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Author SHA1 Message Date
GitHub Actions
387ae21eba chore: release v0.2.4 2025-08-08 07:14:51 +00:00
Andy Lee
3cc329c3e7 fix: remove hardcoded paths from MCP server and documentation 2025-08-08 00:08:56 -07:00
Andy Lee
5567302316 feat: promote Claude Code integration as primary RAG feature 2025-08-07 23:19:19 -07:00
8 changed files with 35 additions and 173 deletions

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@@ -16,9 +16,7 @@ LEANN is an innovative vector database that democratizes personal AI. Transform
LEANN achieves this through *graph-based selective recomputation* with *high-degree preserving pruning*, computing embeddings on-demand instead of storing them all. [Illustration Fig →](#-architecture--how-it-works) | [Paper →](https://arxiv.org/abs/2506.08276)
**Ready to RAG Everything?** Transform your laptop into a personal AI assistant that can search your **[file system](#-personal-data-manager-process-any-documents-pdf-txt-md)**, **[emails](#-your-personal-email-secretary-rag-on-apple-mail)**, **[browser history](#-time-machine-for-the-web-rag-your-entire-browser-history)**, **[chat history](#-wechat-detective-unlock-your-golden-memories)**, or external knowledge bases (i.e., 60M documents) - all on your laptop, with zero cloud costs and complete privacy.
> **🚀 NEW: Claude Code Integration!** LEANN now provides native MCP integration for Claude Code users. Index your codebase and get intelligent code assistance directly in Claude Code. [Setup Guide →](packages/leann-mcp/README.md)
**Ready to RAG Everything?** Transform your laptop into a personal AI assistant that can search your **[codebase](#-claude-code-integration-transform-your-development-workflow)**, **[file system](#-personal-data-manager-process-any-documents-pdf-txt-md)**, **[emails](#-your-personal-email-secretary-rag-on-apple-mail)**, **[browser history](#-time-machine-for-the-web-rag-your-entire-browser-history)**, **[chat history](#-wechat-detective-unlock-your-golden-memories)**, or external knowledge bases (i.e., 60M documents) - all on your laptop, with zero cloud costs and complete privacy.
@@ -213,6 +211,30 @@ All RAG examples share these common parameters. **Interactive mode** is availabl
</details>
### 🚀 Claude Code Integration: Transform Your Development Workflow!
**The future of code assistance is here.** Transform your development workflow with LEANN's native MCP integration for Claude Code. Index your entire codebase and get intelligent code assistance directly in your IDE.
<p align="center">
<img src="https://img.shields.io/badge/MCP-Native%20Integration-blue?style=flat-square" alt="MCP Integration">
<a href="https://github.com/yichuan-w/LEANN/tree/feature/graph-partition-support?tab=readme-ov-file#rag-on-everything"><img src="https://img.shields.io/twitter/url?url=https%3A%2F%2Fgithub.com%2Fyichuan-w%2FLEANN&style=social" alt="Twitter"></a>
</p>
**Key features:**
- 🔍 **Semantic code search** across your entire project
- 📚 **Context-aware assistance** for debugging and development
- 🚀 **Zero-config setup** with automatic language detection
- 🔒 **Complete privacy** - your code never leaves your machine
```bash
# Install LEANN globally for MCP integration
uv tool install leann-core
# Setup is automatic - just start using Claude Code!
```
**Ready to supercharge your coding?** [Complete Setup Guide →](packages/leann-mcp/README.md)
### 📄 Personal Data Manager: Process Any Documents (`.pdf`, `.txt`, `.md`)!
Ask questions directly about your personal PDFs, documents, and any directory containing your files!
@@ -417,7 +439,6 @@ Once the index is built, you can ask questions like:
</details>
## 🖥️ Command Line Interface
LEANN includes a powerful CLI for document processing and search. Perfect for quick document indexing and interactive chat.

