Cohere Embed Modal

Embed model turning text into numerical representations of language for deeper insights at scale. Embed makes it possible to algorithmically categorize and score text quickly to extract meaning.

Boilerplates

Cohere is a company that specializes in artificial intelligence. Their mission is to help businesses harness the power of AI to improve their operations. Cohere offers a suite of AI-powered tools that can be used to automate tasks, improve customer service, and boost sales. Their products are designed to be easy to use and integrate with existing business systems. The Cohere natural language processing platform makes it easier for developers to build natural language processing models into applications and helps companies infuse natural language processing capabilities into their business using tools like chatbots, without requiring AI expertise of their own. Useful links: Cohere website, Co:here platform, Co:here Docs

Cohere Libraries

Discover Co:here API SDK's to help you get started

Cohere Node

This package provides functionality developed to simplify interfacing with the cohere.ai natural language API. This SDK provides support for both TypeScript and JavaScript Node.js projects.

JS/TS Cohere Go

This package provides functionality developed to simplify interfacing with the cohere.ai natural language API in Go.

Go Cohere Python

This package provides functionality developed to simplify interfacing with the Cohere API in Python 3.

Python Cohere Ruby

This package provides functionality developed to simplify interfacing with the cohere.ai NLP API in Ruby.

Ruby

Cohere Boilerplates

Boilerplates to help you get started

Nextjs Boilerplate

Article summarizer Boilerplate for Nextjs, Co:here, TailwindCSS, Vercel.

Javascript Streamlit Boilerplate

Hashtag generator Boilerplate for Co:here, Streamlit, Streamlit Cloud.

Python Replit Boilerplate

Generate an email on command with Co:here and Replit.

Python

Cohere Sandbox

Sandbox is a collection of experimental, open-source GitHub repositories that make building applications using large language models fast and easy with Cohere

Sandbox Introduction Blog Post

Sandbox aims to help build and strengthen language AI communities while enabling contributors to build more robust applications and services faster than ever.

Sandbox Conversant - Github repository

Conversational AI tooling & personas built on Cohere's LLMs

Python Sandbox Conversant - PyPi repository

Conversational AI tooling & personas built on Cohere's LLMs

Python Sandbox Conversant Streamlit Demo

Conversational Personas using Cohere and Streamlit

Python

Cohere Semantic Search

Language models give computers the ability to search by meaning and go beyond searching by matching keywords. This capability is called semantic search.

Introductory guide

Article for building a simple semantic search engine.

Collab Notebook - Basic Semantic Search

In this notebook, we'll build a simple semantic search engine

Python Semantic Search with Cohere Sandbox

A demonstration of how a semantic search engine can be quickly built using Cohere's platform.

Python

Cohere Multilingual Model

Cohere's Multilingual Text Understanding Model is Now Available

Sandbox Multilingual

Github Repo for the multilingual sandbox from Cohere

Quick Youtube Tutorial

Giving computers many human languages with Cohere's multilingual embeddings

Demo

Check out this multilingual movies search and recommendation demo that is built with Streamlit and Coheres' multilingual model

Embed Hackathon projects

Solutions built with Embed that have been created during our hackathons by the members of our community

Fetcher the work sidekick

In today's increasingly remote working style, organization’s messaging system, whether it's email or chat, contains lots of invaluable institutional knowledge. However, because these data are often unstructured and scattered, they are usually buried in the organization’s data ecosystem and are hard to search and extract value. Fetcher is a chatbot that integrates into popular chat platforms such as Discord and Slack to seamlessly help users find relevant people and documents to save them from endless frustrating search. It does this by semantically searching chat messages to find the most relevant results and help to deliver actions that leads to a peace of mind. Fetcher differs from traditional keyword search engines in that it searches by the meaning of the query, not just by keywords. It also enables multi lingual search, so that global teams can more quickly find important information even when language is a barrier. Since Fetcher searches in the embedding space, this search engine can extend to multi modal modes that includes audio and images. Fetcher works by collecting a chat channel’s history and embedding them using Cohere’s Embed API, then saving the embeddings to Qdrant’s vector search engine. When a new query comes in, Fetcher embeds the query and searches against the vector database to find the most relevant results, which can then feed into Cohere’s Generate API to summarize the message thread to kick start new conversations. Fetcher offers 3 commands, /fetch, using vector similarities search to find relevant chat messages. /discuss, summarize a message thread, and kick start a conversation with a channel number. /revise, a sentence correction tool similar to Grammarly, allows user to send professional sounding messages.

