ai调试ok
This commit is contained in:
@@ -24,6 +24,7 @@ type Tool interface {
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type ChatMessage struct {
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Role string `json:"role"`
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Content string `json:"content"`
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ImageURL string `json:"image_url,omitempty"`
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}
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var registry []Tool
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@@ -4,10 +4,13 @@ import (
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"bufio"
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"bytes"
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"context"
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"encoding/base64"
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"encoding/json"
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"errors"
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"fmt"
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"io"
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"net/http"
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"net/url"
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"ops/agents"
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"ops/models"
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"strings"
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@@ -32,7 +35,21 @@ type sseEvent struct {
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type tokenUsageStats struct {
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PromptTokens int `json:"prompt_tokens"`
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CompletionTokens int `json:"completion_tokens"`
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ToolPromptTokens int `json:"tool_prompt_tokens"`
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ToolCompletionTokens int `json:"tool_completion_tokens"`
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TotalTokens int `json:"total_tokens"`
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CompletionTokensPerSec float64 `json:"completion_tokens_per_sec"`
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PeakCompletionTokensPerSec float64 `json:"peak_completion_tokens_per_sec"`
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Estimated bool `json:"estimated"`
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}
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const maxImageDataSize = 4 * 1024 * 1024
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var allowedImageTypes = map[string]bool{
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"image/jpeg": true,
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"image/png": true,
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"image/webp": true,
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"image/gif": true,
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}
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// chatRequestFromFrontend is the expected POST body
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@@ -44,6 +61,8 @@ type chatRequest struct {
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type chatMessage struct {
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Role string `json:"role"`
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Content string `json:"content"`
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ImageURL string `json:"image_url,omitempty"`
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ImageURLAlias string `json:"imageURL,omitempty"`
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}
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// openaiChatRequest is the request sent to the upstream OpenAI-compatible API
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@@ -56,6 +75,22 @@ type openaiChatRequest struct {
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}
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type openaiMessage 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 openaiContentPart struct {
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Type string `json:"type"`
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Text string `json:"text,omitempty"`
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ImageURL *openaiImageURL `json:"image_url,omitempty"`
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}
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type openaiImageURL struct {
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URL string `json:"url"`
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Detail string `json:"detail,omitempty"`
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}
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type openaiResponseMessage struct {
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Role string `json:"role"`
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Content string `json:"content"`
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}
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@@ -76,17 +111,27 @@ type openaiChatResponse struct {
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}
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type openaiResponseChoice struct {
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Message openaiMessage `json:"message"`
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Message openaiResponseMessage `json:"message"`
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}
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type toolRouteResponse struct {
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Tools []struct {
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type toolSelection struct {
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Name string `json:"name"`
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Reason string `json:"reason"`
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} `json:"tools"`
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}
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type toolRoutingDecision struct {
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Tools []toolSelection `json:"tools"`
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Reason string `json:"reason"`
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}
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type toolRoutingResult struct {
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Decision toolRoutingDecision
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Selected []string
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Messages []openaiMessage
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Response string
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Usage *openaiUsage
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}
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type openaiChoice struct {
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Index int `json:"index"`
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Delta openaiDelta `json:"delta"`
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@@ -96,6 +141,9 @@ type openaiChoice struct {
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type openaiDelta struct {
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Role string `json:"role,omitempty"`
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Content string `json:"content,omitempty"`
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ReasoningContent string `json:"reasoning_content,omitempty"`
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Reasoning string `json:"reasoning,omitempty"`
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Thinking string `json:"thinking,omitempty"`
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}
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type openaiUsage struct {
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@@ -171,41 +219,60 @@ func handleChat(ctx *gin.Context) {
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return
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}
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toolRouterProfile, hasToolRouterProfile := selectOpenAIProfile(cfg, cfg.ToolRouter.OpenAIName)
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// Convert to agent messages and enrich with tools
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chatMsgs := convertToChatMessages(req.Messages)
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// Set up SSE headers before routing/tools so progress can stream immediately.
