Delete your subprocess wrappers around claude, codex, and gemini. spawnllm subshells all three CLIs — or drives Claude in-process through the bundled Agent SDK — plus local MLX and Apple's on-device Foundation Models, and returns one Pydantic-validated Response, so the per-model plumbing you hand-rolled goes away.
Get started
uvx spawnllm status
Driving with an agent? Paste this:
Run `uv add spawnllm` in this project.
Replace our hand-rolled claude/codex subprocess code with spawnllm's `call_sync`,
or `extract_sync` with a Pydantic response model for structured output.
Verify available backends with `uvx spawnllm status`.
Docs: https://yasyf.github.io/spawnllm/
Use cases
Delete your hand-rolled claude/codex subprocess plumbing
Every small tool grows its own subprocess.run(["claude", "-p", ...]) — argv quirks, stdin piping, exit-code guesswork — and each copy drifts. One call replaces all of it:
from spawnllm import call_sync
print(call_sync("Reply with just the word: pong"))
Prints pong. With no backend=, spawnllm auto-selects the first installed, authenticated backend — a CLI backend gets the prompt over stdin — and retries transient 529/overloaded/rate-limit failures with capped backoff.
Get a validated Pydantic object back, not a string to parse
Scraping JSON out of a model's stdout means regexes, code fences, and silent schema drift. extract_sync validates instead:
from pydantic import BaseModel
from spawnllm import extract_sync
class Capital(BaseModel):
country: str
capital: str
result = extract_sync("What is the capital of France?", Capital)
print(result.capital) # Paris
The backend turns Capital into a JSON-schema constraint on the call itself, and a non-conforming reply raises pydantic.ValidationError instead of sneaking downstream.
Keep billing on your subscription, not a stray API key
An ANTHROPIC_API_KEY left in your shell silently flips the claude CLI from your logged-in plan to per-token API billing. spawnllm strips each provider's key vars from the child environment by default, so every run bills the login:
from spawnllm import call_sync
print(call_sync("Reply with just the word: pong"))
Prints pong, billed to your Claude plan even with ANTHROPIC_API_KEY exported. Pass api_auth=True to opt back into key auth. The same guard covers codex (OPENAI_API_KEY/CODEX_API_KEY) and the Gemini family, in Python, Go, and Rust alike; an explicit RunSpec.env entry always wins.
Call Claude with zero installs
The sdk extra adds a backend over the Claude Agent SDK, whose wheel bundles the Claude Code CLI — no separate claude install:
uv add "spawnllm[sdk]"
claude-sdk registers first in the auto-selection chain and signs in with your existing subscription credentials (keychain login or CLAUDE_CODE_OAUTH_TOKEN), so the call_sync above works on a machine that has never installed the CLI.
Run Apple-Silicon MLX models with fused adapters and prompt-cache reuse
Shipping a LoRA-tuned local model means hand-rolling adapter fusion, model caching, and worker-thread lifecycle. The MLX extra owns all three:
uv add "spawnllm[mlx]"
AdapterFuser.ensure_fused fuses your compressed adapter into the base model once and caches the result in the Hugging Face hub layout; MlxEngine loads it on a dedicated worker thread, precomputes a prompt cache for your shared prefix messages, and batches generation. Wrap the engine in an MlxBackend and the same run_sync call works.
Call Apple's on-device model with zero downloads
Even local MLX starts with a multi-gigabyte model fetch. On a Mac with Apple Intelligence, AppleBackend skips that too: a prebuilt Swift sidecar inside the macOS wheel drives Apple's Foundation Models framework against the model already resident on the device. No extra, no compiler, no credentials, no network — installing spawnllm is the whole setup, uvx spawnllm included:
from spawnllm import AppleBackend, call_sync
print(call_sync("Reply with just the word: pong", backend=AppleBackend()))
Auto-selection tries this backend last and only for model="small"; an explicit backend=AppleBackend() always reaches it. Session and decoding knobs (use_case, guardrails, instructions, temperature, sampling) ride in via RunSpec(provider_configs={"apple": AppleConfig(...)}). Structured extract_sync works too, nested models included, and schema constraints now bind during decoding: minimum/maximum, minItems/maxItems, and string-valued enums are enforced exactly (a non-string enum such as Literal[1, 2] fails before generation, extract_sync raising BackendCallError), and a Field(pattern=...) constrains the value's shape — length, separators, and character families. Apple's decoder rejects bracket character classes, so the sidecar widens each to the narrowest escape it accepts (^[A-Z]{3}-\d{4}$ decodes as \w{3}-\d{4}), and pydantic stays the exact validator: a value that fits the widened shape but violates your regex raises a plain ValidationError. Self-referential models extract cleanly; a mutually recursive pair (A referencing B referencing A) fails cleanly instead, extract_sync raising BackendCallError and run returning an error Response. Requires macOS 26+ on Apple Silicon with Apple Intelligence enabled — every other platform gets the pure-Python wheel and reports the backend as not installed.
Call the same backends from Go or Rust
All three languages run the identical engine: argv planning, output parsing, schema strictification, and retry policy live once in a Rust core — linked natively by the Rust crate, embedded as WASM by the Go module and the Python package — pinned by a shared golden-vector suite and released in lockstep.
go get github.com/yasyf/spawnllm/go # pure Go, no cgo — the core embeds as WASM
cargo add spawnllm # async-first, with a blocking mirror
Both expose Call/call and typed Extract/extract against your existing CLI logins, and both reach Apple's on-device model on a capable Mac with binrun installed to fetch the digest-pinned sidecar — see the Go README and the Rust README. MLX stays Python-only.
More in the docs
- Spec-driven runs — a literal model id, per-provider flag passthrough, and envelope-aware retry via
RunSpec— Running reference - Backend selection — the priority chain, plus
specialty=routing (debuggingandreviewgo to Codex,generalto the Claude Agent SDK backend) — Backends reference - Transport helpers —
run_cli,collect_process, andmap_concurrent, the subprocess plumbing shared by every CLI backend — Transport reference - The CLI —
spawnllm call,status, andbackendsfrom any shell — CLI reference - MLX internals — the adapter codec, fuser, and runtime patches behind the local engine — MLX reference
Read the docs for the full guide and API reference. Licensed under MIT.
Release files for spawnllm 0.13.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| spawnllm-0.13.0.tar.gz | 212.0 kB | Details |
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| spawnllm-0.13.0-py3-none-macosx_26_0_arm64.whl | Python 3 | none | macOS 26.0+ ARM64 | Details |
| spawnllm-0.13.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 748.5 kB
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