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The AI framework that adds the engineering to prompt engineering (Python/TS/Ruby/Java/C#/Rust/Go compatible)
Demo of knowledge graph creation and Graph RAG with BAML and Kuzu
Building Agents with LLM structured generation (BAML), MCP Tools, and 12-Factor Agents principles
Getting started with BAML for creating and querying knowledge graphs with LLMs
Code from the ODSC Agentic Graph RAG workshop combining vector, FTS & graph retrieval for RAG. Includes observability and guardrails for evaluating outputs.
Powerful BAML editor for .NET, built on dnlib
Generate BAML style prompts from dry-schema that can get and check structured responses from LLMs
Experiments and benchmarks with Text2Cypher for Graph RAG
Clairvoyant is your personal assistant with memory. It knows what you need to know to be the best you need to be. Works on the Even Realities G1
Python library for dynamic BAML schema generation and LLM structured data extraction. Built on BoundaryML with support for OpenAI, Anthropic, Ollama, and OpenRouter.
Dynamic BAML is a Python library that simplifies data extraction from text using Large Language Models and dynamically generated schemas. With a focus on ease of use and type safety, it integrates smoothly with various providers, making it a versatile tool for developers. 🐙🌟
Agente de IA simples com acesso à base de dados do INPI e capacidades de cálculo, desenvolvido com BAML e TypeScript
BAML .NET Client Library
Build reliable LLM applications with the 12-Factor Agents principles. Explore best practices and contribute to our open-source project on GitHub! 🚀🌟
Benchmarks to help find the best, fastest and cheapest open models for structured output and tool use