Cohere Generate Model

Generate is powered by a large language model that has read billions of words, learning the patterns and idiosyncrasies of sentences. Using this knowledge, it writes content, predicts outcomes or answers questions at your command

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

Generate Hackathon projects

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

WeCare Caretaker Assistant

We have built a solution for agencies which provide the caretaker services for parents who are in search of babysitters for their child. When users call the agency after business hours or when agents are not available for assistance, we are routing them to leave a voicemail with their babysitter requirement and contact number. With this solution, agents can focus on more complex tasks rather than manually retrieving voicemails, analysing them and coming up with a resolution. When the caller dials the agency phone number during office closed hours or peak hours when agents are not available to serve them, we route the caller to the voicemail menu where we ask them to leave a voicemail with babysitting requirements and their contact details, etc. Once the voicemail is available, we extract it and convert this speech to text using OpenAI’s whisper API which gives us the voicemail transcription. After that, we meticulously perform the prompt engineering for ChatGPT API to provide us all the required information from voicemail like intent, sentiment, babysitting date and time, etc in JSON format. Using this information, we query the EmployeeSchedule table which is in the H2 database. Once we have the information about availability of babysitters, we query RedisJSON to get the employee profile information like employee name, contact details, date of birth, languages spoken, image, etc. We then build a PDF document using itext library. This PDF containing available babysitter information will be sent on the caller’s WhatsApp. After this, we send an SMS to the agency as an alert notification about the customer enquiry and ask them to get in touch with the customer. Github link - https://github.com/technocouple/technocouple-caretaker-assistant Video link - https://drive.google.com/drive/folders/1NBew2U0Xgtm04ubQszjLvZV92fowR6-D?usp=sharing Presentation - https://drive.google.com/file/d/1TBMSU5Ohyn1v2P2u_RqbZOpuCvWv1Crq/view?usp=share_link DEMO is at the end of the video.

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.

Heuristic AI

Heuristic AI brings browsing your Slack chat histories into a new dimension. Fueled by Qdrant vector search engine and the Generative model of Cohere, Heuristic.ai extracts the context from your question and matches it with your chat messages to elaborate the answer. Forget keywords and chats scrolling. We give you the answer and the source message in seconds! Vision: to enable people to find answers to any questions in their digital experience. Mission: to bring browsing chat histories to a new dimension How it works: 1. The user write normal query with the structure we have “hai, setup” or “hai, question” 2. Ngrok forward queries from slack_api to the Amazon server 3. Here, we evaluate the query to take action: - Setup from the sentence <hai, setup> or a sentence which contains hai and setup - Search: from the sentence that contains only the word hai - None, if the message sent in slack is a normal message 4. here we have two scenarios: - in the case of the setup action, we retrieve all the messages from all the channels, then encode them using co.embed prepare to be ready to store in Qdrant vector database - in the case of the search action, we encode the user query to retrieve the first 5 relevant messages from the conversations, then extract the answer to the user query from the first message retrieved using co.generate 5. Qdrant is the vectors search engine that allows us to store our vectors and to search on them. 6. Then lastly, the extracted answer is sent to the user.

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.

Sherlocks Phoenix

Our Sherlock's Phoeniks Search Squad solution is a facial recognition system that utilizes generative AI models like ChatGPT and stable diffusion, as well as computer vision techniques, to identify and locate missing persons in real time . The system will take input in the form of text describing the appearance of the missing person, as well as raw images such as sketches, CCTV footage, or blurry photos. The algorithm will then search through internal databases and internet/social media platforms like Facebook and Twitter to find matches and potentially identify the missing person. This system has the potential to significantly aid Police and Investigating agencies in their efforts to locate and bring missing persons home

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.

