Claw Dev

Claw Dev is a local multi-provider coding assistant launcher for the bundled terminal client in this repository. It gives you one entry point and lets you choose how model requests are resolved at startup:

• Anthropic account login or ANTHROPIC_API_KEY
• OpenAI through a local Anthropic-compatible proxy
• Google Gemini through a local Anthropic-compatible proxy
• Groq through a local Anthropic-compatible proxy
• Copilot through the GitHub Models API
• z.ai through a local Anthropic-compatible proxy
• Ollama through a local Anthropic-compatible proxy

Claw Dev is designed to feel like one tool rather than a provider-specific wrapper. The launcher, provider prompts, environment variables, and documentation are all centered around the Claw Dev name.

Repository Layout

• Leonxlnx-claude-code/
  • bundled terminal client and platform launchers
• src/anthropicCompatProxy.ts
  • local Anthropic-compatible proxy used for OpenAI, Gemini, Groq, Ollama, Copilot, and z.ai
• .env.example
  • optional environment template for local setup
• package.json
  • root scripts for launching, building, and validating the workspace

Supported Providers

Anthropic

Use the bundled client with the normal Anthropic login flow or with ANTHROPIC_API_KEY.

OpenAI

Use an OpenAI API key and route requests through the local compatibility proxy.

Gemini

Use a Google Gemini API key and route requests through the local compatibility proxy.

Groq

Use a Groq API key and route requests through the local compatibility proxy.

Ollama

Use a local or remote Ollama server and route requests through the local compatibility proxy.

This is the best option if you want local inference and do not want to depend on a cloud API provider.

Copilot

Use a GitHub Models-compatible bearer token and route requests through the local compatibility proxy.

z.ai

Use a z.ai API key and route requests through the local compatibility proxy.

Requirements

Install the following before you begin:

• Node.js 22 or newer
• npm
• Windows users should install Git for Windows for the best terminal workflow

Provider-specific requirements:

• Anthropic
  • an Anthropic account for in-app login, or ANTHROPIC_API_KEY
• OpenAI
  • OPENAI_API_KEY
• Gemini
  • GEMINI_API_KEY
• Groq
  • GROQ_API_KEY
• Ollama
  • a running Ollama installation
  • at least one pulled model, such as qwen3
• Copilot
  • COPILOT_TOKEN or another GitHub Models-compatible bearer token
• z.ai
  • ZAI_API_KEY

System Requirements

Minimum project requirements

These requirements apply to Claw Dev itself:

• Node.js 22+
• enough free disk space for Node dependencies and any local model assets you choose to install
• one of the following shells:
  • Windows PowerShell or Command Prompt
  • macOS Terminal, iTerm2, bash, or zsh
  • Linux terminal with bash or zsh

Ollama platform notes

According to the official Ollama documentation:

• Ollama is available for Windows, macOS, and Linux
• the local Ollama API is served by default at http://localhost:11434/api
• no authentication is required for local API access on http://localhost:11434
• on Windows, Ollama reads standard user and system environment variables

Ollama hardware guidance

Official Ollama documentation explains that loaded models may run fully on GPU, fully in system memory, or split across CPU and GPU, and that actual memory use depends on the model you choose. The exact hardware requirement therefore depends primarily on model size.

Practical guidance for Claw Dev users:

• For small local coding models, 16 GB system RAM is a reasonable starting point
• For smoother local work, 32 GB RAM is strongly preferred
• A dedicated GPU helps significantly, especially for larger models and faster response times
• If you do not have a capable GPU, Ollama can still run on CPU, but generation will be slower
• Larger models require substantially more RAM or VRAM and may be impractical on entry-level hardware

Conservative model guidance:

• qwen3 or similar 8B-class models are the easiest place to start on consumer hardware
• mid-size models usually benefit from 16 GB to 24 GB of available VRAM, or enough combined GPU and system memory for mixed CPU/GPU loading
• very large models are generally not a practical default for local coding workflows unless you already have a high-memory workstation

This guidance is an implementation recommendation based on Ollama's documented runtime behavior and common model sizes. It is not an official Ollama sizing table.

Installation

From the repository root on Windows:

cd E:\myclaudecode
npm install
copy .env.example .env

From the repository root on macOS or Linux:

cd /path/to/myclaudecode
npm install
cp .env.example .env

Editing .env is optional. Claw Dev can prompt for missing values interactively when it starts.

Quick Start

Start Claw Dev from the repository root on any platform:

npm run claw-dev

Or launch it directly from the bundled client directory on Windows:

cd E:\myclaudecode\Leonxlnx-claude-code
.\claw-dev.cmd

Or launch it directly from the bundled client directory on macOS or Linux:

cd /path/to/myclaudecode/Leonxlnx-claude-code
chmod +x ./claw-dev.sh
./claw-dev.sh

When Claw Dev starts, it shows a provider selector:

1. Anthropic
2. OpenAI
3. Gemini
4. Groq
5. Copilot
6. z.ai
7. Ollama

If a required API key is missing, Claw Dev prompts for it.

