thzxx
1d185db6b3
- Electron + React + TypeScript 架构 - 三栏布局: Sidebar | ChatPanel | DetailPanel - 9 个内置工具 (文件系统/网络/记忆/命令) - SQLite 持久化 (better-sqlite3) - MUI 暗色/亮色主题系统 - Agent Loop ReAct 状态机引擎 - DeepSeek / Agnes AI / Ollama Provider 适配器 - MCP 协议集成 - 系统托盘 + 全局快捷键 - Tailwind CSS v4 + Tailwind Merge - 修复: Sidebar 缺失 TextField 导入导致黑屏
455 lines
15 KiB
TypeScript
455 lines
15 KiB
TypeScript
/**
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* Ollama Provider Adapter
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*
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* 本地推理引擎，支持 Tool Calling、Thinking 模式、NDJSON 流式。
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* 无需 API Key，连接本地 http://localhost:11434。
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*
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* 完整实现 Ollama API 文档中所有端点和参数：
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* - POST /api/chat (对话)
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* - POST /api/generate (补全)
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* - POST /api/embed (嵌入)
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* - GET /api/tags (列出模型)
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* - POST /api/show (模型详情)
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* - POST /api/pull (下载模型)
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* - GET /api/ps (运行中模型)
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* - GET /api/version (版本)
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* - think 参数（Thinking 模式）
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* - options 参数（temperature/top_k/top_p/stop/num_ctx/num_predict）
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* - format 参数（structured output）
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* - images 参数（多模态）
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* - tool_calls 流式处理
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*
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* @see apis/ollama-api-docs-20260518.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, MetonaStreamEventType } from '../types';
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export class OllamaAdapter extends BaseAdapter {
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override readonly provider: string = 'ollama';
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readonly supportedModels = ['qwen3:latest', 'gemma3:latest', 'deepseek-r1:latest'];
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readonly supportsToolCalling = true;
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readonly supportsThinking = true;
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private baseURL: string;
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constructor(config: ConstructorParameters<typeof BaseAdapter>[0]) {
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super(config);
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this.baseURL = config.baseURL || 'http://localhost:11434';
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}
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// ===== POST /api/chat =====
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async chat(request: MetonaRequest): Promise<MetonaResponse> {
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const nativeRequest = this.toNativeRequest(request);
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const response = await fetch(`${this.baseURL}/api/chat`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ ...nativeRequest, stream: false }),
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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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throw new Error(`Ollama API error: ${response.status}`);
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}
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const data = await response.json();
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return this.toMetonaResponse(data, request.meta.requestId);
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}
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async *chatStream(request: MetonaRequest): AsyncIterable<MetonaStreamEvent> {
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const nativeRequest = this.toNativeRequest(request);
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const response = await fetch(`${this.baseURL}/api/chat`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ ...nativeRequest, stream: true }),
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});
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if (!response.ok || !response.body) {
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throw new Error(`Ollama stream error: ${response.status}`);
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}
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const reader = response.body.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
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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) continue;
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try {
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const chunk = JSON.parse(trimmed);
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// 思考内容
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if (chunk.message?.thinking) {
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yield {
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type: MetonaStreamEventType.REASONING_DELTA,
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requestId: request.meta.requestId,
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sessionId: request.meta.sessionId,
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iteration: request.meta.iteration,
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seq: seq++,
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timestamp: Date.now(),
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delta: chunk.message.thinking,
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};
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}
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// 文本内容
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if (chunk.message?.content) {
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yield {
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type: MetonaStreamEventType.TEXT_DELTA,
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requestId: request.meta.requestId,
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sessionId: request.meta.sessionId,
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iteration: request.meta.iteration,
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seq: seq++,
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timestamp: Date.now(),
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delta: chunk.message.content,
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};
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}
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// 工具调用（Ollama 在最后一个 chunk 中整块返回）
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if (chunk.message?.tool_calls) {
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for (const tc of chunk.message.tool_calls) {
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yield {
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type: MetonaStreamEventType.TOOL_CALL_COMPLETE,
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requestId: request.meta.requestId,
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sessionId: request.meta.sessionId,
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iteration: request.meta.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_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`,
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name: tc.function?.name ?? '',
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args: tc.function?.arguments ?? {},
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iteration: request.meta.iteration,
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timestamp: Date.now(),
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},
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};
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}
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}
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// 流结束
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if (chunk.done) {
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// 发送 usage 信息
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yield {
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type: MetonaStreamEventType.USAGE,
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requestId: request.meta.requestId,
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sessionId: request.meta.sessionId,
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iteration: request.meta.iteration,
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seq: seq++,
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timestamp: Date.now(),
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usage: {
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inputTokens: chunk.prompt_eval_count ?? 0,
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outputTokens: chunk.eval_count ?? 0,
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totalTokens: (chunk.prompt_eval_count ?? 0) + (chunk.eval_count ?? 0),
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},
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};
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yield {
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type: MetonaStreamEventType.DONE,
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requestId: request.meta.requestId,
