Pinme Llm

glitternetwork/pinme/skills/pinme-llm

作者 glitternetwork7822b0501607786958ecb458f3bd02a061933efa无许可证收录于 2026年10月9日更新于 2026年10月9日

Use this skill when a PinMe project (Worker TypeScript) needs to call OpenRouter-backed LLM APIs, including models, chat/completions, streaming, or OpenRouter web search. Guides AI to generate correct Worker TS code.

仅含说明Software DevelopmentAI & Agents
AI 生成的概览

指导编写 PinMe Worker TypeScript 代码，调用 PinMe 的 OpenRouter 代理接口，实现模型列表、对话补全、流式输出和网页搜索。

功能
该技能提供参考说明和 TypeScript 示例，用于在 PinMe Worker 中调用 PinMe 平台的 OpenRouter 代理 API。内容涵盖模型列表接口、支持流式输出和 OpenRouter 网页搜索的对话补全接口、环境变量、错误格式以及错误提取辅助函数。它产出的是指导说明和代码片段，而不是文件或脚本。
适用场景
当 PinMe Worker（TypeScript）项目需要调用由 OpenRouter 支持的 LLM API 时使用，包括列出模型、对话补全、SSE 流式输出或 OpenRouter 网页搜索。它用于生成针对 PinMe 代理的正确 Worker 代码。
运行要求
需要一个 PinMe Worker 项目，并具备自动注入的环境变量 API_KEY 和 PROJECT_NAME，同时需要能访问 PinMe API 基础地址（默认

PinMe Worker OpenRouter API Integration

Guides how to call PinMe platform's OpenRouter proxy APIs in a PinMe Worker (TypeScript). Workers use the PinMe project API key; they never hold the real OpenRouter API key.

Environment Variables

The following environment variables are automatically injected when the Worker is created — no manual configuration needed:

typescript
// backend/src/worker.tsexport interface Env {  DB: D1Database;  API_KEY: string;       // Project API Key from create_worker  PROJECT_NAME: string;  // Actual project_name from create_worker; must match API_KEY  BASE_URL?: string;     // Optional override for PinMe API base URL, defaults to https://pinme.cloud}

API_KEY authenticates the Worker to PinMe. PROJECT_NAME is required for chat/completions and must belong to the same project as API_KEY. When BASE_URL is not set, use https://pinme.cloud.

Models API

Endpoint: GET {BASE_URL}/api/v1/models Authentication: X-API-Key header (using env.API_KEY) Request Body: none

Use this when the Worker needs to list available OpenRouter models. The response body, status, and headers are passed through from OpenRouter /models.

typescript
async function listModels(env: Env): Promise<unknown> {  const baseUrl = env.BASE_URL ?? 'https://pinme.cloud';  const resp = await fetch(`${baseUrl}/api/v1/models`, {    headers: { 'X-API-Key': env.API_KEY },  });
  if (!resp.ok) {    throw new Error(await extractPinmeOpenRouterError(resp));  }
  return await resp.json();}

Chat Completions API

Endpoint: POST {BASE_URL}/api/v1/chat/completions?project_name={project_name} Authentication: X-API-Key header (using env.API_KEY) Request Body: OpenRouter chat/completions format, passed through as-is after a 1MB size check Streaming: Supports SSE (stream: true) Web Search: Supports OpenRouter openrouter:web_search server tool via the tools array

Request Format

json
{  "model": "openai/gpt-4o-mini",  "messages": [    { "role": "system", "content": "You are a helpful assistant." },    { "role": "user", "content": "Hello!" }  ],  "stream": true}

Use env.PROJECT_NAME from create_worker; always URL-encode it in the query string. For available models, call GET /api/v1/models or refer to OpenRouter model IDs.

OpenRouter Web Search

PinMe does not provide a raw search endpoint. To search the web, pass OpenRouter's openrouter:web_search server tool to chat/completions; the model decides whether and when to search.

