Add claude code support

internal/translator/claude/openai/claude_openai_request.go

@@ -0,0 +1,289 @@
+// Package openai provides request translation functionality for OpenAI to Anthropic API.
+// It handles parsing and transforming OpenAI Chat Completions API requests into Anthropic API format,
+// extracting model information, system instructions, message contents, and tool declarations.
+// The package performs JSON data transformation to ensure compatibility
+// between OpenAI API format and Anthropic API's expected format.
+package openai
+
+import (
+	"crypto/rand"
+	"encoding/json"
+	"math/big"
+	"strings"
+
+	"github.com/tidwall/gjson"
+	"github.com/tidwall/sjson"
+)
+
+// ConvertOpenAIRequestToAnthropic parses and transforms an OpenAI Chat Completions API request into Anthropic API format.
+// It extracts the model name, system instruction, message contents, and tool declarations
+// from the raw JSON request and returns them in the format expected by the Anthropic API.
+func ConvertOpenAIRequestToAnthropic(rawJSON []byte) string {
+	// Base Anthropic API template
+	out := `{"model":"","max_tokens":32000,"messages":[]}`
+
+	root := gjson.ParseBytes(rawJSON)
+
+	// Helper for generating tool call IDs in the form: toolu_<alphanum>
+	genToolCallID := func() string {
+		const letters = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
+		var b strings.Builder
+		// 24 chars random suffix
+		for i := 0; i < 24; i++ {
+			n, _ := rand.Int(rand.Reader, big.NewInt(int64(len(letters))))
+			b.WriteByte(letters[n.Int64()])
+		}
+		return "toolu_" + b.String()
+	}
+
+	// Model mapping
+	if model := root.Get("model"); model.Exists() {
+		modelStr := model.String()
+		out, _ = sjson.Set(out, "model", modelStr)
+	}
+
+	// Max tokens
+	if maxTokens := root.Get("max_tokens"); maxTokens.Exists() {
+		out, _ = sjson.Set(out, "max_tokens", maxTokens.Int())
+	}
+
+	// Temperature
+	if temp := root.Get("temperature"); temp.Exists() {
+		out, _ = sjson.Set(out, "temperature", temp.Float())
+	}
+
+	// Top P
+	if topP := root.Get("top_p"); topP.Exists() {
+		out, _ = sjson.Set(out, "top_p", topP.Float())
+	}
+
+	// Stop sequences
+	if stop := root.Get("stop"); stop.Exists() {
+		if stop.IsArray() {
+			var stopSequences []string
+			stop.ForEach(func(_, value gjson.Result) bool {
+				stopSequences = append(stopSequences, value.String())
+				return true
+			})
+			if len(stopSequences) > 0 {
+				out, _ = sjson.Set(out, "stop_sequences", stopSequences)
+			}
+		} else {
+			out, _ = sjson.Set(out, "stop_sequences", []string{stop.String()})
+		}
+	}
+
+	// Stream
+	if stream := root.Get("stream"); stream.Exists() {
+		out, _ = sjson.Set(out, "stream", stream.Bool())
+	}
+
+	// Process messages
+	var anthropicMessages []interface{}
+	var toolCallIDs []string // Track tool call IDs for matching with tool results
+
+	if messages := root.Get("messages"); messages.Exists() && messages.IsArray() {
+		messages.ForEach(func(_, message gjson.Result) bool {
+			role := message.Get("role").String()
+			contentResult := message.Get("content")
+
+			switch role {
+			case "system", "user", "assistant":
+				// Create Anthropic message
+				if role == "system" {
+					role = "user"
+				}
+
+				msg := map[string]interface{}{
+					"role":    role,
+					"content": []interface{}{},
+				}
+
+				// Handle content
+				if contentResult.Exists() && contentResult.Type == gjson.String && contentResult.String() != "" {
+					// Simple text content
+					msg["content"] = []interface{}{
