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Grepai Embeddings Ollama

yoanbernabeu/grepai-skills

This walks you through setting up Ollama as your embedding provider for GrepAI, which means your code never leaves your machine for semantic search. The guide covers four models with real tradeoffs: nomic-embed-text is the sweet spot at 274MB and fast, while mxbai-embed-large gives you maximum accuracy at 670MB. You get actual configuration snippets, performance tuning advice like keeping models loaded to avoid the 5-minute timeout, and troubleshooting for connection issues. Honestly the most useful part is the model comparison table, it tells you exactly what RAM you need and whether to prioritize speed or quality. Good for teams that can't send code to external APIs or don't want to pay embedding costs.

skills.sh installs
770
GitHub stars
20
last updated
Aug 21, 2026
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Install

$ npx -y skills add yoanbernabeu/grepai-skills --skill grepai-embeddings-ollama --agent claude-code

Installs into .claude/skills of the current project.

Files

GrepAI Embeddings with Ollama

This skill covers using Ollama as the embedding provider for GrepAI, enabling 100% private, local code search.

When to Use This Skill

  • Setting up private, local embeddings
  • Choosing the right Ollama model
  • Optimizing Ollama performance
  • Troubleshooting Ollama connection issues

Why Ollama?

AdvantageDescription
🔒 PrivacyCode never leaves your machine
💰 FreeNo API costs or usage limits
⚡ SpeedNo network latency
🔌 OfflineWorks without internet
🔧 ControlChoose your model

Prerequisites

  1. Ollama installed and running
  2. An embedding model downloaded
# Install Ollama
brew install ollama  # macOS
# or
curl -fsSL https://ollama.com/install.sh | sh  # Linux

# Start Ollama
ollama serve

# Download model
ollama pull nomic-embed-text

Configuration

Basic Configuration

# .grepai/config.yaml
embedder:
  provider: ollama
  model: nomic-embed-text
  endpoint: http://localhost:11434

With Custom Endpoint

SKILL.md on GitHub

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Details

Repository
github.com/yoanbernabeu/grepai-skills
Category
AI & Agent Building
First seen
Jun 3, 2026

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