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ctx.Writer.Header().Set("Content-Type", "text/event-stream")
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ctx.Writer.Header().Set("Cache-Control", "no-cache")
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ctx.Writer.Header().Set("Connection", "keep-alive")
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ctx.Writer.Header().Set("X-Accel-Buffering", "no")
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ctx.Writer.WriteHeader(http.StatusOK)
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flusher, _ := ctx.Writer.(http.Flusher)
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tracker := newTokenUsageTracker()
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emitTrace := func(tool, stage, status, message string, data map[string]interface{}) {
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sendSSE(ctx, flusher, sseEvent{Type: "trace", Tool: tool, Stage: stage, Status: status, Message: message, Data: data})
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}
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emitStats := func(stats tokenUsageStats) {
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sendSSE(ctx, flusher, sseEvent{Type: "stats", Stats: &stats})
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}
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toolConfigs := []agents.ToolConfig{}
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if cfg.ToolRouter.Enabled {
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toolConfigs = buildToolConfigs(cfg.ToolRouter.Tools)
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if hasToolRouterProfile && toolRouterProfile.Model != "" && toolRouterProfile.ApiKey != "" {
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selected, err := routeTools(ctx.Request.Context(), toolRouterProfile, cfg.ToolRouter, chatMsgs)
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if err == nil && selected != nil {
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toolConfigs = filterToolConfigs(toolConfigs, selected)
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emitTrace("tool_router", "route", "running", "正在进行工具路由", nil)
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routeResult, routeErr := routeTools(ctx.Request.Context(), toolRouterProfile, cfg.ToolRouter, chatMsgs)
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if routeErr != nil {
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emitTrace("tool_router", "route", "error", "工具路由失败，将继续普通回答", map[string]interface{}{"error": routeErr.Error()})
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toolConfigs = []agents.ToolConfig{}
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} else if routeResult != nil {
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tracker.addToolUsage(routeResult.Usage, estimateOpenAIMessagesTokens(routeResult.Messages), estimateTokenCount(routeResult.Response))
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data := map[string]interface{}{
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"tools": routeResult.Selected,
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"selections": routeResult.Decision.Tools,
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"reason": routeResult.Decision.Reason,
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}
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message := "工具路由结果：无需调用工具"
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if len(routeResult.Selected) > 0 {
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message = "工具路由结果：将调用 " + strings.Join(routeResult.Selected, ", ")
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}
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emitTrace("tool_router", "route", "success", message, data)
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toolConfigs = filterToolConfigs(toolConfigs, routeResult.Selected)
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}
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}
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}
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// Set up SSE headers
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ctx.Writer.Header().Set("Content-Type", "text/event-stream")
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ctx.Writer.Header().Set("Cache-Control", "no-cache")
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ctx.Writer.Header().Set("Connection", "keep-alive")
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ctx.Writer.WriteHeader(http.StatusOK)
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flusher, _ := ctx.Writer.(http.Flusher)
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// Enrich messages with tools (pre-process)
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chatMsgs = agents.EnrichMessages(ctx.Request.Context(), chatMsgs, toolConfigs, func(tool, stage, status, message string, data map[string]interface{}) {
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sendSSE(ctx, flusher, sseEvent{
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Type: "trace",
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Tool: tool,
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Stage: stage,
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Status: status,
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Message: message,
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Data: data,
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})
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})
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chatMsgs = agents.EnrichMessages(ctx.Request.Context(), chatMsgs, toolConfigs, emitTrace)
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// Build OpenAI-compatible request
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openaiMsgs := convertToOpenAIMessages(chatMsgs)
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openaiMsgs, err := convertToOpenAIMessages(chatMsgs)
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if err != nil {
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sendSSE(ctx, flusher, sseEvent{Type: "error", Error: err.Error()})
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sendSSEDone(ctx, flusher)
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return
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}
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apiReq := openaiChatRequest{
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Model: profile.Model,
