refactor(plugins/compat-oai): use ChatCompletionAccumulator for strea…

go/plugins/compat_oai/generate.go

@@ -251,145 +251,110 @@ func (g *ModelGenerator) generateStream(ctx context.Context, handleChunk func(co
 	stream := g.client.Chat.Completions.NewStreaming(ctx, *g.request)
 	defer stream.Close()
 
-	var fullResponse ai.ModelResponse
-	fullResponse.Message = &ai.Message{
-		Role:    ai.RoleModel,
-		Content: make([]*ai.Part, 0),
-	}
-
-	// Initialize request and usage
-	fullResponse.Request = &ai.ModelRequest{}
-	fullResponse.Usage = &ai.GenerationUsage{
-		InputTokens:  0,
-		OutputTokens: 0,
-		TotalTokens:  0,
-	}
-
-	var currentToolCall *ai.ToolRequest
-	var currentArguments string
-	var toolCallCollects []struct {
-		toolCall *ai.ToolRequest
-		args     string
-	}
+	// Use openai-go's accumulator to collect the complete response
+	acc := &openai.ChatCompletionAccumulator{}
 
 	for stream.Next() {
 		chunk := stream.Current()
-		if len(chunk.Choices) > 0 {
-			choice := chunk.Choices[0]
-			modelChunk := &ai.ModelResponseChunk{}
-
-			switch choice.FinishReason {
-			case "tool_calls", "stop":
-				fullResponse.FinishReason = ai.FinishReasonStop
-			case "length":
-				fullResponse.FinishReason = ai.FinishReasonLength
-			case "content_filter":
-				fullResponse.FinishReason = ai.FinishReasonBlocked
-			case "function_call":
-				fullResponse.FinishReason = ai.FinishReasonOther
-			default:
-				fullResponse.FinishReason = ai.FinishReasonUnknown
-			}
+		acc.AddChunk(chunk)
 
-			// handle tool calls
-			for _, toolCall := range choice.Delta.ToolCalls {
-				// first tool call (= current tool call is nil) contains the tool call name
-				if currentToolCall != nil && toolCall.ID != "" && currentToolCall.Ref != toolCall.ID {
-					toolCallCollects = append(toolCallCollects, struct {
-						toolCall *ai.ToolRequest
-						args     string
-					}{
-						toolCall: currentToolCall,
-						args:     currentArguments,
-					})
-					currentToolCall = nil
-					currentArguments = ""
-				}
+		if len(chunk.Choices) == 0 {
+			continue
+		}
 
-				if currentToolCall == nil {
-					currentToolCall = &ai.ToolRequest{
-						Name: toolCall.Function.Name,
-						Ref:  toolCall.ID,
-					}
-				}
+		// Create chunk for callback
+		modelChunk := &ai.ModelResponseChunk{}
 
-				if toolCall.Function.Arguments != "" {
-					currentArguments += toolCall.Function.Arguments
-				}
+		// Handle content delta
+		if chunk.Choices[0].Delta.Content != "" {
+			modelChunk.Content = append(modelChunk.Content, ai.NewTextPart(chunk.Choices[0].Delta.Content))
+		}
 
+		// Handle tool call deltas
+		for _, toolCall := range chunk.Choices[0].Delta.ToolCalls {
+			// Send the incremental tool call part in the chunk
+			if toolCall.Function.Name != "" || toolCall.Function.Arguments != "" {
 				modelChunk.Content = append(modelChunk.Content, ai.NewToolRequestPart(&ai.ToolRequest{
-					Name:  currentToolCall.Name,
+					Name:  toolCall.Function.Name,
 					Input: toolCall.Function.Arguments,
-					Ref:   currentToolCall.Ref,
+					Ref:   toolCall.ID,
 				}))
 			}
+		}
 
