Files
CLIProxyAPIPlus/internal/translator/kiro/claude/kiro_claude_request.go

860 lines
29 KiB
Go

// Package claude provides request translation functionality for Claude API to Kiro format.
// It handles parsing and transforming Claude API requests into the Kiro/Amazon Q API format,
// extracting model information, system instructions, message contents, and tool declarations.
package claude
import (
"encoding/json"
"fmt"
"net/http"
"strings"
"time"
"unicode/utf8"
"github.com/google/uuid"
kirocommon "github.com/router-for-me/CLIProxyAPI/v6/internal/translator/kiro/common"
log "github.com/sirupsen/logrus"
"github.com/tidwall/gjson"
)
// Kiro API request structs - field order determines JSON key order
// KiroPayload is the top-level request structure for Kiro API
type KiroPayload struct {
ConversationState KiroConversationState `json:"conversationState"`
ProfileArn string `json:"profileArn,omitempty"`
InferenceConfig *KiroInferenceConfig `json:"inferenceConfig,omitempty"`
}
// KiroInferenceConfig contains inference parameters for the Kiro API.
type KiroInferenceConfig struct {
MaxTokens int `json:"maxTokens,omitempty"`
Temperature float64 `json:"temperature,omitempty"`
TopP float64 `json:"topP,omitempty"`
}
// KiroConversationState holds the conversation context
type KiroConversationState struct {
ChatTriggerType string `json:"chatTriggerType"` // Required: "MANUAL" - must be first field
ConversationID string `json:"conversationId"`
CurrentMessage KiroCurrentMessage `json:"currentMessage"`
History []KiroHistoryMessage `json:"history,omitempty"`
}
// KiroCurrentMessage wraps the current user message
type KiroCurrentMessage struct {
UserInputMessage KiroUserInputMessage `json:"userInputMessage"`
}
// KiroHistoryMessage represents a message in the conversation history
type KiroHistoryMessage struct {
UserInputMessage *KiroUserInputMessage `json:"userInputMessage,omitempty"`
AssistantResponseMessage *KiroAssistantResponseMessage `json:"assistantResponseMessage,omitempty"`
}
// KiroImage represents an image in Kiro API format
type KiroImage struct {
Format string `json:"format"`
Source KiroImageSource `json:"source"`
}
// KiroImageSource contains the image data
type KiroImageSource struct {
Bytes string `json:"bytes"` // base64 encoded image data
}
// KiroUserInputMessage represents a user message
type KiroUserInputMessage struct {
Content string `json:"content"`
ModelID string `json:"modelId"`
Origin string `json:"origin"`
Images []KiroImage `json:"images,omitempty"`
UserInputMessageContext *KiroUserInputMessageContext `json:"userInputMessageContext,omitempty"`
}
// KiroUserInputMessageContext contains tool-related context
type KiroUserInputMessageContext struct {
ToolResults []KiroToolResult `json:"toolResults,omitempty"`
Tools []KiroToolWrapper `json:"tools,omitempty"`
}
// KiroToolResult represents a tool execution result
type KiroToolResult struct {
Content []KiroTextContent `json:"content"`
Status string `json:"status"`
ToolUseID string `json:"toolUseId"`
}
// KiroTextContent represents text content
type KiroTextContent struct {
Text string `json:"text"`
}
// KiroToolWrapper wraps a tool specification
type KiroToolWrapper struct {
ToolSpecification KiroToolSpecification `json:"toolSpecification"`
}
// KiroToolSpecification defines a tool's schema
type KiroToolSpecification struct {
Name string `json:"name"`
Description string `json:"description"`
InputSchema KiroInputSchema `json:"inputSchema"`
}
// KiroInputSchema wraps the JSON schema for tool input
type KiroInputSchema struct {
JSON interface{} `json:"json"`
}
// KiroAssistantResponseMessage represents an assistant message
type KiroAssistantResponseMessage struct {
Content string `json:"content"`
ToolUses []KiroToolUse `json:"toolUses,omitempty"`
}
// KiroToolUse represents a tool invocation by the assistant
type KiroToolUse struct {
ToolUseID string `json:"toolUseId"`
Name string `json:"name"`
Input map[string]interface{} `json:"input"`
IsTruncated bool `json:"-"` // Internal flag, not serialized
TruncationInfo *TruncationInfo `json:"-"` // Truncation details, not serialized
}
// ConvertClaudeRequestToKiro converts a Claude API request to Kiro format.
