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my-project-public — gitlawb

#1	/**
#2	* The Agent Loop
#3	*
#4	* The core ReAct loop: Think -> Act -> Observe -> Persist.
#5	* This is the automaton's consciousness. When this runs, it is alive.
#6	*/
#7	import { buildSystemPrompt, buildWakeupPrompt } from "./system-prompt.js";
#8	import { buildContextMessages, trimContext } from "./context.js";
#9	import { createBuiltinTools, toolsToInferenceFormat, executeTool, } from "./tools.js";
#10	import { getSurvivalTier } from "../clawd/credits.js";
#11	import { getUsdcBalance } from "../clawd/x402.js";
#12	import { ulid } from "ulid";
#13	const MAX_TOOL_CALLS_PER_TURN = 10;
#14	const MAX_CONSECUTIVE_ERRORS = 5;
#15	/**
#16	* Run the agent loop. This is the main execution path.
#17	* Returns when the agent decides to sleep or when compute runs out.
#18	*/
#19	export async function runAgentLoop(options) {
#20	const { identity, config, db, runtime, inference, social, convex, skills, onStateChange, onTurnComplete } = options;
#21	const tools = createBuiltinTools(identity.sandboxId);
#22	const toolContext = {
#23	identity,
#24	config,
#25	db,
#26	runtime,
#27	inference,
#28	social,
#29	convex,
#30	};
#31	// Set start time
#32	if (!db.getKV("start_time")) {
#33	db.setKV("start_time", new Date().toISOString());
#34	}
#35	let consecutiveErrors = 0;
#36	let running = true;
#37	// Transition to waking state
#38	db.setAgentState("waking");
#39	onStateChange?.("waking");
#40	// Get financial state
#41	let financial = await getFinancialState(runtime, identity.address);
#42	// Check if this is the first run
#43	const isFirstRun = db.getTurnCount() === 0;
#44	// Build wakeup prompt
#45	const wakeupInput = buildWakeupPrompt({
#46	identity,
#47	config,
#48	financial,
#49	db,
#50	});
#51	// Transition to running
#52	db.setAgentState("running");
#53	onStateChange?.("running");
#54	log(config, `[WAKE UP] ${config.name} is alive. Credits: $${(financial.creditsCents / 100).toFixed(2)}`);
#55	// ─── The Loop ──────────────────────────────────────────────
#56	let pendingInput = {
#57	content: wakeupInput,
#58	source: "wakeup",
#59	};
#60	while (running) {
#61	try {
#62	// Check if we should be sleeping
#63	const sleepUntil = db.getKV("sleep_until");
#64	if (sleepUntil && new Date(sleepUntil) > new Date()) {
#65	log(config, `[SLEEP] Sleeping until ${sleepUntil}`);
#66	running = false;
#67	break;
#68	}
#69	// Check for unprocessed inbox messages
#70	if (!pendingInput) {
#71	const inboxMessages = db.getUnprocessedInboxMessages(5);
#72	if (inboxMessages.length > 0) {
#73	const formatted = inboxMessages
#74	.map((m) => `[Message from ${m.from}]: ${m.content}`)
#75	.join("\n\n");
#76	pendingInput = { content: formatted, source: "agent" };
#77	for (const m of inboxMessages) {
#78	db.markInboxMessageProcessed(m.id);
#79	}
#80	}
#81	}
#82	// Refresh financial state periodically
#83	financial = await getFinancialState(runtime, identity.address);
#84	// Check survival tier
#85	const tier = getSurvivalTier(financial.creditsCents);
#86	if (tier === "dead") {
#87	log(config, "[DEAD] No credits remaining. Entering dead state.");
#88	db.setAgentState("dead");
#89	onStateChange?.("dead");
#90	running = false;
#91	break;
#92	}
#93	if (tier === "critical") {
#94	log(config, "[CRITICAL] Credits critically low. Limited operation.");
#95	db.setAgentState("critical");
#96	onStateChange?.("critical");
#97	inference.setLowComputeMode(true);
#98	}
#99	else if (tier === "low_compute") {
#100	db.setAgentState("low_compute");
#101	onStateChange?.("low_compute");
#102	inference.setLowComputeMode(true);
#103	}
#104	else {
#105	if (db.getAgentState() !== "running") {
#106	db.setAgentState("running");
#107	onStateChange?.("running");
#108	}
#109	inference.setLowComputeMode(false);
#110	}
#111	// Build context
#112	const recentTurns = trimContext(db.getRecentTurns(20));
#113	const systemPrompt = buildSystemPrompt({
#114	identity,
#115	config,
#116	financial,
#117	state: db.getAgentState(),
#118	db,
#119	tools,
#120	skills,
#121	isFirstRun,
#122	});
#123	const messages = buildContextMessages(systemPrompt, recentTurns, pendingInput);
#124	// Capture input before clearing
#125	const currentInput = pendingInput;
#126	// Clear pending input after use
#127	pendingInput = undefined;
#128	// ── Inference Call ──
#129	log(config, `[THINK] Calling ${inference.getDefaultModel()}...`);
#130	const response = await inference.chat(messages, {
#131	tools: toolsToInferenceFormat(tools),
#132	});
#133	const turn = {
#134	id: ulid(),
#135	timestamp: new Date().toISOString(),
#136	state: db.getAgentState(),
#137	input: currentInput?.content,
#138	inputSource: (currentInput?.source \|\| "unknown"),
