Wrap Claude Code with Z.ai GLM settings
Project description
glm-launch
A Python CLI tool that wraps Claude Code with GLM settings. Instead of running a local proxy, it configures environment variables, then exec's the claude binary directly. (codex is not supported — Z.AI has no OpenAI Responses API endpoint.)
It works with Z.AI and their GLM series of models. You'll need a Z.AI API key — grab one with a Z.AI Coding Plan subscription. Using that referral link gives you 10% off and gets me 10% off too. Prefer not to? Here's a non-affiliate link.
Requires Python 3.13+.
Usage
# 1. Set your Z.AI auth token
export GLM_AUTH_TOKEN="your-zai-api-key"
# 2. Launch Claude Code routed through Z.AI (defaults to glm-5.2)
uv run glm-launch # bare command defaults to `claude`
uv run glm-launch claude # same thing, explicit
# Pick a different model
uv run glm-launch claude --model glm-5.1 # long-horizon flagship
uv run glm-launch claude --model glm-5-turbo # fast
uv run glm-launch claude --model glm-4.5-air # cheap
# Bootstrap your current shell so a plain `claude` uses Z.AI
eval "$(uv run glm-launch shell)"
claude
# See available models (built-in list, or --remote for the live API list)
uv run glm-launch models
uv run glm-launch models --remote
# Sanity-check connectivity / latency
uv run glm-launch bench
Examples use the installed
glm-launchentrypoint. Beforeuv syncyou can run the script directly withuv run src/main.py …— the two are interchangeable.
Installation
uv sync
This installs a glm-launch entrypoint. Run commands via uv run glm-launch <command>, or uv tool install . to get glm-launch on your PATH directly. You can also run the script without installing via uv run src/main.py <command>.
Run without cloning (uvx)
glm-launch is on PyPI, so you can run it directly with uvx (uv tool run) — no clone or manual install needed.
# From PyPI
uvx glm-launch launch claude
# Or straight from GitHub
uvx --from git+https://github.com/jefftriplett/glm-launch glm-launch launch claude
# Pin to a tag/branch/commit
uvx --from git+https://github.com/jefftriplett/glm-launch@main glm-launch models
Commands
launch claude
Launch Claude Code with GLM environment settings. Sets Anthropic env vars to route requests through Z.AI's Anthropic-compatible endpoint, then exec's the claude binary.
The
launchprefix is optional:glm-launch claudeis equivalent toglm-launch launch claude, and a bareglm-launchdefaults toclaude.
uv run glm-launch launch claude
Options:
| Flag | Env var | Default | Description |
|---|---|---|---|
--model / -m |
— | glm-5.2 |
Model name passed to claude --model |
--base-url |
GLM_BASE_URL |
https://api.z.ai/api/anthropic |
API endpoint |
--api-key |
GLM_API_KEY |
"" |
API key |
--auth-token |
GLM_AUTH_TOKEN |
(required) | Z.AI auth token |
--api-timeout-ms |
API_TIMEOUT_MS |
3000000 |
Request timeout in milliseconds |
--default-haiku-model |
ANTHROPIC_DEFAULT_HAIKU_MODEL |
glm-4.5-air |
Model for Haiku-tier requests |
--default-sonnet-model |
ANTHROPIC_DEFAULT_SONNET_MODEL |
glm-5.2 |
Model for Sonnet-tier requests |
--default-opus-model |
ANTHROPIC_DEFAULT_OPUS_MODEL |
glm-5.2 |
Model for Opus-tier requests |
--subagent-model |
CLAUDE_CODE_SUBAGENT_MODEL |
glm-4.5-air |
Model used for spawned subagents |
--effort-level |
CLAUDE_CODE_EFFORT_LEVEL |
max |
Effort level for the agent loop |
--attribution-header |
CLAUDE_CODE_ATTRIBUTION_HEADER |
0 |
Attribution header toggle (0 disables it) |
--auto-compact-window |
CLAUDE_CODE_AUTO_COMPACT_WINDOW |
200000 |
Auto-compact context window in tokens (empty to leave unset) |
--dry-run |
— | false |
Print the resolved command and masked GLM environment without launching |
The following env vars are set before exec'ing claude:
