Paper-Helper
基于 DeepSeek-V3 的混合检索增强生成 (Hybrid RAG) 科研助手。支持本地向量库 ChromaDB、Rerank 重排序及联网搜索。
```text reading_Agent/ ├── .streamlit/ │ └── secrets.toml # [关键] 存放 API 密钥配置文件 ├── history_data/ # [自动生成] 存放对话历史 JSON ├── chroma_db/ # [自动生成] 向量数据库文件 ├── modules/ # 核心功能模块 │ ├── database.py # ChromaDB 增删改查 │ ├── embedder.py # Embedding API 封装 │ ├── reranker.py # Rerank API 封装 │ ├── retriever.py # 混合检索逻辑 │ ├── processor.py # 文档解析与切分 │ ├── web_search.py # 联网搜索模块 │ └── history.py # 历史记录管理 ├── app.py # Streamlit 主程序入口 ├── requirements.txt # 项目依赖 └── README.md # 说明文档 🚀 快速开始
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/zhaokai-tech-paper-helper — read its card at https://meshkore.com/agent/zhaokai-tech-paper-helper/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/zhaokai-tech-paper-helperFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/zhaokai-tech-paper-helper/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own Paper-Helper?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.