// This is the main entry point for request translation.
func ConvertClaudeRequestToKiro(modelName string, inputRawJSON []byte, stream bool) []byte {
// For Kiro, we pass through the Claude format since buildKiroPayload
// expects Claude format and does the conversion internally.
// The actual conversion happens in the executor when building the HTTP request.
return inputRawJSON
}
// BuildKiroPayload constructs the Kiro API request payload from Claude format.
// Supports tool calling - tools are passed via userInputMessageContext.
// origin parameter determines which quota to use: "CLI" for Amazon Q, "AI_EDITOR" for Kiro IDE.
// isAgentic parameter enables chunked write optimization prompt for -agentic model variants.
// isChatOnly parameter disables tool calling for -chat model variants (pure conversation mode).
// headers parameter allows checking Anthropic-Beta header for thinking mode detection.
// metadata parameter is kept for API compatibility but no longer used for thinking configuration.
// Supports thinking mode - when enabled, injects thinking tags into system prompt.
// Returns the payload and a boolean indicating whether thinking mode was injected.
func BuildKiroPayload(claudeBody []byte, modelID, profileArn, origin string, isAgentic, isChatOnly bool, headers http.Header, metadata map[string]any) ([]byte, bool) {
// Extract max_tokens for potential use in inferenceConfig
// Handle -1 as "use maximum" (Kiro max output is ~32000 tokens)
const kiroMaxOutputTokens = 32000
var maxTokens int64
if mt := gjson.GetBytes(claudeBody, "max_tokens"); mt.Exists() {
maxTokens = mt.Int()
if maxTokens == -1 {
maxTokens = kiroMaxOutputTokens
log.Debugf("kiro: max_tokens=-1 converted to %d", kiroMaxOutputTokens)
}
}
// Extract temperature if specified
var temperature float64
var hasTemperature bool
if temp := gjson.GetBytes(claudeBody, "temperature"); temp.Exists() {
temperature = temp.Float()
hasTemperature = true
}
// Extract top_p if specified
var topP float64
var hasTopP bool
if tp := gjson.GetBytes(claudeBody, "top_p"); tp.Exists() {
topP = tp.Float()
hasTopP = true
log.Debugf("kiro: extracted top_p: %.2f", topP)
}
// Normalize origin value for Kiro API compatibility
origin = normalizeOrigin(origin)
log.Debugf("kiro: normalized origin value: %s", origin)
messages := gjson.GetBytes(claudeBody, "messages")
// For chat-only mode, don't include tools
var tools gjson.Result
if !isChatOnly {
tools = gjson.GetBytes(claudeBody, "tools")
}
// Extract system prompt
systemPrompt := extractSystemPrompt(claudeBody)
// Check for thinking mode using the comprehensive IsThinkingEnabledWithHeaders function
// This supports Claude API format, OpenAI reasoning_effort, AMP/Cursor format, and Anthropic-Beta header
thinkingEnabled := IsThinkingEnabledWithHeaders(claudeBody, headers)
// Inject timestamp context
timestamp := time.Now().Format("2006-01-02 15:04:05 MST")
timestampContext := fmt.Sprintf("[Context: Current time is %s]", timestamp)
if systemPrompt != "" {
systemPrompt = timestampContext + "\n\n" + systemPrompt
} else {
systemPrompt = timestampContext
}
log.Debugf("kiro: injected timestamp context: %s", timestamp)
// Inject agentic optimization prompt for -agentic model variants
if isAgentic {
if systemPrompt != "" {
systemPrompt += "\n"
}
systemPrompt += kirocommon.KiroAgenticSystemPrompt
}
// Handle tool_choice parameter - Kiro doesn't support it natively, so we inject system prompt hints
// Claude tool_choice values: {"type": "auto/any/tool", "name": "..."}
toolChoiceHint := extractClaudeToolChoiceHint(claudeBody)
if toolChoiceHint != "" {
if systemPrompt != "" {
systemPrompt += "\n"
}
systemPrompt += toolChoiceHint
log.Debugf("kiro: injected tool_choice hint into system prompt")
}
// Convert Claude tools to Kiro format
kiroTools := convertClaudeToolsToKiro(tools)
// Thinking mode implementation:
// Kiro API supports official thinking/reasoning mode via <thinking_mode> tag.
