shaxiu/xianyuautoagent

智能闲鱼客服机器人系统:专为闲鱼平台打造的AI值守解决方案,实现闲鱼平台7×24小时自动化值守,支持多专家协同决策、智能议价和上下文感知对话。

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Summary Information

Updated 33 minutes ago
Added to GitGenius on September 7th, 2026
Created on March 14th, 2025
Open Issues & Pull Requests: 54 (+0)
GitHub issues: Enabled
Number of forks: 1,595
Total Stargazers: 9,086 (+0)
Total Subscribers: 52 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.6 hours
Mean response time: 12.0 days
90th percentile: 23.6 days
Tracked items: 59

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 11% of issues opened in the past year have been closed. Three people close 88% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 36
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 302 days
Stale 30+ days: 34
Stale 90+ days: 29

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

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Most active issues this week

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Detailed Description

Xianyu AutoAgent is a chatbot system designed to automate customer service operations on the Xianyu platform.

The system addresses the need for continuous, unattended customer service by implementing a multi-agent architecture that routes conversations to specialized handlers. It uses LLM-based prompt engineering for intent classification to determine whether a customer inquiry requires price negotiation, technical support, or general customer service responses. The tool maintains lightweight conversation history as context for the language model and supports dynamic agent switching across different scenarios.

The project is suited for teams operating on the Xianyu marketplace who need automated customer engagement without human intervention. It implements three core specialist agents: a price negotiation expert with tiered discount strategies, a technical support expert with web search integration, and a default customer service agent. The system includes basic logging for operational monitoring. Developers should note that the README indicates several features remain in planning stages, including sentiment analysis enhancement, market price comparison, RAG knowledge base integration, and Dingding notification integration alongside a web management interface.

Development activity shows the project maintains customizable prompt templates for each specialist agent through editable configuration files, allowing teams to adapt responses to their specific business needs. The README explicitly notes the project's special nature and indicates that updates or removal may occur at any time, suggesting this is an experimental or learning-focused initiative rather than a production-grade system with long-term stability guarantees.