Today I will explain to you how to create AI co-agents or Copilot-powered applications.
CoAgent offers a set of tools required to integrate LanGraph agents into React applications in order to build native agent applications. In this post we will talk about this tool and see how one can build AI CoAgents or Copilot powered applications.How to create AI co-agents or Copilot-powered applications.
CoAgent offers a set of tools required to integrate LanGraph agents into React applications in order to build native agent applications. In this post we will talk about this tool and see how one can build AI CoAgents or Copilot powered applications.
What is CoAgents?
As mentioned earlier, CoAgent is a set of tools that will allow you to integrate AI agents into applications for developing native agent applications. Let us now talk about some of its features.
- CoAgents has a feature called Shared State, whereby even just a line of code allows your application to get information from the agent, and the agent can get the information from the application because they are synchronized and can interact in real time.
- It also gives you real time frontend agents that can do frontend and backend actions based on the user provided context and application state, assume it is a generative UI, these tool calls are automatically broadcasted as per the requirement. Human-in-the-Loop enables seamless integration of human monitoring and intervention into AI workflows, specifying breakpoints for input or approval to improve safety and performance.
- We also have Stream Intermediate Agent State, which shows agent thought flow processes in real-time to provide transparency and engaging user experiences that are crucial to an agent’s performance and a user experience that meets their expectations.
- CoAgent’s Agentic generative UI creates dynamic AI-generated interfaces that adapt to user needs and agent output, providing visibility into agent state and building trust.
- If you like the features mentioned above, you may want to consider using CoAgents for your business. Let’s see how to do it.
Build AI CoAgents or Copilot-powered apps
Follow the steps listed below to build AI CoAgents or Copilot-powered apps.
- Install CopilotKit
- Setting up the remote backend endpoint
- Adding a LangGraph Agent
Let’s see them in detail.
1] Installing CopilotKit
Before we get started with CoAgents, we first need to install CopilotKit on your device. We assume that you have already installed Node.js and npm on your computer and created a folder for React apps; however, the last part is optional for this step. CopilotKit uses an open-source LLM model; in this tutorial, we will be using the OpenAI API key. Without further ado, let’s get started.
- Open Windows Terminal and navigate to the location where you have created the React app using the cd (change directory) command.
cd C:\React\My\App
- Now, run the following command.
npm install @copilotkit/react-core @copilotkit/react-ui @copilotkit/runtime
Then, run the below-mentioned command to install OpenAI.
- npm install openai
- In your project, go to the .eve file, which will be located at the root, and add the following line.
OPENAI_API_KEY=your_api_key_here
After making changes to the file, we recommend you navigate to docs.copilot.ai/quickstart to learn how to configure the endpoint and setup the CopilotKit provider in your project.
2] Configure the backend remote endpoint
To integrate Python-based services (or any other Node.js alternative), we need to connect the Copilot application to a remote backend endpoint. To do so, we first install the Copilot dependencies in Windows Terminal using the following query.
pip install copilotkit fastapi uvicorn --extra-index-url https://copilotkit.gateway.scarf.sh/simple/
Now, we need to configure the FastAI server, for that, run the commands mentioned below.
mkdir my_copilotkit_remote_endpointcd my_copilotkit_remote_endpointecho. > server.py
If echo didn't work, you can open the folder in Visual Studio Code and then create the server.py file.
Open the server.py file in VSCode and then paste the following lines of code.
from fastapi import FastAPI app = FastAPI() @app.get("/") def read_root(): return {"Hello": "World"}
Now, go back to Windows Terminal and install FastAPI and Uvicorn.
pip install fastapi uvicorn
Once you're done with that, head over to the docs.copilot.ai guides for more information.
3] Add LangGraph Agent
Next, we need to integrate the LangGraph agent into the server.py file. First, locate the CopilotKitSDK instance inside your Python remote endpoint, which is usually located in server.py. Next, adjust the CopilotKitSDK instance (set in the previous step) to accommodate the LangGraph agents. You need to add the following lines of code.
agents=[ Lanonfig={ # if you use Google Gemini, uncomment this code (and import `copilotkit_messages_to_langchain`, see above) # "convert_messages": copilotkit_messages_to_langchain(use_function_call=True) # } ) ],
This must be put under the tag CopilotKitSDK.
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