// When set to "enabled", Kiro returns reasoning content as official reasoningContentEvent
// rather than inline <thinking> tags in assistantResponseEvent.
// We cap max_thinking_length to reserve space for tool outputs and prevent truncation.
if thinkingEnabled {
thinkingHint := `<thinking_mode>enabled</thinking_mode>
<max_thinking_length>16000</max_thinking_length>`
if systemPrompt != "" {
systemPrompt = thinkingHint + "\n\n" + systemPrompt
} else {
systemPrompt = thinkingHint
}
log.Infof("kiro: injected thinking prompt (official mode), has_tools: %v", len(kiroTools) > 0)
}
// Process messages and build history
history, currentUserMsg, currentToolResults := processMessages(messages, modelID, origin)
// Build content with system prompt (only on first turn to avoid re-injection)
if currentUserMsg != nil {
effectiveSystemPrompt := systemPrompt
if len(history) > 0 {
effectiveSystemPrompt = "" // Don't re-inject on subsequent turns
}
currentUserMsg.Content = buildFinalContent(currentUserMsg.Content, effectiveSystemPrompt, currentToolResults)
// Deduplicate currentToolResults
currentToolResults = deduplicateToolResults(currentToolResults)
// Build userInputMessageContext with tools and tool results
if len(kiroTools) > 0 || len(currentToolResults) > 0 {
currentUserMsg.UserInputMessageContext = &KiroUserInputMessageContext{
Tools: kiroTools,
ToolResults: currentToolResults,
}
}
}
// Build payload
var currentMessage KiroCurrentMessage
if currentUserMsg != nil {
currentMessage = KiroCurrentMessage{UserInputMessage: *currentUserMsg}
} else {
fallbackContent := ""
if systemPrompt != "" {
fallbackContent = "--- SYSTEM PROMPT ---\n" + systemPrompt + "\n--- END SYSTEM PROMPT ---\n"
}
currentMessage = KiroCurrentMessage{UserInputMessage: KiroUserInputMessage{
Content: fallbackContent,
ModelID: modelID,
Origin: origin,
}}
}
// Build inferenceConfig if we have any inference parameters
// Note: Kiro API doesn't actually use max_tokens for thinking budget
var inferenceConfig *KiroInferenceConfig
if maxTokens > 0 || hasTemperature || hasTopP {
inferenceConfig = &KiroInferenceConfig{}
if maxTokens > 0 {
inferenceConfig.MaxTokens = int(maxTokens)
}
if hasTemperature {
inferenceConfig.Temperature = temperature
}
if hasTopP {
inferenceConfig.TopP = topP
}
}
payload := KiroPayload{
ConversationState: KiroConversationState{
ChatTriggerType: "MANUAL",
ConversationID: uuid.New().String(),
CurrentMessage: currentMessage,
History: history,
},
ProfileArn: profileArn,
InferenceConfig: inferenceConfig,
}
result, err := json.Marshal(payload)
if err != nil {
log.Debugf("kiro: failed to marshal payload: %v", err)
return nil, false
}
return result, thinkingEnabled
}
// normalizeOrigin normalizes origin value for Kiro API compatibility
func normalizeOrigin(origin string) string {
switch origin {
case "KIRO_CLI":
return "CLI"
case "KIRO_AI_EDITOR":
return "AI_EDITOR"
case "AMAZON_Q":
return "CLI"
case "KIRO_IDE":
return "AI_EDITOR"
default:
return origin
}
}
// extractSystemPrompt extracts system prompt from Claude request
func extractSystemPrompt(claudeBody []byte) string {
systemField := gjson.GetBytes(claudeBody, "system")
if systemField.IsArray() {
var sb strings.Builder
for _, block := range systemField.Array() {
if block.Get("type").String() == "text" {
sb.WriteString(block.Get("text").String())
} else if block.Type == gjson.String {
sb.WriteString(block.String())
}
}
return sb.String()
}
return systemField.String()
}
// checkThinkingMode checks if thinking mode is enabled in the Claude request
func checkThinkingMode(claudeBody []byte) (bool, int64) {
thinkingEnabled := false
var budgetTokens int64 = 24000
thinkingField := gjson.GetBytes(claudeBody, "thinking")
if thinkingField.Exists() {
thinkingType := thinkingField.Get("type").String()
if thinkingType == "enabled" {
thinkingEnabled = true
if bt := thinkingField.Get("budget_tokens"); bt.Exists() {
budgetTokens = bt.Int()
if budgetTokens <= 0 {
thinkingEnabled = false
log.Debugf("kiro: thinking mode disabled via budget_tokens <= 0")
}
}
if thinkingEnabled {
log.Debugf("kiro: thinking mode enabled via Claude API parameter, budget_tokens: %d", budgetTokens)
}
}
}
return thinkingEnabled, budgetTokens
}
// hasThinkingTagInBody checks if the request body already contains thinking configuration tags.
