mirror of
https://github.com/router-for-me/CLIProxyAPI.git
synced 2026-02-03 04:50:52 +08:00
feat(translator): add token counting functionality for Gemini, Claude, and CLI - Introduced `TokenCount` handling across various Codex translators (Gemini, Claude, CLI) with respective implementations. - Added utility methods for token counting and formatting responses. - Integrated `tiktoken-go/tokenizer` library for tokenization. - Updated CodexExecutor with token counting logic to support multiple models including GPT-5 variants. - Refined go.mod and go.sum to include new dependencies. feat(runtime): add token counting functionality across executors - Implemented token counting in OpenAICompatExecutor, QwenExecutor, and IFlowExecutor. - Added utilities for token counting and response formatting using `tiktoken-go/tokenizer`. - Integrated token counting into translators for Gemini, Claude, and Gemini CLI. - Enhanced multiple model support, including GPT-5 variants, for token counting. docs: update environment variable instructions for multi-model support - Added details for setting `ANTHROPIC_DEFAULT_OPUS_MODEL`, `ANTHROPIC_DEFAULT_SONNET_MODEL`, and `ANTHROPIC_DEFAULT_HAIKU_MODEL` for version 2.x.x. - Clarified usage of `ANTHROPIC_MODEL` and `ANTHROPIC_SMALL_FAST_MODEL` for version 1.x.x. - Expanded examples for setting environment variables across different models including Gemini, GPT-5, Claude, and Qwen3.
235 lines
6.9 KiB
Go
235 lines
6.9 KiB
Go
package executor
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import (
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"fmt"
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"strings"
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"github.com/tidwall/gjson"
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"github.com/tiktoken-go/tokenizer"
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)
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// tokenizerForModel returns a tokenizer codec suitable for an OpenAI-style model id.
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func tokenizerForModel(model string) (tokenizer.Codec, error) {
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sanitized := strings.ToLower(strings.TrimSpace(model))
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switch {
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case sanitized == "":
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return tokenizer.Get(tokenizer.Cl100kBase)
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case strings.HasPrefix(sanitized, "gpt-5"):
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return tokenizer.ForModel(tokenizer.GPT5)
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case strings.HasPrefix(sanitized, "gpt-4.1"):
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return tokenizer.ForModel(tokenizer.GPT41)
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case strings.HasPrefix(sanitized, "gpt-4o"):
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return tokenizer.ForModel(tokenizer.GPT4o)
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case strings.HasPrefix(sanitized, "gpt-4"):
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return tokenizer.ForModel(tokenizer.GPT4)
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case strings.HasPrefix(sanitized, "gpt-3.5"), strings.HasPrefix(sanitized, "gpt-3"):
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return tokenizer.ForModel(tokenizer.GPT35Turbo)
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case strings.HasPrefix(sanitized, "o1"):
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return tokenizer.ForModel(tokenizer.O1)
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case strings.HasPrefix(sanitized, "o3"):
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return tokenizer.ForModel(tokenizer.O3)
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case strings.HasPrefix(sanitized, "o4"):
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return tokenizer.ForModel(tokenizer.O4Mini)
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default:
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return tokenizer.Get(tokenizer.O200kBase)
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}
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}
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// countOpenAIChatTokens approximates prompt tokens for OpenAI chat completions payloads.
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func countOpenAIChatTokens(enc tokenizer.Codec, payload []byte) (int64, error) {
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if enc == nil {
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return 0, fmt.Errorf("encoder is nil")
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}
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if len(payload) == 0 {
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return 0, nil
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}
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root := gjson.ParseBytes(payload)
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segments := make([]string, 0, 32)
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collectOpenAIMessages(root.Get("messages"), &segments)
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collectOpenAITools(root.Get("tools"), &segments)
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collectOpenAIFunctions(root.Get("functions"), &segments)
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collectOpenAIToolChoice(root.Get("tool_choice"), &segments)
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collectOpenAIResponseFormat(root.Get("response_format"), &segments)
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addIfNotEmpty(&segments, root.Get("input").String())
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addIfNotEmpty(&segments, root.Get("prompt").String())
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joined := strings.TrimSpace(strings.Join(segments, "\n"))
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if joined == "" {
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return 0, nil
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}
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count, err := enc.Count(joined)
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if err != nil {
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return 0, err
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}
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return int64(count), nil
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}
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// buildOpenAIUsageJSON returns a minimal usage structure understood by downstream translators.
