What is CopilotKit?
CopilotKit is an open source framework designed to make it easier to integrate AI into applications. With 4.4k+💫Git Stars, it received great appreciation within the open source community. It enables the creation of personalized AI co-pilots, including in-app AI chatbots and agents that can dynamically interact with the application environment. The framework is designed to streamline AI integration by handling complex aspects such as context awareness and application interaction.
Please feature CopilotKit to support their work:
https://github.com/CopilotKit/CopilotKit
Challenges solved with CopilotKit
Here are the four challenges among many others that CopilotKit helps to overcome:
![](https://www.marktechpost.com/wp-content/uploads/2024/04/Screenshot-2024-04-24-at-5.00.55-AM-1024x500.png)
CopilotKit Components
The CopilotKit offers many components that you can use for your applications. It natively supports LangChain, LangGraph and LangServe and also provides built-in native UI/UX components that you can use as part of your applications:
- Co-pilot cat: This tool helps create application-aware AI chatbots that can interact with the application frontend and backend, as well as third-party services.
- Copilot Textarea: It acts as an immediate replacement for any '
' and offers AI-assisted text generation and editing. - In-app agents: CopilotKit enables real-time contextual access to applications and allows agents to take action within applications.
- Co-agents: It will be released soon and can allow end users to intervene and restart agent operations if necessary.
- Objective-specific LLM channels: It customizes language model chains for specific applications.
- Built-in UI components: It also includes components such as 'Co-pilot sidebar' And 'CopilotPopup' for user interface customization.
How does CopilotKit work?
Let's look at the key points of how CopilotKit works:
- The framework first: a framework to connect each component of your application to the copilot engine.
- The co-pilot engine: Receives the user's request, extracts the relevant application context, formats it for the LLM, and then initiates an action in the application on behalf of the user. Integrates deeply into the front and backend.
- AI Components: Customizable, headless UI components for native AI capabilities: chatbots, AI agents, and AI-powered text boxes.
- Generative user interface: Custom interactive user interfaces rendered in chat, rendered alongside AI-initiated actions.
- In-app agents: bring LangChain agents as interactive components of the application. They can see the application context in real time and initiate an action within the application.
- Cloud Copilot: Turnkey cloud services for co-pilot scaling and production: co-pilot memory and chat histories, guardrails, self-learning (co-pilot gets smarter with use)
- Ease of integration: Integrating CopilotKit into existing application infrastructures is made easy with simple entry points, making applications with advanced AI capabilities easy to use.
Use Case: CoPilotKit Presentation Builder
Let's create something cool using CopilotKit, a text to Powerpoint creation application.
We must meet a few prerequisites before continuing:
Now let's follow the essential steps to get the desired slide creation app by following the steps:
git clone https://github.com/CopilotKit/presentation-demo
- Go to the cloned repository and install the packages:
npm install
- Create a “.env.local” file in the root directory of the project and mention the two API keys obtained in the prerequisites section:
OPENAI_API_KEY = "...."
TAVILY_API_KEY = "........"
npm run dev
- Open http://localhost:3000 in your browser to view the application:
- A CopilotSidebar will be here. Let’s enter this prompt: “Create a slide about the benefits of AI in healthcare. » You will get the slide you want:
Here is what CopiloKit did on the backend:
- It takes the prompt and sends it to TAVILY to search for the topic.
- The response can then be passed to OpenAI to create the slide content.
- CopiloKit then places the OpenAI LLM output in the desired locations, using its updating capabilities.
Trending examples of CoipilotKit application
- Discuss with your CV: AI-powered resume builder app using Nextjs, CopilotKit, and OpenAI.
- Text to Powerpoint synthesis application: This AI-powered PowerPoint app can search the web to automatically make a presentation on any topic. It integrates AI into your application using Next.js, OpenAI, LangChain & Tavily and CopilotKit.
- AI-powered blogging platform: AI-powered blogging platform that can search the web and find any topic for a blog post using Next.js, OpenAI, LangChain & Tavily, CopilotKit and Supabase.
Conclusion
The introduction of CopilotKit reveals a robust and promising framework for smoothly integrating AI capabilities into your applications. By incorporating CopilotKit, developers gain access to a suite of tools that provide a simplified method for creating interactive AI features with user enhancement through intuitive interfaces such as CopilotChat, CopilotSidebar and CopilotTextarea. The initial setup process, comprehensive documentation, and illustrative code samples ensure that even someone who is not tech-savvy and new to AI can smoothly embark on this journey with confidence. Whether you're trying to build AI-powered chatbots, enrich text boxes with smart completions, or create fully personalized AI interactions within your apps, CopilotKit can help.
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of artificial intelligence for social good. Its most recent project is the launch of an artificial intelligence media platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news, both technically sound and easily understandable to a wide audience. The platform has more than 2 million monthly views, illustrating its popularity among the public.