baml-integration

Automate BAML-based LLM prompting with type-safe patterns across Python and TypeScript.

8|1|Updated Jul 11, 2025
One-click install
npx skills add https://github.com/Consiliency/treesitter-chunker --skill baml-integration-consiliency
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: baml-integration
Source: https://github.com/Consiliency/treesitter-chunker/tree/main/.ai-dev-kit/skills/baml-integration
Command: npx skills add https://github.com/Consiliency/treesitter-chunker --skill baml-integration-consiliency

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a framework for consistent, type-safe BAML prompting and generated clients across Python and TypeScript, helping teams enforce structure and reduce errors in LLM integrations.

Core Features & Use Cases

  • DTO-driven prompts: Define input/output DTOs that map to generated Python and TypeScript types.
  • Framework-agnostic clients: Auto-generate language-specific clients and wrappers for seamless integration.
  • Cross-language codegen: Maintain synchronized schemas across languages for reliable multi-platform workflows.

Quick Start

Install BAML CLI and generate clients from your BAML definitions:

  • pip install baml-cli
  • baml-cli generate

Frequently Asked Questions about baml-integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate type-safe client code for LLM prompts across Python and TypeScript?

Type-safe codegen for LLM clients uses BAML to define input/output DTOs, then automatically generates language-specific types and wrappers. Run `baml-cli generate` to create synchronized Python and TypeScript clients from your BAML definitions, enforcing strict typing across both languages.

Can I use BAML to standardize prompts and responses across multiple programming languages?

Yes. BAML enables cross-language codegen by maintaining synchronized schemas in a single definition file. Both Python and TypeScript clients are generated from identical BAML specs, ensuring consistent prompts and response structures without manual synchronization.

What's the best way to structure LLM integrations to reduce type errors and inconsistencies?

Use DTO-driven prompts with BAML to define contracts upfront. Framework-agnostic generated clients enforce types at compile time across Python and TypeScript, catching schema mismatches before runtime and eliminating manual serialization errors.

How does BAML codegen simplify multi-platform LLM deployments?

BAML codegen eliminates manual client and DTO writing by auto-generating typed wrappers for each language. Once defined in BAML, a single schema generates both Python and TypeScript implementations, reducing deployment friction and maintenance burden.

Do I need to install separate tools to generate BAML clients for both languages?

No. Install the BAML CLI once with `pip install baml-cli`. A single `baml-cli generate` command produces type-safe clients and DTOs for both Python and TypeScript from your BAML definitions in one step.