// This is used to prevent duplicate injection when client (e.g., AMP/Cursor) already includes thinking config.
func hasThinkingTagInBody(body []byte) bool {
bodyStr := string(body)
return strings.Contains(bodyStr, "<thinking_mode>") || strings.Contains(bodyStr, "<max_thinking_length>")
}
// IsThinkingEnabledFromHeader checks if thinking mode is enabled via Anthropic-Beta header.
// Claude CLI uses "Anthropic-Beta: interleaved-thinking-2025-05-14" to enable thinking.
func IsThinkingEnabledFromHeader(headers http.Header) bool {
if headers == nil {
return false
}
betaHeader := headers.Get("Anthropic-Beta")
if betaHeader == "" {
return false
}
// Check for interleaved-thinking beta feature
if strings.Contains(betaHeader, "interleaved-thinking") {
log.Debugf("kiro: thinking mode enabled via Anthropic-Beta header: %s", betaHeader)
return true
}
return false
}
// IsThinkingEnabled is a public wrapper to check if thinking mode is enabled.
// This is used by the executor to determine whether to parse <thinking> tags in responses.
// When thinking is NOT enabled in the request, <thinking> tags in responses should be
// treated as regular text content, not as thinking blocks.
//
// Supports multiple formats:
// - Claude API format: thinking.type = "enabled"
// - OpenAI format: reasoning_effort parameter
// - AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
func IsThinkingEnabled(body []byte) bool {
return IsThinkingEnabledWithHeaders(body, nil)
}
// IsThinkingEnabledWithHeaders checks if thinking mode is enabled from body or headers.
// This is the comprehensive check that supports all thinking detection methods:
// - Claude API format: thinking.type = "enabled"
// - OpenAI format: reasoning_effort parameter
// - AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
// - Anthropic-Beta header: interleaved-thinking-2025-05-14
func IsThinkingEnabledWithHeaders(body []byte, headers http.Header) bool {
// Check Anthropic-Beta header first (Claude Code uses this)
if IsThinkingEnabledFromHeader(headers) {
return true
}
// Check Claude API format first (thinking.type = "enabled")
enabled, _ := checkThinkingMode(body)
if enabled {
log.Debugf("kiro: IsThinkingEnabled returning true (Claude API format)")
return true
}
// Check OpenAI format: reasoning_effort parameter
// Valid values: "low", "medium", "high", "auto" (not "none")
reasoningEffort := gjson.GetBytes(body, "reasoning_effort")
if reasoningEffort.Exists() {
effort := reasoningEffort.String()
if effort != "" && effort != "none" {
log.Debugf("kiro: thinking mode enabled via OpenAI reasoning_effort: %s", effort)
return true
}
}
// Check AMP/Cursor format: <thinking_mode>interleaved</thinking_mode> in system prompt
// This is how AMP client passes thinking configuration
bodyStr := string(body)
if strings.Contains(bodyStr, "<thinking_mode>") && strings.Contains(bodyStr, "</thinking_mode>") {
// Extract thinking mode value
startTag := "<thinking_mode>"
endTag := "</thinking_mode>"
startIdx := strings.Index(bodyStr, startTag)
if startIdx >= 0 {
startIdx += len(startTag)
endIdx := strings.Index(bodyStr[startIdx:], endTag)
if endIdx >= 0 {
thinkingMode := bodyStr[startIdx : startIdx+endIdx]
if thinkingMode == "interleaved" || thinkingMode == "enabled" {
log.Debugf("kiro: thinking mode enabled via AMP/Cursor format: %s", thinkingMode)
return true
}
}
}
}
// Check OpenAI format: max_completion_tokens with reasoning (o1-style)
// Some clients use this to indicate reasoning mode
if gjson.GetBytes(body, "max_completion_tokens").Exists() {
// If max_completion_tokens is set, check if model name suggests reasoning
model := gjson.GetBytes(body, "model").String()
if strings.Contains(strings.ToLower(model), "thinking") ||
strings.Contains(strings.ToLower(model), "reason") {
log.Debugf("kiro: thinking mode enabled via model name hint: %s", model)
return true
}
}
log.Debugf("kiro: IsThinkingEnabled returning false (no thinking mode detected)")
return false
}
// shortenToolNameIfNeeded shortens tool names that exceed 64 characters.