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Messages: openaiMsgs,
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@@ -219,24 +286,48 @@ func handleChat(ctx *gin.Context) {
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apiReq.Messages = append([]openaiMessage{{Role: "system", Content: profile.SystemPrompt}}, apiReq.Messages...)
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}
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err := streamOpenAI(ctx.Request.Context(), profile, apiReq, func(chunk openaiStreamChunk) {
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modelPromptTokens := estimateOpenAIMessagesTokens(apiReq.Messages)
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completionTokens := 0
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modelUsageReceived := false
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streamStarted := time.Now()
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windowStarted := streamStarted
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windowTokens := 0
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peakTokensPerSecond := 0.0
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emitTrace("model", "stream", "running", "正在请求模型回复", nil)
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err = streamOpenAI(ctx.Request.Context(), profile, apiReq, func(chunk openaiStreamChunk) {
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for _, choice := range chunk.Choices {
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reasoningText := choice.Delta.ReasoningContent
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if reasoningText == "" {
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reasoningText = choice.Delta.Reasoning
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}
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if reasoningText == "" {
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reasoningText = choice.Delta.Thinking
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}
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if reasoningText != "" {
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sendSSE(ctx, flusher, sseEvent{Type: "reasoning", Text: reasoningText})
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}
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if choice.Delta.Content != "" {
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sendSSE(ctx, flusher, sseEvent{
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Type: "delta",
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Text: choice.Delta.Content,
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})
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deltaTokens := estimateTokenCount(choice.Delta.Content)
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completionTokens += deltaTokens
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windowTokens += deltaTokens
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elapsedWindow := time.Since(windowStarted).Seconds()
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if elapsedWindow >= 1 {
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peakTokensPerSecond = maxFloat(peakTokensPerSecond, float64(windowTokens)/elapsedWindow)
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windowStarted = time.Now()
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windowTokens = 0
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} else if peakTokensPerSecond == 0 && elapsedWindow > 0.25 {
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peakTokensPerSecond = maxFloat(peakTokensPerSecond, float64(windowTokens)/elapsedWindow)
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}
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stats := tracker.setModelEstimate(modelPromptTokens, completionTokens).snapshot(tokensPerSecond(completionTokens, streamStarted), peakTokensPerSecond)
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sendSSE(ctx, flusher, sseEvent{Type: "delta", Text: choice.Delta.Content, Stats: &stats})
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}
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}
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if chunk.Usage != nil {
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sendSSE(ctx, flusher, sseEvent{
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Type: "stats",
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Stats: &tokenUsageStats{
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PromptTokens: chunk.Usage.PromptTokens,
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CompletionTokens: chunk.Usage.CompletionTokens,
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TotalTokens: chunk.Usage.TotalTokens,
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},
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})
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modelUsageReceived = true
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stats := tracker.setModelUsage(chunk.Usage).snapshot(tokensPerSecond(tracker.completionTokens, streamStarted), peakTokensPerSecond)
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emitStats(stats)
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}
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})
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if err != nil {
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@@ -245,6 +336,18 @@ func handleChat(ctx *gin.Context) {
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return
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}
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if windowTokens > 0 {
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elapsedWindow := time.Since(windowStarted).Seconds()
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if elapsedWindow > 0 {
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peakTokensPerSecond = maxFloat(peakTokensPerSecond, float64(windowTokens)/elapsedWindow)
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}
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}
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emitTrace("model", "stream", "success", "模型回复完成", nil)
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if modelUsageReceived {
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emitStats(tracker.snapshot(tokensPerSecond(tracker.completionTokens, streamStarted), peakTokensPerSecond))
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} else {
