package service
import (
"encoding/json"
"fmt"
"strings"
)
var codexModelMap = map[string]string{
"gpt-5.5": "gpt-5.5",
"gpt-5.4": "gpt-5.4",
"gpt-5.4-mini": "gpt-5.4-mini",
"gpt-5.4-none": "gpt-5.4",
"gpt-5.4-low": "gpt-5.4",
"gpt-5.4-medium": "gpt-5.4",
"gpt-5.4-high": "gpt-5.4",
"gpt-5.4-xhigh": "gpt-5.4",
"gpt-5.4-chat-latest": "gpt-5.4",
"gpt-5.3": "gpt-5.3-codex",
"gpt-5.3-none": "gpt-5.3-codex",
"gpt-5.3-low": "gpt-5.3-codex",
"gpt-5.3-medium": "gpt-5.3-codex",
"gpt-5.3-high": "gpt-5.3-codex",
"gpt-5.3-xhigh": "gpt-5.3-codex",
"gpt-5.3-codex": "gpt-5.3-codex",
"gpt-5.3-codex-spark": "gpt-5.3-codex-spark",
"gpt-5.3-codex-spark-low": "gpt-5.3-codex-spark",
"gpt-5.3-codex-spark-medium": "gpt-5.3-codex-spark",
"gpt-5.3-codex-spark-high": "gpt-5.3-codex-spark",
"gpt-5.3-codex-spark-xhigh": "gpt-5.3-codex-spark",
"gpt-5.3-codex-low": "gpt-5.3-codex",
"gpt-5.3-codex-medium": "gpt-5.3-codex",
"gpt-5.3-codex-high": "gpt-5.3-codex",
"gpt-5.3-codex-xhigh": "gpt-5.3-codex",
"gpt-5.2": "gpt-5.2",
"gpt-5.2-none": "gpt-5.2",
"gpt-5.2-low": "gpt-5.2",
"gpt-5.2-medium": "gpt-5.2",
"gpt-5.2-high": "gpt-5.2",
"gpt-5.2-xhigh": "gpt-5.2",
}
type codexTransformResult struct {
Modified bool
NormalizedModel string
PromptCacheKey string
}
const (
codexImageGenerationBridgeMarker = ""
codexImageGenerationBridgeText = codexImageGenerationBridgeMarker + "\nWhen the user asks for raster image generation or editing, use the OpenAI Responses native `image_generation` tool attached to this request. The local Codex client may not expose an `image_gen` namespace, but that does not mean image generation is unavailable. Do not ask the user to switch to CLI fallback solely because `image_gen` is absent.\n"
codexSparkImageUnsupportedMarker = ""
codexSparkImageUnsupportedText = codexSparkImageUnsupportedMarker + "\nThe current model is gpt-5.3-codex-spark, which does not support image generation, image editing, image input, the `image_generation` tool, or Codex `image_gen`/`$imagegen` workflows. If the user asks for image generation or image editing, clearly explain this model limitation and ask them to switch to a non-Spark Codex model such as gpt-5.3-codex or gpt-5.4. Do not claim that the local environment merely lacks image_gen tooling, and do not suggest CLI fallback as the primary fix while the model remains Spark.\n"
)
func applyCodexOAuthTransform(reqBody map[string]any, isCodexCLI bool, isCompact bool) codexTransformResult {
result := codexTransformResult{}
// 工具续链需求会影响存储策略与 input 过滤逻辑。
needsToolContinuation := NeedsToolContinuation(reqBody)
model := ""
if v, ok := reqBody["model"].(string); ok {
model = v
}
normalizedModel := strings.TrimSpace(model)
if normalizedModel != "" {
if model != normalizedModel {
reqBody["model"] = normalizedModel
result.Modified = true
}
result.NormalizedModel = normalizedModel
}
if isCompact {
if _, ok := reqBody["store"]; ok {
delete(reqBody, "store")
result.Modified = true
}
if _, ok := reqBody["stream"]; ok {
delete(reqBody, "stream")
result.Modified = true
}
} else {
// OAuth 走 ChatGPT internal API 时,store 必须为 false;显式 true 也会强制覆盖。
// 避免上游返回 "Store must be set to false"。
if v, ok := reqBody["store"].(bool); !ok || v {
reqBody["store"] = false
result.Modified = true
}
if v, ok := reqBody["stream"].(bool); !ok || !v {
reqBody["stream"] = true
result.Modified = true
}
}
// Strip parameters unsupported by codex models via the Responses API.
for _, key := range []string{
"max_output_tokens",
"max_completion_tokens",
"temperature",
"top_p",
"frequency_penalty",
"presence_penalty",
// prompt_cache_retention is a newer Responses API parameter (cache TTL).