// MCP tools often have long names like "mcp__server-name__tool-name".
// This preserves the "mcp__" prefix and last segment when possible.
func shortenToolNameIfNeeded(name string) string {
const limit = 64
if len(name) <= limit {
return name
}
// For MCP tools, try to preserve prefix and last segment
if strings.HasPrefix(name, "mcp__") {
idx := strings.LastIndex(name, "__")
if idx > 0 {
cand := "mcp__" + name[idx+2:]
if len(cand) > limit {
return cand[:limit]
}
return cand
}
}
return name[:limit]
}
func ensureKiroInputSchema(parameters interface{}) interface{} {
if parameters != nil {
return parameters
}
return map[string]interface{}{
"type": "object",
"properties": map[string]interface{}{},
}
}
// convertClaudeToolsToKiro converts Claude tools to Kiro format
func convertClaudeToolsToKiro(tools gjson.Result) []KiroToolWrapper {
var kiroTools []KiroToolWrapper
if !tools.IsArray() {
return kiroTools
}
for _, tool := range tools.Array() {
name := tool.Get("name").String()
description := tool.Get("description").String()
inputSchemaResult := tool.Get("input_schema")
var inputSchema interface{}
if inputSchemaResult.Exists() && inputSchemaResult.Type != gjson.Null {
inputSchema = inputSchemaResult.Value()
}
inputSchema = ensureKiroInputSchema(inputSchema)
// Shorten tool name if it exceeds 64 characters (common with MCP tools)
originalName := name
name = shortenToolNameIfNeeded(name)
if name != originalName {
log.Debugf("kiro: shortened tool name from '%s' to '%s'", originalName, name)
}
// CRITICAL FIX: Kiro API requires non-empty description
if strings.TrimSpace(description) == "" {
description = fmt.Sprintf("Tool: %s", name)
log.Debugf("kiro: tool '%s' has empty description, using default: %s", name, description)
}
// Truncate long descriptions (individual tool limit)
if len(description) > kirocommon.KiroMaxToolDescLen {
truncLen := kirocommon.KiroMaxToolDescLen - 30
for truncLen > 0 && !utf8.RuneStart(description[truncLen]) {
truncLen--
}
description = description[:truncLen] + "... (description truncated)"
}
kiroTools = append(kiroTools, KiroToolWrapper{
ToolSpecification: KiroToolSpecification{
Name: name,
Description: description,
InputSchema: KiroInputSchema{JSON: inputSchema},
},
})
}
// Apply dynamic compression if total tools size exceeds threshold
// This prevents 500 errors when Claude Code sends too many tools
kiroTools = compressToolsIfNeeded(kiroTools)
return kiroTools
}
// processMessages processes Claude messages and builds Kiro history
func processMessages(messages gjson.Result, modelID, origin string) ([]KiroHistoryMessage, *KiroUserInputMessage, []KiroToolResult) {
var history []KiroHistoryMessage
var currentUserMsg *KiroUserInputMessage
var currentToolResults []KiroToolResult
// Merge adjacent messages with the same role
messagesArray := kirocommon.MergeAdjacentMessages(messages.Array())
for i, msg := range messagesArray {
role := msg.Get("role").String()
isLastMessage := i == len(messagesArray)-1
if role == "user" {
userMsg, toolResults := BuildUserMessageStruct(msg, modelID, origin)
if isLastMessage {
currentUserMsg = &userMsg
currentToolResults = toolResults
} else {
// CRITICAL: Kiro API requires content to be non-empty for history messages too
if strings.TrimSpace(userMsg.Content) == "" {
if len(toolResults) > 0 {
userMsg.Content = "Tool results provided."
