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Quick Start Guide

Get started with SteadyText in minutes.

Installation

pip install steadytext

uv add steadytext

poetry add steadytext

First Steps

1. Basic Text Generation

import steadytext

# Generate deterministic text
text = steadytext.generate("Write a Python function to calculate fibonacci")
print(text)

2. Streaming Generation

For real-time output:

for token in steadytext.generate_iter("Explain machine learning"):
    print(token, end="", flush=True)

3. Create Embeddings

# Single text
vector = steadytext.embed("Hello world")
print(f"Embedding shape: {vector.shape}")  # (1024,)

# Multiple texts (averaged)
vector = steadytext.embed(["Hello", "world", "AI"])

Command Line Usage

SteadyText includes both steadytext and st commands:

# Generate text
st generate "write a haiku about programming"

# Stream generation
st generate "explain quantum computing" --stream

# Create embeddings  
st embed "machine learning concepts"

# JSON output
st generate "list 3 colors" --json

# Preload models (optional)
st models --preload

Model Management

Models are automatically downloaded on first use to:

  • Linux/Mac: ~/.cache/steadytext/models/
  • Windows: %LOCALAPPDATA%\steadytext\steadytext\models\
# Check where models are stored
cache_dir = steadytext.get_model_cache_dir()
print(f"Models stored at: {cache_dir}")

# Preload models manually (optional)
steadytext.preload_models(verbose=True)

Configuration

Control caching via environment variables:

# Generation cache settings
export STEADYTEXT_GENERATION_CACHE_CAPACITY=512
export STEADYTEXT_GENERATION_CACHE_MAX_SIZE_MB=100

# Embedding cache settings  
export STEADYTEXT_EMBEDDING_CACHE_CAPACITY=1024
export STEADYTEXT_EMBEDDING_CACHE_MAX_SIZE_MB=200

Next Steps

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