refactor: 解耦 Provider Adapter 继承关系
问题：AgnesAdapter extends DeepSeekAdapter 在架构上不合理。 DeepSeek、Agnes AI、Ollama 是三个完全不同的 API，不应有继承关系。 重构： BaseAdapter ├── DeepSeekAdapter (独立) ├── AgnesAdapter (独立) └── OllamaAdapter (独立) 变更： - 新增 shared/openai-format.ts — 提取 OpenAI 兼容消息/工具格式构建 - 新增 shared/sse-stream.ts — 提取 SSE 流式解析逻辑 - DeepSeekAdapter 重写为独立继承 BaseAdapter，使用共享工具 - AgnesAdapter 重写为独立继承 BaseAdapter，使用共享工具 - OllamaAdapter 无需变更（原本就独立继承） - adapters/index.ts 清理导出，移除隐式耦合
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thzxx
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/**
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* SSE 流式解析工具
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*
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* 解析 OpenAI 兼容的 Server-Sent Events (SSE) 流式响应，
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* 产出 MetonaStreamEvent。DeepSeek 和 Agnes AI 共享此工具。
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*
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* SSE 格式：data: {json}\n\n
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* 结束标记：data: [DONE]
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*/
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import { nanoid } from 'nanoid';
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import type { MetonaStreamEvent, MetonaTokenUsage } from '../../types';
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import { MetonaStreamEventType } from '../../types';
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/**
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* 解析 OpenAI 兼容 SSE 流式响应
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*
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* @param responseBody - fetch Response.body (ReadableStream<Uint8Array>)
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* @param requestId - 对应的请求 ID
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* @param sessionId - 会话 ID
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* @param iteration - 当前迭代轮次
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* @yields MetonaStreamEvent
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*/
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export async function* parseSSEStream(
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responseBody: ReadableStream<Uint8Array>,
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requestId: string,
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sessionId: string,
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iteration: number,
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): AsyncGenerator<MetonaStreamEvent> {
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const reader = responseBody.getReader();
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const decoder = new TextDecoder();
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let seq = 0;
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let buffer = '';
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// 工具调用缓冲区：index → { name, argsBuffer }
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const toolCallsBuffer = new Map<number, { name: string; argsBuffer: string }>();
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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buffer += decoder.decode(value, { stream: true });
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const lines = buffer.split('\n');
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buffer = lines.pop() ?? '';
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for (const line of lines) {
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const trimmed = line.trim();
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if (!trimmed || !trimmed.startsWith('data: ')) continue;
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const data = trimmed.slice(6);
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// 流结束
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if (data === '[DONE]') {
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// 将缓冲区中未完成拼接的工具调用发送
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for (const [index, buf] of toolCallsBuffer) {
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try {
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yield {
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type: MetonaStreamEventType.TOOL_CALL_COMPLETE,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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toolCall: {
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id: `tc_${nanoid(8)}`,
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name: buf.name,
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args: buf.argsBuffer ? JSON.parse(buf.argsBuffer) : {},
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iteration,
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timestamp: Date.now(),
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},
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};
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} catch {
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// JSON 解析失败，跳过
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}
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}
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toolCallsBuffer.clear();
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yield {
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type: MetonaStreamEventType.DONE,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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};
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return;
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}
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try {
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const chunk = JSON.parse(data);
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const delta = chunk.choices?.[0]?.delta;
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// 文本内容增量
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if (delta?.content) {
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yield {
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type: MetonaStreamEventType.TEXT_DELTA,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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delta: delta.content,
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};
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}
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// 推理内容增量（Thinking 模式）
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if (delta?.reasoning_content) {
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yield {
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type: MetonaStreamEventType.REASONING_DELTA,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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delta: delta.reasoning_content,
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};
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}
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// 工具调用增量 — 缓冲拼接
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if (delta?.tool_calls) {
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for (const tc of delta.tool_calls) {
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const idx = tc.index ?? 0;
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if (!toolCallsBuffer.has(idx)) {
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toolCallsBuffer.set(idx, { name: tc.function?.name ?? '', argsBuffer: '' });
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}
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const buf = toolCallsBuffer.get(idx)!;
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if (tc.function?.name) buf.name = tc.function.name;
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if (tc.function?.arguments) buf.argsBuffer += tc.function.arguments;
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yield {
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type: MetonaStreamEventType.TOOL_CALL_DELTA,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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toolCallDelta: {
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index: idx,
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name: tc.function?.name,
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argsDelta: tc.function?.arguments,
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},
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};
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}
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}
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// Token 使用统计
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if (chunk.usage) {
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const usage: MetonaTokenUsage = {
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inputTokens: chunk.usage.prompt_tokens ?? 0,
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outputTokens: chunk.usage.completion_tokens ?? 0,
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totalTokens: chunk.usage.total_tokens ?? 0,
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reasoningTokens: chunk.usage.completion_tokens_details?.reasoning_tokens,
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cacheHitTokens: chunk.usage.prompt_cache_hit_tokens,
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cacheMissTokens: chunk.usage.prompt_cache_miss_tokens,
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};
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yield {
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type: MetonaStreamEventType.USAGE,
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requestId,
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sessionId,
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iteration,
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seq: seq++,
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timestamp: Date.now(),
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usage,
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};
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}
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} catch {
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// 跳过解析失败的行
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}
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}
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}
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}
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/**
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* 解析 OpenAI 兼容的非流式 JSON 响应 → MetonaResponse
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*/
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export function parseOpenAICompatibleResponse(
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data: Record<string, unknown>,
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requestId: string,
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provider: string,
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defaultModel: string,
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): {
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content: string;
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reasoningContent?: string;
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toolCalls?: Array<{ id: string; name: string; args: Record<string, unknown>; iteration: number; timestamp: number }>;
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finishReason: string;
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usage: MetonaTokenUsage;
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} {
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const choice = (data.choices as Array<Record<string, unknown>>)?.[0];
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const message = choice?.message as Record<string, unknown> | undefined;
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const usage = data.usage as Record<string, unknown> | undefined;
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const rawToolCalls = message?.tool_calls as Array<Record<string, unknown>> | undefined;
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return {
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content: (message?.content as string) ?? '',
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reasoningContent: message?.reasoning_content as string | undefined,
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toolCalls: rawToolCalls?.map((tc) => {
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const fn = tc.function as Record<string, unknown>;
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return {
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id: tc.id as string,
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name: fn.name as string,
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args: JSON.parse(fn.arguments as string),
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iteration: 0,
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timestamp: Date.now(),
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};
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}),
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finishReason: mapOpenAIFinishReason(choice?.finish_reason as string),
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usage: {
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inputTokens: (usage?.prompt_tokens as number) ?? 0,
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outputTokens: (usage?.completion_tokens as number) ?? 0,
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totalTokens: (usage?.total_tokens as number) ?? 0,
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reasoningTokens: (usage?.completion_tokens_details as Record<string, unknown>)?.reasoning_tokens as number | undefined,
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cacheHitTokens: usage?.prompt_cache_hit_tokens as number | undefined,
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cacheMissTokens: usage?.prompt_cache_miss_tokens as number | undefined,
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},
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};
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}
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function mapOpenAIFinishReason(reason: string): string {
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switch (reason) {
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case 'stop': return 'stop';
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case 'length': return 'length';
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case 'tool_calls': return 'tool_calls';
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case 'content_filter': return 'content_filter';
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default: return 'stop';
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}
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}
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