Merge pull request #823 from router-for-me/translator

feat(translator): enhance Claude-to-OpenAI conversion with thinking block and tool result handling

internal/registry/model_definitions.go

@@ -740,7 +740,7 @@ func GetIFlowModels() []*ModelInfo {
 		{ID: "qwen3-235b-a22b-thinking-2507", DisplayName: "Qwen3-235B-A22B-Thinking", Description: "Qwen3 235B A22B Thinking (2507)", Created: 1753401600},
 		{ID: "qwen3-235b-a22b-instruct", DisplayName: "Qwen3-235B-A22B-Instruct", Description: "Qwen3 235B A22B Instruct", Created: 1753401600},
 		{ID: "qwen3-235b", DisplayName: "Qwen3-235B-A22B", Description: "Qwen3 235B A22B", Created: 1753401600},
-		{ID: "minimax-m2", DisplayName: "MiniMax-M2", Description: "MiniMax M2", Created: 1758672000},
+		{ID: "minimax-m2", DisplayName: "MiniMax-M2", Description: "MiniMax M2", Created: 1758672000, Thinking: iFlowThinkingSupport},
 		{ID: "minimax-m2.1", DisplayName: "MiniMax-M2.1", Description: "MiniMax M2.1", Created: 1766448000, Thinking: iFlowThinkingSupport},
 	}
 	models := make([]*ModelInfo, 0, len(entries))

internal/runtime/executor/iflow_executor.go

@@ -441,21 +441,18 @@ func ensureToolsArray(body []byte) []byte {
 	return updated
 }
 
-// preserveReasoningContentInMessages ensures reasoning_content from assistant messages in the
+// preserveReasoningContentInMessages checks if reasoning_content from assistant messages
-// conversation history is preserved when sending to iFlow models that support thinking.
+// is preserved in conversation history for iFlow models that support thinking.
-// This is critical for multi-turn conversations where the model needs to see its previous
+// This is helpful for multi-turn conversations where the model may benefit from seeing
-// reasoning to maintain coherent thought chains across tool calls and conversation turns.
+// its previous reasoning to maintain coherent thought chains.
 //
-// For GLM-4.7 and MiniMax-M2.1, the full assistant response (including reasoning) must be
+// For GLM-4.6/4.7 and MiniMax M2/M2.1, it is recommended to include the full assistant
-// appended back into message history before the next call.
+// response (including reasoning_content) in message history for better context continuity.
 func preserveReasoningContentInMessages(body []byte) []byte {
 	model := strings.ToLower(gjson.GetBytes(body, "model").String())
 
 	// Only apply to models that support thinking with history preservation
-	needsPreservation := strings.HasPrefix(model, "glm-4.7") ||
+	needsPreservation := strings.HasPrefix(model, "glm-4") || strings.HasPrefix(model, "minimax-m2")
-		strings.HasPrefix(model, "glm-4-7") ||
-		strings.HasPrefix(model, "minimax-m2.1") ||
-		strings.HasPrefix(model, "minimax-m2-1")
 
 	if !needsPreservation {
 		return body
@@ -493,45 +490,35 @@ func preserveReasoningContentInMessages(body []byte) []byte {
 // This should be called after NormalizeThinkingConfig has processed the payload.
 //
 // Model-specific handling:
-//   - GLM-4.7: Uses extra_body={"thinking": {"type": "enabled"}, "clear_thinking": false}
+//   - GLM-4.6/4.7: Uses chat_template_kwargs.enable_thinking (boolean) and chat_template_kwargs.clear_thinking=false
-//   - MiniMax-M2.1: Uses reasoning_split=true for OpenAI-style reasoning separation
+//   - MiniMax M2/M2.1: Uses reasoning_split=true for OpenAI-style reasoning separation
-//   - Other iFlow models: Uses chat_template_kwargs.enable_thinking (boolean)
 func applyIFlowThinkingConfig(body []byte) []byte {
 	effort := gjson.GetBytes(body, "reasoning_effort")
-	model := strings.ToLower(gjson.GetBytes(body, "model").String())
+	if !effort.Exists() {
-
+		return body
-	// Check if thinking should be enabled
-	val := ""
-	if effort.Exists() {
-		val = strings.ToLower(strings.TrimSpace(effort.String()))
 	}
-	enableThinking := effort.Exists() && val != "none" && val != ""
+
+	model := strings.ToLower(gjson.GetBytes(body, "model").String())
+	val := strings.ToLower(strings.TrimSpace(effort.String()))
+	enableThinking := val != "none" && val != ""
 