// The ChatGPT internal Codex endpoint rejects it with
// "Unsupported parameter: prompt_cache_retention". Defense-in-depth
// for any OAuth path that reaches this transform — the Cursor
// Responses-shape short-circuit in ForwardAsChatCompletions strips
// it earlier too, but we keep this line so other OAuth callers are
// equally protected.
"prompt_cache_retention",
} {
if _, ok := reqBody[key]; ok {
delete(reqBody, key)
result.Modified = true
}
}
// 兼容遗留的 functions 和 function_call,转换为 tools 和 tool_choice
if functionsRaw, ok := reqBody["functions"]; ok {
if functions, k := functionsRaw.([]any); k {
tools := make([]any, 0, len(functions))
for _, f := range functions {
tools = append(tools, map[string]any{
"type": "function",
"function": f,
})
}
reqBody["tools"] = tools
}
delete(reqBody, "functions")
result.Modified = true
}
if fcRaw, ok := reqBody["function_call"]; ok {
if fcStr, ok := fcRaw.(string); ok {
// e.g. "auto", "none"
reqBody["tool_choice"] = fcStr
} else if fcObj, ok := fcRaw.(map[string]any); ok {
// e.g. {"name": "my_func"}
if name, ok := fcObj["name"].(string); ok && strings.TrimSpace(name) != "" {
reqBody["tool_choice"] = map[string]any{
"type": "function",
"function": map[string]any{
"name": name,
},
}
}
}
delete(reqBody, "function_call")
result.Modified = true
}
if normalizeCodexTools(reqBody) {
result.Modified = true
}
if normalizeCodexToolChoice(reqBody) {
result.Modified = true
}
if v, ok := reqBody["prompt_cache_key"].(string); ok {
result.PromptCacheKey = strings.TrimSpace(v)
}
// 提取 input 中 role:"system" 消息至 instructions(OAuth 上游不支持 system role)。
if extractSystemMessagesFromInput(reqBody) {
result.Modified = true
}
// instructions 处理逻辑:根据是否是 Codex CLI 分别调用不同方法
if applyInstructions(reqBody, isCodexCLI) {
result.Modified = true
}
if isCodexSparkModel(normalizedModel) && applyCodexSparkImageUnsupportedInstructions(reqBody) {
result.Modified = true
}
// 续链场景保留 item_reference 与 id,避免 call_id 上下文丢失。
if input, ok := reqBody["input"].([]any); ok {
if normalizedInput, modified := normalizeCodexToolRoleMessages(input); modified {
input = normalizedInput
result.Modified = true
}
if normalizedInput, modified := normalizeCodexMessageContentText(input); modified {
input = normalizedInput
result.Modified = true
}
input = filterCodexInput(input, needsToolContinuation)
reqBody["input"] = input
result.Modified = true
} else if inputStr, ok := reqBody["input"].(string); ok {
// ChatGPT codex endpoint requires input to be a list, not a string.
// Convert string input to the expected message array format.
