Buildt

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.

Sourcegraph is a universal code search tool that lets you find and fix things across ALL your code -- any code host, any repo, any language. Stay in flow and find your answers quickly with smart filters, and more.

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 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 embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.

FishEye provides a read-only window into your Subversion, Perforce, CVS, Git, and Mercurial repositories, all in one place. Keep a pulse on everything about your code: Visualize and report on activity, integrate source with JIRA issues, and search for commits, files, revisions, or people.

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 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.

Hound is an extremely fast source code search engine. The core is based on this article (and code) from Russ Cox: Regular Expression Matching with a Trigram Index. Hound itself is a static React frontend that talks to a Go backend. The backend keeps an up-to-date index for each repository and answers searches through a minimal API.

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 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.

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 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.

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.

It is an industry-leading semantic code analysis engine that is used to discover vulnerabilities across a codebase. It lets you query code as though it were data. Write a query to find all variants of a vulnerability, eradicating it forever. Then share your query to help others do the same.

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.

Search engine to find source code across all your Git repositories quickly. Search using keywords, exact code, fuzzy, semantic search & more.

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 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 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 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 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 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 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 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.

It is a fast and usable source code search and cross reference engine, written in Java. It helps you search, cross-reference and navigate your source tree. It can understand various program file formats and version control histories of many source code management systems.

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

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 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 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 the interface between your app and hosted LLMs. It streamlines API requests to OpenAI, Anthropic, Mistral, LLama2, Anyscale, Google Gemini, and more with a unified API.

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 low code platform to rapidly annotate data, train and then deploy custom Natural Language Processing (NLP) models. It takes care of model training, data selection and deployment for you. You upload your data and we provide an annotation interface for you to teach a classifier. As you label we train a model, work out what data is most valuable and then deploy the model for you.

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

It is a new scripting language to automate your interaction with a Large Language Model (LLM), namely OpenAI. The ultimate goal is to create a natural language programming experience. The syntax of GPTScript is largely natural language, making it very easy to learn and use.

It is a language model that aligns a frozen visual encoder with a frozen large language model (LLM) called Vicuna, using just one projection layer. It possesses many capabilities similar to GPT-4, including generating detailed image descriptions and creating websites from handwritten drafts.

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

It is a Python library to label, clean, and enrich text datasets with any Large Language Models (LLMs) of your choice.

It is a framework for building and running Generative AI (Gen AI) applications. It is designed to make it easy to build and run Gen AI applications that can process data in real-time.

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 to easily create LLM powered bots over any dataset. It abstracts the entire process of loading a dataset, chunking it, creating embeddings, and then storing it in a vector database.

It is an LLM playground you can run on your laptop. It allows experimenting with multiple language models. You can compare models side-by-side with the same prompt, individually tune model parameters, and retry with different parameters.

It is an open-source package that combines threeJS and Stable diffusion to build a virtual photo studio for product photography. Load a 3D model into the browser and virtual shoot it in any kind of scene you can imagine.