 	// Remove reasoning_effort as we'll convert to model-specific format
-	if effort.Exists() {
 	body, _ = sjson.DeleteBytes(body, "reasoning_effort")
-	}
+	body, _ = sjson.DeleteBytes(body, "thinking")
 
-	// GLM-4.7: Use extra_body with thinking config and clear_thinking: false
+	// GLM-4.6/4.7: Use chat_template_kwargs
-	if strings.HasPrefix(model, "glm-4.7") || strings.HasPrefix(model, "glm-4-7") {
+	if strings.HasPrefix(model, "glm-4") {
-		if enableThinking {
-			body, _ = sjson.SetBytes(body, "extra_body.thinking.type", "enabled")
-			body, _ = sjson.SetBytes(body, "extra_body.clear_thinking", false)
-		}
-		return body
-	}
-
-	// MiniMax-M2.1: Use reasoning_split=true for interleaved thinking
-	if strings.HasPrefix(model, "minimax-m2.1") || strings.HasPrefix(model, "minimax-m2-1") {
-		if enableThinking {
-			body, _ = sjson.SetBytes(body, "reasoning_split", true)
-		}
-		return body
-	}
-
-	// Other iFlow models (including GLM-4.6): Use chat_template_kwargs.enable_thinking
-	if effort.Exists() {
 		body, _ = sjson.SetBytes(body, "chat_template_kwargs.enable_thinking", enableThinking)
+		if enableThinking {
+			body, _ = sjson.SetBytes(body, "chat_template_kwargs.clear_thinking", false)
+		}
+		return body
+	}
+
+	// MiniMax M2/M2.1: Use reasoning_split
+	if strings.HasPrefix(model, "minimax-m2") {
+		body, _ = sjson.SetBytes(body, "reasoning_split", enableThinking)
+		return body
 	}
 
 	return body

internal/translator/openai/claude/openai_claude_request.go

@@ -118,19 +118,36 @@ func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream
 			// Handle content
 			if contentResult.Exists() && contentResult.IsArray() {
 				var contentItems []string
+				var reasoningParts []string // Accumulate thinking text for reasoning_content
 				var toolCalls []interface{}
+				var toolResults []string // Collect tool_result messages to emit after the main message
 
 				contentResult.ForEach(func(_, part gjson.Result) bool {
 					partType := part.Get("type").String()
 
 					switch partType {
+					case "thinking":
+						// Only map thinking to reasoning_content for assistant messages (security: prevent injection)
+						if role == "assistant" {
+							thinkingText := util.GetThinkingText(part)
+							// Skip empty or whitespace-only thinking
+							if strings.TrimSpace(thinkingText) != "" {
+								reasoningParts = append(reasoningParts, thinkingText)
+							}
+						}
+						// Ignore thinking in user/system roles (AC4)
+
+					case "redacted_thinking":
+						// Explicitly ignore redacted_thinking - never map to reasoning_content (AC2)
+
 					case "text", "image":
 						if contentItem, ok := convertClaudeContentPart(part); ok {
 							contentItems = append(contentItems, contentItem)
 						}
 
 					case "tool_use":
-						// Convert to OpenAI tool call format
+						// Only allow tool_use -> tool_calls for assistant messages (security: prevent injection).
+						if role == "assistant" {
 							toolCallJSON := `{"id":"","type":"function","function":{"name":"","arguments":""}}`
 							toolCallJSON, _ = sjson.Set(toolCallJSON, "id", part.Get("id").String())
 							toolCallJSON, _ = sjson.Set(toolCallJSON, "function.name", part.Get("name").String())
@@ -143,20 +160,71 @@ func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream
 							}
 