-			// when tool call is complete
-			if choice.FinishReason == "tool_calls" && currentToolCall != nil {
-				// parse accumulated arguments string
-				for _, toolcall := range toolCallCollects {
-					args, err := jsonStringToMap(toolcall.args)
-					if err != nil {
-						return nil, fmt.Errorf("could not parse tool args: %w", err)
-					}
-					toolcall.toolCall.Input = args
-					fullResponse.Message.Content = append(fullResponse.Message.Content, ai.NewToolRequestPart(toolcall.toolCall))
-				}
-				if currentArguments != "" {
-					args, err := jsonStringToMap(currentArguments)
-					if err != nil {
-						return nil, fmt.Errorf("could not parse tool args: %w", err)
-					}
-					currentToolCall.Input = args
-				}
-				fullResponse.Message.Content = append(fullResponse.Message.Content, ai.NewToolRequestPart(currentToolCall))
-			}
-
-			content := chunk.Choices[0].Delta.Content
-			// when starting a tool call, the content is empty
-			if content != "" {
-				modelChunk.Content = append(modelChunk.Content, ai.NewTextPart(content))
-				fullResponse.Message.Content = append(fullResponse.Message.Content, modelChunk.Content...)
-			}
-
+		// Call the chunk handler with incremental data
+		if len(modelChunk.Content) > 0 {
 			if err := handleChunk(ctx, modelChunk); err != nil {
 				return nil, fmt.Errorf("callback error: %w", err)
 			}
-
-			fullResponse.Usage.InputTokens += int(chunk.Usage.PromptTokens)
-			fullResponse.Usage.OutputTokens += int(chunk.Usage.CompletionTokens)
-			fullResponse.Usage.TotalTokens += int(chunk.Usage.TotalTokens)
 		}
 	}
 
 	if err := stream.Err(); err != nil {
 		return nil, fmt.Errorf("stream error: %w", err)
 	}
 
-	return &fullResponse, nil
+	// Convert accumulated ChatCompletion to ai.ModelResponse
+	return convertChatCompletionToModelResponse(&acc.ChatCompletion)
 }
 
-// generateComplete generates a complete model response
-func (g *ModelGenerator) generateComplete(ctx context.Context, req *ai.ModelRequest) (*ai.ModelResponse, error) {
-	completion, err := g.client.Chat.Completions.New(ctx, *g.request)
-	if err != nil {
-		return nil, fmt.Errorf("failed to create completion: %w", err)
+// convertChatCompletionToModelResponse converts openai.ChatCompletion to ai.ModelResponse
+func convertChatCompletionToModelResponse(completion *openai.ChatCompletion) (*ai.ModelResponse, error) {
+	if len(completion.Choices) == 0 {
+		return nil, fmt.Errorf("no choices in completion")
+	}
+
+	choice := completion.Choices[0]
+
+	// Build usage information with detailed token breakdown
+	usage := &ai.GenerationUsage{
+		InputTokens:  int(completion.Usage.PromptTokens),
+		OutputTokens: int(completion.Usage.CompletionTokens),
+		TotalTokens:  int(completion.Usage.TotalTokens),
+	}
+
+	// Add reasoning tokens (thoughts tokens) if available
+	if completion.Usage.CompletionTokensDetails.ReasoningTokens > 0 {
+		usage.ThoughtsTokens = int(completion.Usage.CompletionTokensDetails.ReasoningTokens)
+	}
+
+	// Add cached tokens if available
+	if completion.Usage.PromptTokensDetails.CachedTokens > 0 {
+		usage.CachedContentTokens = int(completion.Usage.PromptTokensDetails.CachedTokens)
+	}
+
+	// Add audio tokens to custom field if available
+	if completion.Usage.CompletionTokensDetails.AudioTokens > 0 {
+		if usage.Custom == nil {
+			usage.Custom = make(map[string]float64)
+		}
+		usage.Custom["audioTokens"] = float64(completion.Usage.CompletionTokensDetails.AudioTokens)
+	}
+
+	// Add prediction tokens to custom field if available
+	if completion.Usage.CompletionTokensDetails.AcceptedPredictionTokens > 0 {
+		if usage.Custom == nil {
+			usage.Custom = make(map[string]float64)
+		}
+		usage.Custom["acceptedPredictionTokens"] = float64(completion.Usage.CompletionTokensDetails.AcceptedPredictionTokens)
+	}
+	if completion.Usage.CompletionTokensDetails.RejectedPredictionTokens > 0 {
+		if usage.Custom == nil {
+			usage.Custom = make(map[string]float64)
+		}
+		usage.Custom["rejectedPredictionTokens"] = float64(completion.Usage.CompletionTokensDetails.RejectedPredictionTokens)
 	}
 