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emitStats(tracker.setModelEstimate(modelPromptTokens, completionTokens).snapshot(tokensPerSecond(completionTokens, streamStarted), peakTokensPerSecond))
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}
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sendSSEDone(ctx, flusher)
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flusher.Flush()
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}
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@@ -345,17 +448,251 @@ func sendSSEError(ctx *gin.Context, message string) {
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func convertToChatMessages(msgs []chatMessage) []agents.ChatMessage {
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result := make([]agents.ChatMessage, 0, len(msgs))
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for _, m := range msgs {
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result = append(result, agents.ChatMessage{Role: m.Role, Content: m.Content})
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imageURL := m.ImageURL
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if imageURL == "" {
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imageURL = m.ImageURLAlias
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}
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result = append(result, agents.ChatMessage{Role: m.Role, Content: m.Content, ImageURL: imageURL})
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}
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return result
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}
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func convertToOpenAIMessages(msgs []agents.ChatMessage) []openaiMessage {
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func convertToOpenAIMessages(msgs []agents.ChatMessage) ([]openaiMessage, error) {
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result := make([]openaiMessage, 0, len(msgs))
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for _, m := range msgs {
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result = append(result, openaiMessage{Role: m.Role, Content: m.Content})
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content, err := buildOpenAIContent(m)
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if err != nil {
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return nil, err
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}
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return result
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result = append(result, openaiMessage{Role: m.Role, Content: content})
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}
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return result, nil
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}
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func buildOpenAIContent(m agents.ChatMessage) (any, error) {
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if strings.TrimSpace(m.ImageURL) == "" {
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return m.Content, nil
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}
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imageURL, err := normalizeImageURL(m.ImageURL)
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if err != nil {
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return nil, err
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}
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parts := []openaiContentPart{
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{
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Type: "image_url",
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ImageURL: &openaiImageURL{
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URL: imageURL,
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Detail: "auto",
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},
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},
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}
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if m.Content != "" {
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parts = append(parts, openaiContentPart{Type: "text", Text: m.Content})
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}
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return parts, nil
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}
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func normalizeImageURL(raw string) (string, error) {
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value := strings.TrimSpace(raw)
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if value == "" {
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return "", errors.New("图片地址为空")
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}
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if strings.HasPrefix(strings.ToLower(value), "data:") {
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return normalizeImageDataURI(value)
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}
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parsed, err := url.Parse(value)
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if err != nil || parsed.Host == "" || (parsed.Scheme != "http" && parsed.Scheme != "https") {
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return "", errors.New("图片地址无效，仅支持 http/https URL 或 base64 data URI")
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}
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return value, nil
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}
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func normalizeImageDataURI(raw string) (string, error) {
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commaIndex := strings.Index(raw, ",")
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if commaIndex == -1 {
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return "", errors.New("图片 data URI 格式无效")
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}
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metadata := strings.TrimSpace(raw[len("data:"):commaIndex])
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payload := strings.TrimSpace(raw[commaIndex+1:])
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if metadata == "" || payload == "" {
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return "", errors.New("图片 data URI 格式无效")
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}
