A unified TypeScript client for interacting with various LLM providers
LLM Chain - OPENAI - todo
n8n community node for DeepSeek chat models (Pro / Flash) with reasoning_content (Chain-of-Thought) support, usable as a LangChain sub-node inside the AI Agent and Basic LLM Chain.
n8n supply node for Groq API - Provides Groq language models for use with Basic LLM Chain and other AI nodes. Ultra-fast inference with Llama, Mixtral, Gemma, and GPT-OSS models.
Rooyai Message / Chat Model for n8n - A first-class LLM provider node compatible with AI Agent, Basic LLM Chain, and other n8n AI workflows
n8n community node for DeepSeek chat models (Pro / Flash) with reasoning_content (Chain-of-Thought) support, usable as a LangChain sub-node inside the AI Agent and Basic LLM Chain.
Typescript bindings for langchain
n8n community node to connect RunPod Serverless LLM endpoints to Basic LLM Chain and AI Agent
Old abstractions from LangChain.js
Chain functions, generators, Node streams, and Web streams into a pipeline with backpressure support.
HANDLE CONFIGURATION ONCE AND FOR ALL
A utility for managing a prototype chain
API for combining call site modifiers
TypeScript definitions for stream-chain
Access Google Gemini AI models from Rooyai.com in n8n! Get your free API key at https://rooyai.com and use Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.0 Flash, Gemini 1.5 Pro and more with AI Agent, Basic LLM Chain, and other n8n AI nodes.
HTTP daemon and CLI for agent-driven browser extension testing with Playwright
Flame-chart latency profiler for LLM chains
Enforce real-time token budgets and spending limits for OpenAI, Anthropic Claude, and Google Gemini API calls in Node.js
A simple asynchronous tool
BlockRun SDK - Pay-per-request AI (LLM, Image, Video, Music, Voice) via x402 on Base and Solana
The Aikido Safe Chain wraps around the [npm cli](https://github.com/npm/cli), [npx](https://github.com/npm/cli/blob/latest/docs/content/commands/npx.md), [yarn](https://yarnpkg.com/), [pnpm](https://pnpm.io/), [pnpx](https://pnpm.io/cli/dlx), [rush](https
Display language model outputs in your React project.
Hardware accelerated language model chats on browsers
[llm-ui](https://llm-ui.com) markdown block.
A library for running chains of LLMs (such as ChatGPT) in series to complete complex tasks, such as text summation.
A library implementing `llm-chains` for OpenAI's models. Chains can be use to apply the model series to complete complex tasks, such as text summation.
A library implementing `llm-chains` for OpenAI's models. Chains can be use to apply the model series to complete complex tasks, such as text summation.
For using hnsw with llm-chain
For using Qdrant with llm-chain
A library for providing Large Language Models with tools (also known as 'actions') that they can trigger
Use `llm-chain` with a local [`llm`](https://github.com/rustformers/llm) backend.
Use `llm-chain` with a mock backend. Useful for testing.
Use `llm-chain` with a SageMaker Endpoint backend.
A library implementing `llm-chains` for LLamA. Chains can be use to apply the model series to complete complex tasks, such as agents.
Set of macros for use with llm-chain
A Discord bot for LLM chain apps
LLM Chain is a powerful Ruby framework that provides tools for building sophisticated LLM-powered applications. It includes support for prompt management, conversation chains, memory systems, vector storage integration, and seamless LLM provider connections. Key features: • Chain-based conversation flows • Memory management with Redis • Vector storage with Weaviate • Multiple LLM provider support • Prompt templating and management • Easy integration with existing Ruby applications
ace-sim executes preset-driven simulation chains across multiple providers so teams can validate ideas, review tasks, and compare synthesis outcomes before taking action.
Ruby chain tools to work with LLMs
rails_ai_promptable makes it easy to integrate AI-driven features into your Rails application. It allows you to define promptable methods, chain context, and connect with AI APIs like OpenAI, Anthropic, or local LLMs with minimal setup.
AsktiveRecord bridges human language and database queries. It lets you interact with your Rails database as if you were having a conversation with a knowledgeable assistant. Instead of writing SQL or chaining ActiveRecord methods, you simply ask questions in plain English (or any language) and get clear, human-friendly answers powered by LLMs.
A comprehensive Ruby implementation of a Knowledge-Based System featuring: • RETE Algorithm: Optimized forward-chaining inference engine with unlinking optimization for high-performance pattern matching • Declarative DSL: Readable, expressive syntax for rule definition with built-in condition helpers • Blackboard Architecture: Multi-agent coordination with message passing and knowledge source registration • Flexible Persistence: SQLite (durable), Redis (fast), and hybrid storage backends with audit trails • Concurrent Execution: Thread-safe auto-inference mode for real-time processing • AI Integration: Native support for LLM integration (Ollama, OpenAI) for hybrid symbolic/neural reasoning • Production Features: Session management, fact history, query API, statistics tracking Perfect for expert systems, trading algorithms, IoT monitoring, portfolio management, and AI-enhanced decision systems.
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