Emil
e196593c84
Autonomous research agent with web search, source analysis, and report synthesis. Built on Pi agent core. Available as CLI, programmatic API, and MCP server. Features: - 4 built-in tools: web_search, read_url, save_note, synthesize_report - CLI with TUI and print modes - Programmatic API via ResearchAgent class - MCP server with 3 tools: research, quick_search, read_url - Skills system for custom research behavior - Automatic .env file loading for API keys - Configurable max turns, output formats (markdown/JSON/bullet) - Automatic report saving to research-output/
41 lines
962 B
TypeScript
41 lines
962 B
TypeScript
/**
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* Custom Model Example
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*
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* Demonstrates how to use a custom model with the ResearchAgent.
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*
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* Run with:
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* TAVILY_API_KEY=*** \
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* OPENROUTER_API_KEY=*** \
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* npx tsx examples/custom-model.ts
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*/
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import { getModels } from "@earendil-works/pi-ai";
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import { ResearchAgent } from "../src/index.ts";
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const models = getModels("openrouter");
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const gpt4o = models.find((m) => m.id === "openai/gpt-4o");
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if (!gpt4o) {
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console.error("GPT-4o model not found");
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process.exit(1);
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}
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const agent = new ResearchAgent({
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model: gpt4o,
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thinkingLevel: "high",
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maxTurns: 15,
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});
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agent.subscribe((event) => {
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if (event.type === "message_update" && event.assistantMessageEvent.type === "text_delta") {
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process.stdout.write(event.assistantMessageEvent.delta);
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}
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});
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const topic = "Comparison of renewable energy storage solutions";
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console.log(`Researching: ${topic}\n`);
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const result = await agent.research(topic);
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console.log("\n\n" + result.report);
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