Migrate LLM client to OpenAI SDK and implement WebUI-specific fileID handling
This commit is contained in:
@@ -5,28 +5,83 @@ import (
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"context"
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"encoding/json"
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"fmt"
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"io"
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"mime/multipart"
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"net/http"
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"strings"
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"time"
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"laodingbot/internal/config"
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"laodingbot/internal/logger"
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openai "github.com/openai/openai-go" // imported as openai
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"github.com/openai/openai-go/option"
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"github.com/openai/openai-go/packages/param"
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"github.com/openai/openai-go/shared"
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)
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type Client interface {
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Generate(ctx context.Context, systemPrompt, userPrompt string) (string, error)
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}
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type PromptMessage struct {
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Role string `json:"role"`
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Content string `json:"content"`
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ToolCalls []ToolCall `json:"tool_calls,omitempty"`
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ToolCallID string `json:"tool_call_id,omitempty"`
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Name string `json:"name,omitempty"`
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}
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type MessageChatClient interface {
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GenerateMessages(ctx context.Context, messages []PromptMessage) (string, error)
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}
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type FileChatClient interface {
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GenerateWithFiles(ctx context.Context, systemPrompt, userPrompt string, fileIDs []string) (string, error)
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GenerateWithFiles(ctx context.Context, systemPrompt, userPrompt string, fileIDs []string, appendFileIDText bool) (string, error)
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}
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type FileMessageChatClient interface {
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GenerateMessagesWithFiles(ctx context.Context, messages []PromptMessage, fileIDs []string, appendFileIDText bool) (string, error)
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}
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type FileUploader interface {
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UploadFile(ctx context.Context, file InputFile, purpose string) (string, error)
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}
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// ToolCallChatClient 支持原生 function calling 的 LLM 客户端接口。
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type ToolCallChatClient interface {
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GenerateWithTools(ctx context.Context, messages []PromptMessage, tools []ToolDefinition, fileIDs []string, appendFileIDText bool) (*ChatCompletion, error)
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}
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// ToolDefinition 描述一个可供 LLM 调用的工具函数定义。
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type ToolDefinition struct {
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Type string `json:"type"`
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Function ToolFunctionDef `json:"function"`
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}
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// ToolFunctionDef 是工具函数的名称、描述和参数 JSON Schema。
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type ToolFunctionDef struct {
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Name string `json:"name"`
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Description string `json:"description"`
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Parameters json.RawMessage `json:"parameters,omitempty"`
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}
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// ToolCall 是 LLM 在响应中返回的工具调用请求。
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type ToolCall struct {
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ID string `json:"id"`
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Type string `json:"type"`
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Function ToolCallFunction `json:"function"`
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}
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// ToolCallFunction 包含工具调用的函数名和参数。
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type ToolCallFunction struct {
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Name string `json:"name"`
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Arguments string `json:"arguments"`
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}
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// ChatCompletion 是 LLM 响应的结构化表示，包含文本内容和可选的工具调用。
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type ChatCompletion struct {
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Content string
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ToolCalls []ToolCall
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}
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type InputFile struct {
