistant"
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// }
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//
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// // Create OpenAI message
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// msg := map[string]interface{}{
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// "role": role,
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// "content": "",
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// }
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//
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// var contentParts []string
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// var toolCalls []interface{}
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//
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// if parts.Exists() && parts.IsArray() {
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// parts.ForEach(func(_, part gjson.Result) bool {
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// // Handle text parts
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// if text := part.Get("text"); text.Exists() {
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// contentParts = append(contentParts, text.String())
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// }
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//
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// // Handle function calls (Gemini) -> tool calls (OpenAI)
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// if functionCall := part.Get("functionCall"); functionCall.Exists() {
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// toolCallID := genToolCallID()
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// toolCallIDs = append(toolCallIDs, toolCallID)
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//
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// toolCall := map[string]interface{}{
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// "id": toolCallID,
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// "type": "function",
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// "function": map[string]interface{}{
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// "name": functionCall.Get("name").String(),
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// },
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// }
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//
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// // Convert args to arguments JSON string
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// if args := functionCall.Get("args"); args.Exists() {
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// argsJSON, _ := json.Marshal(args.Value())
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// toolCall["function"].(map[string]interface{})["arguments"] = string(argsJSON)
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// } else {
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// toolCall["function"].(map[string]interface{})["arguments"] = "{}"
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// }
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//
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// toolCalls = append(toolCalls, toolCall)
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// }
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//
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// return true
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// })
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// }
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//
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// // Set content
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// if len(contentParts) > 0 {
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// msg["content"] = strings.Join(contentParts, "")
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// }
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//
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// // Set tool calls if any
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// if len(toolCalls) > 0 {
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// msg["tool_calls"] = toolCalls
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// }
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//
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// openAIMessages = append(openAIMessages, msg)
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//
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// case "function":
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// // Handle Gemini function role -> OpenAI tool role
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// if parts.Exists() && parts.IsArray() {
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// parts.ForEach(func(_, part gjson.Result) bool {
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// // Handle function responses (Gemini) -> tool role messages (OpenAI)
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// if functionResponse := part.Get("functionResponse"); functionResponse.Exists() {
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// // Create tool message for function response
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// toolMsg := map[string]interface{}{
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// "role": "tool",
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// "tool_call_id": "", // Will be set based on context
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// "content": "",
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// }
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//
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// // Convert response.content to JSON string
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// if response := functionResponse.Get("response"); response.Exists() {
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// if content = response.Get("content"); content.Exists() {
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// // Use the content field from the response
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// contentJSON, _ := json.Marshal(content.Value())
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// toolMsg["content"] = string(contentJSON)
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// } else {
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// // Fallback to entire response
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// responseJSON, _ := json.Marshal(response.Value())
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// toolMsg["content"] = string(responseJSON)
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// }
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// }
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//
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// // Try to match with previous tool call ID
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// _ = functionResponse.Get("name").String() // functionName not used for now
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// if len(toolCallIDs) > 0 {
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// // Use the last tool call ID (simple matching by function name)
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// // In a real implementation, you might want more sophisticated matching
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// toolMsg["tool_call_id"] = toolCallIDs[len(toolCallIDs)-1]