trimmed := strings.TrimSpace(inputStr)
if trimmed != "" {
reqBody["input"] = []any{
map[string]any{
"type": "message",
"role": "user",
"content": inputStr,
},
}
} else {
reqBody["input"] = []any{}
}
result.Modified = true
}
return result
}
func normalizeCodexToolChoice(reqBody map[string]any) bool {
choice, ok := reqBody["tool_choice"]
if !ok || choice == nil {
return false
}
choiceMap, ok := choice.(map[string]any)
if !ok {
return false
}
choiceType := strings.TrimSpace(firstNonEmptyString(choiceMap["type"]))
if choiceType == "" || codexToolsContainType(reqBody["tools"], choiceType) {
return false
}
reqBody["tool_choice"] = "auto"
return true
}
func codexToolsContainType(rawTools any, toolType string) bool {
tools, ok := rawTools.([]any)
if !ok || strings.TrimSpace(toolType) == "" {
return false
}
for _, rawTool := range tools {
tool, ok := rawTool.(map[string]any)
if !ok {
continue
}
if strings.TrimSpace(firstNonEmptyString(tool["type"])) == toolType {
return true
}
}
return false
}
func normalizeCodexToolRoleMessages(input []any) ([]any, bool) {
if len(input) == 0 {
return input, false
}
modified := false
normalized := make([]any, 0, len(input))
for _, item := range input {
m, ok := item.(map[string]any)
if !ok {
normalized = append(normalized, item)
continue
}
role, _ := m["role"].(string)
if strings.TrimSpace(role) != "tool" {
normalized = append(normalized, item)
continue
}
callID := firstNonEmptyString(m["call_id"], m["tool_call_id"], m["id"])
callID = strings.TrimSpace(callID)
if callID == "" {
// Responses does not accept role:"tool". If no call id is available,
// preserve the text as a user message instead of sending invalid input.
fallback := make(map[string]any, len(m))
for key, value := range m {
fallback[key] = value
}
fallback["role"] = "user"
delete(fallback, "tool_call_id")
normalized = append(normalized, fallback)
modified = true
continue
}
output := extractTextFromContent(m["content"])
if output == "" {
if value, ok := m["output"].(string); ok {
output = value
}
}
if output == "" && m["content"] != nil {
if b, err := json.Marshal(m["content"]); err == nil {
output = string(b)
}
}
normalized = append(normalized, map[string]any{
"type": "function_call_output",
"call_id": callID,
"output": output,
})
modified = true
}
if !modified {
return input, false
}
return normalized, true
}
func normalizeCodexMessageContentText(input []any) ([]any, bool) {
if len(input) == 0 {
return input, false
}
modified := false
normalized := make([]any, 0, len(input))
for _, item := range input {
m, ok := item.(map[string]any)
if !ok || strings.TrimSpace(firstNonEmptyString(m["type"])) != "message" {
normalized = append(normalized, item)
continue
}
parts, ok := m["content"].([]any)
if !ok {
normalized = append(normalized, item)
continue
}
var newItem map[string]any
var newParts []any
ensureItemCopy := func() {
if newItem != nil {
return
}
newItem = make(map[string]any, len(m))
for key, value := range m {
newItem[key] = value
}
newParts = make([]any, len(parts))
copy(newParts, parts)
}
for i, rawPart := range parts {
part, ok := rawPart.(map[string]any)
if !ok {
continue
}
text, hasText := part["text"]
if !hasText {
continue
}
if _, ok := text.(string); ok {
continue
}
ensureItemCopy()
newPart := make(map[string]any, len(part))
for key, value := range part {
newPart[key] = value
}
newPart["text"] = stringifyCodexContentText(text)
newParts[i] = newPart
modified = true
}
if newItem != nil {
newItem["content"] = newParts
normalized = append(normalized, newItem)
continue
}
normalized = append(normalized, item)
}
if !modified {
return input, false
}
return normalized, true
}
func stringifyCodexContentText(value any) string {
switch v := value.(type) {
case string:
return v
case nil:
return ""
default:
if b, err := json.Marshal(v); err == nil {
return string(b)
}
return fmt.Sprint(v)
}
}
func normalizeCodexModel(model string) string {
model = strings.TrimSpace(model)
if model == "" {
return "gpt-5.4"
}
if isOpenAIImageGenerationModel(model) {
return model
}
modelID := model
if strings.Contains(modelID, "/") {
parts := strings.Split(modelID, "/")
