aipromptbucket 0.1.0

Python SDK for AI Prompt Bucket — managed prompt registry for teams

AI Prompt Bucket — Python SDK

Python SDK for AI Prompt Bucket, a managed prompt registry for teams.

Installation

pip install aipromptbucket

Or with uv:

uv add aipromptbucket

Configuration

Set environment variables or pass directly to the client:

export AIPROMPTBUCKET_API_KEY="sk-api01-your-key-here"
export AIPROMPTBUCKET_URL="https://aipromptbucket.com"  # optional, this is the default

Quick Start — get_prompt()

The simplest way to use AI Prompt Bucket. One function, no boilerplate:

from aipromptbucket import get_prompt

# Fetch a rendered prompt
text = get_prompt("my-prompt")

# With variables
text = get_prompt("my-prompt", variables={"name": "Alice"})

# With a specific label
text = get_prompt("my-prompt", label="staging")

# With a fallback if the service is unreachable
text = get_prompt("my-prompt", fallback="You are a helpful assistant.")

# With TTL caching (seconds)
text = get_prompt("my-prompt", ttl=300)

Set global defaults so you don't repeat yourself:

import aipromptbucket

aipromptbucket.configure(
    api_key="sk-api01-...",
    base_url="https://aipromptbucket.com",
    default_label="production",
    default_ttl=300,
)

Using the Full Client

For advanced use cases (creating prompts, managing versions, labels, etc.):

from aipromptbucket import Client

client = Client()

# List all prompts
result = client.list_prompts()
if result.ok:
    for prompt in result.data:
        print(f"{prompt.slug}: {prompt.name}")

# Get a specific prompt
result = client.get_prompt("my-prompt")
if result.ok:
    print(result.data.name)

# Render a prompt with variables
result = client.render("my-prompt", variables={"name": "World"})
if result.ok:
    print(result.data.rendered_text)

# Create a new prompt
result = client.create_prompt(
    name="Greeting Prompt",
    slug="greeting-prompt",
    template_text="Hello, {{ name }}! You are a {{ role }}.",
    template_format="jinja2",
    tags=["greetings"],
)

# Create a new version
result = client.create_version(
    "greeting-prompt",
    template_text="Hi {{ name }}! Your role is {{ role }}.",
    change_note="Simplified greeting",
)

# Promote a version to a label
result = client.promote("greeting-prompt", version=2, label="production")

CLI Scanner

The package includes a CLI tool to scan your codebase for hardcoded prompts:

# Preview what the scanner finds
apb scan ./src --team my-team --dry-run

# Import all found prompts
apb scan ./src --team my-team --auto

# Interactive import
apb scan ./src --team my-team

Scanner Flags

Flag	Description
<path>	Directory to scan (required)
--team <slug>	Team slug to import into (required)
--dry-run	Show findings without importing
--auto	Import all without confirmation
--min-length N	Minimum string length (default: 100)

API Reference

All methods return APIResponse[T] with fields:

• ok: bool — whether the request succeeded
• status_code: int — HTTP status code
• data: T | None — response data (when ok is True)
• error: str | None — error message (when ok is False)

Prompts

Method	Description
list_prompts(tag?, search?)	List all prompts
get_prompt(slug)	Get prompt details
create_prompt(...)	Create a new prompt
update_prompt(slug, ...)	Update prompt metadata
delete_prompt(slug)	Delete a prompt

Versions

Method	Description
list_versions(slug)	List all versions
get_version(slug, version_number)	Get specific version
create_version(slug, ...)	Create a new version

Rendering

Method	Description
render(slug, label?, variables?)	Render a prompt template

Labels

Method	Description
list_labels()	List team labels
create_label(name, ...)	Create a team label
delete_label(name)	Delete a team label
list_prompt_labels(slug)	List labels for a prompt
assign_label(slug, label, version)	Assign label to version
label_impact(slug)	Analyze change impact

Promote / Rollback

Method	Description
promote(slug, version, label)	Assign label to a version
rollback(slug, label)	Rollback label to previous version

Snapshots

Method	Description
list_snapshots()	List snapshots
create_snapshot(name, ...)	Create a snapshot
restore_snapshot(snapshot_id)	Restore a snapshot

Health & Analysis

Method	Description
get_health(slug)	Get prompt health score
refresh_health(slug)	Recompute health score
list_analysis(limit?)	List analysis results
run_analysis()	Run new analysis

System

Method	Description
health_check()	Check API health

Using the Scanner Programmatically

from aipromptbucket import Scanner

scanner = Scanner(min_length=100)
findings = scanner.scan("./src")

for finding in findings:
    print(f"{finding.file}:{finding.line} — {finding.detected_format}")
    print(f"  Variables: {finding.variables}")

License

MIT — Bright Wing Solutions LLC