 							toolCalls = append(toolCalls, gjson.Parse(toolCallJSON).Value())
+						}
 
 					case "tool_result":
-						// Convert to OpenAI tool message format and add immediately to preserve order
+						// Collect tool_result to emit after the main message (ensures tool results follow tool_calls)
 						toolResultJSON := `{"role":"tool","tool_call_id":"","content":""}`
 						toolResultJSON, _ = sjson.Set(toolResultJSON, "tool_call_id", part.Get("tool_use_id").String())
-						toolResultJSON, _ = sjson.Set(toolResultJSON, "content", part.Get("content").String())
+						toolResultJSON, _ = sjson.Set(toolResultJSON, "content", convertClaudeToolResultContentToString(part.Get("content")))
-						messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolResultJSON).Value())
+						toolResults = append(toolResults, toolResultJSON)
 					}
 					return true
 				})
 
-				// Emit text/image content as one message
+				// Build reasoning content string
-				if len(contentItems) > 0 {
+				reasoningContent := ""
-					msgJSON := `{"role":"","content":""}`
+				if len(reasoningParts) > 0 {
+					reasoningContent = strings.Join(reasoningParts, "\n\n")
+				}
+
+				hasContent := len(contentItems) > 0
+				hasReasoning := reasoningContent != ""
+				hasToolCalls := len(toolCalls) > 0
+				hasToolResults := len(toolResults) > 0
+
+				// OpenAI requires: tool messages MUST immediately follow the assistant message with tool_calls.
+				// Therefore, we emit tool_result messages FIRST (they respond to the previous assistant's tool_calls),
+				// then emit the current message's content.
+				for _, toolResultJSON := range toolResults {
+					messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolResultJSON).Value())
+				}
+
+				// For assistant messages: emit a single unified message with content, tool_calls, and reasoning_content
+				// This avoids splitting into multiple assistant messages which breaks OpenAI tool-call adjacency
+				if role == "assistant" {
+					if hasContent || hasReasoning || hasToolCalls {
+						msgJSON := `{"role":"assistant"}`
+
+						// Add content (as array if we have items, empty string if reasoning-only)
+						if hasContent {
+							contentArrayJSON := "[]"
+							for _, contentItem := range contentItems {
+								contentArrayJSON, _ = sjson.SetRaw(contentArrayJSON, "-1", contentItem)
+							}
+							msgJSON, _ = sjson.SetRaw(msgJSON, "content", contentArrayJSON)
+						} else {
+							// Ensure content field exists for OpenAI compatibility
+							msgJSON, _ = sjson.Set(msgJSON, "content", "")
+						}
+
+						// Add reasoning_content if present
+						if hasReasoning {
+							msgJSON, _ = sjson.Set(msgJSON, "reasoning_content", reasoningContent)
+						}
+
+						// Add tool_calls if present (in same message as content)
+						if hasToolCalls {
+							msgJSON, _ = sjson.Set(msgJSON, "tool_calls", toolCalls)
+						}
+
+						messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
+					}
+				} else {
+					// For non-assistant roles: emit content message if we have content
+					// If the message only contains tool_results (no text/image), we still processed them above
+					if hasContent {
+						msgJSON := `{"role":""}`
 						msgJSON, _ = sjson.Set(msgJSON, "role", role)
 
 						contentArrayJSON := "[]"
@@ -165,31 +233,12 @@ func ConvertClaudeRequestToOpenAI(modelName string, inputRawJSON []byte, stream
 						}
 						msgJSON, _ = sjson.SetRaw(msgJSON, "content", contentArrayJSON)
 