modelID = parts[len(parts)-1]
}
if mapped := getNormalizedCodexModel(modelID); mapped != "" {
return mapped
}
normalized := strings.ToLower(modelID)
if strings.Contains(normalized, "gpt-5.5") || strings.Contains(normalized, "gpt 5.5") {
return "gpt-5.5"
}
if strings.Contains(normalized, "gpt-5.4-mini") || strings.Contains(normalized, "gpt 5.4 mini") {
return "gpt-5.4-mini"
}
if strings.Contains(normalized, "gpt-5.4") || strings.Contains(normalized, "gpt 5.4") {
return "gpt-5.4"
}
if strings.Contains(normalized, "gpt-5.2") || strings.Contains(normalized, "gpt 5.2") {
return "gpt-5.2"
}
if strings.Contains(normalized, "gpt-5.3-codex-spark") || strings.Contains(normalized, "gpt 5.3 codex spark") {
return "gpt-5.3-codex-spark"
}
if strings.Contains(normalized, "gpt-5.3-codex") || strings.Contains(normalized, "gpt 5.3 codex") {
return "gpt-5.3-codex"
}
if strings.Contains(normalized, "gpt-5.3") || strings.Contains(normalized, "gpt 5.3") {
return "gpt-5.3-codex"
}
if strings.Contains(normalized, "codex") {
return "gpt-5.3-codex"
}
if strings.Contains(normalized, "gpt-5") || strings.Contains(normalized, "gpt 5") {
return "gpt-5.4"
}
return "gpt-5.4"
}
func isCodexSparkModel(model string) bool {
return normalizeCodexModel(model) == "gpt-5.3-codex-spark"
}
func hasOpenAIImageGenerationTool(reqBody map[string]any) bool {
rawTools, ok := reqBody["tools"]
if !ok || rawTools == nil {
return false
}
tools, ok := rawTools.([]any)
if !ok {
return false
}
for _, rawTool := range tools {
toolMap, ok := rawTool.(map[string]any)
if !ok {
continue
}
if strings.TrimSpace(firstNonEmptyString(toolMap["type"])) == "image_generation" {
return true
}
}
return false
}
func hasOpenAIInputImage(reqBody map[string]any) bool {
if reqBody == nil {
return false
}
return hasOpenAIInputImageValue(reqBody["input"]) || hasOpenAIInputImageValue(reqBody["messages"])
}
func hasOpenAIInputImageValue(value any) bool {
switch v := value.(type) {
case []any:
for _, item := range v {
if hasOpenAIInputImageValue(item) {
return true
}
}
case map[string]any:
if strings.TrimSpace(firstNonEmptyString(v["type"])) == "input_image" {
return true
}
if _, ok := v["image_url"]; ok {
return true
}
return hasOpenAIInputImageValue(v["content"])
}
return false
}
func validateCodexSparkInput(reqBody map[string]any, model string) error {
if !isCodexSparkModel(model) || !hasOpenAIInputImage(reqBody) {
return nil
}
return fmt.Errorf("model %q does not support image input", strings.TrimSpace(model))
}
func normalizeOpenAIResponsesImageGenerationTools(reqBody map[string]any) bool {
rawTools, ok := reqBody["tools"]
if !ok || rawTools == nil {
return false
}
tools, ok := rawTools.([]any)
if !ok {
return false
}
modified := false
for _, rawTool := range tools {
toolMap, ok := rawTool.(map[string]any)
if !ok || strings.TrimSpace(firstNonEmptyString(toolMap["type"])) != "image_generation" {
continue
}
if _, ok := toolMap["output_format"]; !ok {
if value := strings.TrimSpace(firstNonEmptyString(toolMap["format"])); value != "" {
toolMap["output_format"] = value
modified = true
}
}
if _, ok := toolMap["output_compression"]; !ok {
if value, exists := toolMap["compression"]; exists && value != nil {
toolMap["output_compression"] = value
modified = true
}
}
if _, ok := toolMap["format"]; ok {
delete(toolMap, "format")
modified = true
}
if _, ok := toolMap["compression"]; ok {
delete(toolMap, "compression")
modified = true
}
}
return modified
}
func ensureOpenAIResponsesImageGenerationTool(reqBody map[string]any) bool {
if len(reqBody) == 0 {
return false
}
if isCodexSparkModel(firstNonEmptyString(reqBody["model"])) {
return false
}
tool := map[string]any{
"type": "image_generation",
"output_format": "png",
}
rawTools, ok := reqBody["tools"]
if !ok || rawTools == nil {
reqBody["tools"] = []any{tool}
return true
}
tools, ok := rawTools.([]any)
if !ok {
reqBody["tools"] = []any{tool}
return true
}
for _, rawTool := range tools {
toolMap, ok := rawTool.(map[string]any)
if !ok {
continue
}
if strings.TrimSpace(firstNonEmptyString(toolMap["type"])) == "image_generation" {
return false
}
}
reqBody["tools"] = append(tools, tool)