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metadataParts := strings.Split(metadata, ";")
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mimeType := strings.ToLower(strings.TrimSpace(metadataParts[0]))
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if !allowedImageTypes[mimeType] {
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return "", errors.New("图片格式不支持，仅支持 jpeg/png/webp/gif")
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}
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hasBase64 := false
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for _, part := range metadataParts[1:] {
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if strings.EqualFold(strings.TrimSpace(part), "base64") {
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hasBase64 = true
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break
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}
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}
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if !hasBase64 {
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return "", errors.New("图片 data URI 必须使用 base64 编码")
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}
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if len(payload) > maxImageDataSize*4/3+16 {
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return "", errors.New("图片过大，请选择小于 4MB 的图片")
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}
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decoded, err := base64.StdEncoding.DecodeString(payload)
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if err != nil {
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return "", errors.New("图片 base64 数据无效")
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}
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if len(decoded) > maxImageDataSize {
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return "", errors.New("图片过大，请选择小于 4MB 的图片")
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}
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return "data:" + mimeType + ";base64," + payload, nil
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}
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type tokenUsageTracker struct {
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promptTokens int
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completionTokens int
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toolPromptTokens int
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toolCompletionTokens int
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estimated bool
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}
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func newTokenUsageTracker() *tokenUsageTracker {
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return &tokenUsageTracker{estimated: true}
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}
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func (t *tokenUsageTracker) addToolUsage(usage *openaiUsage, estimatedPromptTokens, estimatedCompletionTokens int) {
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if usage != nil {
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t.toolPromptTokens += usage.PromptTokens
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t.toolCompletionTokens += usage.CompletionTokens
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return
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}
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t.toolPromptTokens += estimatedPromptTokens
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t.toolCompletionTokens += estimatedCompletionTokens
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t.estimated = true
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}
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func (t *tokenUsageTracker) setModelEstimate(promptTokens, completionTokens int) *tokenUsageTracker {
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t.promptTokens = promptTokens
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t.completionTokens = completionTokens
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t.estimated = true
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return t
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}
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func (t *tokenUsageTracker) setModelUsage(usage *openaiUsage) *tokenUsageTracker {
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if usage == nil {
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return t
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}
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t.promptTokens = usage.PromptTokens
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t.completionTokens = usage.CompletionTokens
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return t
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}
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func (t *tokenUsageTracker) snapshot(completionTokensPerSec, peakCompletionTokensPerSec float64) tokenUsageStats {
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totalTokens := t.promptTokens + t.completionTokens + t.toolPromptTokens + t.toolCompletionTokens
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return tokenUsageStats{
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PromptTokens: t.promptTokens,
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CompletionTokens: t.completionTokens,
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ToolPromptTokens: t.toolPromptTokens,
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ToolCompletionTokens: t.toolCompletionTokens,
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TotalTokens: totalTokens,
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CompletionTokensPerSec: completionTokensPerSec,
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PeakCompletionTokensPerSec: peakCompletionTokensPerSec,
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Estimated: t.estimated,
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}
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}
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func estimateOpenAIMessagesTokens(messages []openaiMessage) int {
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total := 0
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for _, message := range messages {
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total += estimateTokenCount(message.Role) + 4