+						map[string]interface{}{
+							"type": "text",
+							"text": contentResult.String(),
+						},
+					}
+				} else if contentResult.Exists() && contentResult.IsArray() {
+					// Array of content parts
+					var contentParts []interface{}
+					contentResult.ForEach(func(_, part gjson.Result) bool {
+						partType := part.Get("type").String()
+
+						switch partType {
+						case "text":
+							contentParts = append(contentParts, map[string]interface{}{
+								"type": "text",
+								"text": part.Get("text").String(),
+							})
+
+						case "image_url":
+							// Convert OpenAI image format to Anthropic format
+							imageURL := part.Get("image_url.url").String()
+							if strings.HasPrefix(imageURL, "data:") {
+								// Extract base64 data and media type
+								parts := strings.Split(imageURL, ",")
+								if len(parts) == 2 {
+									mediaTypePart := strings.Split(parts[0], ";")[0]
+									mediaType := strings.TrimPrefix(mediaTypePart, "data:")
+									data := parts[1]
+
+									contentParts = append(contentParts, map[string]interface{}{
+										"type": "image",
+										"source": map[string]interface{}{
+											"type":       "base64",
+											"media_type": mediaType,
+											"data":       data,
+										},
+									})
+								}
+							}
+						}
+						return true
+					})
+					if len(contentParts) > 0 {
+						msg["content"] = contentParts
+					}
+				} else {
+					// Initialize empty content array for tool calls
+					msg["content"] = []interface{}{}
+				}
+
+				// Handle tool calls (for assistant messages)
+				if toolCalls := message.Get("tool_calls"); toolCalls.Exists() && toolCalls.IsArray() && role == "assistant" {
+					var contentParts []interface{}
+
+					// Add existing text content if any
+					if existingContent, ok := msg["content"].([]interface{}); ok {
+						contentParts = existingContent
+					}
+
+					toolCalls.ForEach(func(_, toolCall gjson.Result) bool {
+						if toolCall.Get("type").String() == "function" {
+							toolCallID := toolCall.Get("id").String()
+							if toolCallID == "" {
+								toolCallID = genToolCallID()
+							}
+							toolCallIDs = append(toolCallIDs, toolCallID)
+
+							function := toolCall.Get("function")
+							toolUse := map[string]interface{}{
+								"type": "tool_use",
+								"id":   toolCallID,
+								"name": function.Get("name").String(),
+							}
+
+							// Parse arguments
+							if args := function.Get("arguments"); args.Exists() {
+								argsStr := args.String()
+								if argsStr != "" {
+									var argsMap map[string]interface{}
+									if err := json.Unmarshal([]byte(argsStr), &argsMap); err == nil {
+										toolUse["input"] = argsMap
+									} else {
+										toolUse["input"] = map[string]interface{}{}
+									}
+								} else {
+									toolUse["input"] = map[string]interface{}{}
+								}
+							} else {
+								toolUse["input"] = map[string]interface{}{}
+							}
+
+							contentParts = append(contentParts, toolUse)
+						}
+						return true
+					})
+					msg["content"] = contentParts
+				}
+
+				anthropicMessages = append(anthropicMessages, msg)
+
+			case "tool":
+				// Handle tool result messages
+				toolCallID := message.Get("tool_call_id").String()
+				content := message.Get("content").String()
+
+				// Create tool result message
+				msg := map[string]interface{}{
+					"role": "user",
+					"content": []interface{}{
+						map[string]interface{}{
+							"type":        "tool_result",
