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eladrave-filechat-rageladrave filechat RAG 搜索

Agent Skill

用于搭建或维护带检索增强的 RAG 工作流,适合让 Agent 处理知识库问答、向量检索、来源引用和事实核查。它可以辅助整理数据接入、Embedding、向量库、召回参数和回答生成流程。使用时需要确认数据来源、更新频率、召回阈值和引用展示方式,避免把未命中的资料或过期内容包装成确定事实。

总安装

3,493

周安装

147

GitHub Stars

公开资料未说明

下载量

1,223
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:eladrave-filechat-rag(eladrave filechat RAG 搜索)
来源仓库:https://github.com/eladrave/eladrave-filechat-rag
安装命令:
openclaw skills install eladrave-filechat-rag
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install eladrave-filechat-rag

简介

eladrave-filechat-rag 基于语义向量检索技术实现文档问答与知识库交互。

  • 适合处理 Google Drive 中存储的文档查询、来源引用和事实核查任务。
  • 支持多格式文档接入、Embedding 向量化及自定义召回阈值设置。
  • 使用时需授权访问指定文件夹,并注意数据更新频率与引用展示规范。
  • 避免将未命中结果包装为确定事实,确保回答附带可追溯来源。

SKILL.md

name
filechat-rag
description
>
metadata
openclaw
category
knowledge
requires
bins
["node", "npm", "gws"]
install
kind
node
package
@googleworkspace/cli
bins
["gws"]
label
Install Google Workspace CLI
kind
script
script
cd ./skills/filechat && npm install
label
Install FileChat Dependencies

FileChat RAG Skill

Your personal RAG (Retrieval-Augmented Generation) document library backed by Google Drive. Supports multiple Google Drive folders dynamically and allows choosing between Gemini or OpenAI for embeddings.

Setup & Bootstrap

If the user asks to use FileChat or asks a question about their files, FIRST verify that the required environment variables are set in /workspace/skills/filechat/.env:

  1. EMBEDDING_PROVIDER (either gemini or openai)
  2. GEMINI_API_KEY or OPENAI_API_KEY (Depending on the provider)

If they are missing, STOP and ask the user to provide them. Create the .env file like this:

echo "EMBEDDING_PROVIDER=gemini" > ./skills/filechat/.env
echo "GEMINI_API_KEY=your_key_here" >> ./skills/filechat/.env

How to Sync the Library

When the user asks to "sync", "flush", or "update" a specific FileChat folder, you must run the ingestion script. This connects to Google Drive, downloads all new/changed files (including PDFs, resolving shortcuts, and traversing sub-folders), chunks the text, gets embeddings, and saves them to a local JSON vector database keyed by the Folder ID.

You must supply the FOLDER_ID to the script. If you don't know the folder ID the user wants, ask them.

cd ./skills/filechat && node sync.js <FOLDER_ID>

How to Answer User Questions (RAG)

When a user asks a question about the contents of their documents, you MUST query the local vector store to fetch the relevant text chunks. You need the Folder ID.

cd ./skills/filechat && node query.js <FOLDER_ID> "What does my medical discharge say?"

The output will give you the most relevant text snippets, the original file names, and the Google Drive File IDs. Use the text snippets to formulate a comprehensive answer for the user. Always cite the file name you are referencing.

How to Retrieve and Send a Physical File

If the user asks for the actual file (e.g., "Send me the discharge PDF"), first find the File ID using the query script.

Then, use the gws CLI to download the file into your workspace:

gws drive files get --params '{"fileId": "<FILE_ID>", "alt": "media"}' --output /workspace/discharge.pdf

Then, reply to the user using the OpenClaw media attachment syntax: MEDIA:/workspace/discharge.pdf to send the physical file directly to their chat window.

How to Store a New File for the User

If the user uploads a file and asks you to "store" or "save" it:

  1. Upload it to their specific FileChat Google Drive folder using gws:
   gws drive files create \
     --json '{"name": "filename.pdf", "parents": ["<FOLDER_ID>"]}' \
     --upload /path/to/uploaded/file.pdf
  1. Trigger the sync process so the new file is immediately readable by the vector database:
   cd ./skills/filechat && node sync.js <FOLDER_ID>

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.44%
按下载量换算1,020

安全审计

VirusTotal

未展示

ClawScan

可疑

Static analysis

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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