-					contentValue := gjson.Get(msgJSON, "content")
-					hasContent := false
-					switch {
-					case !contentValue.Exists():
-						hasContent = false
-					case contentValue.Type == gjson.String:
-						hasContent = contentValue.String() != ""
-					case contentValue.IsArray():
-						hasContent = len(contentValue.Array()) > 0
-					default:
-						hasContent = contentValue.Raw != "" && contentValue.Raw != "null"
-					}
-
-					if hasContent {
 						messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(msgJSON).Value())
+					} else if hasToolResults && !hasContent {
+						// tool_results already emitted above, no additional user message needed
 					}
 				}
 
-				// Emit tool calls in a separate assistant message
-				if role == "assistant" && len(toolCalls) > 0 {
-					toolCallMsgJSON := `{"role":"assistant","tool_calls":[]}`
-					toolCallMsgJSON, _ = sjson.Set(toolCallMsgJSON, "tool_calls", toolCalls)
-					messagesJSON, _ = sjson.Set(messagesJSON, "-1", gjson.Parse(toolCallMsgJSON).Value())
-				}
-
 			} else if contentResult.Exists() && contentResult.Type == gjson.String {
 				// Simple string content
 				msgJSON := `{"role":"","content":""}`
@@ -307,3 +356,43 @@ func convertClaudeContentPart(part gjson.Result) (string, bool) {
 		return "", false
 	}
 }
+
+func convertClaudeToolResultContentToString(content gjson.Result) string {
+	if !content.Exists() {
+		return ""
+	}
+
+	if content.Type == gjson.String {
+		return content.String()
+	}
+
+	if content.IsArray() {
+		var parts []string
+		content.ForEach(func(_, item gjson.Result) bool {
+			switch {
+			case item.Type == gjson.String:
+				parts = append(parts, item.String())
+			case item.IsObject() && item.Get("text").Exists() && item.Get("text").Type == gjson.String:
+				parts = append(parts, item.Get("text").String())
+			default:
+				parts = append(parts, item.Raw)
+			}
+			return true
+		})
+
+		joined := strings.Join(parts, "\n\n")
+		if strings.TrimSpace(joined) != "" {
+			return joined
+		}
+		return content.Raw
+	}
+
+	if content.IsObject() {
+		if text := content.Get("text"); text.Exists() && text.Type == gjson.String {
+			return text.String()
+		}
+		return content.Raw
+	}
+
+	return content.Raw
+}

