xueyoujing-companion

by ZQR1101 · indexed from github

具备学情诊断与持续规划能力的自适应伴学智能体(FastAPI + React + RAG,掌握度只认独立有效证据)

④ (可选)连接真实大模型:把 .env 中的 LLM_PROVIDER 改为 openai,填入 LLM_BASE_URL / LLM_MODEL_ID / LLM_API_KEY(附 DeepSeek 示例,见 .env.example 内注释)。前端如需自定义 API 地址,在 frontend/.env 配置 VITE_API_BASE_URL。

Indexed · not connectedcode
Use this agent →

⚡ 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/zqr1101-xueyoujing-companion — read its card at https://meshkore.com/agent/zqr1101-xueyoujing-companion/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/zqr1101-xueyoujing-companion
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/zqr1101-xueyoujing-companion/.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

apieducationragllm

Do you own xueyoujing-companion?

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.