Always set max_results and max_total_results to keep search volume and cost bounded.

typescript
async function searchWithLLM(env: Env, query: string): Promise<string> {  const baseUrl = env.BASE_URL ?? 'https://pinme.cloud';  const resp = await fetch(    `${baseUrl}/api/v1/chat/completions?project_name=${encodeURIComponent(env.PROJECT_NAME)}`,    {      method: 'POST',      headers: {        'Content-Type': 'application/json',        'X-API-Key': env.API_KEY,      },      body: JSON.stringify({        model: 'openai/gpt-5.2',        messages: [{ role: 'user', content: query }],        tools: [          {            type: 'openrouter:web_search',            parameters: {              engine: 'auto',              max_results: 5,              max_total_results: 10,            },          },        ],      }),    },  );
  if (!resp.ok) {    throw new Error(await extractPinmeOpenRouterError(resp));  }
  const data = await resp.json() as { choices: Array<{ message?: { content?: string } }> };  return data.choices[0]?.message?.content ?? '';}

Response Format

Successful requests return OpenRouter's raw response body.

Non-streaming Success (200):

json
{  "id": "chatcmpl-...",  "choices": [{ "message": { "role": "assistant", "content": "Hello!" }, "finish_reason": "stop" }],  "usage": { "prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15 }}

Streaming Success (200): SSE format

data: {"choices":[{"delta":{"content":"Hello"}}]}data: {"choices":[{"delta":{"content":" there"}}]}data: [DONE]

Errors:

HTTP StatusMeaningdata.error Example
401API Key missing, invalid, or mismatched with project_name"X-API-Key header is required" / "Invalid API key" / "Invalid API key or project name"
400project_name missing or OpenRouter key not configured"project_name is required" / "LLM service not configured for this project"
403LLM balance insufficient or disabled"Insufficient balance, please recharge to continue using LLM service"
413Request body exceeds 1MB"Request body too large (max 1MB)"
500Proxy failed before upstream request"Failed to build request"
502LLM service unavailable"LLM service unavailable"

If OpenRouter receives the request and returns a 4xx/5xx, PinMe passes through OpenRouter's status, headers, and response body instead of wrapping it.

Worker Example Code — Non-streaming

typescript
async function callLLM(  env: Env,  messages: Array<{ role: string; content: string }>,  model = 'openai/gpt-4o-mini',): Promise<{ content: string; error?: string }> {  const baseUrl = env.BASE_URL ?? 'https://pinme.cloud';  const resp = await fetch(    `${baseUrl}/api/v1/chat/completions?project_name=${encodeURIComponent(env.PROJECT_NAME)}`,    {      method: 'POST',      headers: {        'Content-Type': 'application/json',        'X-API-Key': env.API_KEY,      },      body: JSON.stringify({ model, messages }),    },  );
  if (!resp.ok) {    return { content: '', error: await extractPinmeOpenRouterError(resp) };  }
  const data = await resp.json() as { choices: Array<{ message: { content: string } }> };  return { content: data.choices[0]?.message?.content || '' };}
// Usage in routesasync function handleChat(request: Request, env: Env): Promise<Response> {  const { question } = await request.json() as { question: string };
  const result = await callLLM(env, [    { role: 'system', content: 'You are a helpful assistant.' },    { role: 'user', content: question },  ]);
  if (result.error) {    return json({ error: result.error }, 502);  }  return json({ answer: result.content });}

Worker Example Code — Streaming (SSE Passthrough)

typescript
async function handleChatStream(request: Request, env: Env): Promise<Response> {  const body = await request.text();  const baseUrl = env.BASE_URL ?? 'https://pinme.cloud';
  // Ensure stream=true in the request  let parsed = JSON.parse(body);  parsed.stream = true;
  const resp = await fetch(    `${baseUrl}/api/v1/chat/completions?project_name=${encodeURIComponent(env.PROJECT_NAME)}`,    {      method: 'POST',      headers: {        'Content-Type': 'application/json',        'X-API-Key': env.API_KEY,      },      body: JSON.stringify(parsed),    },  );
  if (!resp.ok) {    return json({ error: await extractPinmeOpenRouterError(resp) }, resp.status);  }
  // Pass through SSE stream directly  return new Response(resp.body, {    status: 200,    headers: {      'Content-Type': 'text/event-stream',      'Cache-Control': 'no-cache',      'Connection': 'keep-alive',      ...CORS_HEADERS,    },  });}

