flashbacker/lib/agents/base/flashback-agent.js

Claude Code state management with session continuity and AI personas

"use strict";
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.FlashbackAgent = void 0;
const fs_extra_1 = __importDefault(require("fs-extra"));
const path_1 = __importDefault(require("path"));
// Use runtime requires to minimize TypeScript type-load for heavy AI SDK types
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { generateText, stepCountIs } = require('ai');
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { openai } = require('@ai-sdk/openai');
class FlashbackAgent {
    async readAgentTemplate(projectDir, relativePath) {
        const promptsRoot = path_1.default.join(projectDir, '.claude', 'flashback', 'prompts');
        const fullPath = path_1.default.join(promptsRoot, relativePath);
        const raw = await fs_extra_1.default.readFile(fullPath, 'utf-8');
        // Simple parsing: first line as title (ignored), full file as system; prompt minimal
        return {
            system: raw,
            prompt: 'Execute the agent workflow as instructed by the system prompt.',
        };
    }
    async logAgentCost(projectDir, agentName, usage, toolCallsCount) {
        try {
            const logDir = path_1.default.join(projectDir, '.claude', 'flashback', 'log');
            await fs_extra_1.default.ensureDir(logDir);
            const logPath = path_1.default.join(logDir, 'agents.log');
            const tokens = usage?.totalTokens ?? 0;
            const line = `${new Date().toISOString()} agent=${agentName} tokens=${tokens} toolCalls=${toolCallsCount ?? 0}`;
            await fs_extra_1.default.appendFile(logPath, line + '\n');
        }
        catch {
            // best-effort logging
        }
    }
    async prepareStepCompression(messages) {
        if (!Array.isArray(messages) || messages.length <= 20)
            return {};
        const early = messages.slice(0, 5);
        const recent = messages.slice(-10);
        // Basic naive summary token to inform the model; real summarization can be added later
        const summary = 'Previous context summarized for brevity.';
        return {
            messages: [
                ...early,
                { role: 'system', content: `Previous context: ${summary}` },
                ...recent,
            ],
        };
    }
    async executeWithTemplate(options) {
        const { projectDir, agentName, stepLimit, tokenBudget = 200000, tools = {}, templatePath } = options;
        try {
            const template = await this.readAgentTemplate(projectDir, templatePath);
            const result = await generateText({
                model: openai('gpt-5-nano'),
                tools: tools,
                stopWhen: stepCountIs(stepLimit),
                system: template.system,
                prompt: template.prompt,
                prepareStep: async ({ messages }) => {
                    return this.prepareStepCompression(messages);
                },
                onStepFinish: async ({ usage, toolCalls }) => {
                    await this.logAgentCost(projectDir, agentName, usage, toolCalls?.length ?? 0);
                    if ((usage?.totalTokens ?? 0) > tokenBudget) {
                        throw new Error(`Agent ${agentName} exceeded token budget: ${usage?.totalTokens}`);
                    }
                },
            });
            return {
                success: true,
                text: result.text,
                toolCalls: result.steps?.flatMap((s) => s.toolCalls) ?? [],
                tokensUsed: result.usage?.totalTokens,
            };
        }
        catch (error) {
            return {
                success: false,
                error: error instanceof Error ? error.message : String(error),
            };
        }
    }
}
exports.FlashbackAgent = FlashbackAgent;
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