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total += estimateOpenAIContentTokens(message.Content)
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}
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return total
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}
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func estimateOpenAIContentTokens(content any) int {
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switch value := content.(type) {
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case string:
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return estimateTokenCount(value)
|
||||
case []openaiContentPart:
|
||||
total := 0
|
||||
for _, part := range value {
|
||||
switch part.Type {
|
||||
case "text":
|
||||
total += estimateTokenCount(part.Text)
|
||||
case "image_url":
|
||||
total += 85
|
||||
}
|
||||
}
|
||||
return total
|
||||
case []interface{}:
|
||||
data, err := json.Marshal(value)
|
||||
if err != nil {
|
||||
return 0
|
||||
}
|
||||
return estimateTokenCount(string(data))
|
||||
default:
|
||||
data, err := json.Marshal(value)
|
||||
if err != nil {
|
||||
return 0
|
||||
}
|
||||
return estimateTokenCount(string(data))
|
||||
}
|
||||
}
|
||||
|
||||
func estimateTokenCount(text string) int {
|
||||
text = strings.TrimSpace(text)
|
||||
if text == "" {
|
||||
return 0
|
||||
}
|
||||
|
||||
tokens := 0
|
||||
asciiRunes := 0
|
||||
flushASCII := func() {
|
||||
if asciiRunes > 0 {
|
||||
tokens += (asciiRunes + 3) / 4
|
||||
asciiRunes = 0
|
||||
}
|
||||
}
|
||||
|
||||
for _, r := range text {
|
||||
if r <= 127 {
|
||||
if r == ' ' || r == '\n' || r == '\t' || r == '\r' {
|
||||
flushASCII()
|
||||
continue
|
||||
}
|
||||
asciiRunes++
|
||||
continue
|
||||
}
|
||||
flushASCII()
|
||||
tokens++
|
||||
}
|
||||
flushASCII()
|
||||
if tokens == 0 {
|
||||
return 1
|
||||
}
|
||||
return tokens
|
||||
}
|
||||
|
||||
func tokensPerSecond(tokens int, start time.Time) float64 {
|
||||
elapsed := time.Since(start).Seconds()
|
||||
if tokens <= 0 || elapsed <= 0 {
|
||||
return 0
|
||||
}
|
||||
return float64(tokens) / elapsed
|
||||
}
|
||||
|
||||
func maxFloat(a, b float64) float64 {
|
||||
if b > a {
|
||||
return b
|
||||
}
|
||||
return a
|
||||
}
|
||||
|
||||
func buildToolConfigs(configs []models.ConfigsAIChatTool_) []agents.ToolConfig {
|
||||
@@ -390,13 +727,14 @@ func selectOpenAIProfile(cfg models.ConfigsAIChat_, name string) (models.Configs
|
||||
return models.ConfigsAIChatOpenAI_{}, false
|
||||
}
|
||||
|
||||
func routeTools(ctx context.Context, profile models.ConfigsAIChatOpenAI_, router models.ConfigsAIChatToolRouter_, messages []agents.ChatMessage) ([]string, error) {
|
||||
openaiMsgs := []openaiMessage{}
|
||||
lastUserContent := agents.LastUserContent(messages)
|
||||
if lastUserContent != "" {
|
||||
openaiMsgs = append(openaiMsgs, openaiMessage{Role: "user", Content: lastUserContent})
|
||||
func routeTools(ctx context.Context, profile models.ConfigsAIChatOpenAI_, router models.ConfigsAIChatToolRouter_, messages []agents.ChatMessage) (*toolRoutingResult, error) {
|
||||
lastUserContent := strings.TrimSpace(agents.LastUserContent(messages))
|
||||
if lastUserContent == "" {
|
||||
return nil, nil
|
||||
}
|
||||
|
||||
openaiMsgs := []openaiMessage{{Role: "user", Content: lastUserContent}}
|
||||
|
||||
toolNames := make([]string, 0, len(router.Tools))
|
||||
for _, t := range router.Tools {
|
||||
if t.Enabled {
|
||||
@@ -418,7 +756,10 @@ func routeTools(ctx context.Context, profile models.ConfigsAIChatOpenAI_, router
|
||||
Temperature: 0.1,
|
||||
}
|
||||
|
||||
bodyBytes, _ := json.Marshal(req)
|
||||
bodyBytes, err := json.Marshal(req)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
url := strings.TrimRight(profile.BaseUrl, "/") + "/chat/completions"
|
||||
httpReq, err := http.NewRequestWithContext(ctx, http.MethodPost, url, bytes.NewReader(bodyBytes))
|
||||
if err != nil {
|
||||
@@ -433,34 +774,42 @@ func routeTools(ctx context.Context, profile models.ConfigsAIChatOpenAI_, router
|
||||
}
|
||||
defer resp.Body.Close()
|
||||
|
||||
if resp.StatusCode != http.StatusOK {
|
||||
body, _ := io.ReadAll(resp.Body)
|
||||
return nil, fmt.Errorf("工具路由返回 %d: %s", resp.StatusCode, string(body))
|
||||
}
|
||||
|
||||
var result openaiChatResponse
|
||||
if err := json.NewDecoder(resp.Body).Decode(&result); err != nil {
|
||||
return nil, err
|
||||
}
|
||||
if len(result.Choices) == 0 {
|
||||
return nil, nil
|
||||
return &toolRoutingResult{Messages: openaiMsgs, Usage: result.Usage}, nil
|
||||
}
|
||||
|
||||
response := result.Choices[0].Message.Content
|
||||
toolRouteResponse := extractToolsFromResponse(response)
|
||||
return toolRouteResponse, nil
|
||||
decision := extractToolRoutingDecision(response)
|
||||
selected := make([]string, 0, len(decision.Tools))
|
||||
for _, t := range decision.Tools {
|
||||
name := strings.TrimSpace(t.Name)
|
||||
if name != "" {
|
||||
selected = append(selected, name)
|
||||
}
|
||||
}
|
||||
return &toolRoutingResult{Decision: decision, Selected: selected, Messages: openaiMsgs, Response: response, Usage: result.Usage}, nil
|
||||
}
|
||||
|
||||
func extractToolsFromResponse(response string) []string {
|
||||
func extractToolRoutingDecision(response string) toolRoutingDecision {
|
||||
start := strings.Index(response, "{")
|
||||
end := strings.LastIndex(response, "}")
|
||||
if start == -1 || end == -1 || end <= start {
|
||||
return nil
|
||||
return toolRoutingDecision{}
|
||||
}
|
||||
var parsed toolRouteResponse
|
||||
var parsed toolRoutingDecision
|
||||
if err := json.Unmarshal([]byte(response[start:end+1]), &parsed); err != nil {
|
||||
return nil
|
||||
return toolRoutingDecision{}
|
||||
}
|
||||
tools := make([]string, 0, len(parsed.Tools))
|
||||
for _, t := range parsed.Tools {
|
||||
tools = append(tools, t.Name)
|
||||
}
|
||||
return tools
|
||||
return parsed
|
||||
}
|
||||
|
||||
func filterToolConfigs(configs []agents.ToolConfig, selected []string) []agents.ToolConfig {
|
||||
|
||||
@@ -81,6 +81,10 @@ export async function streamChat(messages, options = {}, handlers = {}) {
|
||||
switch (frame.type) {
|
||||
case 'delta':
|
||||
handlers.onDelta?.(frame.text || '')
|
||||
if (frame.stats) handlers.onStats?.(frame.stats)
|
||||
break
|
||||
case 'reasoning':
|
||||
handlers.onReasoning?.(frame.text || '', frame)
|
||||
break
|
||||
case 'trace':
|
||||
handlers.onTrace?.(frame)
|
||||
|
||||
@@ -54,7 +54,29 @@
|
||||