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@@ -1,150 +0,0 @@
# Claude Code x LEANN 集成指南
## ✅ 现状:已经可以工作!
好消息LEANN CLI已经完全可以在Claude Code中使用无需任何修改
## 🚀 立即开始
### 1. 激活环境
```bash
# 在LEANN项目目录下
source .venv/bin/activate.fish # fish shell
# 或
source .venv/bin/activate # bash shell
```
### 2. 基本命令
#### 查看现有索引
```bash
leann list
```
#### 搜索文档
```bash
leann search my-docs "machine learning" --recompute-embeddings
```
#### 问答对话
```bash
echo "What is machine learning?" | leann ask my-docs --llm ollama --model qwen3:8b --recompute-embeddings
```
#### 构建新索引
```bash
leann build project-docs --docs ./src --recompute-embeddings
```
## 💡 Claude Code 使用技巧
### 在Claude Code中直接使用
1. **激活环境**
```bash
cd /Users/andyl/Projects/LEANN-RAG
source .venv/bin/activate.fish
```
2. **搜索代码库**
```bash
leann search my-docs "authentication patterns" --recompute-embeddings --top-k 10
```
3. **智能问答**
```bash
echo "How does the authentication system work?" | leann ask my-docs --llm ollama --model qwen3:8b --recompute-embeddings
```
### 批量操作示例
```bash
# 构建项目文档索引
leann build project-docs --docs ./docs --force
# 搜索多个关键词
leann search project-docs "API authentication" --recompute-embeddings
leann search project-docs "database schema" --recompute-embeddings
leann search project-docs "deployment guide" --recompute-embeddings
# 问答模式
echo "What are the API endpoints?" | leann ask project-docs --recompute-embeddings
```
## 🎯 Claude 可以立即执行的工作流
### 代码分析工作流
```bash
# 1. 构建代码库索引
leann build codebase --docs ./src --backend hnsw --recompute-embeddings
# 2. 分析架构
echo "What is the overall architecture?" | leann ask codebase --recompute-embeddings
# 3. 查找特定功能
leann search codebase "user authentication" --recompute-embeddings --top-k 5
# 4. 理解实现细节
echo "How is user authentication implemented?" | leann ask codebase --recompute-embeddings
```
### 文档理解工作流
```bash
# 1. 索引项目文档
leann build docs --docs ./docs --recompute-embeddings
# 2. 快速查找信息
leann search docs "installation requirements" --recompute-embeddings
# 3. 获取详细说明
echo "What are the system requirements?" | leann ask docs --recompute-embeddings
```
## ⚠️ 重要提示
1. **必须使用 `--recompute-embeddings`** - 这是关键参数,不加会报错
2. **需要先激活虚拟环境** - 确保有LEANN的Python环境
3. **Ollama需要预先安装** - ask功能需要本地LLM
## 🔥 立即可用的Claude提示词
```
Help me analyze this codebase using LEANN:
1. First, activate the environment:
cd /Users/andyl/Projects/LEANN-RAG && source .venv/bin/activate.fish
2. Build an index of the source code:
leann build codebase --docs ./src --recompute-embeddings
3. Search for authentication patterns:
leann search codebase "authentication middleware" --recompute-embeddings --top-k 10
4. Ask about the authentication system:
echo "How does user authentication work in this codebase?" | leann ask codebase --recompute-embeddings
Please execute these commands and help me understand the code structure.
```
## 📈 下一步改进计划
虽然现在已经可以用,但还可以进一步优化:
1. **简化命令** - 默认启用recompute-embeddings
2. **配置文件** - 避免重复输入参数
3. **状态管理** - 自动检测环境和索引
4. **输出格式** - 更适合Claude解析的格式
但这些都是锦上添花,现在就能用起来!
## 🎉 总结
**LEANN现在就可以在Claude Code中完美工作**
- ✅ 搜索功能正常
- ✅ RAG问答功能正常
- ✅ 索引构建功能正常
- ✅ 支持多种数据源
- ✅ 支持本地LLM
只需要记住加上 `--recompute-embeddings` 参数就行!

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@@ -4,8 +4,8 @@ build-backend = "scikit_build_core.build"
[project]
name = "leann-backend-diskann"
version = "0.2.2"
dependencies = ["leann-core==0.2.2", "numpy", "protobuf>=3.19.0"]
version = "0.2.4"
dependencies = ["leann-core==0.2.4", "numpy", "protobuf>=3.19.0"]
[tool.scikit-build]
# Key: simplified CMake path

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@@ -6,10 +6,10 @@ build-backend = "scikit_build_core.build"
[project]
name = "leann-backend-hnsw"
version = "0.2.2"
version = "0.2.4"
description = "Custom-built HNSW (Faiss) backend for the Leann toolkit."
dependencies = [
"leann-core==0.2.2",
"leann-core==0.2.4",
"numpy",
"pyzmq>=23.0.0",
"msgpack>=1.0.0",

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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "leann-core"
version = "0.2.2"
version = "0.2.4"
description = "Core API and plugin system for LEANN"
readme = "README.md"
requires-python = ">=3.9"

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@@ -1,7 +1,6 @@
#!/usr/bin/env python3
import json
import os
import subprocess
import sys
@@ -62,10 +61,6 @@ def handle_request(request):
tool_name = request["params"]["name"]
args = request["params"].get("arguments", {})
# Set working directory and environment
env = os.environ.copy()
cwd = "/Users/andyl/Projects/LEANN-RAG"
try:
if tool_name == "leann_search":
cmd = [
@@ -76,18 +71,14 @@ def handle_request(request):
"--recompute-embeddings",
f"--top-k={args.get('top_k', 5)}",
]
result = subprocess.run(cmd, capture_output=True, text=True, cwd=cwd, env=env)
result = subprocess.run(cmd, capture_output=True, text=True)
elif tool_name == "leann_ask":
cmd = f'echo "{args["question"]}" | leann ask {args["index_name"]} --recompute-embeddings --llm ollama --model qwen3:8b'
result = subprocess.run(
cmd, shell=True, capture_output=True, text=True, cwd=cwd, env=env
)
result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
elif tool_name == "leann_list":
result = subprocess.run(
["leann", "list"], capture_output=True, text=True, cwd=cwd, env=env
)
result = subprocess.run(["leann", "list"], capture_output=True, text=True)
return {
"jsonrpc": "2.0",

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@@ -7,7 +7,7 @@ Intelligent code assistance using LEANN's vector search directly in Claude Code.
First, install LEANN CLI globally:
```bash
uv tool install leann
uv tool install leann-core
```
This makes the `leann` command available system-wide, which `leann_mcp` requires.

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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "leann"
version = "0.2.2"
version = "0.2.4"
description = "LEANN - The smallest vector index in the world. RAG Everything with LEANN!"
readme = "README.md"
requires-python = ">=3.9"