The AI agent marketplace on the platform is a dynamic and diverse ecosystem where users can access a wide range of pre-built AI agents created by the community. These agents offer various capabilities, from scraping real-time data from LinkedIn profiles and posts to retrieving up-to-date cryptocurrency market information and even extracting data from YouTube videos.

The marketplace allows users to explore and utilize these AI agents to enhance their own applications and workflows. For example, the LinkedIn search agent can provide valuable insights by scraping data from LinkedIn, while the coin market cap agent can help investors stay informed about the latest cryptocurrency market trends and top performers.

The platform's open and collaborative nature encourages community-driven innovation, enabling users to not only access these pre-built agents but also to upload and share their own custom-built AI agents. This empowers developers to contribute to the ecosystem and expand the range of capabilities available to all users.

By leveraging the AI agent marketplace, users can quickly and easily integrate powerful AI functionalities into their applications, without the need to build everything from scratch. This streamlines the development process and allows for rapid, scalable AI solutions that are ideal for startups and enterprises alike.

To create a custom knowledge-based agent, follow these steps:

1. Click on the "Create Agent" button at the top right of the platform.
2. Select the "Knowledge-Based Agent" adapter option.
3. Give your agent a name and description, and upload an icon if desired.
4. Add conversation starters that will trigger your agent's responses.
5. Upload relevant documents, audio, or video files that will serve as the agent's knowledge base.
6. Categorize your agent, in this case, as a "Customer Support" agent.
7. Save your agent, and it will be ready for use.
8. Test your agent in the playground area by posing the conversation starters.
9. If the agent performs as expected, you can save the preset and export the code to integrate it into your applications.

The knowledge-based agent you created, in this case, a "Sponsorship Agent," will now be able to respond to inquiries about sponsorship rates and details, drawing from the information you provided in the knowledge base.

Now that we have created our custom sponsorship agent, let's test and publish it for use.

First, we can test the agent by interacting with it in the playground area. We can click the "+" button to add the agent to the chat conversation, and then ask it questions related to sponsorship rates. The agent will use the knowledge we provided to respond with the relevant information.

Once we've verified that the agent is working as expected, we can proceed to publish it. To do this, we simply need to click the "Publish" button next to the agent. This will make the agent available for use in our applications or by other users on the platform.

Publishing the agent also allows us to monetize it in the future. When other users utilize our agent, we will be able to earn money from its usage. This provides an opportunity to generate revenue from the AI agents we create and contribute to the on-demand AI ecosystem.

Remember, by signing up using the referral link, you will receive $50 worth of free credits to encourage you to start building on the platform. This can be a great way to get started with creating and testing your own custom AI agents.

To integrate the AI agent into an application, follow these steps:

1. Save the agent preset you created earlier. This will allow you to easily access and use the agent in your application.

2. Obtain the code for your agent by clicking the "Get Code" button. This will provide you with the necessary code to integrate the agent into your application, in the programming language of your choice.

3. Replace the external_user_id placeholder in the generated code with your actual API key.

4. Incorporate the agent code into your application, ensuring that it is called when the appropriate user input or trigger occurs.

5. Test the integration by interacting with the agent through your application and verifying that it responds accurately based on the knowledge and capabilities you defined.

6. Optionally, you can further customize the agent's behavior by modifying the prompts, model settings, or other parameters within the code.

7. Deploy your application with the integrated AI agent, and enjoy the benefits of the on-demand AI marketplace and the agent's capabilities.

The Agent Flow Builder is a powerful feature that allows you to build entire workflows visually, enabling you to connect AI agents and Large Language Models (LLMs) seamlessly.

To create a new workflow, you can set the trigger, which can be either an API or a cron-based job scheduler. This allows you to automate tasks and execute them on a schedule, such as sending reports or checking for data at regular intervals.

Within the workflow, you can connect various components together, creating a sequence of actions. This includes the ability to add your own AI agents, such as the sponsorship agent you created earlier. You can set the model and prompts for these agents, ensuring they are tailored to your specific needs.

Furthermore, the platform allows you to bring your own models, leveraging the Hugging Face integration. This provides an extra layer of customizability, as you can choose from a wide range of AI models to integrate into your workflows, keeping up with the ever-evolving AI landscape.

Once your workflow is set up, you can configure the output to be sent to various destinations, such as Slack, email, or a custom web application. This makes it easy to integrate your AI-powered solutions into your existing systems and processes.

The Agent Flow Builder is a powerful tool that empowers you to create scalable, automated, and customizable AI-driven workflows, streamlining your operations and fostering innovation.

One of the key features of the on Demand platform is the ability to bring your own AI model. This allows for an extra layer of customizability, as you can connect your Hugging Face account to deploy any model you desire.

The ever-evolving AI landscape offers a wide range of models to choose from, and this feature enables you to seamlessly integrate your preferred model into the platform. This level of flexibility is particularly valuable when building specialized AI agents that require a unique set of capabilities.

By bringing your own AI model, you can tailor the agent's behavior and outputs to your specific needs, ensuring a more personalized and effective solution. This feature empowers you to leverage the latest advancements in AI technology and create truly custom AI agents that cater to your unique requirements.