用自动化多智能体生成高质量波斯语销售对话数据集，助力伊朗中小企业电商客服升级。
MegaChat: A Synthetic Persian Q&A Dataset for High-Quality Sales Chatbot Evaluation
- 设计多智能体系统，自动从真实聊天频道抓取并生成带角色设定的问答对。
- 在6个不同频道测试中，新系统在5项质量指标中有4项优于传统检索增强生成模型。
- 适合需要低成本构建波斯语电商聊天机器人的中小企业及低资源语言研究者。
伊朗的中小型企业越来越多地利用Telegram进行销售，实时互动对转化至关重要。然而，开发针对此类场景的AI聊天机器人需要大量高质量的问答（Q&A）数据集，而这类数据集通常成本高昂且资源密集，尤其对于波斯语等低资源语言更是如此。本文提出MegaChat，首个专为评估基于Telegram的电商智能销售聊天机器人而设计的全合成波斯语问答数据集。我们设计了一种新颖的自动化多智能体架构，通过从活跃的Telegram购物频道收集数据，生成带有角色设定的问答对。系统包含专门负责问题生成、验证和优化的智能体，确保生成对话的真实性和多样性。为评估答案生成能力，我们对比了三种经典检索增强生成（RAG）模型与我们的先进代理系统，该系统具备多查询检索、重排序及角色对齐响应合成功能。使用GPT-5.1在六个不同维度上评估，结果显示，在五个多样化频道中，代理架构在四项指标上优于传统RAG模型，证明其可在不依赖昂贵人工标注或复杂微调的情况下，生成可扩展的高质量数据。MegaChat为中小企业提供了高效、低成本的解决方案，以构建专业化商业领域的智能客户交互系统，推动低资源语言的多语言对话AI发展。下载地址：https://github.com/MegaChat-Tech/MegaChat-DataSet
原文摘要 · Abstract (English)
Small and medium-sized enterprises (SMEs) in Iran increasingly leverage Telegram for sales, where real-time engagement is essential for conversion. However, developing AI-driven chatbots for this purpose requires large, high-quality question-and-answer (Q&A) datasets, which are typically expensive and resource-intensive to produce, especially for low-resource languages like Persian. In this paper, we introduce MegaChat, the first fully synthetic Persian Q&A dataset designed to evaluate intelligent sales chatbots in Telegram-based e-commerce. We propose a novel, automated multi-agent architecture that generates persona-aware Q&A pairs by collecting data from active Telegram shopping channels. The system employs specialized agents for question generation, validation, and refinement, ensuring the production of realistic and diverse conversational data. To evaluate answer generation, we compare three classic retrieval-augmented generation (RAG) models with our advanced agentic system, which features multi-query retrieval, reranking, and persona-aligned response synthesis. Using GPT-5.1 for evaluation across six quality dimensions, our results show that the agentic architecture outperformed traditional RAG models in 4 out of 5 diverse channels, demonstrating its ability to generate scalable, high-quality datasets without relying on expensive human annotation or complex fine-tuning. MegaChat provides SMEs with an efficient, cost-effective solution for building intelligent customer engagement systems in specialized commercial domains, enabling advancements in multilingual conversational AI for low-resource languages. Download: https://github.com/MegaChat-Tech/MegaChat-DataSet
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