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// } else {
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// // Generate a tool call ID if none available
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// toolMsg["tool_call_id"] = genToolCallID()
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// }
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//
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// openAIMessages = append(openAIMessages, toolMsg)
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// }
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//
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// return true
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// })
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// }
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// }
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return true
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})
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}
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// Set messages
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if len(openAIMessages) > 0 {
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messagesJSON, _ := json.Marshal(openAIMessages)
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out, _ = sjson.SetRaw(out, "messages", string(messagesJSON))
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}
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// Tools mapping: Gemini tools -> OpenAI tools
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if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
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var openAITools []interface{}
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tools.ForEach(func(_, tool gjson.Result) bool {
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if functionDeclarations := tool.Get("functionDeclarations"); functionDeclarations.Exists() && functionDeclarations.IsArray() {
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functionDeclarations.ForEach(func(_, funcDecl gjson.Result) bool {
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openAITool := map[string]interface{}{
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"type": "function",
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"function": map[string]interface{}{
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"name": funcDecl.Get("name").String(),
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"description": funcDecl.Get("description").String(),
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},
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}
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// Convert parameters schema
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if parameters := funcDecl.Get("parameters"); parameters.Exists() {
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openAITool["function"].(map[string]interface{})["parameters"] = parameters.Value()
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} else if parameters = funcDecl.Get("parametersJsonSchema"); parameters.Exists() {
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openAITool["function"].(map[string]interface{})["parameters"] = parameters.Value()
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}
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openAITools = append(openAITools, openAITool)
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return true
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})
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}
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return true
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})
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if len(openAITools) > 0 {
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toolsJSON, _ := json.Marshal(openAITools)
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out, _ = sjson.SetRaw(out, "tools", string(toolsJSON))
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}
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}
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// Tool choice mapping (Gemini doesn't have direct equivalent, but we can handle it)
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if toolConfig := root.Get("toolConfig"); toolConfig.Exists() {
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if functionCallingConfig := toolConfig.Get("functionCallingConfig"); functionCallingConfig.Exists() {
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mode := functionCallingConfig.Get("mode").String()
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switch mode {
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case "NONE":
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out, _ = sjson.Set(out, "tool_choice", "none")
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case "AUTO":
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out, _ = sjson.Set(out, "tool_choice", "auto")
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case "ANY":
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out, _ = sjson.Set(out, "tool_choice", "required")
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}
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}
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}
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return out
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}
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353
internal/translator/openai/gemini/openai_gemini_response.go
Normal file
353
internal/translator/openai/gemini/openai_gemini_response.go
Normal file
@@ -0,0 +1,353 @@
|
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// Package gemini provides response translation functionality for OpenAI to Gemini API.
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// This package handles the conversion of OpenAI Chat Completions API responses into Gemini API-compatible
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// JSON format, transforming streaming events and non-streaming responses into the format
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// expected by Gemini API clients. It supports both streaming and non-streaming modes,
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// handling text content, tool calls, and usage metadata appropriately.
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package gemini
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import (
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"encoding/json"
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"strings"
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"github.com/tidwall/gjson"
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"github.com/tidwall/sjson"
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)
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// ConvertOpenAIResponseToGeminiParams holds parameters for response conversion
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type ConvertOpenAIResponseToGeminiParams struct {
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// Tool calls accumulator for streaming
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ToolCallsAccumulator map[int]*ToolCallAccumulator
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// Content accumulator for streaming
