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Author SHA1 Message Date
GitHub Actions
b6ab6f1993 chore: release v0.2.5 2025-08-08 22:32:27 +00:00
joshuashaffer
9f2e82a838 Propagate hosts argument for ollama through chat.py (#21)
* Propigate hosts argument for ollama through chat.py

* Apply suggestions from code review

Good AI slop suggestions.

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2025-08-08 15:31:15 -07:00
yichuan520030910320
0b2b799d5a [README]fix instructions in cli 2025-08-08 01:04:13 -07:00
yichuan520030910320
0f790fbbd9 docs: polish README and add optimized MCP integration image
- Improve grammar and sentence structure in MCP section
- Add proper markdown image formatting with relative paths
- Optimize mcp_leann.png size (1.3MB -> 224KB)
- Update data description to be more specific about Chinese content
2025-08-08 00:58:36 -07:00
8 changed files with 43 additions and 44 deletions

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@@ -6,6 +6,7 @@
<img src="https://img.shields.io/badge/Python-3.9%2B-blue.svg" alt="Python 3.9+">
<img src="https://img.shields.io/badge/License-MIT-green.svg" alt="MIT License">
<img src="https://img.shields.io/badge/Platform-Linux%20%7C%20macOS-lightgrey" alt="Platform">
<img src="https://img.shields.io/badge/MCP-Native%20Integration-blue?style=flat-square" alt="MCP Integration">
</p>
<h2 align="center" tabindex="-1" class="heading-element" dir="auto">
@@ -16,7 +17,10 @@ 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 **[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.
**Ready to RAG Everything?** Transform your laptop into a personal AI assistant that can semantic 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)**, **[codebase](#-claude-code-integration-transform-your-development-workflow)**\* , or external knowledge bases (i.e., 60M documents) - all on your laptop, with zero cloud costs and complete privacy.
\* Claude Code only supports basic `grep`-style keyword search. **LEANN** is a drop-in **semantic search MCP service fully compatible with Claude Code**, unlocking intelligent retrieval without changing your workflow.
@@ -26,7 +30,7 @@ LEANN achieves this through *graph-based selective recomputation* with *high-deg
<img src="assets/effects.png" alt="LEANN vs Traditional Vector DB Storage Comparison" width="70%">
</p>
> **The numbers speak for themselves:** Index 60 million Wikipedia chunks in just 6GB instead of 201GB. From emails to browser history, everything fits on your laptop. [See detailed benchmarks for different applications below ↓](#storage-comparison)
> **The numbers speak for themselves:** Index 60 million text chunks in just 6GB instead of 201GB. From emails to browser history, everything fits on your laptop. [See detailed benchmarks for different applications below ↓](#storage-comparison)
🔒 **Privacy:** Your data never leaves your laptop. No OpenAI, no cloud, no "terms of service".
@@ -211,30 +215,6 @@ 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!
@@ -243,7 +223,7 @@ Ask questions directly about your personal PDFs, documents, and any directory co
<img src="videos/paper_clear.gif" alt="LEANN Document Search Demo" width="600">
</p>
The example below asks a question about summarizing our paper (uses default data in `data/`, which is a directory with diverse data sources: two papers, Pride and Prejudice, and a README in Chinese) and this is the **easiest example** to run here:
The example below asks a question about summarizing our paper (uses default data in `data/`, which is a directory with diverse data sources: two papers, Pride and Prejudice, and a Technical report about LLM in Huawei in Chinese), and this is the **easiest example** to run here:
```bash
source .venv/bin/activate # Don't forget to activate the virtual environment
@@ -438,6 +418,26 @@ Once the index is built, you can ask questions like:
</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.
**Key features:**
- 🔍 **Semantic code search** across your entire project
- 📚 **Context-aware assistance** for debugging and development
- 🚀 **Zero-config setup** with automatic language detection
```bash
# Install LEANN globally for MCP integration
uv tool install leann-core
# Setup is automatic - just start using Claude Code!
```
Try our fully agentic pipeline with auto query rewriting, semantic search planning, and more:
![LEANN MCP Integration](assets/mcp_leann.png)
**Ready to supercharge your coding?** [Complete Setup Guide →](packages/leann-mcp/README.md)
## 🖥️ Command Line Interface
@@ -467,11 +467,8 @@ leann --help
### Usage Examples
```bash
# Build an index from current directory (default)
leann build my-docs
# Or from specific directory
leann build my-docs --docs ./documents
# build from a specific directory, and my_docs is the index name
leann build my-docs --docs ./your_documents
# Search your documents
leann search my-docs "machine learning concepts"

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@@ -4,8 +4,8 @@ build-backend = "scikit_build_core.build"
[project]
name = "leann-backend-diskann"
version = "0.2.4"
dependencies = ["leann-core==0.2.4", "numpy", "protobuf>=3.19.0"]
version = "0.2.5"
dependencies = ["leann-core==0.2.5", "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 = "0.2.4"
version = "0.2.5"
description = "Custom-built HNSW (Faiss) backend for the Leann toolkit."
dependencies = [
"leann-core==0.2.4",
"leann-core==0.2.5",
"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 = "0.2.4"
version = "0.2.5"
description = "Core API and plugin system for LEANN"
readme = "README.md"
requires-python = ">=3.9"

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@@ -17,12 +17,12 @@ logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def check_ollama_models() -> list[str]:
def check_ollama_models(host: str) -> list[str]:
"""Check available Ollama models and return a list"""
try:
import requests
response = requests.get("http://localhost:11434/api/tags", timeout=5)
response = requests.get(f"{host}/api/tags", timeout=5)
if response.status_code == 200:
data = response.json()
return [model["name"] for model in data.get("models", [])]
@@ -309,10 +309,12 @@ def search_hf_models(query: str, limit: int = 10) -> list[str]:
return search_hf_models_fuzzy(query, limit)
def validate_model_and_suggest(model_name: str, llm_type: str) -> str | None:
def validate_model_and_suggest(
model_name: str, llm_type: str, host: str = "http://localhost:11434"
) -> str | None:
"""Validate model name and provide suggestions if invalid"""
if llm_type == "ollama":
available_models = check_ollama_models()
available_models = check_ollama_models(host)
if available_models and model_name not in available_models:
error_msg = f"Model '{model_name}' not found in your local Ollama installation."
@@ -469,7 +471,7 @@ class OllamaChat(LLMInterface):
requests.get(host)
# Pre-check model availability with helpful suggestions
model_error = validate_model_and_suggest(model, "ollama")
model_error = validate_model_and_suggest(model, "ollama", host)
if model_error:
raise ValueError(model_error)

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@@ -30,7 +30,7 @@ claude mcp add leann-server -- leann_mcp
```bash
# Build an index for your project
leann build my-project
leann build my-project --docs ./ #change to your doc PATH
# Start Claude Code
claude

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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "leann"
version = "0.2.4"
version = "0.2.5"
description = "LEANN - The smallest vector index in the world. RAG Everything with LEANN!"
readme = "README.md"
requires-python = ">=3.9"