ANTHROPIC_BASE_URL— from--base-url/GLM_BASE_URLANTHROPIC_API_KEY— from--api-key/GLM_API_KEYANTHROPIC_AUTH_TOKEN— from--auth-token/GLM_AUTH_TOKENAPI_TIMEOUT_MS— from--api-timeout-ms/API_TIMEOUT_MSANTHROPIC_DEFAULT_HAIKU_MODEL— from--default-haiku-modelANTHROPIC_DEFAULT_SONNET_MODEL— from--default-sonnet-modelANTHROPIC_DEFAULT_OPUS_MODEL— from--default-opus-modelCLAUDE_CODE_SUBAGENT_MODEL— from--subagent-modelCLAUDE_CODE_EFFORT_LEVEL— from--effort-levelCLAUDE_CODE_ATTRIBUTION_HEADER— from--attribution-headerCLAUDE_CODE_AUTO_COMPACT_WINDOW— from--auto-compact-window(only when non-empty)
Examples:
# Use defaults (glm-5.2, Z.AI endpoint)
uv run glm-launch launch claude
# Flagship reasoning/coding model (the default)
uv run glm-launch launch claude --model glm-5.2
# Long-horizon agentic flagship
uv run glm-launch launch claude --model glm-5.1
# Fast, speed-optimized GLM-5 variant
uv run glm-launch launch claude --model glm-5-turbo
# Lightweight, low-cost model for cheaper runs
uv run glm-launch launch claude --model glm-4.5-air
# Tune the model tiers independently (e.g. cheap subagents, flagship main)
uv run glm-launch launch claude \
--model glm-5.2 \
--subagent-model glm-4.5-air \
--default-haiku-model glm-4.5-air
# Pass extra args through to claude
uv run glm-launch launch claude -- --verbose
# Inspect the command/env without launching claude
uv run glm-launch launch claude --dry-run
# Override via env vars
GLM_AUTH_TOKEN="my-token" uv run glm-launch launch claude
Run uv run glm-launch models to see all valid model names (or --remote for the live list).
If claude is not on your PATH, the tool falls back to ~/.claude/local/claude.
launch codex (not supported)
Codex is not supported by glm-launch. Current codex only speaks the OpenAI Responses API (it removed wire_api = "chat"), but Z.AI's GLM endpoints are Anthropic Messages and OpenAI Chat Completions only — there is no /responses endpoint, so codex requests return 404. The codex command is intentionally disabled and exits with this explanation.
Use launch claude instead — it uses Z.AI's Anthropic-compatible endpoint. If Z.AI later ships a Responses-compatible endpoint, codex support can be revisited.
shell
Print export lines that bootstrap your current shell with the GLM env vars — without launching anything. Eval the output and a plain claude (or any Anthropic SDK tool) will talk to Z.AI.
eval "$(uv run glm-launch shell)"
claude
Accepts the same model/auth options as launch claude (--model, --auth-token, --default-*-model, etc.). Secrets are shell-quoted; empty values are skipped. Sets ANTHROPIC_MODEL plus all the ANTHROPIC_* / CLAUDE_CODE_* vars listed under launch claude.
# Inspect what would be exported
uv run glm-launch shell
# Bootstrap with a specific model
eval "$(uv run glm-launch shell --model glm-5.1)"
models
List Z.AI GLM models. By default prints a built-in, annotated list; --remote fetches the live list from the Z.AI PaaS endpoint.
# Built-in list (no token needed)
uv run glm-launch models
# Live list from the API (needs GLM_AUTH_TOKEN)
uv run glm-launch models --remote
Options:
| Flag | Env var | Default | Description |
|---|---|---|---|
--remote / -r |
— | false |
Fetch the live list from the Z.AI API |
--models-url |
GLM_MODELS_URL |
https://api.z.ai/api/paas/v4/models |
PaaS models endpoint (used with --remote) |
--auth-token |
GLM_AUTH_TOKEN |
— | Auth token (required with --remote) |
--timeout |
— | 30.0 |
Request timeout in seconds |
The live endpoint is the OpenAI-compatible PaaS base (/api/paas/v4/models) and uses Authorization: Bearer <token> — distinct from the Anthropic-style chat base (/api/anthropic) used by launch claude and bench.
bench
Time a single /v1/messages round-trip against the configured GLM endpoint. Useful as a sanity check that your auth token, base URL, and chosen model are reachable.
uv run glm-launch bench
Options:
| Flag | Env var | Default | Description |
|---|---|---|---|
--model / -m |
— | glm-5.2 |
Model to benchmark |
--base-url |
GLM_BASE_URL |
https://api.z.ai/api/anthropic |
API endpoint |
--auth-token |
GLM_AUTH_TOKEN |
(required) | Auth token for the endpoint |
--timeout |
— | 30.0 |
Request timeout in seconds |
Sends a minimal 32-token request and prints the round-trip time. Exits non-zero on HTTP error or timeout.