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sessionId: request.meta.sessionId,
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iteration: request.meta.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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} 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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// ===== POST /api/generate =====
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async generate(params: {
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model: string;
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prompt: string;
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suffix?: string;
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system?: string;
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stream?: boolean;
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think?: boolean | string;
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format?: string | object;
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images?: string[];
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options?: Record<string, unknown>;
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}): Promise<{ response: string; thinking?: string; done: boolean; totalDuration: number; evalCount: number }> {
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const response = await fetch(`${this.baseURL}/api/generate`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ ...params, stream: false }),
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signal: AbortSignal.timeout(300_000),
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});
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if (!response.ok) throw new Error(`Ollama generate error: ${response.status}`);
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const data = await response.json() as {
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response?: string; thinking?: string; done?: boolean;
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total_duration?: number; eval_count?: number;
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};
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return {
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response: data.response ?? '',
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thinking: data.thinking,
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done: data.done ?? true,
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totalDuration: data.total_duration ?? 0,
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evalCount: data.eval_count ?? 0,
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};
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}
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// ===== POST /api/embed =====
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async embed(params: {
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model: string;
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input: string | string[];
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dimensions?: number;
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}): Promise<{ embeddings: number[][]; totalDuration: number }> {
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const response = await fetch(`${this.baseURL}/api/embed`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(params),
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signal: AbortSignal.timeout(60_000),
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});
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if (!response.ok) throw new Error(`Ollama embed error: ${response.status}`);
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const data = await response.json() as { embeddings?: number[][]; total_duration?: number };
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return {
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embeddings: data.embeddings ?? [],
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totalDuration: data.total_duration ?? 0,
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};
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}
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// ===== GET /api/tags =====
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async listModels(): Promise<string[]> {
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try {
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const response = await fetch(`${this.baseURL}/api/tags`, {
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signal: AbortSignal.timeout(10_000),
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});
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if (!response.ok) return this.supportedModels;
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const data = await response.json() as { models?: Array<{ name: string }> };
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return data.models?.map((m) => m.name) ?? this.supportedModels;
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} catch {
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return this.supportedModels;
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}
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}
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// ===== POST /api/show =====
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async showModel(model: string): Promise<{ parameters: string; template: string; capabilities: string[] } | null> {
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try {
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const response = await fetch(`${this.baseURL}/api/show`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ model }),
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signal: AbortSignal.timeout(10_000),
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});
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if (!response.ok) return null;
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const data = await response.json() as { parameters?: string; template?: string; capabilities?: string[] };
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return {
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parameters: data.parameters ?? '',
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template: data.template ?? '',
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capabilities: data.capabilities ?? [],
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};
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} catch {
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return null;
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}
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}
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// ===== POST /api/pull =====
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async pullModel(model: string, onProgress?: (progress: { status: string; completed?: number; total?: number }) => void): Promise<void> {
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const response = await fetch(`${this.baseURL}/api/pull`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ model, stream: true }),
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});
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if (!response.ok || !response.body) throw new Error(`Ollama pull error: ${response.status}`);
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const reader = response.body.getReader();
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const decoder = new TextDecoder();
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let buffer = '';
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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buffer += decoder.decode(value, { stream: true });
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const lines = buffer.split('\n');
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buffer = lines.pop() ?? '';
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for (const line of lines) {
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if (!line.trim()) continue;
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try {
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const chunk = JSON.parse(line);
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onProgress?.({ status: chunk.status, completed: chunk.completed, total: chunk.total });
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} catch {}
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}
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}
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}
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// ===== GET /api/ps =====
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async listRunning(): Promise<Array<{ name: string; size: number; sizeVram: number; contextLength: number }>> {
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try {
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const response = await fetch(`${this.baseURL}/api/ps`, {
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signal: AbortSignal.timeout(10_000),
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});
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if (!response.ok) return [];
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const data = await response.json() as { models?: Array<{ name: string; size?: number; size_vram?: number; context_length?: number }> };
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return (data.models ?? []).map((m) => ({
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name: m.name ?? '',
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size: m.size ?? 0,
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sizeVram: m.size_vram ?? 0,
