The llm-agent is a TypeScript project designed to facilitate interactions with language models from multiple providers. It supports various LLM API providers that are compatible with the OpenAI API structure, allowing users to manage chat interactions and
Core interfaces, types, and lightweight default implementations for LLM agent orchestration.
LLM-Agent-First Specification schemas and conformance tooling
BeeAI Framework - LLM Agent Framework
LLM Agent Framework and Observe connector
Anthropic (Claude) LLM provider (ILlm) for @mcp-abap-adt/llm-agent.
OpenAI LLM provider (ILlm) for @mcp-abap-adt/llm-agent.
一个轻量级 LLM Agent
Alice - Feishu LLM agent connector runtime
High-performance fuzzy file finder for Bun - perfect for LLM agent tools
High-performance fuzzy file finder for Node.js - perfect for LLM agent tools
DeepSeek LLM provider (ILlm, extends OpenAIProvider) for @mcp-abap-adt/llm-agent.
SAP AI Core LLM provider (ILlm) for @mcp-abap-adt/llm-agent.
QdrantRag vector store and QdrantRagProvider for @mcp-abap-adt/llm-agent.
ANTLR4 grammar for the Plurnk LLM agent protocol
OpenAI embedding provider (IEmbedderBatch) for @mcp-abap-adt/llm-agent.
Shared types for exposing schema methods and properties to an LLM agent
PgVectorRag (PostgreSQL + pgvector) and PgVectorRagProvider for @mcp-abap-adt/llm-agent.
Lightweight multi-LLM agent library for building CLI AI assistants
Create browser automations with an LLM agent and replay them as Playwright scripts.
Ollama embedding provider and OllamaRag convenience class for @mcp-abap-adt/llm-agent.
LLM agent loop + remote/WASM/local providers + MCP wrapper
SAP AI Core embedding provider (IEmbedder) for @mcp-abap-adt/llm-agent.
OpenTelemetry GenAI utility for standardized telemetry collection across LLM, Agent, Embedding, Tool, Retrieval, Rerank, Memory and more
The agent library to build LLM applications that work with any LLM providers.
Foundation types for an LLM-agent workflow framework
Fast, scriptable command-line interface for the Tripletex REST API v2 (Norway's accounting platform). Self-refreshing session auth, 22 resource groups, JSON/table/CSV output, and a skills.sh manifest for LLM agents.
LLM Agents for Agent Stream Kit
Agent Runtime for LeLLM — ToolUseLoop, Executor, Fallback
Unified Tokio agent runtime -- orchestration, memory, knowledge graph, and ReAct loop in one crate
RustLLM - rustllm-agent component (placeholder)
Drop-in Rails engine to register JSON-schema tools, let an Llm fill missing fields, validate input, and execute handlers safely.
A Rails engine for creating, managing, and monitoring LLM-powered agents. Includes a DSL for agent configuration, execution tracking, cost analytics, and a mountable dashboard UI.
A minimal coding agent supporting Ollama, Anthropic, OpenAI, and VertexAI.
Memory infrastructure for agents: short-term checkpointing, long-term file-based and graph-based memory, retrieval with time decay, and maintenance jobs.
AgentRuby is a Ruby library that allows you to create and manage workflows using LLMs (Large Language Models). It provides a simple and intuitive interface for defining tasks, managing dependencies, and executing workflows.
Soka is a Ruby framework for building AI agents using the ReAct (Reasoning and Acting) pattern. It supports multiple AI providers including Gemini AI Studio, OpenAI, and Anthropic.
AgentRuby is a Ruby library that allows you to create and manage workflows using LLMs (Large Language Models). It provides a simple and intuitive interface for defining tasks, managing dependencies, and executing workflows.
OrchestraAI is a Ruby library that allows you to create and manage workflows using LLMs (Large Language Models). It provides a simple and intuitive interface for defining tasks, managing dependencies, and executing workflows.
A modular and extendable Rails engine that provides an Agent model and LLM client integration for building AI-powered applications.
Ruby-native LLM agent framework with provider adapters (Anthropic, OpenAI, Google), tool calling, streaming, and session persistence.
Kulu is a powerful orchestration tool for managing LLM agents and their data, inspired by the functionality of CrewAI models. It simplifies the process of integrating and coordinating multiple language models to solve complex problems efficiently.
Ruby AI Agents SDK enables creating complex AI workflows with multi-agent orchestration, tool execution, safety guardrails, and provider-agnostic LLM integration.
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