- AI Agents Frameworks
BAML is a domain-specific language for structured text generation and LLM function development.
- Free
- Open Source
- Horizontal
BAML
Introduction
BAML is a domain-specific language designed for structured text generation and the development of LLM functions. These functions are essentially prompt templates with defined input variables and specific output types, such as classes, enums, unions, or optional strings. BAML seamlessly integrates with languages like Python, TS, and others, allowing developers to focus more on engineering rather than prompting. It surpasses current methods of obtaining structured data, even with GPT-3.5, and outperforms tool-optimized models in the Berkeley Function Calling Benchmark. Explore our interactive results and learn more about the Schema-Aligned Parser.
BAML
Features
✨ Universal Model Support: BAML provides seamless compatibility with all major models like OpenAI, Anthropic, Gemini, Bedrock, VLLM, and more, making it highly versatile.
✨ Comprehensive Language Integration: It works with various programming languages, including Python, TypeScript, Ruby, Java, Go, and others, ensuring flexibility for developers.
✨ Lifecycle Management: BAML covers the entire lifecycle, from development and deployment to monitoring, streamlining the process for users.
✨ Structured Outputs for All Models: It guarantees structured outputs for any model used, ensuring consistency and reliability across different platforms.
BAML
Use Cases
✓ Chatbots: BAML can be utilized to design and enhance chatbots, allowing them to understand and process complex prompts for better interaction and responses.
✓ Parse Bank Statements: BAML’s structured text generation capabilities make it ideal for parsing and extracting relevant information from bank statements efficiently.
✓ Virtually Anything: The versatility of BAML enables it to be applied in a wide range of tasks, from simple prompts to complex data extraction, making it adaptable to almost any project.
✓ Build Multi-Agent Workflows: BAML can be used to create and manage multi-agent workflows, helping automate tasks and processes in various environments.