return true
}
func applyCodexImageGenerationBridgeInstructions(reqBody map[string]any) bool {
if len(reqBody) == 0 || !hasOpenAIImageGenerationTool(reqBody) {
return false
}
if isCodexSparkModel(firstNonEmptyString(reqBody["model"])) {
return false
}
existing, _ := reqBody["instructions"].(string)
if strings.Contains(existing, codexImageGenerationBridgeMarker) {
return false
}
existing = strings.TrimRight(existing, " \t\r\n")
if strings.TrimSpace(existing) == "" {
reqBody["instructions"] = codexImageGenerationBridgeText
return true
}
reqBody["instructions"] = existing + "\n\n" + codexImageGenerationBridgeText
return true
}
func applyCodexSparkImageUnsupportedInstructions(reqBody map[string]any) bool {
if len(reqBody) == 0 {
return false
}
existing, _ := reqBody["instructions"].(string)
if strings.Contains(existing, codexSparkImageUnsupportedMarker) {
return false
}
existing = strings.TrimRight(existing, " \t\r\n")
if strings.TrimSpace(existing) == "" {
reqBody["instructions"] = codexSparkImageUnsupportedText
return true
}
reqBody["instructions"] = existing + "\n\n" + codexSparkImageUnsupportedText
return true
}
func validateOpenAIResponsesImageModel(reqBody map[string]any, model string) error {
if !hasOpenAIImageGenerationTool(reqBody) {
return nil
}
model = strings.TrimSpace(model)
if !isOpenAIImageGenerationModel(model) {
return nil
}
return fmt.Errorf("/v1/responses image_generation requests require a Responses-capable text model; image-only model %q is not allowed", model)
}
func normalizeOpenAIResponsesImageOnlyModel(reqBody map[string]any) bool {
if len(reqBody) == 0 {
return false
}
imageModel := strings.TrimSpace(firstNonEmptyString(reqBody["model"]))
if !isOpenAIImageGenerationModel(imageModel) {
return false
}
modified := false
tools, _ := reqBody["tools"].([]any)
imageToolIndex := -1
for i, rawTool := range tools {
toolMap, ok := rawTool.(map[string]any)
if !ok {
continue
}
if strings.TrimSpace(firstNonEmptyString(toolMap["type"])) == "image_generation" {
imageToolIndex = i
break
}
}
if imageToolIndex < 0 {
tools = append(tools, map[string]any{
"type": "image_generation",
"model": imageModel,
})
imageToolIndex = len(tools) - 1
reqBody["tools"] = tools
modified = true
}
if toolMap, ok := tools[imageToolIndex].(map[string]any); ok {
if strings.TrimSpace(firstNonEmptyString(toolMap["model"])) == "" {
toolMap["model"] = imageModel
modified = true
}
for _, key := range []string{
"size",
"quality",
"background",
"output_format",
"output_compression",
"moderation",
"style",
"partial_images",
} {
if value, exists := reqBody[key]; exists && value != nil {
if _, toolHas := toolMap[key]; !toolHas {
toolMap[key] = value
}
delete(reqBody, key)
modified = true
}
}
}
if prompt := strings.TrimSpace(firstNonEmptyString(reqBody["prompt"])); prompt != "" {
if _, hasInput := reqBody["input"]; !hasInput {
reqBody["input"] = prompt
}
delete(reqBody, "prompt")
modified = true
}
if _, ok := reqBody["tool_choice"]; !ok {
reqBody["tool_choice"] = map[string]any{"type": "image_generation"}
modified = true
}
if imageModel != openAIImagesResponsesMainModel {
modified = true
}
reqBody["model"] = openAIImagesResponsesMainModel
return modified
}
func normalizeOpenAIModelForUpstream(account *Account, model string) string {
if account == nil || account.Type == AccountTypeOAuth {
return normalizeCodexModel(model)
}
return strings.TrimSpace(model)
}
func SupportsVerbosity(model string) bool {
if !strings.HasPrefix(model, "gpt-") {
return true
}
var major, minor int
n, _ := fmt.Sscanf(model, "gpt-%d.%d", &major, &minor)
if major > 5 {
return true
}
if major < 5 {
return false
}
// gpt-5
if n == 1 {
return true
}
return minor >= 3
}
func getNormalizedCodexModel(modelID string) string {
if modelID == "" {
return ""
}
if mapped, ok := codexModelMap[modelID]; ok {
return mapped
}
lower := strings.ToLower(modelID)
for key, value := range codexModelMap {
if strings.ToLower(key) == lower {
return value
}
}
return ""
}
// extractTextFromContent extracts plain text from a content value that is either
// a Go string or a []any of content-part maps with type:"text".
