WeKnora deployment source with the reviewed wiki identity, summary and recovery fixes

internal/models/chat/openai_request.go

@@ -0,0 +1,242 @@
+package chat
+
+import (
+	"encoding/json"
+	"fmt"
+
+	"github.com/sashabaranov/go-openai"
+)
+
+// ConvertMessages 转换消息格式为 OpenAI 格式（导出供子类使用）
+func (c *RemoteAPIChat) ConvertMessages(messages []Message) []openai.ChatCompletionMessage {
+	openaiMessages := make([]openai.ChatCompletionMessage, 0, len(messages))
+	for _, msg := range messages {
+		openaiMsg := openai.ChatCompletionMessage{
+			Role: msg.Role,
+		}
+
+		// 优先处理多内容消息（包含图片等）
+		if len(msg.MultiContent) > 0 {
+			openaiMsg.MultiContent = make([]openai.ChatMessagePart, 0, len(msg.MultiContent))
+			for _, part := range msg.MultiContent {
+				switch part.Type {
+				case "text":
+					openaiMsg.MultiContent = append(openaiMsg.MultiContent, openai.ChatMessagePart{
+						Type: openai.ChatMessagePartTypeText,
+						Text: part.Text,
+					})
+				case "image_url":
+					if part.ImageURL != nil {
+						openaiMsg.MultiContent = append(openaiMsg.MultiContent, openai.ChatMessagePart{
+							Type: openai.ChatMessagePartTypeImageURL,
+							ImageURL: &openai.ChatMessageImageURL{
+								URL:    part.ImageURL.URL,
+								Detail: openai.ImageURLDetail(part.ImageURL.Detail),
+							},
+						})
+					}
+				}
+			}
+		} else if len(msg.Images) > 0 && msg.Role == "user" {
+			parts := make([]openai.ChatMessagePart, 0, len(msg.Images)+1)
+			for _, imgURL := range msg.Images {
+				resolved := resolveImageURLForLLM(imgURL)
+				parts = append(parts, openai.ChatMessagePart{
+					Type: openai.ChatMessagePartTypeImageURL,
+					ImageURL: &openai.ChatMessageImageURL{
+						URL:    resolved,
+						Detail: openai.ImageURLDetailAuto,
+					},
+				})
+			}
+			parts = append(parts, openai.ChatMessagePart{
+				Type: openai.ChatMessagePartTypeText,
+				Text: msg.Content,
+			})
+			openaiMsg.MultiContent = parts
+		} else if msg.Content != "" {
+			openaiMsg.Content = msg.Content
+		}
+
+		if len(msg.ToolCalls) > 0 {
+			openaiMsg.ToolCalls = make([]openai.ToolCall, 0, len(msg.ToolCalls))
+			for _, tc := range msg.ToolCalls {
+				toolType := openai.ToolType(tc.Type)
+				openaiMsg.ToolCalls = append(openaiMsg.ToolCalls, openai.ToolCall{
+					ID:   tc.ID,
+					Type: toolType,
+					Function: openai.FunctionCall{
+						Name:      tc.Function.Name,
+						Arguments: tc.Function.Arguments,
+					},
+				})
+			}
+		}
+
+		if msg.Role == "tool" {
+			openaiMsg.ToolCallID = msg.ToolCallID
+			openaiMsg.Name = msg.Name
+		}
+
+		// Round-trip reasoning_content on assistant turns. MiMo and DeepSeek V3.2+
+		// thinking mode reject multi-turn requests where the prior assistant
+		// message lacks its reasoning_content with HTTP 400 ("The reasoning_content
+		// in the thinking mode must be passed back to the API."). Providers that
+		// don't recognize the field ignore it harmlessly.