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FileName string
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MimeType string
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@@ -34,206 +89,312 @@ type InputFile struct {
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}
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type OpenAICompatibleClient struct {
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baseURL string
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apiKey string
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client openai.Client
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model string
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fileModel string
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filePromptMode string
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http *http.Client
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log *logger.Logger
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}
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func NewOpenAICompatibleClient(cfg config.LLMConfig, log *logger.Logger) *OpenAICompatibleClient {
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opts := []option.RequestOption{
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option.WithAPIKey(cfg.APIKey),
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option.WithRequestTimeout(60 * time.Second),
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}
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if strings.TrimSpace(cfg.BaseURL) != "" {
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opts = append(opts, option.WithBaseURL(cfg.BaseURL))
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}
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return &OpenAICompatibleClient{
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baseURL: cfg.BaseURL,
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apiKey: cfg.APIKey,
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client: openai.NewClient(opts...),
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model: cfg.Model,
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fileModel: cfg.FileModel,
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filePromptMode: cfg.FilePromptMode,
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http: &http.Client{Timeout: 60 * time.Second},
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log: log,
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}
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}
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type chatRequest struct {
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Model string `json:"model"`
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Messages []chatMessage `json:"messages"`
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}
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type chatMessage struct {
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Role string `json:"role"`
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Content any `json:"content"`
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}
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type chatContentPart struct {
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Type string `json:"type"`
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Text string `json:"text,omitempty"`
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FileID string `json:"file_id,omitempty"`
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}
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type chatResponse struct {
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Choices []struct {
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Message struct {
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Role string `json:"role"`
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Content string `json:"content"`
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} `json:"message"`
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} `json:"choices"`
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Error *struct {
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Message string `json:"message"`
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} `json:"error,omitempty"`
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}
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type fileUploadResponse struct {
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ID string `json:"id"`
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Bytes int64 `json:"bytes,omitempty"`
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CreatedAt int64 `json:"created_at,omitempty"`
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Filename string `json:"filename,omitempty"`
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Object string `json:"object,omitempty"`
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Purpose string `json:"purpose,omitempty"`
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Code int `json:"code,omitempty"`
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Message string `json:"message,omitempty"`
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Status any `json:"status,omitempty"`
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StatusDetails any `json:"status_details,omitempty"`
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Data *struct {
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ID string `json:"id"`
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} `json:"data,omitempty"`
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Error *struct {
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Message string `json:"message"`
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} `json:"error,omitempty"`
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}
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func (c *OpenAICompatibleClient) Generate(ctx context.Context, systemPrompt, userPrompt string) (string, error) {
