通过逐接口对比 DeepSeek/AgnesAI/Ollama 官方文档与实现代码,发现并修复:
DeepSeek (4 fix):
- temperature 默认值: 错误发送 0(API默认=1),改为 undefined 让 API 用默认值
- thinking 禁用: API 默认 enabled,不传=开启。改为显式发送 {type:disabled}
- reasoning_effort: 补充 xhigh→max 映射(文档规定)
- stream 请求: 补充 AbortSignal.timeout 超时控制
Agnes AI (2 fix):
- temperature 默认值: 同上
- 图片 image_url: 移除文档未提及的 detail 字段
Ollama (3 fix):
- temperature 默认值: 同上(Ollama默认≈0.8)
- tool_calls arguments: 从对象改为 JSON 字符串(REST API 要求)
- finishReason: 使用 done_reason 字段正确映射(之前始终返回 STOP)
160 lines
5.2 KiB
TypeScript
160 lines
5.2 KiB
TypeScript
/**
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* Agnes AI Provider Adapter
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*
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* OpenAI 兼容 API。支持 Tool Calling、Thinking 模式、多模态(图片)。
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*
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* 独立继承 BaseAdapter,通过 shared/openai-format 和 shared/sse-stream 复用
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* OpenAI 兼容格式构建和 SSE 流式解析逻辑。不与其他 Provider Adapter 耦合。
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*
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* 与 DeepSeek 的差异:
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* - Thinking 模式使用 chat_template_kwargs(非 thinking 字段)
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* - 默认 max_tokens 更大(65536 vs 8192)
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*
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* @see apis/agnes-ai-api-docs-20260625.html
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*/
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import { BaseAdapter } from './base-adapter';
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import type { MetonaRequest, MetonaResponse, MetonaStreamEvent } from '../types';
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import { MetonaFinishReason } from '../types';
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import { buildOpenAICompatibleMessages, buildOpenAICompatibleTools } from './shared/openai-format';
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import { parseSSEStream, parseOpenAICompatibleResponse } from './shared/sse-stream';
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export class AgnesAdapter extends BaseAdapter {
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override readonly provider: string = 'agnes';
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readonly supportedModels = ['agnes-2.0-flash'];
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readonly supportsToolCalling = true;
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readonly supportsThinking = true;
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// ===== POST /chat/completions (非流式) =====
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async chat(request: MetonaRequest): Promise<MetonaResponse> {
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const body = this.toNativeRequest(request, false);
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const response = await fetch(`${this.config.baseURL}/chat/completions`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${this.config.apiKey}`,
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...this.config.headers,
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},
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body: JSON.stringify(body),
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signal: AbortSignal.timeout(this.config.timeoutMs ?? 300_000),
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});
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if (!response.ok) {
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const errorBody = await response.text().catch(() => '');
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throw new Error(`Agnes AI API error: ${response.status} ${response.statusText} - ${errorBody}`);
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}
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const data = await response.json() as Record<string, unknown>;
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const parsed = parseOpenAICompatibleResponse(data, request.meta.requestId, this.provider, this.config.defaultModel);
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return {
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meta: {
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requestId: request.meta.requestId,
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provider: this.provider,
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model: (data.model as string) ?? this.config.defaultModel,
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latencyMs: 0,
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timestamp: Date.now(),
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},
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content: parsed.content,
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reasoningContent: parsed.reasoningContent,
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toolCalls: parsed.toolCalls,
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usage: parsed.usage,
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finishReason: parsed.finishReason as MetonaFinishReason,
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};
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}
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// ===== POST /chat/completions (流式) =====
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async *chatStream(request: MetonaRequest): AsyncIterable<MetonaStreamEvent> {
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const body = this.toNativeRequest(request, true);
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const response = await fetch(`${this.config.baseURL}/chat/completions`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${this.config.apiKey}`,
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...this.config.headers,
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},
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body: JSON.stringify(body),
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});
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if (!response.ok || !response.body) {
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throw new Error(`Agnes AI stream error: ${response.status}`);
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}
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yield* parseSSEStream(
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response.body,
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request.meta.requestId,
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request.meta.sessionId,
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request.meta.iteration,
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);
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}
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// ========== 私有方法 ==========
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/**
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* 构建 Agnes AI 原生请求体
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*
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* Agnes AI 特有参数:
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* - 多模态图片:user 消息的 images[] → OpenAI content 数组 [{type:"text"}, {type:"image_url"}]
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* - chat_template_kwargs: { enable_thinking: true } — 启用思考模式(非 thinking 字段)
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* - 默认 max_tokens: 65536(512K 上下文)
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*/
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private toNativeRequest(request: MetonaRequest, stream: boolean): Record<string, unknown> {
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const messages = buildOpenAICompatibleMessages(request);
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const tools = buildOpenAICompatibleTools(request.tools);
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// === Agnes 多模态:将 images 转为 OpenAI content 数组 ===
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// buildOpenAICompatibleMessages 不处理图片(各 Provider 自行处理)
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const nonSystemMsgs = request.messages.filter((m) => m.role !== 'system');
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for (let i = 0; i < messages.length; i++) {
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// messages[0] 是 system,非 system 消息从 messages[1] 开始
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if (i === 0) continue;
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const origMsg = nonSystemMsgs[i - 1];
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if (!origMsg?.images?.length) continue;
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const contentParts: Array<Record<string, unknown>> = [];
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if (origMsg.content) {
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contentParts.push({ type: 'text', text: origMsg.content });
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}
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for (const img of origMsg.images) {
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contentParts.push({
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type: 'image_url',
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image_url: { url: img.url },
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});
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}
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messages[i].content = contentParts;
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}
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const body: Record<string, unknown> = {
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model: this.config.defaultModel,
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messages,
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temperature: request.params.temperature,
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max_tokens: request.params.maxTokens ?? 65536,
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stream,
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};
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if (stream) {
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body.stream_options = { include_usage: true };
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}
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if (tools) {
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body.tools = tools;
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}
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// Thinking 模式:Agnes 使用 chat_template_kwargs 而非 thinking
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if (request.params.thinkingEnabled) {
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body.chat_template_kwargs = { enable_thinking: true };
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}
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// 停止序列
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if (request.params.stopSequences?.length) {
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body.stop = request.params.stopSequences;
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}
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return body;
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}
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}
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