Creating AI Agents

Creating AI agents on AIDIVN is designed to be intuitive, flexible, and accessible to both developers and non-developers. The platform provides a set of powerful tools, including an open Software Development Kit (SDK) and an Application Programming Interface (API), to allow users to build, customize, and deploy intelligent assistants. Here's a step-by-step guide on how users can create their own AI agents:

1. Accessing the SDK and API

SDK for Developers: Developers can leverage AIDIVN’s open SDK to create AI agents that can perform specific tasks, integrate with external services, or adapt to unique workflows. The SDK provides pre-built libraries, templates, and frameworks for easy integration of AI models and tools like Natural Language Processing (NLP), machine learning, and sentiment analysis.
API for Non-Developers: For non-technical users, AIDIVN’s API offers simplified access to AI models and functionalities, allowing them to create custom AI agents without writing extensive code. The API comes with user-friendly documentation and pre-configured templates for quick setup.

2. Customizing Your AI Agent

Once access to the SDK or API is obtained, users can begin designing and customizing their AI agents. Customization options include:

Task Specialization: Users can define the specific tasks their AI agent will perform, such as scheduling, reminders, email management, or customer support.
Personalization: AI agents can be tailored to reflect the user’s preferences, such as preferred language, tone of communication, and even personality traits. For example, users can set an AI assistant to be formal, casual, humorous, or empathetic depending on their needs.
Integration of AI Tools: AIDIVN allows the integration of various AI technologies, such as:

Natural Language Processing (NLP): Enables the AI agent to understand and respond to user queries in a human-like way.

Machine Learning Models: Allows agents to learn from user interactions and continuously improve performance over time.

Image and Speech Recognition: Integrate visual or auditory input to make AI agents more versatile and capable of handling multimedia tasks.

Modular Functionality: Users can build modular AI agents, where different functionalities (such as task management, communication, or research) can be added or removed based on their needs. These modules can also be updated independently, allowing for continuous improvement.

3. Deploying AI Agents

Once the AI agent is created and customized, it’s time to deploy it on the AIDIVN platform:

Blockchain Deployment: After creation, the AI agent is deployed on the blockchain, ensuring that the ownership, functionality, and customizations are secure and immutable. The blockchain integration guarantees that the agent remains tamper-proof and that creators maintain full control over their AI models.
Smart Contracts: Smart contracts are automatically created for each AI agent upon deployment. These contracts define the terms of usage, monetization, and creator rewards. Once deployed, users and other participants interact with the agent based on the terms set in the smart contract.

4. Testing & Iterating

Before an AI agent is made available for public use, creators can test its functionality to ensure it performs as expected. AIDIVN offers:

Sandbox Environment: A safe testing space where AI agents can be interacted with and fine-tuned before they go live. Users can simulate various tasks and inputs to see how the agent responds.
Feedback Loop: Creators can gather feedback from early testers or internal users, making improvements and adjustments to the AI agent's performance. This ensures that only high-quality agents are deployed on the platform.

Once the AI agent is tested and ready, it can be made publicly available on the AIDIVN platform. Creators have the option to:

List Agents for Public Use: Creators can publish their AI agents on the platform’s marketplace, where other users can browse, access, and interact with them. Each agent comes with detailed descriptions, usage instructions, and customizable options.
Monetization: Through the "Create-to-Earn" model, creators can monetize their AI agents. Every time a user interacts with or subscribes to the agent, creators earn a portion of the transaction fees automatically via smart contracts.
Continuous Updates: Creators can continue to improve their AI agents after deployment by releasing updates that enhance performance, add new features, or adjust to evolving user preferences.

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1. Accessing the SDK and API

SDK for Developers: Developers can leverage AIDIVN’s open SDK to create AI agents that can perform specific tasks, integrate with external services, or adapt to unique workflows. The SDK provides pre-built libraries, templates, and frameworks for easy integration of AI models and tools like Natural Language Processing (NLP), machine learning, and sentiment analysis.

API for Non-Developers: For non-technical users, AIDIVN’s API offers simplified access to AI models and functionalities, allowing them to create custom AI agents without writing extensive code. The API comes with user-friendly documentation and pre-configured templates for quick setup.

2. Customizing Your AI Agent

Once access to the SDK or API is obtained, users can begin designing and customizing their AI agents. Customization options include:

Task Specialization: Users can define the specific tasks their AI agent will perform, such as scheduling, reminders, email management, or customer support.

Personalization: AI agents can be tailored to reflect the user’s preferences, such as preferred language, tone of communication, and even personality traits. For example, users can set an AI assistant to be formal, casual, humorous, or empathetic depending on their needs.

Integration of AI Tools: AIDIVN allows the integration of various AI technologies, such as:

Natural Language Processing (NLP): Enables the AI agent to understand and respond to user queries in a human-like way.

Machine Learning Models: Allows agents to learn from user interactions and continuously improve performance over time.

Image and Speech Recognition: Integrate visual or auditory input to make AI agents more versatile and capable of handling multimedia tasks.

Modular Functionality: Users can build modular AI agents, where different functionalities (such as task management, communication, or research) can be added or removed based on their needs. These modules can also be updated independently, allowing for continuous improvement.

3. Deploying AI Agents

Once the AI agent is created and customized, it’s time to deploy it on the AIDIVN platform:

Blockchain Deployment: After creation, the AI agent is deployed on the blockchain, ensuring that the ownership, functionality, and customizations are secure and immutable. The blockchain integration guarantees that the agent remains tamper-proof and that creators maintain full control over their AI models.

Smart Contracts: Smart contracts are automatically created for each AI agent upon deployment. These contracts define the terms of usage, monetization, and creator rewards. Once deployed, users and other participants interact with the agent based on the terms set in the smart contract.

4. Testing & Iterating

Before an AI agent is made available for public use, creators can test its functionality to ensure it performs as expected. AIDIVN offers:

Sandbox Environment: A safe testing space where AI agents can be interacted with and fine-tuned before they go live. Users can simulate various tasks and inputs to see how the agent responds.

Feedback Loop: Creators can gather feedback from early testers or internal users, making improvements and adjustments to the AI agent's performance. This ensures that only high-quality agents are deployed on the platform.

5. Publishing & Sharing AI Agents

Once the AI agent is tested and ready, it can be made publicly available on the AIDIVN platform. Creators have the option to:

List Agents for Public Use: Creators can publish their AI agents on the platform’s marketplace, where other users can browse, access, and interact with them. Each agent comes with detailed descriptions, usage instructions, and customizable options.

Monetization: Through the "Create-to-Earn" model, creators can monetize their AI agents. Every time a user interacts with or subscribes to the agent, creators earn a portion of the transaction fees automatically via smart contracts.

Continuous Updates: Creators can continue to improve their AI agents after deployment by releasing updates that enhance performance, add new features, or adjust to evolving user preferences.