geeks-accelerator/ollama-herd · Archived

local-coding

Local coding assistant — run DeepSeek-Coder, Codestral, StarCoder, and Qwen-Coder across your device fleet.

First seen Jun 17, 2026

Installation

$ npx skills add geeks-accelerator/ollama-herd --skill local-coding

Summary

  • Local coding assistant — run DeepSeek-Coder, Codestral, StarCoder, and Qwen-Coder across your device fleet.
  • Code generation, review, refactoring, and debugging routed to the best available machine.
  • Works with Aider, Continue.dev, Cline, and any OpenAI-compatible coding tool.
  • No cloud API costs, all code stays local.

Stronger alternatives

This repository is archived — consider an actively maintained alternative.

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Also in this package

Other skills from geeks-accelerator/ollama-herd.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Declared
Windsurf Not declared
Gemini CLI Not declared
Cline Declared
OpenCode Not declared

Repository health

Stars 9
License LICENSE
Default branch main
Open issues 2
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Version1.0.1
Declared agents github-copilot cline clawdbot

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,606 B
  • docs SUMMARY.md 339 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Local Coding Assistant — Code Models Across Your Fleet

Run the best open-source coding models on your own hardware. DeepSeek-Coder, Codestral, StarCoder, and Qwen-Coder routed across your devices — the fleet picks the best machine for every code generation request.

Your code never leaves your network. No GitHub Copilot subscription, no cloud API costs.

Coding models available

Model Parameters Ollama name Strengths
Codestral 22B codestral 80+ languages, fill-in-the-middle, Mistral's code specialist
DeepSeek-Coder-V2 236B MoE (21B active) deepseek-coder-v2 Matches GPT-4 Turbo on code tasks
DeepSeek-Coder 6.7B, 33B deepseek-coder:33b Purpose-built for code (87% code training data)
Qwen2.5-Coder 7B, 32B qwen2.5-coder:32b Strong multi-language code generation
StarCoder2 3B, 7B, 15B starcoder2:15b Trained on The Stack v2, 600+ languages
CodeGemma 7B codegemma Google's code-focused Gemma variant

Quick start

pip install ollama-herd    # PyPI: https://pypi.org/project/ollama-herd/
herd                       # start the router (port 11435)
herd-node                  # run on each device — finds the router automatically

No models are downloaded during installation. All pulls require user confirmation.

Code generation

Write new code

from openai import OpenAI

client = OpenAI(base_url="http://localhost:11435/v1", api_key="not-needed")

response = client.chat.completions.create(
    model="codestral",
    messages=[{"role": "user", "content": "Write a thread-safe LRU cache in Python with TTL support"}],
)
print(response.choices[0].message.content)

Code review

curl http://localhost:11435/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-coder-v2:16b",
    "messages": [{"role": "user", "content": "Review this code for bugs and security issues:\n\n```python\ndef process_payment(amount, card_number):\n    ...\n```"}]
  }'

Refactoring

curl http://localhost:11435/api/chat -d '{
  "model": "qwen2.5-coder:32b",
  "messages": [{"role": "user", "content": "Refactor this to use async/await: ..."}],
  "stream": false
}'

Works with your IDE tools

The fleet exposes an OpenAI-compatible API at http://localhost:11435/v1. Point any coding tool at it:

Tool Config
Aider aider --openai-api-base http://localhost:11435/v1 --model codestral
Continue.dev Set API base to http://localhost:11435/v1 in VS Code settings
Cline Set provider to OpenAI-compatible, base URL http://localhost:11435/v1
Open WebUI Set Ollama URL to http://localhost:11435
LangChain ChatOpenAI(base_url="http://localhost:11435/v1";, model="codestral")

Pick the right model for your RAM

Cross-platform: These are example configurations. Any device (Mac, Linux, Windows) with equivalent RAM works.

Device RAM Best coding model
MacBook Air (8GB) 8GB starcoder2:3b or deepseek-coder:6.7b
Mac Mini (16GB) 16GB codestral or starcoder2:15b
Mac Mini (32GB) 32GB qwen2.5-coder:32b or deepseek-coder:33b
Mac Studio (128GB) 128GB deepseek-coder-v2 — frontier code quality

Check what's running

# Models loaded in memory
curl -s http://localhost:11435/api/ps | python3 -m json.tool

# All available models
curl -s http://localhost:11435/api/tags | python3 -m json.tool

# Recent coding request traces
curl -s "http://localhost:11435/dashboard/api/traces?limit=5" | python3 -m json.tool

Also available on this fleet

General-purpose LLMs

Llama 3.3, Qwen 3.5, DeepSeek-R1, Mistral Large — for non-code tasks through the same endpoint.

Image generation

curl http://localhost:11435/api/generate-image \
  -d '{"model": "z-image-turbo", "prompt": "developer workspace illustration", "width": 512, "height": 512}'

Speech-to-text

curl http://localhost:11435/api/transcribe -F "[email protected]" -F "model=qwen3-asr"

Full documentation

Guardrails

  • Model downloads require explicit user confirmation — coding models range from 2GB to 130GB+. Always confirm before pulling.
  • Model deletion requires explicit user confirmation.
  • Never delete or modify files in ~/.fleet-manager/.
  • No models are downloaded automatically — all pulls are user-initiated or require opt-in.
  • Your code stays local — no prompts or generated code leave your network.