"default_profile": "Default profile",
|
||||
"tool_router": "Tool router",
|
||||
"enter_hint": "Enter to send, Shift + Enter for a new line",
|
||||
"error_prefix": "Request failed: "
|
||||
"error_prefix": "Request failed: ",
|
||||
"attach_image": "Attach image",
|
||||
"remove_image": "Remove image",
|
||||
"image_type_error": "Unsupported image type. Supported formats: jpeg/png/webp/gif",
|
||||
"image_size_error": "Image is too large. Please choose an image smaller than 4 MB",
|
||||
"image_read_error": "Failed to read image. Please try another file",
|
||||
"reasoning": "Reasoning",
|
||||
"trace_details": "Call details",
|
||||
"trace_database": "Database",
|
||||
"trace_rows": "Rows",
|
||||
"trace_columns": "Columns",
|
||||
"trace_count": "Count",
|
||||
"trace_tools": "Tools",
|
||||
"trace_reason": "Reason",
|
||||
"trace_error": "Error",
|
||||
"trace_truncated": "Result truncated",
|
||||
"tokens_avg_speed": "Average speed",
|
||||
"tokens_peak_speed": "Peak speed",
|
||||
"tokens_total": "Total tokens",
|
||||
"tokens_prompt": "Input",
|
||||
"tokens_completion": "Output",
|
||||
"tokens_tool": "Tools",
|
||||
"tokens_estimated": "local estimate"
|
||||
},
|
||||
"aiconfig": {
|
||||
"title": "AI Config",
|
||||
|
||||
@@ -54,7 +54,29 @@
|
||||
"default_profile": "默认接口",
|
||||
"tool_router": "工具路由",
|
||||
"enter_hint": "Enter 发送，Shift + Enter 换行",
|
||||
"error_prefix": "请求失败："
|
||||
"error_prefix": "请求失败：",
|
||||
"attach_image": "添加图片",
|
||||
"remove_image": "移除图片",
|
||||
"image_type_error": "图片格式不支持，仅支持 jpeg/png/webp/gif",
|
||||
"image_size_error": "图片过大，请选择小于 4MB 的图片",
|
||||
"image_read_error": "图片读取失败，请尝试其他文件",
|
||||
"reasoning": "思考内容",
|
||||
"trace_details": "调用详情",
|
||||
"trace_database": "数据库",
|
||||
"trace_rows": "行数",
|
||||
"trace_columns": "列数",
|
||||
"trace_count": "结果数",
|
||||
"trace_tools": "工具",
|
||||
"trace_reason": "原因",
|
||||
"trace_error": "错误",
|
||||
"trace_truncated": "结果已截断",
|
||||
"tokens_avg_speed": "平均速度",
|
||||
"tokens_peak_speed": "峰值速度",
|
||||
"tokens_total": "总 token",
|
||||
"tokens_prompt": "输入",
|
||||
"tokens_completion": "输出",
|
||||
"tokens_tool": "工具",
|
||||
"tokens_estimated": "本地估算"
|
||||
},
|
||||
"aiconfig": {
|
||||
"title": "AI 配置",
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
<script setup>
|
||||
import { nextTick, onMounted, ref } from 'vue'
|
||||
import { useI18n } from 'vue-i18n'
|
||||
import { IconRobot, IconSend, IconTrash, IconUser, IconLoader2 } from '@tabler/icons-vue'
|
||||
import { IconLoader2, IconPhoto, IconRobot, IconSend, IconTrash, IconUser, IconX } from '@tabler/icons-vue'
|
||||
import { fetchOpenAIProfiles, streamChat } from '@/api/aichat'
|
||||
import { usePageTitle } from '@/composables/usePageTitle'
|
||||
import { useToastStore } from '@/stores/toast'
|
||||
@@ -13,13 +13,19 @@ usePageTitle('appname.aichat')
|
||||
|
||||
const messages = ref([])
|
||||
const inputText = ref('')
|
||||
const selectedImage = ref(null)
|
||||
const pending = ref(false)
|
||||
const traces = ref([])
|
||||
const reasoning = ref('')
|
||||
const stats = ref(null)
|
||||
const profiles = ref([])
|
||||
const activeProfile = ref('')
|
||||
const toolRouter = ref(null)
|
||||
const messageListRef = ref(null)
|
||||
const fileInputRef = ref(null)
|
||||
|
||||
const MAX_IMAGE_SIZE = 4 * 1024 * 1024
|
||||
const ALLOWED_IMAGE_TYPES = ['image/jpeg', 'image/png', 'image/webp', 'image/gif']
|
||||
|
||||
onMounted(loadProfiles)
|
||||
|
||||
@@ -57,18 +63,114 @@ function clearChat() {
|
||||
if (pending.value) return
|
||||
messages.value = []
|
||||
traces.value = []
|
||||
reasoning.value = ''
|
||||
stats.value = null
|
||||
clearSelectedImage()
|
||||
}
|
||||
|
||||
function triggerImagePicker() {
|
||||
if (pending.value) return
|
||||
fileInputRef.value?.click()
|
||||
}
|
||||
|
||||
function onImageSelected(event) {
|
||||
const file = event.target.files?.[0]
|
||||
event.target.value = ''
|
||||
if (!file) return
|
||||
|
||||
if (!ALLOWED_IMAGE_TYPES.includes(file.type)) {
|
||||
toast.error(t('aichat.image_type_error'))
|
||||
return
|
||||
}
|
||||
if (file.size > MAX_IMAGE_SIZE) {
|
||||
toast.error(t('aichat.image_size_error'))
|
||||
return
|
||||
}
|
||||
|
||||
const reader = new FileReader()
|
||||
reader.onload = (loadEvent) => {
|
||||
selectedImage.value = {
|
||||
dataUrl: loadEvent.target?.result || '',
|
||||
name: file.name,
|
||||
size: file.size,
|
||||
type: file.type,
|
||||
}
|
||||
}
|
||||
reader.onerror = () => {
|
||||
toast.error(t('aichat.image_read_error'))
|
||||
}
|
||||
reader.readAsDataURL(file)
|
||||
}
|
||||
|
||||
function clearSelectedImage() {
|
||||
selectedImage.value = null
|
||||
}
|
||||
|
||||
function formatFileSize(size) {
|
||||
if (size >= 1024 * 1024) {
|
||||
return `${(size / 1024 / 1024).toFixed(1)} MB`
|
||||
}
|
||||
return `${Math.max(1, Math.round(size / 1024))} KB`
|
||||
}
|
||||
|
||||
function messageImage(message) {
|
||||
return message.image_url || message.imageURL || ''
|
||||
}
|
||||
|
||||
function formatTraceData(data) {
|
||||
if (!data) return []
|
||||
const parts = []
|
||||
if (data.database) parts.push(`${t('aichat.trace_database')}: ${data.database}`)
|
||||
if (data.sql) parts.push(data.sql)
|
||||
if (typeof data.rows === 'number') parts.push(`${t('aichat.trace_rows')}: ${data.rows}`)
|
||||
if (typeof data.columns === 'number') parts.push(`${t('aichat.trace_columns')}: ${data.columns}`)
|
||||
if (typeof data.count === 'number') parts.push(`${t('aichat.trace_count')}: ${data.count}`)
|
||||
if (Array.isArray(data.tools)) parts.push(`${t('aichat.trace_tools')}: ${data.tools.join(', ') || '-'}`)
|
||||
if (Array.isArray(data.selections) && data.selections.length) {
|
||||
parts.push(data.selections.map((item) => `${item.name}: ${item.reason || '-'}`).join('\n'))
|
||||
}
|
||||
if (data.reason) parts.push(`${t('aichat.trace_reason')}: ${data.reason}`)
|
||||
if (data.error) parts.push(`${t('aichat.trace_error')}: ${data.error}`)
|
||||
if (data.truncated) parts.push(t('aichat.trace_truncated'))
|
||||
if (data.max_rows) parts.push(`max_rows: ${data.max_rows}`)
|
||||
return parts
|
||||
}
|
||||
|
||||
function formatFixed(value) {
|
||||
return typeof value === 'number' ? value.toFixed(1) : '0.0'
|
||||
}
|
||||
|
||||
function formatTokenStats(value) {
|
||||
if (!value) return ''
|
||||
const toolTokens = (value.tool_prompt_tokens || 0) + (value.tool_completion_tokens || 0)
|
||||
const parts = [
|
||||
`${t('aichat.tokens_avg_speed')}: ${formatFixed(value.completion_tokens_per_sec)} tokens/sec`,