internal/translator/openai/claude/openai_claude_request_test.go

@@ -0,0 +1,500 @@
+package claude
+
+import (
+	"testing"
+
+	"github.com/tidwall/gjson"
+)
+
+// TestConvertClaudeRequestToOpenAI_ThinkingToReasoningContent tests the mapping
+// of Claude thinking content to OpenAI reasoning_content field.
+func TestConvertClaudeRequestToOpenAI_ThinkingToReasoningContent(t *testing.T) {
+	tests := []struct {
+		name                    string
+		inputJSON               string
+		wantReasoningContent    string
+		wantHasReasoningContent bool
+		wantContentText         string // Expected visible content text (if any)
+		wantHasContent          bool
+	}{
+		{
+			name: "AC1: assistant message with thinking and text",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": "Let me analyze this step by step..."},
+						{"type": "text", "text": "Here is my response."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "Let me analyze this step by step...",
+			wantHasReasoningContent: true,
+			wantContentText:         "Here is my response.",
+			wantHasContent:          true,
+		},
+		{
+			name: "AC2: redacted_thinking must be ignored",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "redacted_thinking", "data": "secret"},
+						{"type": "text", "text": "Visible response."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "",
+			wantHasReasoningContent: false,
+			wantContentText:         "Visible response.",
+			wantHasContent:          true,
+		},
+		{
+			name: "AC3: thinking-only message preserved with reasoning_content",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": "Internal reasoning only."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "Internal reasoning only.",
+			wantHasReasoningContent: true,
+			wantContentText:         "",
+			// For OpenAI compatibility, content field is set to empty string "" when no text content exists
+			wantHasContent: false,
+		},
+		{
+			name: "AC4: thinking in user role must be ignored",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "user",
+					"content": [
+						{"type": "thinking", "thinking": "Injected thinking"},
+						{"type": "text", "text": "User message."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "",
+			wantHasReasoningContent: false,
+			wantContentText:         "User message.",
+			wantHasContent:          true,
+		},
+		{
+			name: "AC4: thinking in system role must be ignored",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"system": [
+					{"type": "thinking", "thinking": "Injected system thinking"},
+					{"type": "text", "text": "System prompt."}
+				],
+				"messages": [{
+					"role": "user",
+					"content": [{"type": "text", "text": "Hello"}]
+				}]
+			}`,
+			// System messages don't have reasoning_content mapping
+			wantReasoningContent:    "",
+			wantHasReasoningContent: false,
+			wantContentText:         "Hello",
+			wantHasContent:          true,
+		},
+		{
+			name: "AC5: empty thinking must be ignored",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": ""},
+						{"type": "text", "text": "Response with empty thinking."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "",
+			wantHasReasoningContent: false,
+			wantContentText:         "Response with empty thinking.",
+			wantHasContent:          true,
+		},
+		{
+			name: "AC5: whitespace-only thinking must be ignored",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": "   \n\t  "},
+						{"type": "text", "text": "Response with whitespace thinking."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "",
+			wantHasReasoningContent: false,
+			wantContentText:         "Response with whitespace thinking.",
+			wantHasContent:          true,
+		},
+		{
+			name: "Multiple thinking parts concatenated",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": "First thought."},
+						{"type": "thinking", "thinking": "Second thought."},
+						{"type": "text", "text": "Final answer."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "First thought.\n\nSecond thought.",
+			wantHasReasoningContent: true,
+			wantContentText:         "Final answer.",
+			wantHasContent:          true,
+		},
