Files
vibn-agent-runner/dist/agent-runner.js
2026-02-26 14:50:20 -08:00

118 lines
4.2 KiB
JavaScript

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.runAgent = runAgent;
const genai_1 = require("@google/genai");
const tools_1 = require("./tools");
const job_store_1 = require("./job-store");
const MAX_TURNS = 40; // safety cap — prevents infinite loops
/**
* Core Gemini agent loop.
*
* Sends the task to Gemini with the agent's system prompt and tools,
* then loops: execute tool calls → send results back → repeat until
* the model stops calling tools or MAX_TURNS is reached.
*/
async function runAgent(job, config, task, ctx) {
const apiKey = process.env.GOOGLE_API_KEY;
if (!apiKey) {
throw new Error('GOOGLE_API_KEY environment variable is not set');
}
const genai = new genai_1.GoogleGenAI({ apiKey });
// Build Gemini function declarations from our tool definitions
const functionDeclarations = config.tools.map(tool => ({
name: tool.name,
description: tool.description,
parameters: tool.parameters
}));
const tools = functionDeclarations.length > 0
? [{ functionDeclarations }]
: [];
const model = genai.models;
// Build conversation history
const history = [];
// Initial user message
let currentMessage = {
role: 'user',
parts: [{ text: task }]
};
let toolCallCount = 0;
let turn = 0;
let finalText = '';
(0, job_store_1.updateJob)(job.id, { status: 'running', progress: `Starting ${config.name} agent...` });
while (turn < MAX_TURNS) {
turn++;
// Add current message to history
history.push(currentMessage);
// Call Gemini
const response = await model.generateContent({
model: config.model || 'gemini-2.0-flash',
contents: history,
config: {
systemInstruction: config.systemPrompt,
tools: tools.length > 0 ? tools : undefined,
temperature: 0.2,
maxOutputTokens: 8192
}
});
const candidate = response.candidates?.[0];
if (!candidate) {
throw new Error('No response from Gemini');
}
// Add model response to history
const modelContent = {
role: 'model',
parts: candidate.content?.parts || []
};
history.push(modelContent);
// Extract function calls from the response
const functionCalls = candidate.content?.parts?.filter(p => p.functionCall) ?? [];
if (functionCalls.length === 0) {
// No tool calls — the agent is done
finalText = candidate.content?.parts
?.filter(p => p.text)
.map(p => p.text)
.join('') ?? '';
break;
}
// Execute all tool calls
const toolResultParts = [];
for (const part of functionCalls) {
const call = part.functionCall;
const callName = call.name ?? 'unknown';
const callArgs = (call.args ?? {});
toolCallCount++;
(0, job_store_1.updateJob)(job.id, {
progress: `Turn ${turn}: calling ${callName}...`,
toolCalls: [...(job.toolCalls || []), {
turn,
tool: callName,
args: callArgs,
timestamp: new Date().toISOString()
}]
});
let result;
try {
result = await (0, tools_1.executeTool)(callName, callArgs, ctx);
}
catch (err) {
result = { error: err instanceof Error ? err.message : String(err) };
}
toolResultParts.push({
functionResponse: {
name: callName,
response: { result }
}
});
}
// Next turn: send tool results back to the model
currentMessage = {
role: 'user',
parts: toolResultParts
};
}
if (turn >= MAX_TURNS && !finalText) {
finalText = `Agent reached the ${MAX_TURNS}-turn safety limit. Last tool call count: ${toolCallCount}.`;
}
return { finalText, toolCallCount, turns: turn };
}