coaxer 0.3.13

Evals-first prompt optimization. Label examples, get better prompts.

coaxer

Label examples. Derive the prompt. Consume it as a string.

Full docs: https://thekevinscott.github.io/coaxer/ · ship-with-package source in docs/.

Motivation

Writing prompts by hand is slow, and the prose grows brittle as cases accumulate. Coaxer flips it: label examples of the behavior you want, derive the prompt from those labels — when it drifts, add more labels instead of rewriting.

Labels are the source of truth. The prompt is a build artifact.

Install

uv add coaxer        # Python
npm install coaxer   # TypeScript

Quick start

coax labels/repo-classification --out prompts/repo-classification

from coaxer import CoaxedPrompt

p = CoaxedPrompt("prompts/repo-classification")
filled = p(readme=new_readme, stars=1200)

The TypeScript version is in docs/guide/getting-started.md.

Getting Started

Label folder is one directory per record; record.json plus sibling files for large text or binary inputs. coax compiles the folder into a prompt artifact you load with CoaxedPrompt. Default optimizer is none (schema-derived, no network).

Full walkthrough: docs/guide/getting-started.md.

CoaxedPrompt

CoaxedPrompt(path, **bound) is a str subclass. str(p) is the raw template; p(**vars) renders it. Missing vars raise MissingVariableError. Bound defaults at construction; call-time vars override. p.fields lists the input variables the template expects.

For structured-output APIs, p.response_format is a Pydantic model derived from the compiled output schema.

Reference: docs/api/coaxed-prompt.md.

CLI

coax <labels-dir> --out <prompts-dir> [--optimizer {none,gepa}] [--output-name NAME]

Reference: docs/api/cli.md.

AgentLM

DSPy BaseLM backed by the Claude Agent SDK. **kwargs forward to ClaudeAgentOptions (tools, allowed_tools, max_turns, …).

from coaxer import AgentLM
lm = AgentLM(tools=[])

Reference: docs/api/agent-lm.md.

OpenAILM

DSPy BaseLM for any OpenAI-compatible chat endpoint (Ollama, vLLM, OpenAI, LM Studio, …).

from coaxer import OpenAILM
lm = OpenAILM(model="gpt-4o", base_url="https://api.openai.com/v1", api_key="sk-...")

Reference: docs/api/openai-lm.md.

Migrations

Downstream-consumer upgrade instructions for breaking changes live in MIGRATIONS.md (also published at docs/migrations.md). The full release log is in CHANGELOG.md.

Development

uv sync --extra dev
uv run just test-unit   # Unit tests
uv run just ci          # Full CI (lint + format + typecheck + tests)