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Initial monorepo setup with npm workspaces and dual TypeScript configuration
- Set up npm workspaces for three packages: pi-tui, pi-agent, and pi (pods) - Implemented dual TypeScript configuration: - Root tsconfig.json with path mappings for development and type checking - Package-specific tsconfig.build.json for clean production builds - Configured lockstep versioning with sync script for inter-package dependencies - Added comprehensive documentation for development and publishing workflows - All packages at version 0.5.0 ready for npm publishing
This commit is contained in:
Mario Zechner
commit
a74c5da112
63 changed files with 14558 additions and 0 deletions
294
packages/agent/src/cli.ts
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294
packages/agent/src/cli.ts
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#!/usr/bin/env node
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import chalk from "chalk";
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import { createInterface } from "readline";
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import type { AgentConfig } from "./agent.js";
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import { Agent } from "./agent.js";
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import { parseArgs, printHelp as printHelpArgs } from "./args.js";
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import { ConsoleRenderer } from "./renderers/console-renderer.js";
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import { JsonRenderer } from "./renderers/json-renderer.js";
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import { TuiRenderer } from "./renderers/tui-renderer.js";
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import { SessionManager } from "./session-manager.js";
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// Define argument structure
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const argDefs = {
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"base-url": {
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type: "string" as const,
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default: "https://api.openai.com/v1",
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description: "API base URL",
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},
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"api-key": {
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type: "string" as const,
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default: process.env.OPENAI_API_KEY || "",
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description: "API key",
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showDefault: "$OPENAI_API_KEY",
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},
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model: {
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type: "string" as const,
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default: "gpt-5-mini",
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description: "Model name",
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},
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api: {
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type: "string" as const,
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default: "completions",
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description: "API type",
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choices: [
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{ value: "completions", description: "OpenAI Chat Completions API (most models)" },
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{ value: "responses", description: "OpenAI Responses API (GPT-OSS models)" },
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],
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},
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"system-prompt": {
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type: "string" as const,
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default: "You are a helpful assistant.",
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description: "System prompt",
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},
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continue: {
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type: "flag" as const,
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alias: "c",
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description: "Continue previous session",
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},
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json: {
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type: "flag" as const,
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description: "Output as JSONL",
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},
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help: {
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type: "flag" as const,
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alias: "h",
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description: "Show this help message",
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},
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};
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interface JsonCommand {
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type: "message" | "interrupt";
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content?: string;
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}
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function printHelp(): void {
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const usage = `Usage: pi-agent [options] [messages...]
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Examples:
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# Single message (default OpenAI, GPT-5 Mini, OPENAI_API_KEY env var)
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pi-agent "What is 2+2?"
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# Multiple messages processed sequentially
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pi-agent "What is 2+2?" "What about 3+3?"
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# Interactive chat mode (no messages = interactive)
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pi-agent
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# Continue most recently modified session in current directory
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pi-agent --continue "Follow up question"
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# GPT-OSS via Groq
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pi-agent --base-url https://api.groq.com/openai/v1 --api-key $GROQ_API_KEY --model openai/gpt-oss-120b
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# GLM 4.5 via OpenRouter
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pi-agent --base-url https://openrouter.ai/api/v1 --api-key $OPENROUTER_API_KEY --model z-ai/glm-4.5
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# Claude via Anthropic (no prompt caching support - see https://docs.anthropic.com/en/api/openai-sdk)
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pi-agent --base-url https://api.anthropic.com/v1 --api-key $ANTHROPIC_API_KEY --model claude-opus-4-1-20250805`;
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printHelpArgs(argDefs, usage);
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}
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async function runJsonInteractiveMode(config: AgentConfig, sessionManager: SessionManager): Promise<void> {
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const rl = createInterface({
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input: process.stdin,
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output: process.stdout,
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terminal: false, // Don't interpret control characters
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});
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const renderer = new JsonRenderer();
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const agent = new Agent(config, renderer, sessionManager);
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let isProcessing = false;
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let pendingMessage: string | null = null;
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const processMessage = async (content: string): Promise<void> => {
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isProcessing = true;
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try {
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await agent.ask(content);
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} catch (e: any) {
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await renderer.on({ type: "error", message: e.message });
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} finally {
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isProcessing = false;
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// Process any pending message
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if (pendingMessage) {
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const msg = pendingMessage;
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pendingMessage = null;
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await processMessage(msg);
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}
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}
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};
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// Listen for lines from stdin
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rl.on("line", (line) => {
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try {
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const command = JSON.parse(line) as JsonCommand;
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switch (command.type) {
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case "interrupt":
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agent.interrupt();
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isProcessing = false;
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break;
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case "message":
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if (!command.content) {
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renderer.on({ type: "error", message: "Message content is required" });
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return;
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}
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if (isProcessing) {