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return c.generateInternal(ctx, systemPrompt, userPrompt, nil)
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messages := []PromptMessage{
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{Role: "system", Content: systemPrompt},
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{Role: "user", Content: userPrompt},
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}
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return c.generateWithMessagesInternal(ctx, messages, nil, false)
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}
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func (c *OpenAICompatibleClient) GenerateWithFiles(ctx context.Context, systemPrompt, userPrompt string, fileIDs []string) (string, error) {
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return c.generateInternal(ctx, systemPrompt, userPrompt, fileIDs)
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func (c *OpenAICompatibleClient) GenerateWithFiles(ctx context.Context, systemPrompt, userPrompt string, fileIDs []string, appendFileIDText bool) (string, error) {
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messages := []PromptMessage{
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{Role: "system", Content: systemPrompt},
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{Role: "user", Content: userPrompt},
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}
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return c.generateWithMessagesInternal(ctx, messages, fileIDs, appendFileIDText)
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}
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func (c *OpenAICompatibleClient) generateInternal(ctx context.Context, systemPrompt, userPrompt string, fileIDs []string) (string, error) {
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func (c *OpenAICompatibleClient) GenerateMessages(ctx context.Context, messages []PromptMessage) (string, error) {
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return c.generateWithMessagesInternal(ctx, messages, nil, false)
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}
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func (c *OpenAICompatibleClient) GenerateMessagesWithFiles(ctx context.Context, messages []PromptMessage, fileIDs []string, appendFileIDText bool) (string, error) {
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return c.generateWithMessagesInternal(ctx, messages, fileIDs, appendFileIDText)
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}
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// GenerateWithTools 使用原生 function calling 发送请求，返回结构化的 ChatCompletion。
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func (c *OpenAICompatibleClient) GenerateWithTools(ctx context.Context, messages []PromptMessage, tools []ToolDefinition, fileIDs []string, appendFileIDText bool) (*ChatCompletion, error) {
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model := c.model
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ids := nonEmptyIDs(fileIDs)
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if len(ids) > 0 {
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if strings.TrimSpace(c.fileModel) != "" {
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model = c.fileModel
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}
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if len(ids) > 0 && strings.TrimSpace(c.fileModel) != "" {
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model = c.fileModel
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}
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sdkMessages := buildSDKMessages(messages, ids, c.normalizedFilePromptMode(), appendFileIDText)
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sdkTools := toSDKTools(tools)
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if c.log != nil {
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c.log.Debugf("llm request start model=%s system_len=%d user_len=%d file_count=%d file_prompt_mode=%s", model, len(systemPrompt), len(userPrompt), len(ids), c.normalizedFilePromptMode())
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c.log.Debugf("llm tool-call request start model=%s messages=%d tools=%d files=%d", model, len(sdkMessages), len(sdkTools), len(ids))
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}
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messages := buildMessages(systemPrompt, userPrompt, ids, c.normalizedFilePromptMode())
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body := chatRequest{
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Model: model,
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Messages: messages,
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params := openai.ChatCompletionNewParams{
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Model: shared.ChatModel(model),
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Messages: sdkMessages,
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}
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b, err := json.Marshal(body)
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if len(sdkTools) > 0 {
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params.Tools = sdkTools
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}
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if c.log != nil {
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if b, err := json.Marshal(params); err == nil {
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c.log.Debugf("llm tool-call request params: %s", string(b))
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}
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}
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resp, err := c.client.Chat.Completions.New(ctx, params)
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if err != nil {
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return nil, fmt.Errorf("llm tool-call request failed: %w", err)
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}
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if len(resp.Choices) == 0 {
