Aska
2248ddce15
- 打通 thinking/tool_call 运行时数据源：openai 发 thinking_*(reasoning_content)/tool_call_* (delta.tool_calls 累积重新组装 Args 非 JSON 串)；anthropic_stream 发 thinking_*(content_block thinking start/delta/stop)。ws_bridge 已映射 thinking.*/tool_call.*，前端渲染活。 - 前端消息模型 + 附件：ChatMessage 加 image?；ChatInput 加附件按钮(file→base64)、预览/移除、 image-aware onSend(text,image)；VisionMessageBody 升级图像卡+识别 chip；VoiceMessageBody 升级通话控制卡(live2D预留/波形/静音/挂断)；HomeMessageBody 读真实 deviceUpdates(去掉 sampleDevices 猜)。 - 激活 voice_input：ChatShell onVoice 不再 no-op → sendUp voice_input + 切 voice mode。 - addTool 改按工具名 upsert(修复 tool_call.start/end 重复卡)；ws_mode_switch 应用 agent 驱动 mode；addUserMessage/beginAssistant 带 image/mode；chatStream/useChat.send 带 image。 - 新增 image/phone 图标。 已知限制(标注)：图片仅前端收集(后端 chatRequest 无 image 字段未接真推理)；流式工具卡无真实 工具名(StreamEvent 只带 ID，回退 tool_<id前缀>)；mode 由 agent 驱动但后端未逐消息下发 mode (mode_switch 回显+默认当前 mode 兜底)；voice 为 UI+voice_input 上行(真实通话后置)。 go build/vet/test + 前端 tsc 绿。
63 lines
2.7 KiB
TypeScript
63 lines
2.7 KiB
TypeScript
import { useCallback, useState } from "react";
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import { chatStream } from "./api";
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import { connectWs, isWsOpen } from "./ws";
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import { useAppStore } from "../store/useAppStore";
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import { useModeStore } from "../store/useModeStore";
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import { now } from "./util";
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/** Drives one user turn: push the user bubble, blanket a streaming assistant
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* bubble, trigger the backend loop over REST (`stream:true`), and let the WS
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* stream render into that bubble. Falls back to the WS `chat` channel when the
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* REST trigger fails so the demo still works without a wired loop.
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*
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* The behavior mode is NOT chosen by the user at send time — the agent / backend
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* hot-switches it (design/01 §3), and each message carries its own mode, so the
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* bubble renders per that message's mode. Until the backend advertises a
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* per-message mode, a new assistant bubble defaults to the current UI mode. */
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export function useSendChat(): {
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send: (text: string, image?: string) => Promise<void>;
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sending: boolean;
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} {
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const [sending, setSending] = useState(false);
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const sessionId = useAppStore((s) => s.sessionId);
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const addUserMessage = useAppStore((s) => s.addUserMessage);
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const beginAssistant = useAppStore((s) => s.beginAssistant);
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const endStream = useAppStore((s) => s.endStream);
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const appendChunk = useAppStore((s) => s.appendChunk);
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const addTool = useAppStore((s) => s.addTool);
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const appendTaskLog = useAppStore((s) => s.appendTaskLog);
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const mode = useModeStore((s) => s.mode);
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const send = useCallback(
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async (text: string, image?: string) => {
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const trimmed = text.trim();
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if ((!trimmed && !image) || sending) return;
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setSending(true);
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if (!isWsOpen()) connectWs();
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// The gateway's chat body still requires a non-empty text, so a pure image
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// turn (vision) falls back to a default prompt to keep the trigger valid.
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const prompt = trimmed || (image ? "分析这张图片" : "");
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addUserMessage(trimmed, undefined, image);
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beginAssistant(mode);
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try {
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await chatStream(sessionId, prompt, image);
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} catch (err: unknown) {
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// Backend loop not wired or gateway unreachable: show the failure inline
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// rather than leaving a permanently-streaming bubble.
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endStream();
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const msg = err instanceof Error ? err.message : "触发失败";
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appendChunk(`[stream 触发失败] ${msg}`);
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appendTaskLog("main", `[error] ${msg}\n`);
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addTool({ name: "stream_trigger", summary: "失败", ok: false, detail: msg, at: now() });
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} finally {
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setSending(false);
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}
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},
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[sending, sessionId, mode, addUserMessage, beginAssistant, endStream, appendChunk, addTool, appendTaskLog]
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);
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return { send, sending };
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}
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