Model listing and resolution for LLM providers
Language Models View
Tokenizer for OpenAI large language models.
Generate llms.txt files to train large language models on your Starlight documentation website
The [OpenRouter](https://openrouter.ai/) provider for the [Vercel AI SDK](https://sdk.vercel.ai/docs) gives access to over 300 large language models on the OpenRouter chat and completion APIs.
DeepSeek provider integration for Metorial - enables using Metorial tools with DeepSeek's language models through function calling.
Together AI provider integration for Metorial - enables using Metorial tools with Together AI's language models through function calling.
Mistral AI provider integration for Metorial - enables using Metorial tools with Mistral's language models through function calling.
A flexible plugin that drives your tests with human-written commands, enhanced by the power of large language models (LLMs)
The OpenRouter TypeScript SDK is a type-safe toolkit for building AI applications with access to 300+ language models through a unified API.
Utility methods for calling language models through the Foundry proxy endpoint
Large language models and functionality for Saltcorn
AI-powered development assistant that brings advanced language models directly to your terminal
Semantically create chunks from large texts. Useful for workflows involving large language models (LLMs).
AIGNE Poe SDK for integrating with Poe's language models and API services
AIGNE XAI SDK for integrating with XAI language models and API services
A simple JSON parser designed to handle malformed JSON from Large Language Models
A lightweight package providing information about various Large Language Models (LLMs), including embedding, reranking, and other models.
TypeScript bridge for recursive-llm: Recursive Language Models for unbounded context processing with structured outputs
Fast tokenizer for language models, supporting BPE, Unigram and WordPiece tokenization
Generate llms.txt files to train large language models on your Starlight documentation website
Search, filter, and compare Large Language Models based on capabilities and attributes
A browser-native implementation of GPT language models built on TensorFlow.js, developed as part of the Finnish Generation AI research project. This library enables training, fine-tuning, and inference of transformer-based language models entirely in the
Generate llms.txt files to train large language models on your astro project
A Rust crate providing an enumeration for various language model types used in machine learning applications, enabling precise model specification through enums.
A procedural macro for deriving batch-oriented language model workflows using annotated client and workspace fields.
A crate for token expansion, leveraging batch workflows and language model APIs.
A Rust library that facilitates precise instructional communication with Language Models by using agent coordinates, emphasizing structured JSON outputs and avoiding vague language.
burn baby dragon hatchling inference and training
burn dragon inference and training
burn dragon core model and utilities
burn (baby) dragon hatchling inference and training
burn (baby) dragon hatchling inference and training
RLM (Recursive Language Model) plugin for elizaOS
An opinionated, simple Rust interface for local LLMs, powered by llama-cpp-2
A fast constrained decoding engine based on context free grammar.
Text Splitter for Large Language Model Datasets.
A parser for the RAML API modeling language.
Drawing the Unified Modeling Language of Rack.
Provides the parser + compiler infrastructure for the Gisele process modeling language.
Scoped search makes it easy to search your ActiveRecord-based models. It will create a named scope :search_for that can be called with a query string. It will build an SQL query using the provided query string and a definition that specifies on what fields to search. Because the functionality is built on named_scope, the result of the search_for call can be used like any other named_scope, so it can be chained with another scope or combined with will_paginate. Because it uses standard SQL, it does not require any setup, indexers or daemons. This makes scoped_search suitable to quickly add basic search functionality to your application with little hassle. On the other hand, it may not be the best choice if it is going to be used on very large datasets or by a large user base.
MetaRuby is a set of module and classes that help one use the Ruby type system as a basis for modelling.
ActiveFacts provides the Constellation Query Language (CQL), a fact modeling and query language. CQL combines a controlled natural language verbalisation with formal logic, producing a formal language that reads like plain English. ActiveFacts compiles fact models in CQL and generates relational and object models in SQL, Ruby and other languages.
The Ruby framework for programming with large language models. DSPy.rb brings structured LLM programming to Ruby developers. Instead of wrestling with prompt strings and parsing responses, you define typed signatures using idiomatic Ruby to compose and decompose AI Worklows and AI Agents.
Leva is a Ruby on Rails framework for evaluating Language Models (LLMs) using ActiveRecord datasets. It provides a flexible structure for creating experiments, managing datasets, and implementing various evaluation logic.
AMoR is a Ruby DSL for mathematical programming. It allows to simply define a mathematical program, but gives you all the features from Ruby for more complex projects
Lightweight CLI client for interacting with AI using large language models (LLM)
76 world's languages and codes
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