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// Queue the message for when the agent is done
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pendingMessage = command.content;
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} else {
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processMessage(command.content);
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}
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break;
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default:
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renderer.on({ type: "error", message: `Unknown command type: ${(command as any).type}` });
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}
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} catch (e) {
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renderer.on({ type: "error", message: `Invalid JSON: ${e}` });
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}
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});
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// Wait for stdin to close
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await new Promise<void>((resolve) => {
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rl.on("close", () => {
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resolve();
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});
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});
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}
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async function runTuiInteractiveMode(agentConfig: AgentConfig, sessionManager: SessionManager): Promise<void> {
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const sessionData = sessionManager.getSessionData();
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if (sessionData) {
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console.log(chalk.dim(`Resuming session with ${sessionData.events.length} events`));
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}
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const renderer = new TuiRenderer();
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// Initialize TUI BEFORE creating the agent to prevent double init
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await renderer.init();
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const agent = new Agent(agentConfig, renderer, sessionManager);
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renderer.setInterruptCallback(() => {
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agent.interrupt();
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});
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if (sessionData) {
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agent.setEvents(sessionData ? sessionData.events.map((e) => e.event) : []);
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for (const sessionEvent of sessionData.events) {
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const event = sessionEvent.event;
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if (event.type === "assistant_start") {
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renderer.renderAssistantLabel();
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} else {
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await renderer.on(event);
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}
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}
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}
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while (true) {
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const userInput = await renderer.getUserInput();
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try {
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await agent.ask(userInput);
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} catch (e: any) {
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await renderer.on({ type: "error", message: e.message });
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}
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}
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}
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async function runSingleShotMode(
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agentConfig: AgentConfig,
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sessionManager: SessionManager,
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messages: string[],
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jsonOutput: boolean,
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): Promise<void> {
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const sessionData = sessionManager.getSessionData();
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const renderer = jsonOutput ? new JsonRenderer() : new ConsoleRenderer();
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const agent = new Agent(agentConfig, renderer, sessionManager);
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if (sessionData) {
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if (!jsonOutput) {
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console.log(chalk.dim(`Resuming session with ${sessionData.events.length} events`));
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}
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agent.setEvents(sessionData ? sessionData.events.map((e) => e.event) : []);
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}
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for (const msg of messages) {
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try {
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await agent.ask(msg);
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} catch (e: any) {
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await renderer.on({ type: "error", message: e.message });
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}
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}
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}
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// Main function to use Agent as standalone CLI
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export async function main(args: string[]): Promise<void> {
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// Parse arguments
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const parsed = parseArgs(argDefs, args);
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// Show help if requested
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if (parsed.help) {
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printHelp();
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return;
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}
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// Extract configuration from parsed args
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const baseURL = parsed["base-url"];
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const apiKey = parsed["api-key"];
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const model = parsed.model;
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const continueSession = parsed.continue;
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const api = parsed.api as "completions" | "responses";
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const systemPrompt = parsed["system-prompt"];
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const jsonOutput = parsed.json;
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const messages = parsed._; // Positional arguments
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if (!apiKey) {
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throw new Error("API key required (use --api-key or set OPENAI_API_KEY)");
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}
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// Determine mode: interactive if no messages provided
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const isInteractive = messages.length === 0;
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// Create session manager
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const sessionManager = new SessionManager(continueSession);
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// Create or restore agent
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let agentConfig: AgentConfig = {
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apiKey,
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baseURL,
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model,
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api,
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systemPrompt,
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};
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if (continueSession) {
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const sessionData = sessionManager.getSessionData();
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if (sessionData) {
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agentConfig = {
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...sessionData.config,
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apiKey, // Allow overriding API key
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};
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}
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}
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// Run in appropriate mode
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if (isInteractive) {
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if (jsonOutput) {
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await runJsonInteractiveMode(agentConfig, sessionManager);
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} else {
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await runTuiInteractiveMode(agentConfig, sessionManager);
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}
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} else {
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await runSingleShotMode(agentConfig, sessionManager, messages, jsonOutput);
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}
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}
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// Run as CLI if invoked directly
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if (import.meta.url === `file://${process.argv[1]}`) {
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main(process.argv.slice(2)).catch((err) => {
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console.error(err);
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process.exit(1);
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});
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}
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