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Extract code patterns into a knowledge base for AI coding assistants
291 lines (290 loc) • 11.8 kB
JavaScript
/**
* OpenAiProvider - OpenAI / DeepSeek / Ollama 兼容提供商
* 使用标准 OpenAI Chat Completions API
*
* v2: 支持原生 Function Calling（结构化工具调用）
* - 使用 Chat Completions API 的 tools + tool_choice 参数
* - 兼容 DeepSeek / Ollama 等 OpenAI-compatible API
*/
import Logger from '#infra/logging/Logger.js';
import { AiProvider, } from '../AiProvider.js';
const OPENAI_BASE = 'https://api.openai.com/v1';
export class OpenAiProvider extends AiProvider {
embedModel;
constructor(config = {}) {
super(config);
this.name = config.name || 'openai';
this.model = config.model || 'gpt-5.4-mini';
this.apiKey = config.apiKey || process.env.ASD_OPENAI_API_KEY || '';
this.baseUrl = config.baseUrl || OPENAI_BASE;
this.embedModel = config.embedModel || process.env.ASD_EMBED_MODEL || 'text-embedding-3-small';
this.logger = Logger.getInstance();
}
/**
* 是否支持原生结构化函数调用
* OpenAI / DeepSeek Chat Completions API 均支持
*/
get supportsNativeToolCalling() {
return true;
}
async chat(prompt, context = {}) {
return this._withRetry(async () => {
const { history = [], temperature = 0.7, maxTokens = 4096 } = context;
const messages = [];
for (const h of history) {
messages.push({ role: h.role, content: h.content });
}
messages.push({ role: 'user', content: prompt });
const body = {
model: this.model,
messages,
temperature,
max_tokens: maxTokens,
};
const data = await this._post(`${this.baseUrl}/chat/completions`, body);
// 提取 token 用量
if (data?.usage) {
this._emitTokenUsage({
inputTokens: data.usage.prompt_tokens || 0,
outputTokens: data.usage.completion_tokens || 0,
totalTokens: data.usage.total_tokens || 0,
});
}
return data?.choices?.[0]?.message?.content || '';
});
}
/**
* 带工具声明的结构化对话 — OpenAI Chat Completions Function Calling
*
* 接受统一消息格式，内部转换为 OpenAI Chat Completions 消息格式。
* 兼容 DeepSeek / Ollama 等 OpenAI-Compatible API。
*
* @param prompt fallback prompt
* @param opts 统一参数
* @returns >|null}>}
*/
async chatWithTools(prompt, opts = {}) {
return this._withRetry(async () => {
const { messages: rawMessages, toolSchemas: rawToolSchemas, toolChoice = 'auto', systemPrompt, temperature = 0.7, maxTokens = 4096, } = opts;
const unifiedMessages = rawMessages;
const toolSchemas = rawToolSchemas;
// 统一消息 → OpenAI Chat Completions messages
const messages = [];
if (systemPrompt) {
messages.push({ role: 'system', content: systemPrompt });
}
const srcMessages = unifiedMessages && unifiedMessages.length > 0
? unifiedMessages
: [{ role: 'user', content: prompt }];
for (const msg of srcMessages) {
if (msg.role === 'user') {
messages.push({ role: 'user', content: msg.content });
}
else if (msg.role === 'assistant') {
const m = { role: 'assistant', content: msg.content || null };
if (msg.toolCalls && msg.toolCalls.length > 0) {
m.tool_calls = msg.toolCalls.map((tc) => ({
id: tc.id,
type: 'function',
function: {
name: tc.name,
arguments: JSON.stringify(tc.args || {}),
},
}));
}
messages.push(m);
}
else if (msg.role === 'tool') {
messages.push({
role: 'tool',
tool_call_id: msg.toolCallId,
content: msg.content || '',
});
}
}
const body = {
model: this.model,
messages,
temperature,
max_tokens: maxTokens,
};
// 标准 tool schemas → OpenAI tools format
if (toolSchemas && toolSchemas.length > 0) {
body.tools = toolSchemas.map((s) => ({
type: 'function',
function: {
name: s.name,
description: s.description || '',
parameters: s.parameters || { type: 'object', properties: {} },
},
}));
}
// toolChoice → OpenAI tool_choice
if (toolChoice === 'required') {
body.tool_choice = 'required';
}
else if (toolChoice === 'none') {
body.tool_choice = 'none';
}
else {
body.tool_choice = 'auto';
}
const data = await this._post(`${this.baseUrl}/chat/completions`, body, opts.abortSignal);
return this.#parseToolResponse(data);
});
}
/**
* 解析 OpenAI Chat Completions 响应 — 提取 tool_calls 或 text
*
* OpenAI 返回格式:
* choices[0].message.tool_calls[]: { id, type: 'function', function: { name, arguments(JSON str) } }
*/