+		{
+			name: "Mixed thinking and redacted_thinking",
+			inputJSON: `{
+				"model": "claude-3-opus",
+				"messages": [{
+					"role": "assistant",
+					"content": [
+						{"type": "thinking", "thinking": "Visible thought."},
+						{"type": "redacted_thinking", "data": "hidden"},
+						{"type": "text", "text": "Answer."}
+					]
+				}]
+			}`,
+			wantReasoningContent:    "Visible thought.",
+			wantHasReasoningContent: true,
+			wantContentText:         "Answer.",
+			wantHasContent:          true,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := ConvertClaudeRequestToOpenAI("test-model", []byte(tt.inputJSON), false)
+			resultJSON := gjson.ParseBytes(result)
+
+			// Find the relevant message (skip system message at index 0)
+			messages := resultJSON.Get("messages").Array()
+			if len(messages) < 2 {
+				if tt.wantHasReasoningContent || tt.wantHasContent {
+					t.Fatalf("Expected at least 2 messages (system + user/assistant), got %d", len(messages))
+				}
+				return
+			}
+
+			// Check the last non-system message
+			var targetMsg gjson.Result
+			for i := len(messages) - 1; i >= 0; i-- {
+				if messages[i].Get("role").String() != "system" {
+					targetMsg = messages[i]
+					break
+				}
+			}
+
+			// Check reasoning_content
+			gotReasoningContent := targetMsg.Get("reasoning_content").String()
+			gotHasReasoningContent := targetMsg.Get("reasoning_content").Exists()
+
+			if gotHasReasoningContent != tt.wantHasReasoningContent {
+				t.Errorf("reasoning_content existence = %v, want %v", gotHasReasoningContent, tt.wantHasReasoningContent)
+			}
+
+			if gotReasoningContent != tt.wantReasoningContent {
+				t.Errorf("reasoning_content = %q, want %q", gotReasoningContent, tt.wantReasoningContent)
+			}
+
+			// Check content
+			content := targetMsg.Get("content")
+			// content has meaningful content if it's a non-empty array, or a non-empty string
+			var gotHasContent bool
+			switch {
+			case content.IsArray():
+				gotHasContent = len(content.Array()) > 0
+			case content.Type == gjson.String:
+				gotHasContent = content.String() != ""
+			default:
+				gotHasContent = false
+			}
+
+			if gotHasContent != tt.wantHasContent {
+				t.Errorf("content existence = %v, want %v", gotHasContent, tt.wantHasContent)
+			}
+
+			if tt.wantHasContent && tt.wantContentText != "" {
+				// Find text content
+				var foundText string
+				content.ForEach(func(_, v gjson.Result) bool {
+					if v.Get("type").String() == "text" {
+						foundText = v.Get("text").String()
+						return false
+					}
+					return true
+				})
+				if foundText != tt.wantContentText {
+					t.Errorf("content text = %q, want %q", foundText, tt.wantContentText)
+				}
+			}
+		})
+	}
+}
+
+// TestConvertClaudeRequestToOpenAI_ThinkingOnlyMessagePreserved tests AC3:
+// that a message with only thinking content is preserved (not dropped).
+func TestConvertClaudeRequestToOpenAI_ThinkingOnlyMessagePreserved(t *testing.T) {
+	inputJSON := `{
+		"model": "claude-3-opus",
+		"messages": [
+			{
+				"role": "user",
+				"content": [{"type": "text", "text": "What is 2+2?"}]
+			},
+			{
+				"role": "assistant",
+				"content": [{"type": "thinking", "thinking": "Let me calculate: 2+2=4"}]
+			},
+			{
+				"role": "user",
+				"content": [{"type": "text", "text": "Thanks"}]
+			}
+		]
+	}`
+
+	result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
+	resultJSON := gjson.ParseBytes(result)
+
+	messages := resultJSON.Get("messages").Array()
+
+	// Should have: system (auto-added) + user + assistant (thinking-only) + user = 4 messages
+	if len(messages) != 4 {
+		t.Fatalf("Expected 4 messages, got %d. Messages: %v", len(messages), resultJSON.Get("messages").Raw)
+	}
+
+	// Check the assistant message (index 2) has reasoning_content
+	assistantMsg := messages[2]
+	if assistantMsg.Get("role").String() != "assistant" {
+		t.Errorf("Expected message[2] to be assistant, got %s", assistantMsg.Get("role").String())
+	}
+
+	if !assistantMsg.Get("reasoning_content").Exists() {
+		t.Error("Expected assistant message to have reasoning_content")
+	}
+