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return nil, fmt.Errorf("llm returned empty choices")
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}
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choice := resp.Choices[0]
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resultToolCalls := fromSDKToolCalls(choice.Message.ToolCalls)
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if c.log != nil {
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c.log.Infof("llm tool-call response success model=%s content_len=%d tool_calls=%d finish=%s",
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model, len(choice.Message.Content), len(resultToolCalls), choice.FinishReason)
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}
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return &ChatCompletion{
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Content: choice.Message.Content,
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ToolCalls: resultToolCalls,
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}, nil
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}
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func (c *OpenAICompatibleClient) generateWithMessagesInternal(ctx context.Context, messages []PromptMessage, fileIDs []string, appendFileIDText bool) (string, error) {
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model := c.model
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ids := nonEmptyIDs(fileIDs)
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if len(ids) > 0 && strings.TrimSpace(c.fileModel) != "" {
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model = c.fileModel
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}
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baseMessages := normalizePromptMessages(messages)
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if len(baseMessages) == 0 {
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baseMessages = []PromptMessage{{Role: "user", Content: ""}}
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}
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systemLen, userLen := promptMessageLengths(baseMessages)
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if c.log != nil {
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c.log.Debugf("llm request start model=%s system_len=%d user_len=%d file_count=%d file_prompt_mode=%s", model, systemLen, userLen, len(ids), c.normalizedFilePromptMode())
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}
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sdkMessages := buildSDKMessages(baseMessages, ids, c.normalizedFilePromptMode(), appendFileIDText)
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params := openai.ChatCompletionNewParams{
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Model: shared.ChatModel(model),
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Messages: sdkMessages,
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}
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resp, err := c.client.Chat.Completions.New(ctx, params)
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if err != nil {
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if c.log != nil {
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c.log.Errorf("marshal llm request failed err=%v", err)
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c.log.Errorf("llm request failed err=%v", err)
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}
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return "", err
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return "", fmt.Errorf("llm request failed: %w", err)
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}
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url := strings.TrimRight(c.baseURL, "/") + "/chat/completions"
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req, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewReader(b))
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if err != nil {
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if len(resp.Choices) == 0 {
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if c.log != nil {
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c.log.Errorf("build llm request failed err=%v", err)
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}
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return "", err
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}
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req.Header.Set("Content-Type", "application/json")
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req.Header.Set("Authorization", "Bearer "+c.apiKey)
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resp, err := c.http.Do(req)
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if err != nil {
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if c.log != nil {
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c.log.Errorf("llm http request failed err=%v", err)
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}
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return "", err
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}
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defer resp.Body.Close()
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raw, err := io.ReadAll(resp.Body)
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if err != nil {
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if c.log != nil {
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c.log.Errorf("llm read response failed err=%v", err)
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}
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return "", err
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}
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var out chatResponse
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if err := json.Unmarshal(raw, &out); err != nil {
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if c.log != nil {
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c.log.Errorf("llm response unmarshal failed status=%d err=%v", resp.StatusCode, err)