Frontend SSE Stream Consumer Example

typescript
async function streamChat(question: string, onChunk: (text: string) => void): Promise<void> {  const resp = await fetch(getApiUrl('/api/chat/stream'), {    method: 'POST',    headers: { 'Content-Type': 'application/json' },    body: JSON.stringify({ question }),  });
  const reader = resp.body!.getReader();  const decoder = new TextDecoder();  let buffer = '';
  while (true) {    const { done, value } = await reader.read();    if (done) break;
    buffer += decoder.decode(value, { stream: true });    const lines = buffer.split('\n');    buffer = lines.pop()!; // Keep incomplete line
    for (const line of lines) {      if (!line.startsWith('data: ')) continue;      const payload = line.slice(6);      if (payload === '[DONE]') return;
      const chunk = JSON.parse(payload) as { choices: Array<{ delta: { content?: string } }> };      const content = chunk.choices[0]?.delta?.content;      if (content) onChunk(content);    }  }}

Error Handling Pattern

For /api/v1/models and /api/v1/chat/completions, successful responses are raw OpenRouter responses. Proxy failures before the OpenRouter request use PinMe's wrapped error format:

typescript
interface PinmeResponse<T = unknown> {  code: number;   // 200=success, other=failure  msg: string;    // "ok" | "error" | "invalid params"  data?: T;       // Business data on success, may contain { error: string } on failure}

Recommended Error Extractor

typescript
async function extractPinmeOpenRouterError(resp: Response): Promise<string> {  const fallback = `HTTP ${resp.status}`;  try {    const body = await resp.clone().json() as PinmeResponse | { error?: { message?: string } } | { error?: string };    if ('data' in body && body.data && typeof body.data === 'object' && 'error' in body.data) {      return String((body.data as { error: unknown }).error);    }    if ('msg' in body && typeof body.msg === 'string' && body.msg) {      return body.msg;    }    if ('error' in body) {      const error = body.error;      if (typeof error === 'string') return error;      if (error && typeof error === 'object' && 'message' in error) {        return String((error as { message: unknown }).message);      }    }  } catch {    try {      const text = await resp.text();      if (text) return text;    } catch {      // Ignore and return fallback below.    }  }  return fallback;}

Optional JSON Helper

Use this helper for non-streaming POST calls. It returns the raw OpenRouter JSON on success.

typescript
async function callOpenRouterJSON<T>(url: string, apiKey: string, body: unknown): Promise<{ data?: T; error?: string }> {  let resp: Response;  try {    resp = await fetch(url, {      method: 'POST',      headers: { 'Content-Type': 'application/json', 'X-API-Key': apiKey },      body: JSON.stringify(body),    });  } catch {    return { error: 'Network error' };  }
  if (!resp.ok) {    return { error: await extractPinmeOpenRouterError(resp) };  }
  return { data: await resp.json() as T };}

Usage Example

typescript
const baseUrl = env.BASE_URL ?? 'https://pinme.cloud';
// Call LLM (non-streaming)const llmResult = await callOpenRouterJSON<{ choices: Array<{ message: { content: string } }> }>(  `${baseUrl}/api/v1/chat/completions?project_name=${encodeURIComponent(env.PROJECT_NAME)}`, env.API_KEY,  { model: 'openai/gpt-4o-mini', messages: [{ role: 'user', content: 'Hi' }] },);if (llmResult.error) return json({ error: llmResult.error }, 502);

来源与署名

来源：glitternetwork/pinme位于skills/pinme-llm提交7822b05

许可证： 无许可证

内容归原作者所有。SourceWeft 从公开仓库中收录这些内容。

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