Agents
Agents are AI-driven entities you can create, train, and deploy. They analyze data, execute tasks, and adapt in real time.
Last updated
Agents are AI-driven entities you can create, train, and deploy. They analyze data, execute tasks, and adapt in real time.
Last updated
Permanently remove an agent from the platform by ID.
The unique identifier of the agent.
Agent deleted successfully. No content in response.
Retrieve a paginated list of all AI agents, with optional filters for limit and page.
A list of agents retrieved successfully.
"agent_12345"
"MarketAnalyzerAgent"
"Analyzes crypto markets and optimizes trading strategies."
"function analyzeMarket(data) { /* ... */ }"
Current status of the agent (idle, training, deployed).
"idle"
Fetch the logs generated by a deployed agent, including any blockchain interactions or function calls.
The unique identifier of the agent.
Logs retrieved successfully.
"2025-01-06T12:34:56Z"
"Agent executed function analyzeMarket"
Deploy a trained agent to the blockchain or a supported environment for live usage.
The unique identifier of the agent.
Agent deployed successfully.
"Agent successfully deployed to mainnet."
Retrieve the current status (in-progress, completed, failed) of an agent's training.
The unique identifier of the agent.
Training status retrieved successfully.
Current training status (in-progress, completed, failed).
"in-progress"
Training progress in percentage.
45
Retrieve details of a specific agent by its unique ID.
The unique identifier of the agent.
Agent details retrieved successfully.
"agent_12345"
"MarketAnalyzerAgent"
"Analyzes crypto markets and optimizes trading strategies."
"function analyzeMarket(data) { /* ... */ }"
Current status of the agent (idle, training, deployed).
"idle"
Initiate the training process for a specific agent using provided data or parameters.
The unique identifier of the agent to train.
Training data and hyperparameters for the agent.
Location or references to the training dataset.
Hyperparameter configurations for the training process.
Training process accepted. The status can be polled.
Current training status (in-progress, completed, failed).
"in-progress"
Training progress in percentage.
45
Create a new AI agent to be trained and deployed on the Aver platform.
Agent created successfully.
"agent_12345"
"MarketAnalyzerAgent"
"Analyzes crypto markets and optimizes trading strategies."
"function analyzeMarket(data) { /* ... */ }"
Current status of the agent (idle, training, deployed).
"idle"
Run one of the agent’s associated functions with your specified input data.
The unique identifier of the agent.
Name of the function to execute.
Any data required by the function.
Function executed successfully.
Output of the executed function.
"Function executed successfully."
Update the metadata of an existing agent. You can edit the name, description, or associated functions.
The unique identifier of the agent.
Agent updated successfully.
"agent_12345"
"MarketAnalyzerAgent"
"Analyzes crypto markets and optimizes trading strategies."
"function analyzeMarket(data) { /* ... */ }"
Current status of the agent (idle, training, deployed).
"idle"