banks
A prompt programming language
Decision gist · record as of 2026-08-14
Yes. Banks is actively maintained, has low install friction, carries a permissive MIT license, and solves a real problem—moving beyond ad-hoc string formatting for LLM prompts. The Beta status and recent release (6 days old) suggest active development. Install it if you're building LLM applications and want structured, versioned, reusable prompts; skip it if you're only calling LLMs with simple one-off strings.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low friction install with a pure-Python wheel.
- Maintenance is active with a recent release (6 days old) and steady repository activity.
- Seven runtime dependencies are all well-established packages, though optional dependencies (litellm, redis) add capability for advanced features.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal restrictions.
last release 2026-08-08 (6 days) · last repo commit 2026-08-08 · 128 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 8,360,654 downloads/mo, #1,631 on PyPI
Alternatives
Verify before relying
pip install banks
from banks import Prompt
prompt_template = """
{% chat role="system" %}
You are a {{ persona }}.
{% endchat %}
"""
p = Prompt(prompt_template)
messages = p.chat_messages({"persona": "helpful assistant"})- Whether optional dependencies (litellm, redis) are required for core templating or only for specific advanced features like LLM-based text generation and caching.
- Performance characteristics when rendering complex templates with many dynamic LLM calls or large image payloads.
- Stability guarantees given Beta development status (Development Status :: 4).
What it is and what it does
Banks is a template-based prompt programming language built on Jinja2 that transforms generic prompt blueprints into structured LLM inputs. Rather than manually formatting prompts with f-strings or string concatenation, you write templates using custom tags like `{% chat %}` to define message roles and content, then render them with context variables. The system handles conversion to chat message objects, image embedding for vision models, and metadata attachment for prompt versioning and management.
The package integrates with LLM providers through optional dependencies: it can invoke LLMs during template rendering to generate few-shot examples or perform function calling, supports prompt caching directives from providers like Anthropic, and stores prompts on disk with version tracking. Core templating requires only the base dependencies (Jinja2, Pydantic, Griffe for documentation), while advanced features like in-prompt LLM completion or Redis-backed caching require optional packages.
Use it for
- Build reusable chat prompt templates with system/user/assistant roles and render them as structured message objects for API calls.
- Include images in prompts for vision models and have Banks handle URL encoding or local file upload during rendering.
- Generate few-shot examples by invoking an LLM during template rendering to populate example sections dynamically.
- Define and version prompts with metadata, storing them on disk for team reuse and tracking changes across iterations.
- Attach function definitions to prompts and let Banks orchestrate LLM tool-calling roundtrips automatically.
- Mark sections of prompts for provider-specific caching (e.g., Anthropic's ephemeral cache) to reduce latency and cost.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Banks is actively maintained, has low install friction, carries a permissive MIT license, and solves a real problem—moving beyond ad-hoc string formatting for LLM prompts. The Beta status and recent release (6 days old) suggest active development. Install it if you're building LLM applications and want structured, versioned, reusable prompts; skip it if you're only calling LLMs with simple one-off strings.
Install
banks on PyPI
Before you install
Low friction install with a pure-Python wheel. Maintenance is active with a recent release (6 days old) and steady repository activity. Seven runtime dependencies are all well-established packages, though optional dependencies (litellm, redis) add capability for advanced features.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal restrictions.
Quickstart
pip install banks
from banks import Prompt
prompt_template = """
{% chat role="system" %}
You are a {{ persona }}.
{% endchat %}
"""
p = Prompt(prompt_template)
messages = p.chat_messages({"persona": "helpful assistant"})Verify before relying
- Whether optional dependencies (litellm, redis) are required for core templating or only for specific advanced features like LLM-based text generation and caching.
- Performance characteristics when rendering complex templates with many dynamic LLM calls or large image payloads.
- Stability guarantees given Beta development status (Development Status :: 4).
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesdeprecatedeval-type-backportfiletypegriffejinja2platformdirspydantic |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 8,360,654 / month, #1,631 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPy |
Evidence: banks-2.5.0-py3-none-any.whl
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