Local Coding

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.

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

bash

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

python

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

bash

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

bash

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

bash

# 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

bash

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

Speech-to-text

bash

curl http://localhost:11435/api/transcribe -F "file=@standup.wav" -F "model=qwen3-asr"

Full documentation

• Agent Setup Guide — all 4 model types
• API Reference — complete endpoint docs

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.