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func buildOpenAIUsageJSON(count int64) []byte {
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return []byte(fmt.Sprintf(`{"usage":{"prompt_tokens":%d,"completion_tokens":0,"total_tokens":%d}}`, count, count))
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}
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func collectOpenAIMessages(messages gjson.Result, segments *[]string) {
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if !messages.Exists() || !messages.IsArray() {
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return
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}
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messages.ForEach(func(_, message gjson.Result) bool {
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addIfNotEmpty(segments, message.Get("role").String())
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addIfNotEmpty(segments, message.Get("name").String())
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collectOpenAIContent(message.Get("content"), segments)
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collectOpenAIToolCalls(message.Get("tool_calls"), segments)
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collectOpenAIFunctionCall(message.Get("function_call"), segments)
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return true
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})
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}
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func collectOpenAIContent(content gjson.Result, segments *[]string) {
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if !content.Exists() {
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return
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}
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if content.Type == gjson.String {
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addIfNotEmpty(segments, content.String())
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return
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}
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if content.IsArray() {
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content.ForEach(func(_, part gjson.Result) bool {
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partType := part.Get("type").String()
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switch partType {
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case "text", "input_text", "output_text":
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addIfNotEmpty(segments, part.Get("text").String())
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case "image_url":
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addIfNotEmpty(segments, part.Get("image_url.url").String())
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case "input_audio", "output_audio", "audio":
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addIfNotEmpty(segments, part.Get("id").String())
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case "tool_result":
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addIfNotEmpty(segments, part.Get("name").String())
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collectOpenAIContent(part.Get("content"), segments)
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default:
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if part.IsArray() {
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collectOpenAIContent(part, segments)
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return true
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}
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if part.Type == gjson.JSON {
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addIfNotEmpty(segments, part.Raw)
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return true
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}
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addIfNotEmpty(segments, part.String())
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}
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return true
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})
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return
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}
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if content.Type == gjson.JSON {
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addIfNotEmpty(segments, content.Raw)
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}
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}
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func collectOpenAIToolCalls(calls gjson.Result, segments *[]string) {
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if !calls.Exists() || !calls.IsArray() {
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return
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}
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calls.ForEach(func(_, call gjson.Result) bool {
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addIfNotEmpty(segments, call.Get("id").String())
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addIfNotEmpty(segments, call.Get("type").String())
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function := call.Get("function")
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if function.Exists() {
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addIfNotEmpty(segments, function.Get("name").String())
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addIfNotEmpty(segments, function.Get("description").String())
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addIfNotEmpty(segments, function.Get("arguments").String())
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if params := function.Get("parameters"); params.Exists() {
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addIfNotEmpty(segments, params.Raw)
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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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func collectOpenAIFunctionCall(call gjson.Result, segments *[]string) {
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if !call.Exists() {
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return
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}
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addIfNotEmpty(segments, call.Get("name").String())
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addIfNotEmpty(segments, call.Get("arguments").String())
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}
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func collectOpenAITools(tools gjson.Result, segments *[]string) {
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if !tools.Exists() {
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return
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}
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if tools.IsArray() {
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tools.ForEach(func(_, tool gjson.Result) bool {
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appendToolPayload(tool, segments)
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return true
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})
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return
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}
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appendToolPayload(tools, segments)
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}
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func collectOpenAIFunctions(functions gjson.Result, segments *[]string) {
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if !functions.Exists() || !functions.IsArray() {
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return
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}
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functions.ForEach(func(_, function gjson.Result) bool {
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addIfNotEmpty(segments, function.Get("name").String())
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addIfNotEmpty(segments, function.Get("description").String())
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if params := function.Get("parameters"); params.Exists() {
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addIfNotEmpty(segments, params.Raw)
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}
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return true
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})
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}
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func collectOpenAIToolChoice(choice gjson.Result, segments *[]string) {
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if !choice.Exists() {
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return
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}
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if choice.Type == gjson.String {
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addIfNotEmpty(segments, choice.String())
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return
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}
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addIfNotEmpty(segments, choice.Raw)
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}
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func collectOpenAIResponseFormat(format gjson.Result, segments *[]string) {
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if !format.Exists() {
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return
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}
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addIfNotEmpty(segments, format.Get("type").String())
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addIfNotEmpty(segments, format.Get("name").String())
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if schema := format.Get("json_schema"); schema.Exists() {
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addIfNotEmpty(segments, schema.Raw)
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}
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if schema := format.Get("schema"); schema.Exists() {
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addIfNotEmpty(segments, schema.Raw)
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}
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}
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func appendToolPayload(tool gjson.Result, segments *[]string) {
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if !tool.Exists() {
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return
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}
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addIfNotEmpty(segments, tool.Get("type").String())
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addIfNotEmpty(segments, tool.Get("name").String())
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addIfNotEmpty(segments, tool.Get("description").String())
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if function := tool.Get("function"); function.Exists() {
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addIfNotEmpty(segments, function.Get("name").String())
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addIfNotEmpty(segments, function.Get("description").String())
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if params := function.Get("parameters"); params.Exists() {
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addIfNotEmpty(segments, params.Raw)
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}
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}
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}
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func addIfNotEmpty(segments *[]string, value string) {
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if segments == nil {
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return
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}
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if trimmed := strings.TrimSpace(value); trimmed != "" {
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*segments = append(*segments, trimmed)
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}
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}
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