Quansloth

It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.

Transform basic prompts into expert-level AI instructions. Enhance, benchmark & optimize prompts for ChatGPT, Claude, Gemini & more.

Vivgrid is an AI agent infrastructure platform that helps developers and startups build, observe, evaluate, and deploy AI agents with safety guardrails and global low-latency inference. Support for GPT-5, Gemini 2.5 Pro, and DeepSeek-V3. Start free with $200 monthly credits. Ship production-ready AI agents confidently.

Infratailors empowers you to optimize and observe the cost, energy, performance of your GPUs

Getting bad AI outputs? Find what's missing in your prompt and fix it in 30 seconds. Free AI-powered diagnosis to transform your prompts to expert level.

Continuously validate your LLM-based application throughout the entire lifecycle from pre-deployment and internal experimentation to production.

It is a no-code compute platform for language models. It is aimed at AI developers and product builders. You can also vibe-check and compare quality, performance, and cost at once across a wide selection of open-source and proprietary LLMs.

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

It is an open-source library designed to help developers build conversational streaming user interfaces in JavaScript and TypeScript. The SDK supports React/Next.js, Svelte/SvelteKit, and Vue/Nuxt as well as Node.js, Serverless, and the Edge Runtime.

Build, train, and deploy state of the art models powered by the reference open source in machine learning.

It allows you to run open-source large language models, such as Llama 2, locally.

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

It is an open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.

It is a Rust ecosystem of libraries for running inference on large language models, inspired by llama.cpp. On top of llm, there is a CLI application, llm-cli, which provides a convenient interface for running inference on supported models.

It is an open-source, drag & drop UI to build your customized LLM flow. It is built on top of LangChainJS, with the aim to make it easy for people to visualize and build LLM apps.

It is the easiest way for customers to build and scale generative AI-based applications using FMs, democratizing access for all builders.

It is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner.

It is an easy to use desktop app for experimenting with local and open-source Large Language Models (LLMs). It supports any ggml Llama, MPT, and StarCoder model on Hugging Face (Llama 2, Orca, Vicuna, Nous Hermes, WizardCoder, MPT, etc.)

It is an open-source product analytics suite for LLM-based applications. Iterate faster on your application with a granular view of exact execution traces, quality, cost, and latency.

It aims to enable developers (and even non-developers) to quickly build useful applications based on large language models, ensuring they are visual, operable, and improvable.

It is a full-stack application and tool suite that enables you to turn any document, resource, or piece of content into a piece of data that any LLM can use as reference during chatting. This application runs with very minimal overhead as by default the LLM and vectorDB are hosted remotely, but can be swapped for local instances.

Find what caused your AI bill. Opsmeter gives endpoint, user, model, and prompt-level AI cost attribution in one view.

Developer CLI tool for AI content compliance. Stamps files with provenance metadata, audits against EU AI Act, SOX, HIPAA. Integrates with GitHub Actions, pre-commit, and MCP.

It is a chat interface that lets you interact with Ollama. It offers features such as code syntax highlighting, Markdown and LaTeX support, local RAG integration, and prompt preset support. It can be installed using Docker or Kubernetes.

It is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation.

A high-performance AI detection infrastructure designed to identify synthetic media. AI Detect Lab leverages advanced neural network analysis to distinguish between human-generated content and AI outputs (Midjourney v7, Stable Diffusion 3.5, DALL-E 3，Flux2.0) with 99%+ accuracy. Supports multi-language text analysis and high-resolution image processing via a streamlined web interface.

Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT, etc.). It offers production-ready tools to build NLP backend services, e.g., question answering or semantic search.

It is an SDK that integrates Large Language Models (LLMs) like OpenAI, Azure OpenAI, and Hugging Face with conventional programming languages like C#, Python, and Java. It achieves this by allowing you to define plugins that can be chained together in just a few lines of code.

It is the framework for solving advanced tasks with language models (LMs) and retrieval models (RMs). It unifies techniques for prompting and fine-tuning LMs — and approaches for reasoning, self-improvement, and augmentation with retrieval and tools.

It provides all you need to build and deploy computer vision models, from data annotation and organization tools to scalable deployment solutions that work across devices.

It is a light package to simplify calling OpenAI, Azure, Cohere, Anthropic, Huggingface API Endpoints. Manages input/output translation.

It is an open-source monitoring & observability for AI apps and agents. It is designed to be usable with any model, not just OpenAI. It is easy to integrate and simple to self-host.

It is a cloud computing platform, primarily designed for AI and machine learning applications. The key offerings include GPU Instances, Serverless GPUs, and AI Endpoints. It is committed to making cloud computing accessible and affordable.

It is a powerful generative large language model that is designed to improve search accuracy and provide personalized recommendations. It is capable of performing a range of generative AI tasks, including text summarization, and text generation, etc.

It improves the cost, performance, and accuracy of Gen AI apps. It takes <2 mins to integrate and with that, it already starts monitoring all of your LLM requests and also makes your app resilient, secure, performant, and more accurate at the same time.

It is a lightning-fast inference platform that helps you serve your large language models (LLMs). Use a state-of-the-art, open-source model or fine-tune and deploy your own at no additional cost.

It is an AI observability and LLM evaluation platform designed to help ML and LLM engineers and data scientists surface model issues quicker, resolve their root cause, and ultimately, improve model performance.

It is an open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. Run inference with any open-source large-language models, deploy to the cloud or on-premise, and build powerful AI apps.

The collaborative testing platform for LLM applications and agents. Your whole team defines quality requirements together, Rhesis generates thousands of test scenarios covering edge cases, simulates realistic multi-turn conversations, and delivers actionable reviews. Testing infrastructure built for Gen AI.

It enables LLMs to use tools by invoking APIs. Given a natural language query, it comes up with the semantically and syntactically correct API to invoke.

It is a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU.

It is a simple-to-use, open-source evaluation framework for LLM applications. It is similar to Pytest but specialized for unit testing LLM applications. It evaluates performance based on metrics such as hallucination, answer relevancy, RAGAS, etc., using LLMs and various other NLP models locally on your machine.

It is a tool that enables fast and efficient local LLM finetuning. It uses a manual autograd engine and Flash Attention v2 to achieve 2-5x speedup and 50% memory reduction compared to QLoRA, without compromising accuracy.

It is a general video interaction platform based on large language models. Build a chatbot for video understanding, processing, and generation.

It is the easiest way to customize and serve LLMs. In LLM Engine, models can be accessed via Scale's hosted version or by using the Helm charts in the repository to run model inference and fine-tuning in your own infrastructure.

It is designed to provide a flexible framework to define and deploy large language model apps without having to write any execution code.

It is a library for creating semantic cache for LLM queries. Slash your LLM API costs by 10x, and boost speed by 100x.

It is a Multi-agent Meta programming framework that assigns different roles to GPTs to form a collaborative software entity for complex tasks. It takes a one-line requirement as input and outputs user stories / competitive analysis / requirements / data structures / APIs / documents, etc.

It is a self-hardening firewall for large language models. Protect your models and your users from adversarial attacks: prompt injections, prompt and PII leakage, toxic language, and more!

It is a framework and no-code GUI designed for fine-tuning state-of-the-art large language models (LLMs).