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}
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return "", err
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}
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if resp.StatusCode < 200 || resp.StatusCode >= 300 {
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if c.log != nil {
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c.log.Errorf("llm bad status=%d", resp.StatusCode)
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}
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if out.Error != nil && out.Error.Message != "" {
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return "", fmt.Errorf("llm error: %s", out.Error.Message)
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}
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return "", fmt.Errorf("llm error status: %d", resp.StatusCode)
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}
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if len(out.Choices) == 0 {
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if c.log != nil {
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c.log.Errorf("llm returned empty choices status=%d", resp.StatusCode)
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c.log.Errorf("llm returned empty choices")
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}
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return "", fmt.Errorf("llm returned empty choices")
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}
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content := resp.Choices[0].Message.Content
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if c.log != nil {
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c.log.Infof("llm response success model=%s output_len=%d", model, len(out.Choices[0].Message.Content))
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c.log.Infof("llm response success model=%s output_len=%d", model, len(content))
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}
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return out.Choices[0].Message.Content, nil
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return content, nil
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}
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func buildMessages(systemPrompt, userPrompt string, fileIDs []string, mode string) []chatMessage {
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// buildSDKMessages 将 PromptMessage 列表转换为 openai SDK 的消息格式，并注入 file_id（如需要）。
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func buildSDKMessages(base []PromptMessage, fileIDs []string, mode string, appendFileIDText bool) []openai.ChatCompletionMessageParamUnion {
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mode = strings.ToLower(strings.TrimSpace(mode))
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if mode == "system_fileid_uri" {
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msgs := []chatMessage{{Role: "system", Content: systemPrompt}}
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for _, id := range fileIDs {
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if strings.TrimSpace(id) == "" {
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continue
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}
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msgs = append(msgs, chatMessage{Role: "system", Content: "fileid://" + strings.TrimSpace(id)})
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out := make([]openai.ChatCompletionMessageParamUnion, 0, len(base)+2)
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for _, m := range base {
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role := normalizeRole(m.Role)
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if role == "" {
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continue
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}
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msgs = append(msgs, chatMessage{Role: "user", Content: userPrompt})
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return msgs
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out = append(out, toSDKMessage(m, role))
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}
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userContent := buildUserContent(userPrompt, fileIDs)
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return []chatMessage{
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{Role: "system", Content: systemPrompt},
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{Role: "user", Content: userContent},
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if len(fileIDs) == 0 {
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return out
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}
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if appendFileIDText {
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// WebUI 场景：将首个 fileID 作为 text part 追加到最后一个 user 消息。
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firstFileID := strings.TrimSpace(fileIDs[0])
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if firstFileID == "" {
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return out
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}
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for i := len(out) - 1; i >= 0; i-- {
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if r := out[i].GetRole(); r != nil && *r == "user" {
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out[i] = buildUserMessageWithFileIDText(out[i], firstFileID)
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return out
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}
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}
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out = append(out, buildUserMessageWithFileIDText(openai.UserMessage(""), firstFileID))
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return out
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}
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// 非 WebUI 场景：保持原有 file content part 方式。