+							"tool_use_id": toolCallID,
+							"content":     content,
+						},
+					},
+				}
+
+				anthropicMessages = append(anthropicMessages, msg)
+			}
+			return true
+		})
+	}
+
+	// Set messages
+	if len(anthropicMessages) > 0 {
+		messagesJSON, _ := json.Marshal(anthropicMessages)
+		out, _ = sjson.SetRaw(out, "messages", string(messagesJSON))
+	}
+
+	// Tools mapping: OpenAI tools -> Anthropic tools
+	if tools := root.Get("tools"); tools.Exists() && tools.IsArray() {
+		var anthropicTools []interface{}
+		tools.ForEach(func(_, tool gjson.Result) bool {
+			if tool.Get("type").String() == "function" {
+				function := tool.Get("function")
+				anthropicTool := map[string]interface{}{
+					"name":        function.Get("name").String(),
+					"description": function.Get("description").String(),
+				}
+
+				// Convert parameters schema
+				if parameters := function.Get("parameters"); parameters.Exists() {
+					anthropicTool["input_schema"] = parameters.Value()
+				}
+
+				anthropicTools = append(anthropicTools, anthropicTool)
+			}
+			return true
+		})
+
+		if len(anthropicTools) > 0 {
+			toolsJSON, _ := json.Marshal(anthropicTools)
+			out, _ = sjson.SetRaw(out, "tools", string(toolsJSON))
+		}
+	}
+
+	// Tool choice mapping
+	if toolChoice := root.Get("tool_choice"); toolChoice.Exists() {
+		switch toolChoice.Type {
+		case gjson.String:
+			choice := toolChoice.String()
+			switch choice {
+			case "none":
+				// Don't set tool_choice, Anthropic will not use tools
+			case "auto":
+				out, _ = sjson.Set(out, "tool_choice", map[string]interface{}{"type": "auto"})
+			case "required":
+				out, _ = sjson.Set(out, "tool_choice", map[string]interface{}{"type": "any"})
+			}
+		case gjson.JSON:
+			// Specific tool choice
+			if toolChoice.Get("type").String() == "function" {
+				functionName := toolChoice.Get("function.name").String()
+				out, _ = sjson.Set(out, "tool_choice", map[string]interface{}{
+					"type": "tool",
+					"name": functionName,
+				})
+			}
+		default:
+		}
+	}
+
+	return out
+}

internal/translator/claude/openai/claude_openai_response.go

@@ -0,0 +1,395 @@
+// Package openai provides response translation functionality for Anthropic to OpenAI API.
+// This package handles the conversion of Anthropic API responses into OpenAI Chat Completions-compatible
+// JSON format, transforming streaming events and non-streaming responses into the format
+// expected by OpenAI API clients. It supports both streaming and non-streaming modes,
+// handling text content, tool calls, and usage metadata appropriately.
+package openai
+
+import (
+	"encoding/json"
+	"strings"
+	"time"
+
+	"github.com/tidwall/gjson"
+	"github.com/tidwall/sjson"
+)
+
+// ConvertAnthropicResponseToOpenAIParams holds parameters for response conversion
+type ConvertAnthropicResponseToOpenAIParams struct {
+	CreatedAt    int64
+	ResponseID   string
+	FinishReason string
+	// Tool calls accumulator for streaming
+	ToolCallsAccumulator map[int]*ToolCallAccumulator
+}
+
+// ToolCallAccumulator holds the state for accumulating tool call data
+type ToolCallAccumulator struct {
+	ID        string
+	Name      string
+	Arguments strings.Builder
+}
+
+// ConvertAnthropicResponseToOpenAI converts Anthropic streaming response format to OpenAI Chat Completions format.
+// This function processes various Anthropic event types and transforms them into OpenAI-compatible JSON responses.
+// It handles text content, tool calls, and usage metadata, outputting responses that match the OpenAI API format.