After you choose a provider, Claw Dev also lets you enter any model id you want for that session. You can press Enter to keep the suggested default, or type a custom model id such as:

• gpt-4.1
• gpt-4o-mini
• gemini-2.5-pro
• openai/gpt-oss-120b
• openai/o4-mini
• qwen2.5-coder:14b

This makes model selection flexible even when the bundled in-app /model picker still shows provider-specific legacy labels.

Additional Cloud Provider Setup

Copilot

Recommended .env values:

COPILOT_TOKEN=your_github_models_token_here
COPILOT_MODEL=openai/gpt-4.1-mini
COPILOT_MODEL_SONNET=openai/gpt-4.1-mini
COPILOT_MODEL_OPUS=openai/gpt-4.1
COPILOT_MODEL_HAIKU=openai/gpt-4.1-mini

z.ai

Recommended .env values:

ZAI_API_KEY=your_zai_api_key_here
ZAI_MODEL=glm-5

OpenAI

Recommended .env values:

OPENAI_API_KEY=your_openai_api_key_here
OPENAI_MODEL=gpt-4.1-mini

How To Use Ollama With Claw Dev

1. Install Ollama

Install Ollama from the official download page:

• Ollama Downloads

After installation, make sure the Ollama application or service is running.

2. Pull a local model

For a lightweight starting point:

ollama pull qwen3

You can verify that the model is available with:

ollama list

3. Start the Ollama server

If Ollama is not already running in the background, start it with:

ollama serve

The default local API base URL is:

http://127.0.0.1:11434

4. Start Claw Dev and choose Ollama

cd E:\myclaudecode
npm run claw-dev

Then choose:

4. Ollama

Claw Dev will point the bundled client at the local compatibility proxy, and the proxy will forward requests to your Ollama server.

5. Optional environment configuration

You can preconfigure Ollama mode in .env:

OLLAMA_BASE_URL=http://127.0.0.1:11434
OLLAMA_MODEL=qwen3
OLLAMA_API_KEY=
OLLAMA_KEEP_ALIVE=30m
OLLAMA_NUM_CTX=2048
OLLAMA_NUM_PREDICT=128

Notes:

• OLLAMA_BASE_URL should point to your Ollama server
• OLLAMA_MODEL is the model name Claw Dev will request
• OLLAMA_API_KEY is not required for local Ollama on localhost
• OLLAMA_API_KEY is only relevant if you are targeting an authenticated remote Ollama endpoint or the hosted Ollama API
• OLLAMA_KEEP_ALIVE keeps the model loaded between turns, which reduces repeated warm-up time
• OLLAMA_NUM_CTX controls prompt context size
• OLLAMA_NUM_PREDICT limits output length and can reduce latency

6. Check that Ollama is really being used

Useful checks:

ollama ps

This shows which models are currently loaded and whether they are using CPU, GPU, or both.

You can also confirm that the Claw Dev proxy is healthy:

npm run proxy:compat

Then open:

http://127.0.0.1:8789/health

When Ollama mode is configured, you should see a JSON response with the active provider and model.

7. Ollama performance tuning

If Ollama feels slow, start with the following assumptions:

• larger context windows are slower
• longer outputs are slower
• first-token latency is usually worst on the first request after model load
• CPU-only inference is much slower than GPU-backed inference

Recommended starting values for a responsive local setup:

OLLAMA_KEEP_ALIVE=30m
OLLAMA_NUM_CTX=2048
OLLAMA_NUM_PREDICT=128

If you need more quality and longer context, increase OLLAMA_NUM_CTX gradually to 4096 or higher. If you want faster responses, keep it smaller.

If you need shorter answers and lower latency, reduce OLLAMA_NUM_PREDICT further.

Recommended Environment Variables

Anthropic

ANTHROPIC_API_KEY=your_anthropic_api_key_here
ANTHROPIC_MODEL=claude-sonnet-4-20250514

OpenAI

OPENAI_API_KEY=your_openai_api_key_here
OPENAI_MODEL=gpt-4.1-mini

Gemini

GEMINI_API_KEY=your_gemini_api_key_here
GEMINI_MODEL=gemini-2.5-flash

Groq

GROQ_API_KEY=your_groq_api_key_here
GROQ_MODEL=openai/gpt-oss-20b

Ollama

OLLAMA_BASE_URL=http://127.0.0.1:11434
OLLAMA_MODEL=qwen3
OLLAMA_API_KEY=
OLLAMA_KEEP_ALIVE=30m
OLLAMA_NUM_CTX=2048
OLLAMA_NUM_PREDICT=128

Copilot

COPILOT_TOKEN=your_github_models_token_here
COPILOT_MODEL=openai/gpt-4.1-mini
COPILOT_MODEL_SONNET=openai/gpt-4.1-mini
COPILOT_MODEL_OPUS=openai/gpt-4.1
COPILOT_MODEL_HAIKU=openai/gpt-4.1-mini

z.ai

ZAI_API_KEY=your_zai_api_key_here
ZAI_MODEL=glm-5

Useful Commands

Check the installed launcher version:

cd E:\myclaudecode\Leonxlnx-claude-code
.\claw-dev.cmd --version

Check the installed launcher version on macOS or Linux:

cd /path/to/myclaudecode/Leonxlnx-claude-code
chmod +x ./claw-dev.sh
./claw-dev.sh --version