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for i := len(out) - 1; i >= 0; i-- {
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if r := out[i].GetRole(); r != nil && *r == "user" {
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out[i] = buildUserMessageWithFiles(out[i], fileIDs)
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return out
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}
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}
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out = append(out, buildUserMessageWithFiles(openai.UserMessage(""), fileIDs))
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return out
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}
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// toSDKMessage 将单个 PromptMessage 转换为 openai SDK 消息类型。
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func toSDKMessage(m PromptMessage, role string) openai.ChatCompletionMessageParamUnion {
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switch role {
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case "system":
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return openai.SystemMessage(m.Content)
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case "user":
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return openai.UserMessage(m.Content)
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case "assistant":
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if len(m.ToolCalls) > 0 {
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sdkToolCalls := make([]openai.ChatCompletionMessageToolCallParam, 0, len(m.ToolCalls))
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for _, tc := range m.ToolCalls {
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sdkToolCalls = append(sdkToolCalls, openai.ChatCompletionMessageToolCallParam{
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ID: tc.ID,
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Function: openai.ChatCompletionMessageToolCallFunctionParam{
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Name: tc.Function.Name,
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Arguments: tc.Function.Arguments,
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},
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})
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}
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msg := openai.AssistantMessage(m.Content)
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msg.OfAssistant.ToolCalls = sdkToolCalls
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return msg
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}
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return openai.AssistantMessage(m.Content)
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case "tool":
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return openai.ToolMessage(m.Content, m.ToolCallID)
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default:
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return openai.UserMessage(m.Content)
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}
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}
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func buildUserContent(userPrompt string, fileIDs []string) any {
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trimmedPrompt := strings.TrimSpace(userPrompt)
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if len(fileIDs) == 0 {
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return userPrompt
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// buildUserMessageWithFileIDText 为 user 消息追加一个 text part，内容为 fileID。
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func buildUserMessageWithFileIDText(msg openai.ChatCompletionMessageParamUnion, fileID string) openai.ChatCompletionMessageParamUnion {
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// 提取已有的文本内容
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text := ""
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if s, ok := msg.GetContent().AsAny().(*string); ok && s != nil {
|
||||
text = *s
|
||||
}
|
||||
fileID = strings.TrimSpace(fileID)
|
||||
if fileID == "" {
|
||||
return msg
|
||||
}
|
||||
|
||||
parts := make([]chatContentPart, 0, len(fileIDs)+1)
|
||||
if trimmedPrompt != "" {
|
||||
parts = append(parts, chatContentPart{Type: "text", Text: userPrompt})
|
||||
parts := make([]openai.ChatCompletionContentPartUnionParam, 0, 2)
|
||||
if strings.TrimSpace(text) != "" {
|
||||
parts = append(parts, openai.TextContentPart(text))
|
||||
}
|
||||
parts = append(parts, openai.TextContentPart(fileID))
|
||||
if len(parts) == 0 {
|
||||
return msg
|
||||
}
|
||||
return openai.UserMessage(parts)
|
||||
}
|
||||
|
||||
// buildUserMessageWithFiles 为 user 消息追加 file content parts。
|
||||
func buildUserMessageWithFiles(msg openai.ChatCompletionMessageParamUnion, fileIDs []string) openai.ChatCompletionMessageParamUnion {
|
||||
text := ""
|
||||
if s, ok := msg.GetContent().AsAny().(*string); ok && s != nil {
|
||||
text = *s
|
||||
}
|
||||
|
||||
parts := make([]openai.ChatCompletionContentPartUnionParam, 0, len(fileIDs)+1)
|
||||
if strings.TrimSpace(text) != "" {
|
||||
parts = append(parts, openai.TextContentPart(text))
|
||||
}
|
||||
for _, id := range fileIDs {
|
||||
id = strings.TrimSpace(id)
|
||||
if id == "" {
|
||||
continue
|
||||
}
|
||||
parts = append(parts, chatContentPart{Type: "file", FileID: id})
|
||||
parts = append(parts, openai.FileContentPart(openai.ChatCompletionContentPartFileFileParam{FileID: param.NewOpt(id)}))
|
||||
}
|
||||
if len(parts) == 0 {
|
||||
return userPrompt
|
||||
return msg
|
||||
}
|
||||
return parts
|
||||
return openai.UserMessage(parts)
|
||||
}
|
||||
|
||||
// toSDKTools 将内部 ToolDefinition 列表转换为 openai SDK 的 ChatCompletionToolParam 列表。
|
||||
func toSDKTools(tools []ToolDefinition) []openai.ChatCompletionToolParam {
|
||||
if len(tools) == 0 {
|
||||
return nil
|
||||
}
|
||||
out := make([]openai.ChatCompletionToolParam, 0, len(tools))
|
||||
