Examples Hub¶

Find runnable scenarios that demonstrate SteadyText in real projects. Pick the surface you’re building on, then drill into verticals or cross-cutting recipes.

Python Library¶

Topic	What you’ll learn	Jump in
Getting deterministic outputs	First-generation patterns, streaming, embeddings	Basic Usage
Controlling seeds	Reproducible experimentation and CI diffs	Custom Seeds
Developer tooling	Build deterministic CLIs and automation	Tooling
Data & pipelines	Batch ETL/ELT integration with the daemon	Data Pipelines
Vertical solutions	Content, logs, customer analytics	Content Management, Log Analysis, Customer Intelligence
Quality gates	Deterministic regression checks	Testing with AI

Postgres Extension¶

Topic	What you’ll learn	Jump in
Install & integrate	Wire SQL functions into existing schemas	Integration Overview
Analytical workloads	Embeddings + reranking for BI dashboards	PostgreSQL Analytics
Content + commerce	Build deterministic editorial & commerce flows	PostgreSQL Blog CMS, PostgreSQL E-commerce
Search & retrieval	Semantic search, query expansion, result shaping	PostgreSQL Search
Real-time apps	LISTEN/NOTIFY, async jobs, background workers	PostgreSQL Realtime

Shared Recipes¶

Caching & performance tuning → Caching, Performance Tuning
Daemon operations → Daemon Usage
Error handling patterns → Error Handling
Tool stack integration → Shell Integration, Vector Indexing

How to Use These Examples¶

Clone the repo

git clone https://github.com/julep-ai/steadytext.git
cd steadytext/examples

Pick your surface — follow the Python or Postgres table above.
Run the code — every script is deterministic; outputs match the docs.
Adapt & link back — reuse the patterns and add AIDEV-REF comments if you extend them.

Same input → same output

Determinism underpins every example. When experimenting, change seeds intentionally and record them so teammates and CI runs can reproduce your outputs precisely.