} else {
userMsg.Content = "Continue"
}
}
// For history messages, embed tool results in context
if len(toolResults) > 0 {
userMsg.UserInputMessageContext = &KiroUserInputMessageContext{
ToolResults: toolResults,
}
}
history = append(history, KiroHistoryMessage{
UserInputMessage: &userMsg,
})
}
} else if role == "assistant" {
assistantMsg := BuildAssistantMessageStruct(msg)
if isLastMessage {
history = append(history, KiroHistoryMessage{
AssistantResponseMessage: &assistantMsg,
})
// Create a "Continue" user message as currentMessage
currentUserMsg = &KiroUserInputMessage{
Content: "Continue",
ModelID: modelID,
Origin: origin,
}
} else {
history = append(history, KiroHistoryMessage{
AssistantResponseMessage: &assistantMsg,
})
}
}
}
return history, currentUserMsg, currentToolResults
}
// buildFinalContent builds the final content with system prompt
func buildFinalContent(content, systemPrompt string, toolResults []KiroToolResult) string {
var contentBuilder strings.Builder
if systemPrompt != "" {
contentBuilder.WriteString("--- SYSTEM PROMPT ---\n")
contentBuilder.WriteString(systemPrompt)
contentBuilder.WriteString("\n--- END SYSTEM PROMPT ---\n\n")
}
contentBuilder.WriteString(content)
finalContent := contentBuilder.String()
// CRITICAL: Kiro API requires content to be non-empty
if strings.TrimSpace(finalContent) == "" {
if len(toolResults) > 0 {
finalContent = "Tool results provided."
} else {
finalContent = "Continue"
}
log.Debugf("kiro: content was empty, using default: %s", finalContent)
}
return finalContent
}
// deduplicateToolResults removes duplicate tool results
func deduplicateToolResults(toolResults []KiroToolResult) []KiroToolResult {
if len(toolResults) == 0 {
return toolResults
}
seenIDs := make(map[string]bool)
unique := make([]KiroToolResult, 0, len(toolResults))
for _, tr := range toolResults {
if !seenIDs[tr.ToolUseID] {
seenIDs[tr.ToolUseID] = true
unique = append(unique, tr)
} else {
log.Debugf("kiro: skipping duplicate toolResult in currentMessage: %s", tr.ToolUseID)
}
}
return unique
}
// extractClaudeToolChoiceHint extracts tool_choice from Claude request and returns a system prompt hint.
// Claude tool_choice values:
// - {"type": "auto"}: Model decides (default, no hint needed)
// - {"type": "any"}: Must use at least one tool
// - {"type": "tool", "name": "..."}: Must use specific tool
func extractClaudeToolChoiceHint(claudeBody []byte) string {
toolChoice := gjson.GetBytes(claudeBody, "tool_choice")
if !toolChoice.Exists() {
return ""
}
toolChoiceType := toolChoice.Get("type").String()
switch toolChoiceType {
case "any":
return "[INSTRUCTION: You MUST use at least one of the available tools to respond. Do not respond with text only - always make a tool call.]"
