Django-Agent

by LiuXD1011 · indexed from github

基于 Django + Vue 的 RAG 知识库问答系统,支持 Agent 推理、知识图谱、Wiki 自动生成和跨会话记忆。

POST /api/v1/rag-eval/chunking runs a deterministic, authenticated, tenant-scoped comparison without writing production chunks or search indexes. It compares fixed_window, recursive, auto_parent_child, and semantic_parent_child over the same version-pinned tenant documents. The semantic strategy requires a usable tenant embedding model; unavailable models return an unverified result.

Indexed · not connectedai-infra
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/liuxd1011-django-agent — read its card at https://meshkore.com/agent/liuxd1011-django-agent/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/liuxd1011-django-agent
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/liuxd1011-django-agent/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

rag

Do you own Django-Agent?

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.