Example output:
glm-5.2 via https://api.z.ai/api/anthropic
OK (200) in 412ms
doctor
Check your environment for correct setup. Reports on environment variables, binary availability, and config files.
uv run glm-launch doctor
Checks performed:
- Environment variables — Whether the GLM, Anthropic default-model, and Claude Code env vars used by the launch commands are set. Secrets are masked in output.
- Binaries — Whether
claudeis found on PATH (with fallback to~/.claude/local/claude).
Exits with code 1 if any binary is missing, 0 otherwise.
Example output:
Environment variables:
GLM_BASE_URL: (not set)
GLM_API_KEY: (not set)
GLM_AUTH_TOKEN: (not set)
GLM_MODELS_URL: (not set)
API_TIMEOUT_MS: (not set)
ANTHROPIC_DEFAULT_HAIKU_MODEL: (not set)
ANTHROPIC_DEFAULT_SONNET_MODEL: (not set)
ANTHROPIC_DEFAULT_OPUS_MODEL: (not set)
CLAUDE_CODE_SUBAGENT_MODEL: (not set)
CLAUDE_CODE_EFFORT_LEVEL: (not set)
CLAUDE_CODE_ATTRIBUTION_HEADER: (not set)
CLAUDE_CODE_AUTO_COMPACT_WINDOW: (not set)
Binaries:
claude: /usr/local/bin/claude
All checks passed.
Environment variables
| Variable | Used by | Description |
|---|---|---|
GLM_BASE_URL |
launch claude, shell |
API base URL |
GLM_API_KEY |
launch claude, shell |
API key |
GLM_AUTH_TOKEN |
launch claude, shell, bench, models --remote |
Z.AI auth token (required) |
GLM_MODELS_URL |
models --remote |
PaaS models endpoint |
API_TIMEOUT_MS |
launch claude, shell |
Request timeout in milliseconds |
ANTHROPIC_DEFAULT_HAIKU_MODEL |
launch claude, shell |
Model for Haiku-tier requests |
ANTHROPIC_DEFAULT_SONNET_MODEL |
launch claude, shell |
Model for Sonnet-tier requests |
ANTHROPIC_DEFAULT_OPUS_MODEL |
launch claude, shell |
Model for Opus-tier requests |
CLAUDE_CODE_SUBAGENT_MODEL |
launch claude, shell |
Model used for spawned subagents |
CLAUDE_CODE_EFFORT_LEVEL |
launch claude, shell |
Effort level for the agent loop |
CLAUDE_CODE_ATTRIBUTION_HEADER |
launch claude, shell |
Attribution header toggle (0 disables it) |
CLAUDE_CODE_AUTO_COMPACT_WINDOW |
launch claude, shell |
Auto-compact context window in tokens |
How it works
launch claude follows three steps:
- Resolve the
claudebinary on PATH (falling back to~/.claude/local/claude) - Set up the GLM environment variables
os.execvpe()the binary — fully replacing the glm process withclaudefor direct stdio passthrough
Z.AI exposes an Anthropic-compatible endpoint at https://api.z.ai/api/anthropic, so no local proxy is needed. The CLI sets the standard ANTHROPIC_* env vars and Claude Code talks directly to Z.AI.
Development
Common tasks are wrapped in a justfile. Run just with no arguments to list them.
| Recipe | Description |
|---|---|
just bootstrap |
Upgrade pip/uv, then uv sync |
just sync |
uv sync the project dependencies |
just lock |
uv lock the dependency versions |
just build |
uv build the wheel and sdist |
just bump *ARGS |
Bump the CalVer version with bumpver (e.g. just bump) |
just bump-dry *ARGS |
Preview a version bump without writing changes |
just release *ARGS |
Bump, relock, and push the tag — CI then publishes to PyPI |
just lint *ARGS |
Run the prek hooks (defaults to --all-files) |
just fmt |
Format the justfile itself |
just demo |
Smoke-test the CLI by listing models |
Versioning follows CalVer (YYYY.MM.INC1), and lint hooks (ruff, pyupgrade, validate-pyproject) are configured in .pre-commit-config.yaml and run with prek.
Releases are automated. Run just release to bump the CalVer version, relock, and push the tag in one step. Pushing a YYYY.MM.INC1 tag triggers the GitHub Actions release workflow, which builds and publishes to PyPI via trusted publishing (OIDC, no API token). A plain git push never publishes — only the tag does.
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