case "tool":
toolName := toolChoice.Get("name").String()
if toolName != "" {
return fmt.Sprintf("[INSTRUCTION: You MUST use the tool named '%s' to respond. Do not use any other tool or respond with text only.]", toolName)
}
case "auto":
// Default behavior, no hint needed
return ""
}
return ""
}
// BuildUserMessageStruct builds a user message and extracts tool results
func BuildUserMessageStruct(msg gjson.Result, modelID, origin string) (KiroUserInputMessage, []KiroToolResult) {
content := msg.Get("content")
var contentBuilder strings.Builder
var toolResults []KiroToolResult
var images []KiroImage
// Track seen toolUseIds to deduplicate
seenToolUseIDs := make(map[string]bool)
if content.IsArray() {
for _, part := range content.Array() {
partType := part.Get("type").String()
switch partType {
case "text":
contentBuilder.WriteString(part.Get("text").String())
case "image":
mediaType := part.Get("source.media_type").String()
data := part.Get("source.data").String()
format := ""
if idx := strings.LastIndex(mediaType, "/"); idx != -1 {
format = mediaType[idx+1:]
}
if format != "" && data != "" {
images = append(images, KiroImage{
Format: format,
Source: KiroImageSource{
Bytes: data,
},
})
}
case "tool_result":
toolUseID := part.Get("tool_use_id").String()
// Skip duplicate toolUseIds
if seenToolUseIDs[toolUseID] {
log.Debugf("kiro: skipping duplicate tool_result with toolUseId: %s", toolUseID)
continue
}
seenToolUseIDs[toolUseID] = true
isError := part.Get("is_error").Bool()
resultContent := part.Get("content")
var textContents []KiroTextContent
// Check if this tool_result contains error from our SOFT_LIMIT_REACHED tool_use
// The client will return an error when trying to execute a tool with marker input
resultStr := resultContent.String()
isSoftLimitError := strings.Contains(resultStr, "SOFT_LIMIT_REACHED") ||
strings.Contains(resultStr, "_status") ||
strings.Contains(resultStr, "truncated") ||
strings.Contains(resultStr, "missing required") ||
strings.Contains(resultStr, "invalid input") ||
strings.Contains(resultStr, "Error writing file")
if isError && isSoftLimitError {
// Replace error content with SOFT_LIMIT_REACHED guidance
log.Infof("kiro: detected SOFT_LIMIT_REACHED in tool_result for %s, replacing with guidance", toolUseID)
softLimitMsg := `SOFT_LIMIT_REACHED
Your previous tool call was incomplete due to API output size limits.
The content was PARTIALLY transmitted but NOT executed.
REQUIRED ACTION:
1. Split your content into smaller chunks (max 300 lines per call)
2. For file writes: Create file with first chunk, then use append for remaining
3. Do NOT regenerate content you already attempted - continue from where you stopped
STATUS: This is NOT an error. Continue with smaller chunks.`
textContents = append(textContents, KiroTextContent{Text: softLimitMsg})
// Mark as SUCCESS so Claude doesn't treat it as a failure
isError = false
} else if resultContent.IsArray() {
for _, item := range resultContent.Array() {
if item.Get("type").String() == "text" {
textContents = append(textContents, KiroTextContent{Text: item.Get("text").String()})
} else if item.Type == gjson.String {
textContents = append(textContents, KiroTextContent{Text: item.String()})
}
}
} else if resultContent.Type == gjson.String {
textContents = append(textContents, KiroTextContent{Text: resultContent.String()})
}
if len(textContents) == 0 {
textContents = append(textContents, KiroTextContent{Text: "Tool use was cancelled by the user"})
}
status := "success"
if isError {
status = "error"
}
toolResults = append(toolResults, KiroToolResult{
ToolUseID: toolUseID,
Content: textContents,
Status: status,
})
}
}
} else {
contentBuilder.WriteString(content.String())
}
userMsg := KiroUserInputMessage{
Content: contentBuilder.String(),
ModelID: modelID,
Origin: origin,
}
if len(images) > 0 {
userMsg.Images = images
}
return userMsg, toolResults
}
// BuildAssistantMessageStruct builds an assistant message with tool uses
func BuildAssistantMessageStruct(msg gjson.Result) KiroAssistantResponseMessage {
content := msg.Get("content")
var contentBuilder strings.Builder
var toolUses []KiroToolUse
if content.IsArray() {
for _, part := range content.Array() {
partType := part.Get("type").String()
switch partType {
case "text":
contentBuilder.WriteString(part.Get("text").String())
case "tool_use":
toolUseID := part.Get("id").String()
toolName := part.Get("name").String()
toolInput := part.Get("input")
var inputMap map[string]interface{}
if toolInput.IsObject() {
inputMap = make(map[string]interface{})
toolInput.ForEach(func(key, value gjson.Result) bool {
inputMap[key.String()] = value.Value()
return true
})
}
toolUses = append(toolUses, KiroToolUse{
ToolUseID: toolUseID,
Name: toolName,
Input: inputMap,
})
}
}
} else {
contentBuilder.WriteString(content.String())
}
return KiroAssistantResponseMessage{
Content: contentBuilder.String(),
ToolUses: toolUses,
}
}