LegalFruit

Our project is aimed at developing a comprehensive legal document search system that makes use of advanced technologies to retrieve relevant legal documents that can be relied upon in court. The system utilizes Cohere's multilingual embedding and Qdrant vector database to provide fast and efficient search results. The use of multilingual embedding ensures that the system is capable of searching through legal documents written in various languages, making it suitable for use in multilingual environments. Qdrant vector database, on the other hand, allows for fast and efficient indexing of large volumes of legal documents, thus reducing search time. Our legal document search system is particularly useful for law firms, legal practitioners, and businesses that require access to legal documents for various purposes, including legal research, contract negotiations, and dispute resolution. With our system, users can easily retrieve legal documents that have been signed by mutual assent, thus ensuring that they are reliable and admissible in court. In addition to the legal document search functionality, we have also implemented a question answering system using Cohere's generate endpoint. This feature enables users to ask specific questions related to the legal documents they have retrieved and receive accurate and relevant answers. The question answering system is particularly useful for legal practitioners who require quick access to specific information in legal documents. Overall, our legal document search system provides an efficient and reliable solution for users who require access to legal documents. By leveraging advanced technologies such as Cohere's multilingual embedding and Qdrant vector database, we have developed a powerful search system that can save time and improve productivity for legal practitioners and businesses alike.

mindmate

In today's fast-paced work environment, information overload can make it challenging to find the information you need quickly. Research shows that knowledge workers spend 1 to 3 hours per day looking for information and documents. A big chunk of that time is spent understanding their organization's internal knowledge base. This process can be time-consuming, frustrating, and inefficient. That's why I created mindmate, an AI-powered assistant that helps users make sense of their company's internal knowledge base. With mindmate, users can easily search their company's internal knowledge base and receive answers to their questions in plain English using a simple chatbot interface. I built a proof of concept using GitLab's employee handbook during the hackathon. I created a simple yet powerful tool that allows users to ask questions and receive natural language answers by processing the handbook's 3,000 pages, creating embeddings with Cohere, storing them with Qdrant, and leveraging Cohere's text generation capabilities. mindmate is easy to use and provides quick access to information related to a variety of topics, including company policies, benefits, and more. By tailoring search results to each user's specific needs, mindmate helps knowledge workers save time and stay focused on their core responsibilities.

Fudl app

Are you tired of overspending on groceries every month and wasting your time reviewing supermarkets' promo materials? Fudl is the answer to all your problems! Our revolutionary AI-powered app is designed to help you save money on your grocery bill without compromising on quality. With Fudl, you can plan your purchases, analyze discounts and special offers, discover analogs of products you need for less price, find more savings with value-sized items, and send your orders directly to the delivery service. Let me explain all the features in a more detailed way: By using Fudl's personalized recommendations, you can use your grocery budget to find the best deals on the products you need. Fudl's AI technology analyzes your shopping list, gives you recommendations based on your individual preferences, and suggests alternative products that are just as good, if not better, at a lower cost. Fudl's innovative technology also allows you to split one order into several from different grocery chains, which can save you up to 50% on your grocery bill. This means you can buy in for the next week or plan your purchases for the weeks ahead, without worrying about overspending. Using Fudl to split your order, you can save money and collect additional points from grocery loyalty programs while still getting the needed products. Fudl uses databases from online stores to provide you with the best possible recommendations. For this example, we tested our algorithms on three major chains in Slovenia - Mercator, Spar, and Tus and got phenomenal savings from 10 to 40% on single bills. To find the most successful alternative for each product, we utilize the power of AI to determine its coordinates in a multidimensional space. By doing so, we can identify products that are similar in quality, volume, and other characteristics. Our intelligent algorithms then display the closest analogs to the original product, giving you the information you need to make an informed purchase decision.