+func ConvertAnthropicResponseToOpenAI(rawJSON []byte, param *ConvertAnthropicResponseToOpenAIParams) []string {
+	root := gjson.ParseBytes(rawJSON)
+	eventType := root.Get("type").String()
+
+	// Base OpenAI streaming response template
+	template := `{"id":"","object":"chat.completion.chunk","created":0,"model":"","choices":[{"index":0,"delta":{},"finish_reason":null}]}`
+
+	// Set model
+	modelResult := gjson.GetBytes(rawJSON, "model")
+	modelName := modelResult.String()
+	if modelName != "" {
+		template, _ = sjson.Set(template, "model", modelName)
+	}
+
+	// Set response ID and creation time
+	if param.ResponseID != "" {
+		template, _ = sjson.Set(template, "id", param.ResponseID)
+	}
+	if param.CreatedAt > 0 {
+		template, _ = sjson.Set(template, "created", param.CreatedAt)
+	}
+
+	switch eventType {
+	case "message_start":
+		// Initialize response with message metadata
+		if message := root.Get("message"); message.Exists() {
+			param.ResponseID = message.Get("id").String()
+			param.CreatedAt = time.Now().Unix()
+
+			template, _ = sjson.Set(template, "id", param.ResponseID)
+			template, _ = sjson.Set(template, "model", modelName)
+			template, _ = sjson.Set(template, "created", param.CreatedAt)
+
+			// Set initial role
+			template, _ = sjson.Set(template, "choices.0.delta.role", "assistant")
+
+			// Initialize tool calls accumulator
+			if param.ToolCallsAccumulator == nil {
+				param.ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
+			}
+		}
+		return []string{template}
+
+	case "content_block_start":
+		// Start of a content block
+		if contentBlock := root.Get("content_block"); contentBlock.Exists() {
+			blockType := contentBlock.Get("type").String()
+
+			if blockType == "tool_use" {
+				// Start of tool call - initialize accumulator
+				toolCallID := contentBlock.Get("id").String()
+				toolName := contentBlock.Get("name").String()
+				index := int(root.Get("index").Int())
+
+				if param.ToolCallsAccumulator == nil {
+					param.ToolCallsAccumulator = make(map[int]*ToolCallAccumulator)
+				}
+
+				param.ToolCallsAccumulator[index] = &ToolCallAccumulator{
+					ID:   toolCallID,
+					Name: toolName,
+				}
+
+				// Don't output anything yet - wait for complete tool call
+				return []string{}
+			}
+		}
+		return []string{template}
+
+	case "content_block_delta":
+		// Handle content delta (text or tool use)
+		if delta := root.Get("delta"); delta.Exists() {
+			deltaType := delta.Get("type").String()
+
+			switch deltaType {
+			case "text_delta":
+				// Text content delta
+				if text := delta.Get("text"); text.Exists() {
+					template, _ = sjson.Set(template, "choices.0.delta.content", text.String())
+				}
+
+			case "input_json_delta":
+				// Tool use input delta - accumulate arguments
+				if partialJSON := delta.Get("partial_json"); partialJSON.Exists() {
+					index := int(root.Get("index").Int())
+					if param.ToolCallsAccumulator != nil {
+						if accumulator, exists := param.ToolCallsAccumulator[index]; exists {
+							accumulator.Arguments.WriteString(partialJSON.String())
+						}
+					}
+				}
+				// Don't output anything yet - wait for complete tool call
+				return []string{}
+			}
+		}
+		return []string{template}
+
+	case "content_block_stop":
+		// End of content block - output complete tool call if it's a tool_use block
+		index := int(root.Get("index").Int())
+		if param.ToolCallsAccumulator != nil {
+			if accumulator, exists := param.ToolCallsAccumulator[index]; exists {
+				// Build complete tool call
+				arguments := accumulator.Arguments.String()
+				if arguments == "" {
+					arguments = "{}"
+				}
+
+				toolCall := map[string]interface{}{
+					"index": index,
+					"id":    accumulator.ID,
+					"type":  "function",
+					"function": map[string]interface{}{
+						"name":      accumulator.Name,
+						"arguments": arguments,
+					},
+				}
+
+				template, _ = sjson.Set(template, "choices.0.delta.tool_calls", []interface{}{toolCall})
+
+				// Clean up the accumulator for this index