#parseToolResponse(data) {
const choice = data?.choices?.[0];
// 提取 token 用量 (OpenAI usage)
const usage = data?.usage
? {
inputTokens: data.usage.prompt_tokens || 0,
outputTokens: data.usage.completion_tokens || 0,
totalTokens: data.usage.total_tokens || 0,
}
: null;
if (!choice) {
return { text: '', functionCalls: null, usage };
}
const message = choice.message;
const text = message?.content || null;
if (message?.tool_calls?.length > 0) {
const functionCalls = message.tool_calls
.filter((tc) => tc.type === 'function')
.map((tc) => ({
id: tc.id,
name: tc.function.name,
args: (() => {
try {
return JSON.parse(tc.function.arguments || '{}');
}
catch {
return {};
}
})(),
}));
if (functionCalls.length > 0) {
this.logger?.debug(`[OpenAI] native function calls: ${functionCalls.map((fc) => fc.name).join(', ')}`);
return { text, functionCalls, usage };
}
}
return { text, functionCalls: null, usage };
}
async summarize(code) {
const prompt = `请对以下代码生成结构化摘要，返回 JSON 格式 {title, description, language, patterns: [], keyAPIs: []}:\n\n${code}`;
return ((await this.chatWithStructuredOutput(prompt, {
temperature: 0.3,
maxTokens: 4096,
})) || { title: '', description: '' });
}
/**
* Structured Output — OpenAI JSON mode
*
* 使用 response_format: { type: 'json_object' } 强制返回合法 JSON。
* 兼容 DeepSeek / Ollama 等 OpenAI-Compatible API。
*/
async chatWithStructuredOutput(prompt, opts = {}) {
return this._withRetry(async () => {
const { temperature = 0.3, maxTokens = 32768, systemPrompt } = opts;
const messages = [];
if (systemPrompt) {
messages.push({ role: 'system', content: systemPrompt });
}
messages.push({ role: 'user', content: prompt });
const body = {
model: this.model,
messages,
temperature,
max_tokens: maxTokens,
response_format: { type: 'json_object' },
};
const data = await this._post(`${this.baseUrl}/chat/completions`, body);
// 提取 token 用量
if (data?.usage) {
this._emitTokenUsage({
inputTokens: data.usage.prompt_tokens || 0,
outputTokens: data.usage.completion_tokens || 0,
totalTokens: data.usage.total_tokens || 0,
});
}
const text = data?.choices?.[0]?.message?.content || '';
if (!text) {
return null;
}
try {
return JSON.parse(text);
}
catch {
// JSON mode 极少出错，降级到 extractJSON
const openChar = opts.openChar || '{';
const closeChar = opts.closeChar || '}';
return this.extractJSON(text, openChar, closeChar);
}
});
}
async embed(text) {
const texts = Array.isArray(text) ? text : [text];
try {
const body = {
model: this.embedModel,
input: texts.map((t) => t.slice(0, 8000)),
};
const data = await this._post(`${this.baseUrl}/embeddings`, body);
const embeddings = (data?.data || [])
.sort((a, b) => a.index - b.index)
.map((d) => d.embedding);
if (embeddings.length === 0) {
return Array.isArray(text) ? [] : [];
}
return Array.isArray(text) ? embeddings : embeddings[0];
}
catch (err) {
this.logger?.warn(`${this.name} embed failed, returning empty`, {
error: err.message,
});
return Array.isArray(text) ? texts.map(() => []) : [];
}
}
async _post(url, body, externalSignal) {
// Ollama 使用固定 dummy key，不需要校验
if (!this.apiKey && this.name !== 'ollama') {
const envKey = this.name === 'deepseek' ? 'ASD_DEEPSEEK_API_KEY' : 'ASD_OPENAI_API_KEY';
const err = new Error(`${this.name} API Key 未配置。请在 .env 中设置 ${envKey}，或运行 asd setup 完成配置。`);
err.code = 'API_KEY_MISSING';
throw err;
}
const controller = new AbortController();
const timer = setTimeout(() => controller.abort(), this.timeout);
// 外部中止信号 → 联动本地 controller
const onExternalAbort = () => controller.abort();
externalSignal?.addEventListener('abort', onExternalAbort, { once: true });
try {
const res = await this._fetch(url, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
Authorization: `Bearer ${this.apiKey}`,
},
body: JSON.stringify(body),
signal: controller.signal,
});
if (!res.ok) {
const err = new Error(`${this.name} API error: ${res.status}`);
err.status = res.status;
throw err;
}
return (await res.json());
}
finally {
clearTimeout(timer);
externalSignal?.removeEventListener('abort', onExternalAbort);
}
}
}
export default OpenAiProvider;