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ContentAccumulator strings.Builder
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// Track if this is the first chunk
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IsFirstChunk bool
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}
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// ToolCallAccumulator holds the state for accumulating tool call data
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type ToolCallAccumulator struct {
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ID string
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Name string
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Arguments strings.Builder
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}
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// ConvertOpenAIResponseToGemini converts OpenAI Chat Completions streaming response format to Gemini API format.
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// This function processes OpenAI streaming chunks and transforms them into Gemini-compatible JSON responses.
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// It handles text content, tool calls, and usage metadata, outputting responses that match the Gemini API format.
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func ConvertOpenAIResponseToGemini(rawJSON []byte, param *ConvertOpenAIResponseToGeminiParams) []string {
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// Handle [DONE] marker
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if strings.TrimSpace(string(rawJSON)) == "[DONE]" {
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return []string{}
|
||||
}
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||||
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||||
root := gjson.ParseBytes(rawJSON)
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||||
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||||
// Initialize accumulators if needed
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if param.ToolCallsAccumulator == nil {
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param.ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
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}
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||||
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// Process choices
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if choices := root.Get("choices"); choices.Exists() && choices.IsArray() {
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||||
// Handle empty choices array (usage-only chunk)
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if len(choices.Array()) == 0 {
|
||||
// This is a usage-only chunk, handle usage and return
|
||||
if usage := root.Get("usage"); usage.Exists() {
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||||
template := `{"candidates":[],"usageMetadata":{}}`
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||||
// 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{}
|
||||
}
|
||||
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||||
var results []string
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||||
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||||
choices.ForEach(func(choiceIndex, choice gjson.Result) bool {
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||||
// Base Gemini response template
|
||||
template := `{"candidates":[{"content":{"parts":[],"role":"model"},"finishReason":"STOP","index":0}]}`
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||||
|
||||
// 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")
|
||||
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||||
// Handle role (only in first chunk)
|
||||
if role := delta.Get("role"); role.Exists() && param.IsFirstChunk {
|
||||
// OpenAI assistant -> Gemini model
|
||||
if role.String() == "assistant" {
|
||||
template, _ = sjson.Set(template, "candidates.0.content.role", "model")
|
||||
}
|
||||
param.IsFirstChunk = false
|
||||
results = append(results, template)
|
||||
return true
|
||||
}
|
||||
|
||||
// Handle content delta
|
||||
if content := delta.Get("content"); content.Exists() && content.String() != "" {
|
||||
contentText := content.String()
|
||||
param.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.ToolCallsAccumulator[toolIndex]; !exists {
|
||||
param.ToolCallsAccumulator[toolIndex] = &ToolCallAccumulator{
|
||||
ID: toolID,
|
||||
Name: functionName,
|
||||
}
|
||||
}
|
||||
|
||||
// Update ID if provided
|
||||
if toolID != "" {
|
||||
param.ToolCallsAccumulator[toolIndex].ID = toolID
|
||||
}
|
||||
|
||||
// Update name if provided
|
||||
if functionName != "" {
|
||||
param.ToolCallsAccumulator[toolIndex].Name = functionName
|
||||
}
|
||||
|
||||
// Accumulate arguments
|
||||
if functionArgs != "" {
|
||||
param.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.ToolCallsAccumulator) > 0 {
|
||||
var parts []interface{}
|
||||
for _, accumulator := range param.ToolCallsAccumulator {
|
||||
argsStr := accumulator.Arguments.String()
|
||||
var argsMap map[string]interface{}
|
||||
|
||||
if argsStr != "" && argsStr != "{}" {
|
||||
// Handle malformed JSON by trying to fix common issues
|
||||
fixedArgs := argsStr
|
||||
// Fix unquoted keys and values (common in the sample)
|
||||
if strings.Contains(fixedArgs, "北京") && !strings.Contains(fixedArgs, "\"北京\"") {
|
||||
fixedArgs = strings.ReplaceAll(fixedArgs, "北京", "\"北京\"")
|
||||
}
|
||||
if strings.Contains(fixedArgs, "celsius") && !strings.Contains(fixedArgs, "\"celsius\"") {
|
||||
fixedArgs = strings.ReplaceAll(fixedArgs, "celsius", "\"celsius\"")
|
||||
}
|
||||
|
||||
if err := json.Unmarshal([]byte(fixedArgs), &argsMap); err != nil {
|
||||
// If still fails, try to parse as raw string
|
||||
if err2 := json.Unmarshal([]byte("\""+argsStr+"\""), &argsMap); err2 != nil {
|
||||
// Last resort: use empty object
|
||||
argsMap = map[string]interface{}{}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
argsMap = map[string]interface{}{}
|
||||
}
|
||||
|
||||
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.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"
|
||||
}
|
||||
}
|
||||
|
||||
// ConvertOpenAINonStreamResponseToGemini converts OpenAI non-streaming response to Gemini format
|
||||
func ConvertOpenAINonStreamResponseToGemini(rawJSON []byte) 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{}
|
||||
if functionArgs != "" && functionArgs != "{}" {
|
||||
// Handle malformed JSON by trying to fix common issues
|
||||
fixedArgs := functionArgs
|
||||
// Fix unquoted keys and values (common in the sample)
|
||||
if strings.Contains(fixedArgs, "北京") && !strings.Contains(fixedArgs, "\"北京\"") {
|
||||
fixedArgs = strings.ReplaceAll(fixedArgs, "北京", "\"北京\"")
|
||||
}
|
||||
if strings.Contains(fixedArgs, "celsius") && !strings.Contains(fixedArgs, "\"celsius\"") {
|
||||
fixedArgs = strings.ReplaceAll(fixedArgs, "celsius", "\"celsius\"")
|
||||
}
|
||||
|
||||
if err := json.Unmarshal([]byte(fixedArgs), &argsMap); err != nil {
|
||||
// If still fails, try to parse as raw string
|
||||
if err2 := json.Unmarshal([]byte("\""+functionArgs+"\""), &argsMap); err2 != nil {
|
||||
// Last resort: use empty object
|
||||
argsMap = map[string]interface{}{}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
argsMap = map[string]interface{}{}
|
||||
}
|
||||
|
||||
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
|
||||
}
|
||||
Reference in New Issue
Block a user