+				delete(param.ToolCallsAccumulator, index)
+
+				return []string{template}
+			}
+		}
+		return []string{}
+
+	case "message_delta":
+		// Handle message-level changes
+		if delta := root.Get("delta"); delta.Exists() {
+			if stopReason := delta.Get("stop_reason"); stopReason.Exists() {
+				param.FinishReason = mapAnthropicStopReasonToOpenAI(stopReason.String())
+				template, _ = sjson.Set(template, "choices.0.finish_reason", param.FinishReason)
+			}
+		}
+
+		// Handle usage information
+		if usage := root.Get("usage"); usage.Exists() {
+			usageObj := map[string]interface{}{
+				"prompt_tokens":     usage.Get("input_tokens").Int(),
+				"completion_tokens": usage.Get("output_tokens").Int(),
+				"total_tokens":      usage.Get("input_tokens").Int() + usage.Get("output_tokens").Int(),
+			}
+			template, _ = sjson.Set(template, "usage", usageObj)
+		}
+		return []string{template}
+
+	case "message_stop":
+		// Final message - send [DONE]
+		return []string{"[DONE]\n"}
+
+	case "ping":
+		// Ping events - ignore
+		return []string{}
+
+	case "error":
+		// Error event
+		if errorData := root.Get("error"); errorData.Exists() {
+			errorResponse := map[string]interface{}{
+				"error": map[string]interface{}{
+					"message": errorData.Get("message").String(),
+					"type":    errorData.Get("type").String(),
+				},
+			}
+			errorJSON, _ := json.Marshal(errorResponse)
+			return []string{string(errorJSON)}
+		}
+		return []string{}
+
+	default:
+		// Unknown event type - ignore
+		return []string{}
+	}
+}
+
+// mapAnthropicStopReasonToOpenAI maps Anthropic stop reasons to OpenAI stop reasons
+func mapAnthropicStopReasonToOpenAI(anthropicReason string) string {
+	switch anthropicReason {
+	case "end_turn":
+		return "stop"
+	case "tool_use":
+		return "tool_calls"
+	case "max_tokens":
+		return "length"
+	case "stop_sequence":
+		return "stop"
+	default:
+		return "stop"
+	}
+}
+
+// ConvertAnthropicStreamingResponseToOpenAINonStream aggregates streaming chunks into a single non-streaming response
+// following OpenAI Chat Completions API format with reasoning content support
+func ConvertAnthropicStreamingResponseToOpenAINonStream(chunks [][]byte) string {
+	// Base OpenAI non-streaming response template
+	out := `{"id":"","object":"chat.completion","created":0,"model":"","choices":[{"index":0,"message":{"role":"assistant","content":""},"finish_reason":"stop"}],"usage":{"prompt_tokens":0,"completion_tokens":0,"total_tokens":0}}`
+
+	var messageID string
+	var model string
+	var createdAt int64
+	var inputTokens, outputTokens int64
+	var reasoningTokens int64
+	var stopReason string
+	var contentParts []string
+	var reasoningParts []string
+	// Use map to track tool calls by index for proper merging
+	toolCallsMap := make(map[int]map[string]interface{})
+	// Track tool call arguments accumulation
+	toolCallArgsMap := make(map[int]strings.Builder)
+
+	for _, chunk := range chunks {
+		root := gjson.ParseBytes(chunk)
+		eventType := root.Get("type").String()
+
+		switch eventType {
+		case "message_start":
+			if message := root.Get("message"); message.Exists() {
+				messageID = message.Get("id").String()
+				model = message.Get("model").String()
+				createdAt = time.Now().Unix()
+				if usage := message.Get("usage"); usage.Exists() {
+					inputTokens = usage.Get("input_tokens").Int()
+				}
+			}
+
+		case "content_block_start":
+			// Handle different content block types
+			if contentBlock := root.Get("content_block"); contentBlock.Exists() {
+				blockType := contentBlock.Get("type").String()
+				if blockType == "thinking" {
+					// Start of thinking/reasoning content
+					continue
+				} else if blockType == "tool_use" {
+					// Initialize tool call tracking
+					index := int(root.Get("index").Int())
+					toolCallsMap[index] = map[string]interface{}{
+						"id":   contentBlock.Get("id").String(),
+						"type": "function",
+						"function": map[string]interface{}{
+							"name":      contentBlock.Get("name").String(),
+							"arguments": "",
