Popular GitHub Repositories for Cohere Embed

Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]

Fully customizable AI chatbot component for your website

Automatic Generation of Visualizations and Infographics using Large Language Models

The "official" unofficial DSPy framework. Build LLM powered agents and other workflows, based on the Stanford DSP paper.

Python & JS/TS SDK for running AI-generated code/code interpreting in your AI app

Create chatbots with ease

Create Custom GPT and add/embed on your site using Assistants api

? Integrating LLMs into structured NLP pipelines

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, Meta, AI21, Cohere, Mistral) using AWS CDK on AWS

BaseAI — The Web AI Framework. The easiest way to build serverless autonomous AI agents with memory. Start building local-first, agentic pipes, tools, and memory. Deploy serverless with one command.

Ship RAG based LLM web apps in seconds.

Agent Cloud is like having your own GPT builder with a bunch extra goodies. The GUI features 1) RAG pipeline which can natively embed 260+ datasources 2) Create Conversational apps (like GPTs) 3) Create Multi Agent process automation apps (crewai) 4) Tools 5) Teams+user permissions. Get started fast with Docker and our install.sh

The all-in-one RWKV runtime box with embed, RAG, AI agents, and more.

A NodeJS RAG framework to easily work with LLMs and embeddings

One .NET library to consume OpenAI, Anthropic, Cohere, Google, Azure, Groq, and self-hosed APIs.

Smoothly Manage Multiple LLMs (OpenAI, Anthropic, Azure) and Image Models (Dall-E, SDXL), Speed Up Responses, and Ensure Non-Stop Reliability.

A Reactive CLI that generates git commit messages with Ollama, ChatGPT, Gemini, Claude, Mistral and other AI

LLMs and Machine Learning done easily

OpenAI-compatible Python client that can call any LLM

Takes in a users question and returns an answer along with URL resources.