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contextLength: m.context_length ?? 0,
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}));
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} catch {
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return [];
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}
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}
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// ===== GET /api/version =====
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async getVersion(): Promise<string> {
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try {
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const response = await fetch(`${this.baseURL}/api/version`, {
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signal: AbortSignal.timeout(5_000),
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});
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if (!response.ok) return 'unknown';
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const data = await response.json() as { version?: string };
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return data.version ?? 'unknown';
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} catch {
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return 'unknown';
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}
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}
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// ========== 私有转换方法 ==========
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private toNativeRequest(request: MetonaRequest): Record<string, unknown> {
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const messages = [
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{
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role: 'system',
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content: [
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request.systemPrompt.roleDefinition,
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request.systemPrompt.outputConstraints,
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request.systemPrompt.safetyGuidelines,
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].filter(Boolean).join('\n\n'),
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},
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...request.messages.filter((m) => m.role !== 'system').map((m) => {
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const msg: Record<string, unknown> = { role: m.role, content: m.content };
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// Ollama 图片使用 images 字段（纯 base64 数组，不含 data: 前缀）
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if (m.images?.length) {
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msg.images = m.images.map((img) => {
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const url = img.url;
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// data:image/png;base64,iVBOR... → iVBOR...
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if (url.startsWith('data:')) {
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const base64Part = url.split(',')[1];
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return base64Part ?? url;
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}
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return url;
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});
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}
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// 工具结果
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if (m.role === 'tool' && m.toolResult) {
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msg.tool_call_id = m.toolResult.toolCallId;
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msg.content = typeof m.toolResult.result === 'string'
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? m.toolResult.result
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: JSON.stringify(m.toolResult.result);
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}
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// assistant 工具调用
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if (m.role === 'assistant' && m.toolCalls?.length) {
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msg.tool_calls = m.toolCalls.map((tc) => ({
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function: { name: tc.name, arguments: tc.args },
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}));
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}
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return msg;
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}),
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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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options: {
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temperature: request.params.temperature ?? 0,
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num_predict: request.params.maxTokens,
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top_p: request.params.topP,
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stop: request.params.stopSequences,
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},
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};
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// Tool Calling
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if (request.tools?.length) {
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body.tools = request.tools.map((t) => ({
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type: 'function',
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function: {
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name: t.name,
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description: t.description,
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parameters: t.parameters,
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},
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}));
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}
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// Thinking 模式
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if (request.params.thinkingEnabled) {
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const effortMap: Record<string, string | boolean> = { low: 'low', medium: 'medium', high: 'high', max: true };
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body.think = effortMap[request.params.thinkingEffort ?? 'high'] ?? true;
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}
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return body;
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}
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private toMetonaResponse(data: Record<string, unknown>, requestId: string): MetonaResponse {
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const message = data.message as Record<string, unknown> | undefined;
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const toolCalls = message?.tool_calls as Array<Record<string, unknown>> | undefined;
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return {
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meta: {
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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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perfStats: {
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loadDurationMs: data.load_duration ? (data.load_duration as number) / 1e6 : undefined,
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promptEvalDurationMs: data.prompt_eval_duration ? (data.prompt_eval_duration as number) / 1e6 : undefined,
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evalDurationMs: data.eval_duration ? (data.eval_duration as number) / 1e6 : undefined,
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tokensPerSecond: data.eval_count && data.eval_duration
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? ((data.eval_count as number) / ((data.eval_duration as number) / 1e9))
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: undefined,
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},
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},
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content: (message?.content as string) ?? '',
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reasoningContent: message?.thinking as string | undefined,
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toolCalls: toolCalls?.map((tc, i) => {
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const fn = tc.function as Record<string, unknown>;
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return {
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id: `tc_${Date.now()}_${i}`,
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name: (fn?.name as string) ?? '',
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args: (fn?.arguments as Record<string, unknown>) ?? {},
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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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usage: {
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inputTokens: (data.prompt_eval_count as number) ?? 0,
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outputTokens: (data.eval_count as number) ?? 0,
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totalTokens: ((data.prompt_eval_count as number) ?? 0) + ((data.eval_count as number) ?? 0),
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},
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finishReason: data.done ? MetonaFinishReason.STOP : MetonaFinishReason.LENGTH,
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};
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}
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}
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