for _, t := range tools {
|
||||
var params shared.FunctionParameters
|
||||
if len(t.Function.Parameters) > 0 {
|
||||
_ = json.Unmarshal(t.Function.Parameters, ¶ms)
|
||||
}
|
||||
out = append(out, openai.ChatCompletionToolParam{
|
||||
Function: shared.FunctionDefinitionParam{
|
||||
Name: t.Function.Name,
|
||||
Description: param.NewOpt(t.Function.Description),
|
||||
Parameters: params,
|
||||
},
|
||||
})
|
||||
}
|
||||
return out
|
||||
}
|
||||
|
||||
// fromSDKToolCalls 将 openai SDK 响应中的 tool calls 转换为内部 ToolCall 类型。
|
||||
func fromSDKToolCalls(sdkCalls []openai.ChatCompletionMessageToolCall) []ToolCall {
|
||||
if len(sdkCalls) == 0 {
|
||||
return nil
|
||||
}
|
||||
out := make([]ToolCall, 0, len(sdkCalls))
|
||||
for _, tc := range sdkCalls {
|
||||
out = append(out, ToolCall{
|
||||
ID: tc.ID,
|
||||
Type: "function",
|
||||
Function: ToolCallFunction{
|
||||
Name: tc.Function.Name,
|
||||
Arguments: tc.Function.Arguments,
|
||||
},
|
||||
})
|
||||
}
|
||||
return out
|
||||
}
|
||||
|
||||
func (c *OpenAICompatibleClient) UploadFile(ctx context.Context, file InputFile, purpose string) (string, error) {
|
||||
@@ -248,7 +409,6 @@ func (c *OpenAICompatibleClient) UploadFile(ctx context.Context, file InputFile,
|
||||
if purpose != "" {
|
||||
purposes = append(purposes, purpose)
|
||||
}
|
||||
// Provider compatibility fallback order.
|
||||
purposes = appendIfMissing(purposes, "file-extract")
|
||||
purposes = appendIfMissing(purposes, "batch")
|
||||
|
||||
@@ -270,77 +430,24 @@ func (c *OpenAICompatibleClient) UploadFile(ctx context.Context, file InputFile,
|
||||
}
|
||||
|
||||
func (c *OpenAICompatibleClient) uploadFileOnce(ctx context.Context, file InputFile, purpose string) (string, error) {
|
||||
|
||||
body := &bytes.Buffer{}
|
||||
writer := multipart.NewWriter(body)
|
||||
if err := writer.WriteField("purpose", purpose); err != nil {
|
||||
return "", err
|
||||
}
|
||||
part, err := writer.CreateFormFile("file", file.FileName)
|
||||
resp, err := c.client.Files.New(ctx, openai.FileNewParams{
|
||||
File: bytes.NewReader(file.Content),
|
||||
Purpose: openai.FilePurpose(purpose),
|
||||
})
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
if _, err := part.Write(file.Content); err != nil {
|
||||
return "", err
|
||||
}
|
||||
if err := writer.Close(); err != nil {
|
||||
return "", err
|
||||
return "", fmt.Errorf("llm file upload failed: %w", err)
|
||||
}
|
||||
|
||||
url := strings.TrimRight(c.baseURL, "/") + "/files"
|
||||
req, err := http.NewRequestWithContext(ctx, http.MethodPost, url, body)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
req.Header.Set("Content-Type", writer.FormDataContentType())
|
||||
req.Header.Set("Authorization", "Bearer "+c.apiKey)
|
||||
|
||||
resp, err := c.http.Do(req)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
raw, err := io.ReadAll(resp.Body)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
|
||||
var out fileUploadResponse
|
||||
if err := json.Unmarshal(raw, &out); err != nil {
|
||||
return "", fmt.Errorf("llm file upload response decode failed: %w body=%s", err, clipForError(raw))
|
||||
}
|
||||
if resp.StatusCode < 200 || resp.StatusCode >= 300 {
|
||||
if strings.TrimSpace(out.Message) != "" {
|
||||
return "", fmt.Errorf("llm file upload error: %s", out.Message)
|
||||
}
|
||||
if out.Error != nil && out.Error.Message != "" {
|
||||
return "", fmt.Errorf("llm file upload error: %s", out.Error.Message)
|
||||
}
|
||||
return "", fmt.Errorf("llm file upload status: %d body=%s", resp.StatusCode, clipForError(raw))
|
||||
}
|
||||
fileID := strings.TrimSpace(out.ID)
|
||||
if fileID == "" && out.Data != nil {
|
||||
fileID = strings.TrimSpace(out.Data.ID)
|
||||
}
|
||||
fileID := strings.TrimSpace(resp.ID)
|
||||
if fileID == "" {
|
||||
return "", fmt.Errorf("llm file upload returned empty file id body=%s", clipForError(raw))
|
||||
return "", fmt.Errorf("llm file upload returned empty file id")
|
||||
}
|
||||
if c.log != nil {
|
||||
c.log.Infof("llm file uploaded name=%s size=%d file_id=%s purpose=%s status=%v", file.FileName, len(file.Content), fileID, purpose, out.Status)
|
||||
c.log.Infof("llm file uploaded name=%s size=%d file_id=%s purpose=%s", file.FileName, len(file.Content), fileID, purpose)
|
||||
}
|
||||
return fileID, nil
|
||||
}
|
||||
|
||||
func clipForError(raw []byte) string {
|
||||
s := strings.TrimSpace(string(raw))
|
||||
const max = 400
|
||||
if len(s) <= max {
|
||||
return s
|
||||
}
|
||||
return s[:max] + "...(truncated)"
|
||||
}
|
||||
|
||||
func appendIfMissing(items []string, value string) []string {
|
||||
value = strings.TrimSpace(value)
|
||||
if value == "" {
|
||||
@@ -374,6 +481,46 @@ func nonEmptyIDs(ids []string) []string {
|
||||
return out
|
||||
}
|
||||
|
||||
func normalizePromptMessages(messages []PromptMessage) []PromptMessage {
|
||||
out := make([]PromptMessage, 0, len(messages))
|
||||
for _, m := range messages {
|
||||
role := normalizeRole(m.Role)
|
||||
if role == "" {
|
||||
continue
|
||||
}
|
||||
out = append(out, PromptMessage{
|
||||
Role: role,
|
||||
Content: m.Content,
|
||||
ToolCalls: m.ToolCalls,
|
||||
ToolCallID: m.ToolCallID,
|
||||
Name: m.Name,
|
||||
})
|
||||
}
|
||||
return out
|
||||
}
|
||||
|
||||
func normalizeRole(role string) string {
|
||||
r := strings.ToLower(strings.TrimSpace(role))
|
||||
if r != "system" && r != "user" && r != "assistant" && r != "tool" {
|
||||
return ""
|
||||
}
|
||||
return r
|
||||
}
|
||||
|
||||
func promptMessageLengths(messages []PromptMessage) (int, int) {
|
||||
systemLen := 0
|
||||
userLen := 0
|
||||
for _, m := range messages {
|
||||
switch normalizeRole(m.Role) {
|
||||
case "system":
|
||||
systemLen += len(m.Content)
|
||||
case "user":
|
||||
userLen += len(m.Content)
|
||||
}
|
||||
}
|
||||
return systemLen, userLen
|
||||
}
|
||||
|
||||
func (c *OpenAICompatibleClient) normalizedFilePromptMode() string {
|
||||
mode := strings.ToLower(strings.TrimSpace(c.filePromptMode))
|
||||
if mode == "system_fileid" || mode == "system_fileid_url" || mode == "system_fileid_uri" {
|
||||
|
||||
Reference in New Issue
Block a user