func extractTextFromContent(content any) string {
switch v := content.(type) {
case string:
return v
case []any:
var parts []string
for _, part := range v {
m, ok := part.(map[string]any)
if !ok {
continue
}
if t, _ := m["type"].(string); t == "text" {
if text, ok := m["text"].(string); ok {
parts = append(parts, text)
}
}
}
return strings.Join(parts, "")
default:
return ""
}
}
// extractSystemMessagesFromInput scans the input array for items with role=="system",
// removes them, and merges their content into reqBody["instructions"].
// If instructions is already non-empty, extracted content is prepended with "\n\n".
// Returns true if any system messages were extracted.
func extractSystemMessagesFromInput(reqBody map[string]any) bool {
input, ok := reqBody["input"].([]any)
if !ok || len(input) == 0 {
return false
}
var systemTexts []string
remaining := make([]any, 0, len(input))
for _, item := range input {
m, ok := item.(map[string]any)
if !ok {
remaining = append(remaining, item)
continue
}
if role, _ := m["role"].(string); role != "system" {
remaining = append(remaining, item)
continue
}
if text := extractTextFromContent(m["content"]); text != "" {
systemTexts = append(systemTexts, text)
}
}
if len(systemTexts) == 0 {
return false
}
extracted := strings.Join(systemTexts, "\n\n")
if existing, ok := reqBody["instructions"].(string); ok && strings.TrimSpace(existing) != "" {
reqBody["instructions"] = extracted + "\n\n" + existing
} else {
reqBody["instructions"] = extracted
}
reqBody["input"] = remaining
return true
}
// applyInstructions 处理 instructions 字段:仅在 instructions 为空时填充默认值。
func applyInstructions(reqBody map[string]any, isCodexCLI bool) bool {
if !isInstructionsEmpty(reqBody) {
return false
}
reqBody["instructions"] = "You are a helpful coding assistant."
return true
}
// isInstructionsEmpty 检查 instructions 字段是否为空
// 处理以下情况:字段不存在、nil、空字符串、纯空白字符串
func isInstructionsEmpty(reqBody map[string]any) bool {
val, exists := reqBody["instructions"]
if !exists {
return true
}
if val == nil {
return true
}
str, ok := val.(string)
if !ok {
return true
}
return strings.TrimSpace(str) == ""
}
// filterCodexInput 按需过滤 item_reference 与 id。
// preserveReferences 为 true 时保持引用与 id,以满足续链请求对上下文的依赖。
func filterCodexInput(input []any, preserveReferences bool) []any {
filtered := make([]any, 0, len(input))
for _, item := range input {
m, ok := item.(map[string]any)
if !ok {
filtered = append(filtered, item)
continue
}
typ, _ := m["type"].(string)
// 仅修正真正的 tool/function call 标识,避免误改普通 message/reasoning id;
// 若 item_reference 指向 legacy call_* 标识,则仅修正该引用本身。
fixCallIDPrefix := func(id string) string {
if id == "" || strings.HasPrefix(id, "fc") {
return id
}
if strings.HasPrefix(id, "call_") {
return "fc" + strings.TrimPrefix(id, "call_")
}
return "fc_" + id
}
if typ == "item_reference" {
if !preserveReferences {
continue
}
newItem := make(map[string]any, len(m))
for key, value := range m {
newItem[key] = value
}
if id, ok := newItem["id"].(string); ok && strings.HasPrefix(id, "call_") {
newItem["id"] = fixCallIDPrefix(id)
}
filtered = append(filtered, newItem)
continue
}
newItem := m
copied := false
// 仅在需要修改字段时创建副本,避免直接改写原始输入。
ensureCopy := func() {
if copied {
return
}
newItem = make(map[string]any, len(m))
