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Rust library for OpenAI
The main features of 64bit/async-openai are: AI Agents and LLM Tools, Artificial Intelligence.
Projects with overlapping indexed features include: pydantic/monty — Monty is a sandboxed execution environment designed primarily for running Python code generated by AI models. It… liquidos-ai/autoagents — A multi-agent framework written in Rust that enables you to build, deploy, and coordinate multiple intelligent agents. boundaryml/baml — BAML is a prompt engineering framework and LLM client generator that defines AI prompts as type-safe functions. It… awakenworks/awaken — AI agent runtime for Rust — type-safe state, multi-protocol serving, plugin extensibility. 0xplaygrounds/rig — Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow… afshinea/stanford-cme-295-transformers-large-language-models — This project is a comprehensive technical course study guide and reference for learning the architectures and training…
BAML is a prompt engineering framework and LLM client generator that defines AI prompts as type-safe functions. It serves as a structured data extraction tool and workflow orchestrator, transforming unstructured model responses into strongly typed objects using a custom schema language and alignment algorithms. The project distinguishes itself by using a compiler to generate language-specific boilerplate code for API communication and output parsing. It features a dedicated environment for designing complex prompt templates with conditional logic and reusable snippets, and employs genetic alg
Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow builder for retrieval-augmented generation systems. It serves as an orchestrator for creating autonomous agents that can maintain conversation state and execute complex tasks through custom prompting and plugins. The project provides standardized interfaces for both completion and embedding model providers, allowing for unified request and response patterns across different engines. It also includes a vector database integration layer that defines a common interface for indexing
AI agent runtime for Rust — type-safe state, multi-protocol serving, plugin extensibility.
A multi-agent framework written in Rust that enables you to build, deploy, and coordinate multiple intelligent agents