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

MyThorch

MyThorch is a revolutionary document interaction app that leverages user behavior to embed vectors and store them in a Redis vector database. This process creates a long-term memory AI that truly understands the user's needs and preferences, leading to a highly efficient reading experience. The user uploads documents and the app filters for key points and also provide content the user cares about. The user can then select any part of the document to clarify further and track down references for specific parts of the generated document, ensuring accuracy and avoiding AI hallucinations. Using React for the frontend and Flask for the backend, we deliver a fast and efficient user experience. The GPT-3 API generates personalized documents based on user focus, while Redis stores previous interactions to reduce token input to GPT-3. Constant data collection helps us adapt to the user's needs for a personalized experience. Future plans include integration with Kindle, Kobo, Google, and Firefox, as well as partnerships with document management systems and cloud storage platforms. Our subscription-based business model offers premium features for $2/month. MyThorch is a game-changer for students, teachers, educators, and researchers, offering enhanced productivity and time-saving benefits.

The Future of AI podcast

An artificial intelligence podcast that is written by ChatGPT, GPT-3.5, Open-AI davinci, and human assistance. The art is generated by Stable Diffusion, Open Journey, and Dall-E 2. It is read by Natural Readers text-to-speech and Lifelike Speech Synthesis Google Cloud. The platform used is Anchor.fm and the availability of the podcast are in Google Podcasts, Apple Podcasts, Amazon Music, Spotify, Castbox, Pocket Casts, RadioPublic, and Stitcher. The podcast description is: "Join us as we explore the rapidly advancing world of artificial intelligence, and what it means for our future. In each episode, we'll discuss the latest AI research and developments, and how they are poised to impact various industries and aspects of our daily lives. From self-driving cars to intelligent virtual assistants, we'll delve into the potential and the challenges of this rapidly evolving technology. Tune in to stay up-to-date on the future of AI and its impact on society." Created and written by Artificial Intelligences and Cyber World. Currently the podcast has 12 episode in season 1 which has one episode for introduction and special and it has 5 episode currently for season 2. AI has come a long way since its inception and has been widely used in various fields such as healthcare, finance, and transportation. AI-powered machines and systems have the ability to learn and adapt to new situations without the need for human intervention. This ability of AI has made it an integral part of various industries and has brought about significant changes in the way we work and live. The current state of the AI industry is quite promising. The AI market is expected to grow from $9.5 billion in 2018 to $118.6 billion by 2025. The adoption of AI is increasing at a rapid pace and is being used in a variety of applications such as image recognition, speech recognition, and natural language processing. The use of AI in healthcare has also shown promising results, with AI-powered systems.

Newscribe

Problem: We use different platforms for accessing various media formats. When come to the user, it is time-consuming, information-overload and quite frustrating. Now, if we move on to content creation, we need to access various platforms to post those content. It also has same limits. So why not create a platform that supports all media formats. With the AI, content creation, moderation, and recommendation becomes easier and effective to both user and creator. This is the main motive of Fusion.AI Newscribe is an AI-powered app that transcribes news videos into written blog posts, simplifying content creation for bloggers and news writers. It demonstrates on how AI can be used in content creation and moderation. It has two interface 1. Home 2. Creator 1. Home - For this demo I've integrated it with a firstpost news channel in youtube. This provides the content. The transcript is send to OpenAI to generate the Blog post also to DallE to generate the image. OpenAI is also used in extracting the keywords and also its details. 2. Creator - This is specifically curated for content creators. Here the creator is able to create content like blog post, generated images.thumbnails and generate tweets. The demo application is build with OpenAI, DallE, TwitterAPI and Streamlit.

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.

Smart Study

Smart Study is a cutting-edge web application designed for students, teachers, and anyone looking to enhance their learning experience. The app provides a unique and convenient way to test and evaluate your understanding of a specific topic or YouTube video. By generating multiple choice quizzes, users can quickly and easily assess their knowledge, retain information better, and identify areas that require further study. The app's interface is user-friendly and intuitive, making it easy for anyone to get started. To generate a quiz, simply input the text content or provide a link to the desired YouTube video. Smart Study will then extract the most important information and create a comprehensive quiz, complete with multiple choice questions and answers. This makes studying for exams, completing homework assignments, or just keeping your knowledge up-to-date more efficient and enjoyable. One of the most significant benefits of Smart Study is its ability to personalize the learning experience for each user. With the app's adaptive learning technology, the difficulty level of the quizzes adjusts based on the user's performance, ensuring that the user is always challenged and engaged. As a result, users can make faster progress and retain information better.