Skip the provider menu and force a specific provider:

.\claw-dev.cmd --provider anthropic
.\\claw-dev.cmd --provider openai
.\claw-dev.cmd --provider gemini
.\claw-dev.cmd --provider groq
.\claw-dev.cmd --provider copilot
.\claw-dev.cmd --provider zai
.\claw-dev.cmd --provider ollama

You can also skip the default model prompt and force any model id directly:

.\claw-dev.cmd --provider openai --model gpt-4.1
.\claw-dev.cmd --provider gemini --model gemini-2.5-pro
.\claw-dev.cmd --provider groq --model openai/gpt-oss-120b
.\claw-dev.cmd --provider copilot --model openai/o4-mini
.\claw-dev.cmd --provider zai --model glm-4.5
.\claw-dev.cmd --provider ollama --model qwen2.5-coder:14b

Equivalent macOS or Linux examples:

./claw-dev.sh --provider openai --model gpt-4.1
./claw-dev.sh --provider ollama --model qwen2.5-coder:14b

If you want extra suggestions to appear in the proxy model catalog, you can define optional comma-separated model lists:

OPENAI_MODELS=gpt-4.1-mini,gpt-4.1,gpt-4o-mini,gpt-4o,o4-mini
GEMINI_MODELS=gemini-2.5-flash,gemini-2.5-pro,gemma-3-27b-it
GROQ_MODELS=openai/gpt-oss-20b,openai/gpt-oss-120b,qwen/qwen3-32b
COPILOT_MODELS=openai/gpt-4.1-mini,openai/gpt-4.1,openai/gpt-4o,openai/o4-mini
ZAI_MODELS=glm-5,glm-4.5,glm-4.5-air
OLLAMA_MODELS=qwen3,qwen2.5-coder:7b,qwen2.5-coder:14b,deepseek-r1:8b

Important note:

• the startup model override accepts any model id
• the bundled /model command inside the client is still based on the bundled UI, so its labels may not match your provider exactly
• Claw Dev uses your startup model choice as the real backend model for the session

Legacy aliases are still accepted:

.\claw-dev.cmd --provider claude
.\claw-dev.cmd --provider grok

Run a one-shot prompt:

echo "Summarize this repository" | .\claw-dev.cmd --bare -p

Git Privacy Before Publishing

Before creating public commits, verify that your local Git identity is safe to publish.

Recommended settings for this repository:

git config user.name "Leonxlnx"
git config user.email "219127460+Leonxlnx@users.noreply.github.com"

You can verify the active values with:

git config user.name
git config user.email

Important notes:

• .env is ignored by .gitignore
• node_modules is ignored
• dist is ignored
• *.log files are ignored
• always review git status before staging
• always review git diff --cached before pushing

Useful checks:

git status --short
git diff --cached

Architecture Overview

Claw Dev works in two modes:

• Anthropic mode
  • the bundled client talks to Anthropic directly
• Compatibility mode
  • the bundled client talks to the local proxy
  • the local proxy translates Anthropic-style /v1/messages requests into OpenAI, Gemini, Groq, Ollama, Copilot, or z.ai API calls

This keeps the terminal experience consistent while allowing different model backends.

Troubleshooting

Ollama does not answer

Check the following:

• Ollama is installed
• the Ollama service or background app is running
• ollama serve is active if needed
• the selected model was pulled successfully
• OLLAMA_BASE_URL points to the correct server

Ollama answers slowly

Common causes:

• the model is running on CPU instead of GPU
• the selected model is too large for your hardware
• the model is partly swapping between GPU and system memory
• the context window is too large for your use case
• the requested answer is longer than necessary

Use:

ollama ps

to inspect how the model is loaded.

If PROCESSOR shows 100% CPU, slow generation is expected.

Recommended fixes:

• keep OLLAMA_NUM_CTX at 2048 first
• keep OLLAMA_NUM_PREDICT low for short answers
• leave OLLAMA_KEEP_ALIVE=30m or longer so the model stays warm
• try a smaller model if local responsiveness matters more than maximum quality

Cloud providers work, but Ollama does not

That usually means Claw Dev is working correctly, but the local Ollama server is not reachable or does not have the requested model.

Sharing With Another User

If you hand this repository to someone else, the shortest setup path is:

1. Install Node.js 22 or newer
2. Run npm install
3. Start npm run claw-dev
4. Choose a provider
5. Supply credentials or run Ollama locally

They do not need a separate global installation of the bundled client in order to use this repository.

Verification

Useful checks:

npm run check
npm run build
npm run claw-dev -- --version

References

Official documentation used for this setup:

• Ollama Documentation
• Ollama API Introduction
• Ollama API Authentication
• Ollama FAQ
• Anthropic Claude Code Quickstart
• OpenAI Chat Completions
• Groq Docs
• GitHub Models API announcement