+	if assistantMsg.Get("reasoning_content").String() != "Let me calculate: 2+2=4" {
+		t.Errorf("Unexpected reasoning_content: %s", assistantMsg.Get("reasoning_content").String())
+	}
+}
+
+func TestConvertClaudeRequestToOpenAI_ToolResultOrderAndContent(t *testing.T) {
+	inputJSON := `{
+		"model": "claude-3-opus",
+		"messages": [
+			{
+				"role": "assistant",
+				"content": [
+					{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}}
+				]
+			},
+			{
+				"role": "user",
+				"content": [
+					{"type": "text", "text": "before"},
+					{"type": "tool_result", "tool_use_id": "call_1", "content": [{"type":"text","text":"tool ok"}]},
+					{"type": "text", "text": "after"}
+				]
+			}
+		]
+	}`
+
+	result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
+	resultJSON := gjson.ParseBytes(result)
+	messages := resultJSON.Get("messages").Array()
+
+	// OpenAI requires: tool messages MUST immediately follow assistant(tool_calls).
+	// Correct order: system + assistant(tool_calls) + tool(result) + user(before+after)
+	if len(messages) != 4 {
+		t.Fatalf("Expected 4 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
+	}
+
+	if messages[0].Get("role").String() != "system" {
+		t.Fatalf("Expected messages[0] to be system, got %s", messages[0].Get("role").String())
+	}
+
+	if messages[1].Get("role").String() != "assistant" || !messages[1].Get("tool_calls").Exists() {
+		t.Fatalf("Expected messages[1] to be assistant tool_calls, got %s: %s", messages[1].Get("role").String(), messages[1].Raw)
+	}
+
+	// tool message MUST immediately follow assistant(tool_calls) per OpenAI spec
+	if messages[2].Get("role").String() != "tool" {
+		t.Fatalf("Expected messages[2] to be tool (must follow tool_calls), got %s", messages[2].Get("role").String())
+	}
+	if got := messages[2].Get("tool_call_id").String(); got != "call_1" {
+		t.Fatalf("Expected tool_call_id %q, got %q", "call_1", got)
+	}
+	if got := messages[2].Get("content").String(); got != "tool ok" {
+		t.Fatalf("Expected tool content %q, got %q", "tool ok", got)
+	}
+
+	// User message comes after tool message
+	if messages[3].Get("role").String() != "user" {
+		t.Fatalf("Expected messages[3] to be user, got %s", messages[3].Get("role").String())
+	}
+	// User message should contain both "before" and "after" text
+	if got := messages[3].Get("content.0.text").String(); got != "before" {
+		t.Fatalf("Expected user text[0] %q, got %q", "before", got)
+	}
+	if got := messages[3].Get("content.1.text").String(); got != "after" {
+		t.Fatalf("Expected user text[1] %q, got %q", "after", got)
+	}
+}
+
+func TestConvertClaudeRequestToOpenAI_ToolResultObjectContent(t *testing.T) {
+	inputJSON := `{
+		"model": "claude-3-opus",
+		"messages": [
+			{
+				"role": "assistant",
+				"content": [
+					{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}}
+				]
+			},
+			{
+				"role": "user",
+				"content": [
+					{"type": "tool_result", "tool_use_id": "call_1", "content": {"foo": "bar"}}
+				]
+			}
+		]
+	}`
+
+	result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
+	resultJSON := gjson.ParseBytes(result)
+	messages := resultJSON.Get("messages").Array()
+
+	// system + assistant(tool_calls) + tool(result)
+	if len(messages) != 3 {
+		t.Fatalf("Expected 3 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
+	}
+
+	if messages[2].Get("role").String() != "tool" {
+		t.Fatalf("Expected messages[2] to be tool, got %s", messages[2].Get("role").String())
+	}
+
+	toolContent := messages[2].Get("content").String()
+	parsed := gjson.Parse(toolContent)
+	if parsed.Get("foo").String() != "bar" {
+		t.Fatalf("Expected tool content JSON foo=bar, got %q", toolContent)
+	}
+}
+
+func TestConvertClaudeRequestToOpenAI_AssistantTextToolUseTextOrder(t *testing.T) {
+	inputJSON := `{
+		"model": "claude-3-opus",
+		"messages": [
+			{
+				"role": "assistant",
+				"content": [
+					{"type": "text", "text": "pre"},
+					{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}},
+					{"type": "text", "text": "post"}
+				]
+			}
+		]
+	}`
+
+	result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
+	resultJSON := gjson.ParseBytes(result)
+	messages := resultJSON.Get("messages").Array()
