Boundary BAML
A domain-specific language and platform for generating reliable, type-safe structured outputs from large language models (LLMs) with enhanced developer experience.
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Product Overview
What is Boundary BAML?
Boundary BAML is a specialized programming language designed to simplify and optimize prompt engineering for LLMs by enabling developers to write structured, type-safe prompts and receive validated structured data outputs. It supports any LLM, programming language, and schema, providing autocomplete, live previews, and robust parsing that corrects LLM errors. BAML significantly improves developer productivity by integrating prompt logic directly into code editors like VSCode, eliminating the need for complex setups and allowing seamless function-like calls to LLMs with guaranteed output structure and type safety.
Key Features
Type-Safe Structured Outputs
Generates fully type-checked, structured data from LLMs, ensuring reliable and predictable outputs even during streaming.
Universal Compatibility
Works with any large language model, programming language, and custom schema, offering maximum flexibility.
Developer-Friendly Environment
Includes a VSCode playground with live prompt previews, autocomplete, linting, and hot-reloading for rapid prompt development.
Efficient Token Usage
Utilizes type-definitions instead of JSON schemas, reducing token consumption by up to 60% without loss of information.
Robust Parsing and Validation
Automatically parses and validates LLM outputs against defined schemas, correcting errors and ensuring data integrity.
Cross-Language SDKs
Provides native SDKs for Python, TypeScript, and Ruby, enabling seamless integration and usage as native functions with autocomplete and type safety.
Use Cases
- Reliable Data Extraction : Extract structured information from unstructured text such as resumes, emails, or documents with high accuracy.
- Agent and Chatbot Development : Build dependable AI agents and chatbots that require precise structured responses and complex prompt logic.
- Prompt Engineering and Testing : Rapidly develop, test, and iterate on prompts within an integrated environment to optimize LLM interactions.
- Enterprise AI Pipelines : Deploy robust AI data processing pipelines with guaranteed structured output for large-scale batch processing.
FAQs
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Analytics of Boundary BAML Website
🇺🇸 US: 56.82%
🇻🇳 VN: 15.05%
🇮🇳 IN: 7.77%
🇹🇷 TR: 3.46%
🇩🇪 DE: 3.05%
Others: 13.85%