Chroma vs LlamaIndex
Overview
🔥 Trending in Text & Language Models on StackShare
The weights and architecture of Mixture-of-Experts model, Grok-1 (By xAI)
Detailed Comparison
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. |
Offers data connectors to your existing data sources and data formats;
Storing context in an easy-to-access format for prompt insertion | Fully-typed, fully-tested, fully-documented;
Dev, Test, Prod: the same API that runs in your Python notebook, scales to your cluster;
Feature-rich;
Free & open source |
Statistics | |
GitHub Stars - | GitHub Stars 24.2K |
GitHub Forks - | GitHub Forks 1.9K |
Stacks 52 | Stacks 41 |
Followers 33 | Followers 15 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to LlamaIndex, Chroma?
Milvus
Milvus is an open source vector database. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.
Ollama
It allows you to run open-source large language models, such as Llama 2, locally.
LangSmith
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.
GPTScript
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.
LangChain
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.
Vercel AI SDK
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.
Hugging Face
Build, train, and deploy state of the art models powered by the reference open source in machine learning.
Qdrant
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.
LLM
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.
Flowise
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.
