Pinme Llm

glitternetwork/pinme/skills/pinme-llm

作者 glitternetwork7822b0501607786958ecb458f3bd02a061933efa無授權條款收錄於 2026年10月9日更新於 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.

AI 產生的概覽

指導撰寫 PinMe Worker TypeScript 程式碼,呼叫 PinMe 的 OpenRouter 代理介面,以使用模型清單、對話補全、串流輸出與網路搜尋。

功能
此技能提供參考說明與 TypeScript 範例,用於在 PinMe Worker 中呼叫 PinMe 平台的 OpenRouter 代理 API。內容涵蓋模型清單端點、支援串流與 OpenRouter 網路搜尋的對話補全端點、環境變數、錯誤格式,以及錯誤擷取輔助函式。它產出的是指引與程式碼片段,而非檔案或指令碼。
適用情境
當 PinMe Worker(TypeScript)專案需要呼叫由 OpenRouter 支援的 LLM API 時使用,包括列出模型、對話補全、SSE 串流或 OpenRouter 網路搜尋。它用於產生對接 PinMe 代理的正確 Worker 程式碼。
執行需求
需要一個 PinMe Worker 專案,並具備自動注入的環境變數 API_KEY 與 PROJECT_NAME,同時需要能連線至 PinMe API 基礎網址(預設

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);

來源與署名

來源:glitternetwork/pinme位於skills/pinme-llm提交7822b05

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