+		if msg.Role == "assistant" && msg.ReasoningContent != "" {
+			openaiMsg.ReasoningContent = msg.ReasoningContent
+		}
+
+		openaiMessages = append(openaiMessages, openaiMsg)
+	}
+	return openaiMessages
+}
+
+// BuildChatCompletionRequest 构建标准聊天请求参数（导出供子类使用）。
+//
+// 这是一个不含任何 provider 特定逻辑的通用实现：所有采样参数（temperature /
+// top_p / penalties）与 max_tokens 都按 opts 直接映射。供应商相关的特判
+// （OpenAI o-series / GPT-5 改用 max_completion_tokens、Moonshot 固定温度等）
+// 由对应的 providerAdapter.ShapeRequest 在事后施加，见 provider.go。
+func (c *RemoteAPIChat) BuildChatCompletionRequest(
+	messages []Message, opts *ChatOptions, isStream bool,
+) openai.ChatCompletionRequest {
+	req := openai.ChatCompletionRequest{
+		Model:    c.modelName,
+		Messages: c.ConvertMessages(messages),
+		Stream:   isStream,
+	}
+
+	if isStream {
+		req.StreamOptions = &openai.StreamOptions{IncludeUsage: true}
+	}
+
+	if opts == nil {
+		return req
+	}
+
+	req.Temperature = float32(opts.Temperature)
+	if opts.TopP > 0 {
+		req.TopP = float32(opts.TopP)
+	}
+	if opts.FrequencyPenalty > 0 {
+		req.FrequencyPenalty = float32(opts.FrequencyPenalty)
+	}
+	if opts.PresencePenalty > 0 {
+		req.PresencePenalty = float32(opts.PresencePenalty)
+	}
+
+	if opts.MaxTokens > 0 {
+		req.MaxTokens = opts.MaxTokens
+	}
+	if opts.MaxCompletionTokens > 0 {
+		req.MaxCompletionTokens = opts.MaxCompletionTokens
+	}
+
+	// 处理 Tools
+	if len(opts.Tools) > 0 {
+		req.Tools = make([]openai.Tool, 0, len(opts.Tools))
+		for _, tool := range opts.Tools {
+			toolType := openai.ToolType(tool.Type)
+			openaiTool := openai.Tool{
+				Type: toolType,
+				Function: &openai.FunctionDefinition{
+					Name:        tool.Function.Name,
+					Description: tool.Function.Description,
+				},
+			}
+			if tool.Function.Parameters != nil {
+				openaiTool.Function.Parameters = tool.Function.Parameters
+			}
+			req.Tools = append(req.Tools, openaiTool)
+		}
+	}
+
+	// 处理 ParallelToolCalls
+	if opts.ParallelToolCalls != nil {
+		val := *opts.ParallelToolCalls
+		req.ParallelToolCalls = val
+	}
+
+	// 处理 ToolChoice（标准实现）
+	if opts.ToolChoice != "" {
+		switch opts.ToolChoice {
+		case "none", "required", "auto":
+			req.ToolChoice = opts.ToolChoice
+		default:
+			req.ToolChoice = openai.ToolChoice{
+				Type: "function",
+				Function: openai.ToolFunction{
+					Name: opts.ToolChoice,
+				},
+			}
+		}
+	}
+
+	if len(opts.Format) > 0 {
+		req.ResponseFormat = &openai.ChatCompletionResponseFormat{
+			Type: openai.ChatCompletionResponseFormatTypeJSONObject,
+		}
+		req.Messages[len(req.Messages)-1].Content += fmt.Sprintf("\nUse this JSON schema: %s", opts.Format)
+	}
+
+	return req
+}
+
+func (c *RemoteAPIChat) buildProviderOpenAIRequest(
+	body any,
+	openAIMessages []openai.ChatCompletionMessage,
+	messages []Message,
+) (map[string]any, error) {
+	data, err := json.Marshal(body)
+	if err != nil {
+		return nil, fmt.Errorf("marshal provider request: %w", err)
+	}
+
+	var out map[string]any
+	if err := json.Unmarshal(data, &out); err != nil {
+		return nil, fmt.Errorf("unmarshal provider request: %w", err)
+	}
+
+	providerMessages := make([]map[string]any, 0, len(openAIMessages))
+	for i, msg := range openAIMessages {
+		msgData, err := json.Marshal(msg)
+		if err != nil {
+			return nil, fmt.Errorf("marshal provider message: %w", err)
+		}
+		var msgMap map[string]any
+		if err := json.Unmarshal(msgData, &msgMap); err != nil {
+			return nil, fmt.Errorf("unmarshal provider message: %w", err)
+		}
+
+		if i < len(messages) && len(messages[i].ToolCalls) > 0 && len(msg.ToolCalls) > 0 {
+			toolCalls := make([]map[string]any, 0, len(msg.ToolCalls))
+			for j, tc := range msg.ToolCalls {
+				tcData, err := json.Marshal(tc)
+				if err != nil {
+					return nil, fmt.Errorf("marshal provider tool call: %w", err)
+				}
+				var tcMap map[string]any
+				if err := json.Unmarshal(tcData, &tcMap); err != nil {
+					return nil, fmt.Errorf("unmarshal provider tool call: %w", err)
+				}
+				if j < len(messages[i].ToolCalls) {
+					c.adapter.InjectToolCallMetadata(tcMap, messages[i].ToolCalls[j].ProviderMetadata)
+				}
+				toolCalls = append(toolCalls, tcMap)
+			}
+			msgMap["tool_calls"] = toolCalls
+		}
+
+		providerMessages = append(providerMessages, msgMap)
+	}
+	out["messages"] = providerMessages
+	return out, nil
+}
+
+func (c *RemoteAPIChat) shapeProviderRequest(body any, req openai.ChatCompletionRequest, messages []Message) (any, error) {
+	if !c.adapter.ForceRawHTTP() {
+		return body, nil
+	}
+	return c.buildProviderOpenAIRequest(body, req.Messages, messages)
+}