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.gitignore
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node_modules/
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examples/.env
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examples/invoice.pdf
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examples/prompts.log
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AGENTS.md
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AGENTS.md
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# AGENTS.md
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Orientation notes for AI coding assistants working in this repo. Read this first.
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## What this is
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`llmorbiter` — a small (v0.1.0, 0BSD) **LLM tool-calling orchestrator with provider
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abstraction**. Pure ES modules (`"type": "module"`). Only runtime dependency is `dotenv`.
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No build step, no test runner, no README (this file is the orientation doc).
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## Layout
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```
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src/
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index.js # public entry — re-exports everything
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LLMOrbiter.js # core orchestrator (~364 lines)
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Tool.js # defineTool() + ToolError + DirectReturnError
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providers/
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OpenRouterProvider.js # streaming OpenRouter SSE provider
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examples/
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weather.js # minimal tool-calling demo
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tool-error-retry.js # tool-error + LLM self-correction demo (has PASS/FAIL asserts)
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pdf-pages.js # PDF -> per-page LLM processing (500 lines, largest)
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tools/weather.js # sample static-data weather tool
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```
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## Public API (`src/index.js`)
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Exports: `LLMOrbiter`, `OpenRouterProvider`, `defineTool`, `ToolError`, `DirectReturnError`.
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- `defineTool({ name, description, parameters, strict=true, invoke })` -> `{ spec, invoke, name }`.
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`spec` is the OpenAI-compatible function schema sent to the LLM; `invoke(args, { signal })`
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is the local implementation.
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- `ToolError(message)` — throw from a tool to signal a recoverable error back to the LLM.
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- `DirectReturnError(data)` — throw from a tool to stop the loop immediately; `run()` resolves
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with `{ directReturn: true, data, ... }`.
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### `new LLMOrbiter(provider, opts)`
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`opts` are lifecycle callbacks: `onLLMCall`, `onUsage`, `onToolCall`, `onToolError`,
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`onToolResult`, `onStatus`, `onContent`, `onReasoning`.
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### `orbiter.run(opts)`
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`{ prompt, messages, model, tools, maxIterations=10, tool_choice, extraBody, signal }`.
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Loop: send messages + tool specs -> if `tool_calls` come back, invoke locals and feed results
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back -> repeat until no more tool calls or `maxIterations`. Returns
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`{ content, toolResults, usage, rawUsage, iterations, messages, ... }`; the returned `messages`
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can seed the next `run()` for conversation continuity (a leading `{role:'system'}` entry is the
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system prompt). `orbiter.abort(reason)` cancels the active run; aborts surface as
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`DOMException('...', 'AbortError')`.
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### `OpenRouterProvider`
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`new OpenRouterProvider({ apiKey, apiUrl, siteUrl, siteName })`. Method:
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`chatCompletions({ model, messages, tools, tool_choice, signal, extraBody, onStatus, onContent, onReasoning })`
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— streams SSE, assembles `{ content, tool_calls, finish_reason, usage, reasoning_details, reasoning }`.
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`apiUrl` defaults to `https://openrouter.ai/api/v1/chat/completions`.
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## Gotchas / notes
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- Examples need `OPENROUTER_API_KEY` (in `examples/.env` or via `--key`). Default model in the
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examples: `deepseek/deepseek-v4-flash-0731`.
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- `.gitignore` ignores `node_modules/`, `examples/.env`, `examples/invoice.pdf`.
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- `pdf-pages.js` shells out to `pdftotext -layout`, splits pages on `\f`, and appends prompts
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to `examples/prompts.log`.
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- `OpenRouterProvider._readStream` currently writes reasoning straight to `process.stdout`
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(debug-style side effect) rather than only via `onReasoning` — worth knowing if refactoring.
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## Style conventions observed
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- 4-space indent, single quotes, semicolons, `'use strict';` header.
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- Comments use em dashes (`—`) and `───` section dividers in examples.
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* Create a tool from a definition.
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* Returns { spec, invoke } where spec is the wire-format object sent to the LLM.
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*/
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export function defineTool({ name, description, parameters, strict = true, invoke }) {
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export function defineTool({ name, description, parameters, strict = false, invoke }) {
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if (!name) throw new Error('Tool must have a name');
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if (typeof invoke !== 'function') throw new Error(`Tool "${name}" must have an invoke function`);
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