Project Peace

Project Peace is a Multilingual Text Detoxifier. It is an innovative solution to identify and neutralize toxic or harmful language in written text. It utilizes advanced AI algorithms powered by Cohere’s multilingual models to understand and analyze text across multiple languages, and flag potentially toxic language, including the ability to convert that toxic language into neutral and non-toxic one. Project Peace’s ability to process text in multiple languages, allows it to address the problem of toxic language on a global scale. Project Peace can be integrated into online platforms, such as social media websites, online forums, and online communities, to help prevent the spread of toxic language and promote a safer online environment. It can be used by businesses and organizations to monitor and control the language used on their website and even in their customer care services. It can also be used by governments and public institutions to monitor and control the language used in online communication channels and to promote social harmony and inclusion. It can be used by educators and schools to help prevent bullying and toxic language in online learning environments, ensuring that students have a safe and supportive learning environment. private individuals as well who want to promote a safer and more inclusive online environment, or who want to ensure that the language they use online is respectful and non-toxic. Project Peace has an appealing future by its scalability and customization. By integrating it with the existing social platforms, it can be made accessible to a wide range of users. Moreover, it has the potential to become an industry standard for detecting and detoxifying toxic texts. The goal of the project remains to create a safer online community by reducing the spread of hate speech, cyberbullying, and other forms of harmful language.

notifAI

notifAI, a note-taking assistant powered by Artificial Intelligence, is a practical tool for students, teachers, or anyone that needs to read and understand large amounts of text. It can be challenging to process complex paragraphs of information, which is why we made notifAI. Using it is as simple as opening the app and taking a picture of the text, and the user will have access to an easy-to-read summary and main ideas. This is made possible with Cohere's large language model for summarizations as well as the Google Cloud Vision API to translate images to text. With this tool, we hope to help others understand the world around them efficiently and effectively.

Docs Buddy

Docs Buddy is a cutting-edge medical semantic search engine that combines the power of coherence embeddings with the reach of Google search. It offers healthcare professionals and pharmaceutical associates an efficient way to access relevant information about symptoms, medications, and treatment procedures. By simply inputting symptoms, users can retrieve a comprehensive list of documents that match their search criteria. Additionally, Docs Buddy also allows users to search for specific medications, providing images, prices, and even the option to buy online. Say goodbye to endless scrolling and hello to fast and accurate results with Docs Buddy. 🚀 Upgrade your medical search game today! 💻

Join one of our AI hackathons to build modern artificial intelligence together with talented members of our lablab community

TBA

HACKATHON

to be announced

AI21 Labs Hackathon #2

🗓️ This will be a 7-day virtual hackathon on 21 - 28 April 💻 Access AI21 Labs' state-of-the-art language models to build innovative applications 💡 Meet and learn from AI21 Labs and Lablab experts 👥 Join the community and find your team ✔️ All levels are welcome, AI tutorials and mentors are there to help you 🏆 Prizes and awards TBA ⭐ Receive a certificate of completion and Wordtune premium for submission 🐱‍💻 Sign up now! It's free!

TBA

HACKATHON

to be announced

Stable Diffusion AI Hackathon

🔥 7 days Hackathon 🦾 Get pre-market access for newest Stability.ai models - special for Hackathon participants 🛠️ Incorporate Stable Diffusion 2.0 and Vercel software to your projects 🚀 Create your complete product MVP 🤝 Find co-founders and mentors on the lablab.ai platform

TBA

HACKATHON

to be announced

Build your AI Startup Hackathon. Episode 2

🛠️ 7 days of Learning and Building 🤝 Come with your team or find one during the Hackathon 🦾 Free access to Generative AI models and Tech Tutorials 🏅 Win a place in the Early Stage StartUp Accelerator program 🚀 Join community of AI experts