+						},
+					}
+					// Initialize arguments builder for this tool call
+					toolCallArgsMap[index] = strings.Builder{}
+				}
+			}
+
+		case "content_block_delta":
+			if delta := root.Get("delta"); delta.Exists() {
+				deltaType := delta.Get("type").String()
+				switch deltaType {
+				case "text_delta":
+					if text := delta.Get("text"); text.Exists() {
+						contentParts = append(contentParts, text.String())
+					}
+				case "thinking_delta":
+					// Anthropic thinking content -> OpenAI reasoning content
+					if thinking := delta.Get("thinking"); thinking.Exists() {
+						reasoningParts = append(reasoningParts, thinking.String())
+					}
+				case "input_json_delta":
+					// Accumulate tool call arguments
+					if partialJSON := delta.Get("partial_json"); partialJSON.Exists() {
+						index := int(root.Get("index").Int())
+						if builder, exists := toolCallArgsMap[index]; exists {
+							builder.WriteString(partialJSON.String())
+							toolCallArgsMap[index] = builder
+						}
+					}
+				}
+			}
+
+		case "content_block_stop":
+			// Finalize tool call arguments for this index
+			index := int(root.Get("index").Int())
+			if toolCall, exists := toolCallsMap[index]; exists {
+				if builder, argsExists := toolCallArgsMap[index]; argsExists {
+					// Set the accumulated arguments
+					arguments := builder.String()
+					if arguments == "" {
+						arguments = "{}"
+					}
+					toolCall["function"].(map[string]interface{})["arguments"] = arguments
+				}
+			}
+
+		case "message_delta":
+			if delta := root.Get("delta"); delta.Exists() {
+				if sr := delta.Get("stop_reason"); sr.Exists() {
+					stopReason = sr.String()
+				}
+			}
+			if usage := root.Get("usage"); usage.Exists() {
+				outputTokens = usage.Get("output_tokens").Int()
+				// Estimate reasoning tokens from thinking content
+				if len(reasoningParts) > 0 {
+					reasoningTokens = int64(len(strings.Join(reasoningParts, "")) / 4) // Rough estimation
+				}
+			}
+		}
+	}
+
+	// Set basic response fields
+	out, _ = sjson.Set(out, "id", messageID)
+	out, _ = sjson.Set(out, "created", createdAt)
+	out, _ = sjson.Set(out, "model", model)
+
+	// Set message content
+	messageContent := strings.Join(contentParts, "")
+	out, _ = sjson.Set(out, "choices.0.message.content", messageContent)
+
+	// Add reasoning content if available (following OpenAI reasoning format)
+	if len(reasoningParts) > 0 {
+		reasoningContent := strings.Join(reasoningParts, "")
+		// Add reasoning as a separate field in the message
+		out, _ = sjson.Set(out, "choices.0.message.reasoning", reasoningContent)
+	}
+
+	// Set tool calls if any
+	if len(toolCallsMap) > 0 {
+		// Convert tool calls map to array, preserving order by index
+		var toolCallsArray []interface{}
+		// Find the maximum index to determine the range
+		maxIndex := -1
+		for index := range toolCallsMap {
+			if index > maxIndex {
+				maxIndex = index
+			}
+		}
+		// Iterate through all possible indices up to maxIndex
+		for i := 0; i <= maxIndex; i++ {
+			if toolCall, exists := toolCallsMap[i]; exists {
+				toolCallsArray = append(toolCallsArray, toolCall)
+			}
+		}
+		if len(toolCallsArray) > 0 {
+			out, _ = sjson.Set(out, "choices.0.message.tool_calls", toolCallsArray)
+			out, _ = sjson.Set(out, "choices.0.finish_reason", "tool_calls")
+		} else {
+			out, _ = sjson.Set(out, "choices.0.finish_reason", mapAnthropicStopReasonToOpenAI(stopReason))
+		}
+	} else {
+		out, _ = sjson.Set(out, "choices.0.finish_reason", mapAnthropicStopReasonToOpenAI(stopReason))
+	}
+
+	// Set usage information
+	totalTokens := inputTokens + outputTokens
+	out, _ = sjson.Set(out, "usage.prompt_tokens", inputTokens)
+	out, _ = sjson.Set(out, "usage.completion_tokens", outputTokens)
+	out, _ = sjson.Set(out, "usage.total_tokens", totalTokens)
+
+	// Add reasoning tokens to usage details if available
+	if reasoningTokens > 0 {
+		out, _ = sjson.Set(out, "usage.completion_tokens_details.reasoning_tokens", reasoningTokens)
+	}
+
+	return out
+}