+
+	// New behavior: content + tool_calls unified in single assistant message
+	// Expect: system + assistant(content[pre,post] + tool_calls)
+	if len(messages) != 2 {
+		t.Fatalf("Expected 2 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
+	}
+
+	if messages[0].Get("role").String() != "system" {
+		t.Fatalf("Expected messages[0] to be system, got %s", messages[0].Get("role").String())
+	}
+
+	assistantMsg := messages[1]
+	if assistantMsg.Get("role").String() != "assistant" {
+		t.Fatalf("Expected messages[1] to be assistant, got %s", assistantMsg.Get("role").String())
+	}
+
+	// Should have both content and tool_calls in same message
+	if !assistantMsg.Get("tool_calls").Exists() {
+		t.Fatalf("Expected assistant message to have tool_calls")
+	}
+	if got := assistantMsg.Get("tool_calls.0.id").String(); got != "call_1" {
+		t.Fatalf("Expected tool_call id %q, got %q", "call_1", got)
+	}
+	if got := assistantMsg.Get("tool_calls.0.function.name").String(); got != "do_work" {
+		t.Fatalf("Expected tool_call name %q, got %q", "do_work", got)
+	}
+
+	// Content should have both pre and post text
+	if got := assistantMsg.Get("content.0.text").String(); got != "pre" {
+		t.Fatalf("Expected content[0] text %q, got %q", "pre", got)
+	}
+	if got := assistantMsg.Get("content.1.text").String(); got != "post" {
+		t.Fatalf("Expected content[1] text %q, got %q", "post", got)
+	}
+}
+
+func TestConvertClaudeRequestToOpenAI_AssistantThinkingToolUseThinkingSplit(t *testing.T) {
+	inputJSON := `{
+		"model": "claude-3-opus",
+		"messages": [
+			{
+				"role": "assistant",
+				"content": [
+					{"type": "thinking", "thinking": "t1"},
+					{"type": "text", "text": "pre"},
+					{"type": "tool_use", "id": "call_1", "name": "do_work", "input": {"a": 1}},
+					{"type": "thinking", "thinking": "t2"},
+					{"type": "text", "text": "post"}
+				]
+			}
+		]
+	}`
+
+	result := ConvertClaudeRequestToOpenAI("test-model", []byte(inputJSON), false)
+	resultJSON := gjson.ParseBytes(result)
+	messages := resultJSON.Get("messages").Array()
+
+	// New behavior: all content, thinking, and tool_calls unified in single assistant message
+	// Expect: system + assistant(content[pre,post] + tool_calls + reasoning_content[t1+t2])
+	if len(messages) != 2 {
+		t.Fatalf("Expected 2 messages, got %d. Messages: %s", len(messages), resultJSON.Get("messages").Raw)
+	}
+
+	assistantMsg := messages[1]
+	if assistantMsg.Get("role").String() != "assistant" {
+		t.Fatalf("Expected messages[1] to be assistant, got %s", assistantMsg.Get("role").String())
+	}
+
+	// Should have content with both pre and post
+	if got := assistantMsg.Get("content.0.text").String(); got != "pre" {
+		t.Fatalf("Expected content[0] text %q, got %q", "pre", got)
+	}
+	if got := assistantMsg.Get("content.1.text").String(); got != "post" {
+		t.Fatalf("Expected content[1] text %q, got %q", "post", got)
+	}
+
+	// Should have tool_calls
+	if !assistantMsg.Get("tool_calls").Exists() {
+		t.Fatalf("Expected assistant message to have tool_calls")
+	}
+
+	// Should have combined reasoning_content from both thinking blocks
+	if got := assistantMsg.Get("reasoning_content").String(); got != "t1\n\nt2" {
+		t.Fatalf("Expected reasoning_content %q, got %q", "t1\n\nt2", got)
+	}
+}

internal/translator/openai/claude/openai_claude_response.go

@@ -480,15 +480,15 @@ func collectOpenAIReasoningTexts(node gjson.Result) []string {
 
 	switch node.Type {
 	case gjson.String:
-		if text := strings.TrimSpace(node.String()); text != "" {
+		if text := node.String(); text != "" {
 			texts = append(texts, text)
 		}
 	case gjson.JSON:
 		if text := node.Get("text"); text.Exists() {
-			if trimmed := strings.TrimSpace(text.String()); trimmed != "" {
+			if textStr := text.String(); textStr != "" {
-				texts = append(texts, trimmed)
+				texts = append(texts, textStr)
 			}
-		} else if raw := strings.TrimSpace(node.Raw); raw != "" && !strings.HasPrefix(raw, "{") && !strings.HasPrefix(raw, "[") {
+		} else if raw := node.Raw; raw != "" && !strings.HasPrefix(raw, "{") && !strings.HasPrefix(raw, "[") {
 			texts = append(texts, raw)
 		}
 	}