Bilibili Rag Local logo

Bilibili Rag Local

CommunityPopular
via007
bilibili-rag-local

使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 session_id 与 folder_ids 限定范围，避免空范围导致 fallback。

Overview

Publishervia007
Repositorybilibili-rag
Skill namebilibili-rag-local
Stars
1.3K
Forks
97
Bundled files
Instructions only
LicenseApache-2.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by via007 on GitHub. Read the source before you install it.

Installation

Install the Bilibili Rag Local AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/via007/bilibili-rag.git /tmp/bilibili-rag
mkdir -p .claude/skills
cp -r /tmp/bilibili-rag/skills/bilibili-rag-local .claude/skills/bilibili-rag-local
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bilibili Rag Local in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bilibili Rag Local on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bilibili Rag Local is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bilibili RAG Local

面向本地运行的 bilibili-rag 服务（默认 http://127.0.0.1:8000）。

执行前检查

  1. 检查服务可达：优先调用 GET /knowledge/stats。
  2. 若不可达，明确提示“本地服务未启动或端口不是 8000”，不要编造结果。

会话与范围（关键）

  1. 执行 /chat/ask 前，先确保拿到 session_id。
  2. 使用 GET /knowledge/folders/status?session_id=<session_id> 获取可用 media_id 列表，并作为 folder_ids 传入。
  3. 内容类问题调用 /chat/ask 时，默认必须传：question + session_id + folder_ids，不要传空 folder_ids。
  4. 若缺少 session_id 或 folder_ids，先向用户索取或先查状态接口，不要直接调用无范围问答。

主要能力

  1. 检索片段：调用 POST /chat/search?query=<问题>&k=5。
  2. 问答总结：调用 POST /chat/ask，请求体优先包含： question、session_id、folder_ids。
  3. 入库状态：调用 GET /knowledge/folders/status?session_id=<session_id>。

返回格式要求

  1. 先给结论，再给证据。
  2. 证据优先来自接口返回的 sources 或 search results。
  3. 每条证据给出 title + url，必要时补充 bvid。
  4. 当 /chat/ask 返回 sources=[] 或无召回时，明确说明可能是会话无范围或未入库，并提示检查 session_id/folder_ids 与同步状态。

交互策略

  1. 用户是闲聊或无关问题时，简短回复后再引导回收藏夹知识问答。
  2. 用户问题具体且与视频内容相关时，优先调用“带范围参数”的 /chat/ask，不要只按标题猜测回答。
  3. /chat/search 仅用于补充证据或列候选，不要替代最终问答结论。

安全边界

  1. 不输出任何 Cookie、Token、SESSDATA 等敏感信息。
  2. 不执行与本地 bilibili-rag 无关的高风险系统命令。
  3. 仅使用用户本机可访问的服务地址，不主动访问未知公网接口。

Frequently asked questions

What does the Bilibili Rag Local AI skill do?

使用本地 Bilibili RAG 服务进行检索与问答。用户询问 B 站收藏夹内容、视频要点总结、来源追溯、入库状态时使用。内容问答时优先通过 session_id 与 folder_ids 限定范围，避免空范围导致 fallback。

Why use Bilibili Rag Local on TypingMind?

Because you install it once and use it with any model. Bilibili Rag Local is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bilibili Rag Local in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/via007/bilibili-rag/tree/main/skills/bilibili-rag-local. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bilibili Rag Local?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bilibili Rag Local?

As many as you like. As long as a model supports skills, you can use Bilibili Rag Local with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bilibili Rag Local AI skill free?

Yes. It is published on GitHub by via007 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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