 	resp := &ai.ModelResponse{
-		Request: req,
-		Usage: &ai.GenerationUsage{
-			InputTokens:  int(completion.Usage.PromptTokens),
-			OutputTokens: int(completion.Usage.CompletionTokens),
-			TotalTokens:  int(completion.Usage.TotalTokens),
-		},
+		Request: &ai.ModelRequest{},
+		Usage:   usage,
 		Message: &ai.Message{
-			Role: ai.RoleModel,
+			Role:    ai.RoleModel,
+			Content: make([]*ai.Part, 0),
 		},
 	}
 
-	choice := completion.Choices[0]
-
+	// Map finish reason
 	switch choice.FinishReason {
 	case "stop", "tool_calls":
 		resp.FinishReason = ai.FinishReasonStop
@@ -403,30 +368,57 @@ func (g *ModelGenerator) generateComplete(ctx context.Context, req *ai.ModelRequ
 		resp.FinishReason = ai.FinishReasonUnknown
 	}
 
-	// handle tool calls
-	var toolRequestParts []*ai.Part
+	// Set finish message if there's a refusal
+	if choice.Message.Refusal != "" {
+		resp.FinishMessage = choice.Message.Refusal
+		resp.FinishReason = ai.FinishReasonBlocked
+	}
+
+	// Add text content
+	if choice.Message.Content != "" {
+		resp.Message.Content = append(resp.Message.Content, ai.NewTextPart(choice.Message.Content))
+	}
+
+	// Add tool calls
 	for _, toolCall := range choice.Message.ToolCalls {
 		args, err := jsonStringToMap(toolCall.Function.Arguments)
 		if err != nil {
-			return nil, err
+			return nil, fmt.Errorf("could not parse tool args: %w", err)
 		}
-		toolRequestParts = append(toolRequestParts, ai.NewToolRequestPart(&ai.ToolRequest{
+		resp.Message.Content = append(resp.Message.Content, ai.NewToolRequestPart(&ai.ToolRequest{
 			Ref:   toolCall.ID,
 			Name:  toolCall.Function.Name,
 			Input: args,
 		}))
 	}
 
-	// content and tool call may exist simultaneously
-	if completion.Choices[0].Message.Content != "" {
-		resp.Message.Content = append(resp.Message.Content, ai.NewTextPart(completion.Choices[0].Message.Content))
+	// Store additional metadata in custom field if needed
+	if completion.SystemFingerprint != "" {
+		resp.Custom = map[string]any{
+			"systemFingerprint": completion.SystemFingerprint,
+			"model":             completion.Model,
+			"id":                completion.ID,
+		}
+	}
+
+	return resp, nil
+}
+
+// generateComplete generates a complete model response
+func (g *ModelGenerator) generateComplete(ctx context.Context, req *ai.ModelRequest) (*ai.ModelResponse, error) {
+	completion, err := g.client.Chat.Completions.New(ctx, *g.request)
+	if err != nil {
+		return nil, fmt.Errorf("failed to create completion: %w", err)
 	}
 
-	if len(toolRequestParts) > 0 {
-		resp.Message.Content = append(resp.Message.Content, toolRequestParts...)
-		return resp, nil
+	resp, err := convertChatCompletionToModelResponse(completion)
+	if err != nil {
+		return nil, err
 	}
 
+	// Set the original request
+	resp.Request = req
+
 	return resp, nil
 }