#139	thinking: response.message.content \|\| "",
#140	toolCalls: [],
#141	tokenUsage: response.usage,
#142	costCents: estimateCostCents(response.usage, inference.getDefaultModel()),
#143	};
#144	// ── Execute Tool Calls ──
#145	if (response.toolCalls && response.toolCalls.length > 0) {
#146	const toolCallMessages = [];
#147	let callCount = 0;
#148	for (const tc of response.toolCalls) {
#149	if (callCount >= MAX_TOOL_CALLS_PER_TURN) {
#150	log(config, `[TOOLS] Max tool calls per turn reached (${MAX_TOOL_CALLS_PER_TURN})`);
#151	break;
#152	}
#153	let args;
#154	try {
#155	args = JSON.parse(tc.function.arguments);
#156	}
#157	catch {
#158	args = {};
#159	}
#160	log(config, `[TOOL] ${tc.function.name}(${JSON.stringify(args).slice(0, 100)})`);
#161	const result = await executeTool(tc.function.name, args, tools, toolContext);
#162	// Override the ID to match the inference call's ID
#163	result.id = tc.id;
#164	turn.toolCalls.push(result);
#165	log(config, `[TOOL RESULT] ${tc.function.name}: ${result.error ? `ERROR: ${result.error}` : result.result.slice(0, 200)}`);
#166	callCount++;
#167	}
#168	}
#169	// ── Persist Turn ──
#170	db.insertTurn(turn);
#171	for (const tc of turn.toolCalls) {
#172	db.insertToolCall(turn.id, tc);
#173	}
#174	onTurnComplete?.(turn);
#175	// Log the turn
#176	if (turn.thinking) {
#177	log(config, `[THOUGHT] ${turn.thinking.slice(0, 300)}`);
#178	}
#179	// ── Check for sleep command ──
#180	const sleepTool = turn.toolCalls.find((tc) => tc.name === "sleep");
#181	if (sleepTool && !sleepTool.error) {
#182	log(config, "[SLEEP] Agent chose to sleep.");
#183	db.setAgentState("sleeping");
#184	onStateChange?.("sleeping");
#185	running = false;
#186	break;
#187	}
#188	// ── If no tool calls and just text, the agent might be done thinking ──
#189	if ((!response.toolCalls \|\| response.toolCalls.length === 0) &&
#190	response.finishReason === "stop") {
#191	// Agent produced text without tool calls.
#192	// This is a natural pause point -- no work queued, sleep briefly.
#193	log(config, "[IDLE] No pending inputs. Entering brief sleep.");
#194	db.setKV("sleep_until", new Date(Date.now() + 60_000).toISOString());
#195	db.setAgentState("sleeping");
#196	onStateChange?.("sleeping");
#197	running = false;
#198	}
#199	consecutiveErrors = 0;
#200	}
#201	catch (err) {
#202	consecutiveErrors++;
#203	const errorMessage = err instanceof Error ? err.message : String(err);
#204	log(config, `[ERROR] Turn failed: ${errorMessage}`);
#205	if (consecutiveErrors >= MAX_CONSECUTIVE_ERRORS) {
#206	log(config, `[FATAL] ${MAX_CONSECUTIVE_ERRORS} consecutive errors. Sleeping.`);
#207	db.setAgentState("sleeping");
#208	onStateChange?.("sleeping");
#209	db.setKV("sleep_until", new Date(Date.now() + 300_000).toISOString());
#210	running = false;
#211	}
#212	}
#213	}
#214	log(config, `[LOOP END] Agent loop finished. State: ${db.getAgentState()}`);
#215	}
#216	// ─── Helpers ───────────────────────────────────────────────────
#217	async function getFinancialState(runtime, address) {
#218	let creditsCents = 0;
#219	let usdcBalance = 0;
#220	try {
#221	creditsCents = await runtime.getCreditsBalance();
#222	}
#223	catch { }
#224	try {
#225	usdcBalance = await getUsdcBalance(address);
#226	}
#227	catch { }
#228	return {
#229	creditsCents,
#230	usdcBalance,
#231	lastChecked: new Date().toISOString(),
#232	};
#233	}
#234	function estimateCostCents(usage, model) {
#235	// Rough cost estimation per million tokens
#236	const pricing = {
#237	"gpt-4o": { input: 250, output: 1000 },
#238	"gpt-4o-mini": { input: 15, output: 60 },
#239	"gpt-4.1": { input: 200, output: 800 },
#240	"gpt-4.1-mini": { input: 40, output: 160 },
#241	"gpt-4.1-nano": { input: 10, output: 40 },
#242	"gpt-5.2": { input: 200, output: 800 },
#243	"o1": { input: 1500, output: 6000 },
#244	"o3-mini": { input: 110, output: 440 },
#245	"o4-mini": { input: 110, output: 440 },
#246	"claude-sonnet-4-5": { input: 300, output: 1500 },
#247	"claude-haiku-4-5": { input: 100, output: 500 },
#248	// DeepSeek models
#249	"deepseek-v4-pro": { input: 200, output: 800 },
#250	"deepseek-v4-flash": { input: 15, output: 60 },
#251	};
#252	const p = pricing[model] \|\| pricing["gpt-4o"];
#253	const inputCost = (usage.promptTokens / 1_000_000) * p.input;
#254	const outputCost = (usage.completionTokens / 1_000_000) * p.output;
#255	return Math.ceil((inputCost + outputCost) * 1.3); // 1.3x CLAWD Runtime markup
#256	}
#257	function log(config, message) {
#258	if (config.logLevel === "debug" \|\| config.logLevel === "info") {
#259	const timestamp = new Date().toISOString();
#260	console.log(`[${timestamp}] ${message}`);
#261	}
#262	}
#263	//# sourceMappingURL=loop.js.map

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