|
||||
`${t('aichat.tokens_peak_speed')}: ${formatFixed(value.peak_completion_tokens_per_sec)} tokens/sec`,
|
||||
`${t('aichat.tokens_total')}: ${value.total_tokens || 0}`,
|
||||
`${t('aichat.tokens_prompt')}: ${value.prompt_tokens || 0}`,
|
||||
`${t('aichat.tokens_completion')}: ${value.completion_tokens || 0}`,
|
||||
]
|
||||
if (toolTokens) parts.push(`${t('aichat.tokens_tool')}: ${toolTokens}`)
|
||||
if (value.estimated) parts.push(t('aichat.tokens_estimated'))
|
||||
return parts.join(' ｜ ')
|
||||
}
|
||||
|
||||
async function sendMessage() {
|
||||
const text = inputText.value.trim()
|
||||
if (!text || pending.value) return
|
||||
const image = selectedImage.value
|
||||
if ((!text && !image) || pending.value) return
|
||||
|
||||
inputText.value = ''
|
||||
clearSelectedImage()
|
||||
traces.value = []
|
||||
reasoning.value = ''
|
||||
stats.value = null
|
||||
|
||||
messages.value.push({ role: 'user', content: text })
|
||||
const userMessage = { role: 'user', content: text }
|
||||
if (image) {
|
||||
userMessage.image_url = image.dataUrl
|
||||
}
|
||||
messages.value.push(userMessage)
|
||||
const assistantMessage = { role: 'assistant', content: '' }
|
||||
messages.value.push(assistantMessage)
|
||||
pending.value = true
|
||||
@@ -76,7 +178,11 @@ async function sendMessage() {
|
||||
|
||||
const history = messages.value
|
||||
.filter((message) => message.role === 'user' || message.role === 'assistant')
|
||||
.map((message) => ({ role: message.role, content: message.content }))
|
||||
.map((message) => {
|
||||
const item = { role: message.role, content: message.content || '' }
|
||||
if (message.image_url) item.image_url = message.image_url
|
||||
return item
|
||||
})
|
||||
.slice(0, -1)
|
||||
|
||||
try {
|
||||
@@ -89,6 +195,10 @@ async function sendMessage() {
|
||||
traces.value.push(frame)
|
||||
scrollToBottom()
|
||||
},
|
||||
onReasoning(delta) {
|
||||
reasoning.value += delta
|
||||
scrollToBottom()
|
||||
},
|
||||
onStats(value) {
|
||||
stats.value = value
|
||||
},
|
||||
@@ -174,10 +284,31 @@ async function sendMessage() {
|
||||
<div v-if="trace.message" class="mt-1 opacity-90">
|
||||
{{ trace.message }}
|
||||
</div>
|
||||
<div v-if="formatTraceData(trace.data).length" class="mt-2 space-y-1 rounded-md border border-blue-100 bg-white/70 px-2 py-1 font-mono text-[11px] leading-5 text-blue-800 dark:border-blue-900/40 dark:bg-dk-card/70 dark:text-blue-100">
|
||||
<div v-for="(line, dataIndex) in formatTraceData(trace.data)" :key="dataIndex" class="whitespace-pre-wrap break-words">
|
||||
{{ line }}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<p class="whitespace-pre-wrap break-words">
|
||||
<div v-if="message.role !== 'user' && index === messages.length - 1 && reasoning" class="mb-3 rounded-lg border border-purple-100 bg-purple-50 px-3 py-2 text-xs text-purple-800 dark:border-purple-900/40 dark:bg-purple-900/20 dark:text-purple-100">
|
||||
<div class="font-medium">
|
||||
{{ t('aichat.reasoning') }}
|
||||
</div>
|
||||
<div class="mt-1 whitespace-pre-wrap break-words">
|
||||
{{ reasoning }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<img
|
||||
v-if="messageImage(message)"
|
||||
:src="messageImage(message)"
|
||||
:alt="message.content || t('aichat.attach_image')"
|
||||
class="mb-2 max-h-64 max-w-full rounded-lg object-contain"
|
||||
/>
|
||||
|
||||
<p v-if="message.content || (message.role === 'assistant' && pending)" class="whitespace-pre-wrap break-words">
|
||||
{{ message.content || (message.role === 'assistant' && pending ? t('aichat.thinking') : '') }}
|
||||
</p>
|
||||
|
||||
@@ -187,7 +318,7 @@ async function sendMessage() {
|
||||
</div>
|
||||
|
||||
<div v-if="message.role !== 'user' && index === messages.length - 1 && stats" class="mt-3 text-xs text-gray-500 dark:text-dk-subtle">
|
||||
{{ t('aichat.tokens') }}: {{ stats.total_tokens || 0 }}
|
||||
{{ formatTokenStats(stats) }}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -199,7 +330,46 @@ async function sendMessage() {
|
||||
</div>
|
||||
|
||||
<div class="border-t border-gray-200 bg-gray-50 p-4 dark:border-dk-muted dark:bg-dk-base">
|
||||
<input
|
||||
ref="fileInputRef"
|
||||
type="file"
|
||||
accept="image/jpeg,image/png,image/webp,image/gif"
|
||||
class="hidden"
|
||||
:disabled="pending"
|
||||
@change="onImageSelected"
|
||||
/>
|
||||
|
||||
<div v-if="selectedImage" class="mb-3 flex items-center gap-3 rounded-lg border border-gray-200 bg-white p-2 dark:border-dk-muted dark:bg-dk-card">
|
||||
<img :src="selectedImage.dataUrl" :alt="selectedImage.name" class="h-14 w-14 rounded object-cover" />
|
||||
<div class="min-w-0 flex-1">
|
||||
<div class="truncate text-sm font-medium text-gray-800 dark:text-dk-text">
|
||||
{{ selectedImage.name }}
|
||||
</div>
|
||||
<div class="text-xs text-gray-500 dark:text-dk-subtle">
|
||||
{{ formatFileSize(selectedImage.size) }}
|
||||
</div>
|
||||
</div>
|
||||
<button
|
||||
type="button"
|
||||
class="inline-flex h-8 w-8 items-center justify-center rounded-md text-gray-500 transition-colors hover:bg-gray-100 disabled:cursor-not-allowed disabled:opacity-60 dark:text-dk-subtle dark:hover:bg-dk-muted"
|
||||
:title="t('aichat.remove_image')"
|
||||
:disabled="pending"
|
||||
@click="clearSelectedImage"
|
||||
>
|
||||
<IconX :size="16" />
|
||||
</button>
|
||||
</div>
|
||||
|
||||
<div class="flex items-end gap-3">
|
||||
<button
|
||||
type="button"
|
||||
class="inline-flex h-[52px] w-[52px] shrink-0 items-center justify-center rounded-lg border border-gray-300 bg-white text-gray-600 transition-colors hover:bg-gray-100 disabled:cursor-not-allowed disabled:opacity-60 dark:border-dk-muted dark:bg-dk-card dark:text-dk-subtle dark:hover:bg-dk-muted"
|
||||
:title="t('aichat.attach_image')"
|
||||
:disabled="pending"
|
||||
@click="triggerImagePicker"
|
||||
>
|
||||
<IconPhoto :size="20" />
|
||||
</button>
|
||||
<textarea
|
||||
v-model="inputText"
|
||||
rows="2"
|
||||
@@ -211,7 +381,7 @@ async function sendMessage() {
|
||||
<button
|
||||
type="button"
|
||||
class="inline-flex h-[52px] items-center gap-2 rounded-lg bg-blue-600 px-4 text-sm font-medium text-white transition-colors hover:bg-blue-700 disabled:cursor-not-allowed disabled:opacity-60"
|
||||
:disabled="pending || !inputText.trim()"
|
||||
:disabled="pending || (!inputText.trim() && !selectedImage)"
|
||||
@click="sendMessage"
|
||||
>
|
||||
<IconLoader2 v-if="pending" :size="18" class="animate-spin" />
|
||||
|
||||
Reference in New Issue
Block a user