Smart Health

Your personal health assistant. SmartHealth is capable of helping users quickly and easily access personalized health advice and guidance. By offering range of services such as symptom checker and personalized health tips to help users stay on top of their health and well-being. Who are We? SmartHealth is composed of passionate and talented team of Computer Science, Medical, Arts and Business individuals. Josh, Lizzie, Jason and Raj continue to apply the latest technology to improve Healthcare. How Do We Do It? We leverage the power of GPT3, Redis Vectorized DB, Python and React to provide you with an interactive, personalized health assistant. We put together a database of health conditions and their symptoms, causes, and treatments. By pairing our secure and personalized database with GPT3 we are able to help you understand your health without having to visit a doctor in person. Our Technologies We chose to use a future proof tech stack to get our ideas to become a reality, below are a few of the technologies we used.

Mentat

Mentat is designed to serve as an AI tutor for personal knowledge management, helping users to organize, connect, and make sense of their notes and ideas. One of the methodologies that Mentat employs is called Zettelkasten, which is a German term that roughly translates to "slip-box" or "card index." Zettelkasten is a note-taking and knowledge management system that was developed by German sociologist Niklas Luhmann. The system involves creating individual notes, or "slips," that are each focused on a single idea or concept. These notes are then linked together using a system of cross-referencing and tagging, allowing users to quickly find related notes and ideas. Mentat incorporates many of the key principles of Zettelkasten into its own methodology, including the emphasis on atomic notes (i.e., notes focused on a single idea or concept), the use of linking and cross-referencing to create connections between ideas, and the importance of creating a flexible, adaptable system that can evolve over time. By incorporating the principles of Zettelkasten into its design, Mentat aims to help users create a more efficient and effective system for managing their knowledge, and to encourage a more creative and insightful approach to thinking and problem-solving.

MagiLink

Magilink's product is a powerful tool for rapid website development and prototyping. With its AI-powered component library and user-friendly interface, users can easily convert natural language text into functioning website components that can be further modified to suit their specific needs. Magilink's innovative tool enables users to accelerate website development, saving them time and resources. With its extensive component library and efficient conversion process, Magilink streamlines the website development process, empowering designers, developers, and creators to create high-quality websites with ease

TaskMate

TaskMate is a solution that can be integrated into any website, providing AI-powered speech interaction with the website. AI plays a significant role in making the solution better because of natural language processing. Speech interaction can address the problems we have identified by providing hands-free interaction, increasing accessibility, improving productivity, and reducing cognitive load. Overall, speech interaction can make it easier to use your phone in a variety of situations and improve accessibility and productivity for all users. We believe that TaskMate has the potential to be a game-changer in the way people interact with websites.

I AM I personalized ChatGPT

Introducing an extension to ChatGPT that takes personalized chatbot technology to the next level. With this new tool, you can pre-train ChatGPT on your latest data, ensuring that you have the most up-to-date and relevant information at your fingertips. By selecting text and feeding it into the AI, you can create a customized knowledge base that is optimized for your specific needs. Powered by OpenAI, ChatGPT offers the best answers to your queries, making it an invaluable tool for individuals, teams, and clients alike. Whether you need to onboard new employees, update documentation, research articles, provide financial advice, or offer customer support, ChatGPT can help you do it faster and more efficiently than ever before. With its ability to generate summaries, recommendations, and insights tailored to your specific interests, ChatGPT is like having a personal research assistant available 24/7. It can help you stay on top of the latest news and trends, provide a comprehensive overview of your market, and even serve as a second brain to help you remember important information and ideas.

Psy Q Bot

Psy-Q Bot is an AI-powered chatbot that provides psychology-related information and resources to users. The development of the bot was guided by the goals of creating a product that is both useful and easy to use, and leveraging the capabilities of Cohere's API as much as possible: we use both generate and embed. The system is composed of a web client built using React and a server that provides centralized access to Cohere. The key component of the application is Cohere, which is used to analyze user questions, match them with relevant sources in the dataset, and generate responses. The Embed endpoint of Cohere is utilized to analyze and compare questions, while the Generate endpoint is used to generate responses and improve the custom Cohere model. The dataset used by the bot has also been partially augmented using Cohere's Generate endpoint, allowing for continuous training and refinement of the model.

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