for key, value := range m {
newItem[key] = value
}
copied = true
}
if isCodexToolCallItemType(typ) {
callID, ok := m["call_id"].(string)
if !ok || strings.TrimSpace(callID) == "" {
if id, ok := m["id"].(string); ok && strings.TrimSpace(id) != "" {
callID = id
ensureCopy()
newItem["call_id"] = callID
}
}
if callID != "" {
fixedCallID := fixCallIDPrefix(callID)
if fixedCallID != callID {
ensureCopy()
newItem["call_id"] = fixedCallID
}
}
}
if !isCodexToolCallItemType(typ) {
ensureCopy()
delete(newItem, "call_id")
}
if codexInputItemRequiresName(typ) {
if strings.TrimSpace(firstNonEmptyString(m["name"])) == "" {
name := firstNonEmptyString(m["tool_name"])
if name == "" {
if function, ok := m["function"].(map[string]any); ok {
name = firstNonEmptyString(function["name"])
}
}
if name == "" {
name = "tool"
}
ensureCopy()
newItem["name"] = name
}
}
if !preserveReferences {
ensureCopy()
delete(newItem, "id")
}
filtered = append(filtered, newItem)
}
return filtered
}
func isCodexToolCallItemType(typ string) bool {
switch typ {
case "function_call",
"tool_call",
"local_shell_call",
"tool_search_call",
"custom_tool_call",
"mcp_tool_call",
"function_call_output",
"mcp_tool_call_output",
"custom_tool_call_output",
"tool_search_output":
return true
default:
return false
}
}
func codexInputItemRequiresName(typ string) bool {
switch strings.TrimSpace(typ) {
case "function_call", "custom_tool_call", "mcp_tool_call":
return true
default:
return false
}
}
func normalizeCodexTools(reqBody map[string]any) bool {
rawTools, ok := reqBody["tools"]
if !ok || rawTools == nil {
return false
}
tools, ok := rawTools.([]any)
if !ok {
return false
}
modified := false
validTools := make([]any, 0, len(tools))
for _, tool := range tools {
toolMap, ok := tool.(map[string]any)
if !ok {
// Keep unknown structure as-is to avoid breaking upstream behavior.
validTools = append(validTools, tool)
continue
}
toolType, _ := toolMap["type"].(string)
toolType = strings.TrimSpace(toolType)
if toolType != "function" {
validTools = append(validTools, toolMap)
continue
}
// OpenAI Responses-style tools use top-level name/parameters.
if name, ok := toolMap["name"].(string); ok && strings.TrimSpace(name) != "" {
validTools = append(validTools, toolMap)
continue
}
// ChatCompletions-style tools use {type:"function", function:{...}}.
functionValue, hasFunction := toolMap["function"]
function, ok := functionValue.(map[string]any)
if !hasFunction || functionValue == nil || !ok || function == nil {
// Drop invalid function tools.
modified = true
continue
}
if _, ok := toolMap["name"]; !ok {
if name, ok := function["name"].(string); ok && strings.TrimSpace(name) != "" {
toolMap["name"] = name
modified = true
}
}
if _, ok := toolMap["description"]; !ok {
if desc, ok := function["description"].(string); ok && strings.TrimSpace(desc) != "" {
toolMap["description"] = desc
modified = true
}
}
if _, ok := toolMap["parameters"]; !ok {
if params, ok := function["parameters"]; ok {
toolMap["parameters"] = params
modified = true
}
}
if _, ok := toolMap["strict"]; !ok {
if strict, ok := function["strict"]; ok {
toolMap["strict"] = strict
modified = true
}
}
validTools = append(validTools, toolMap)
}
if modified {
reqBody["tools"] = validTools
}
return modified
}