Agent Workflow
Agent in the Item Marketplace are designed to execute autonomous workflows using APIs and MCPs (Modular Capability Packages), all built through a streamlined and user-friendly interface.
The agent lifecycle consists of two primary workflows: Agent Creation and Agent Training. These workflows allow users to develop intelligent, context-aware agents that can autonomously manage complex tasks and deliver high-quality interactions across business processes.
Agent Creation
Build an AI agent from scratch or use pre-built templates. This workflow includes four essential steps:
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Define Agent Purpose: Specific the clear goals, core function and objective of the agent. For example, customer support, order processing, or internal automation.
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Connect Resources: Link the agent with necessary resources such as APIs, MCPs, and knowledge bases to equip it with required capabilities.
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Configure Reasoning: Set up logical structures for how the agent should process inputs, make decisions, and respond under various conditions.
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Design Interaction Model: Define how the agent interacts with users, including input types, tone of voice, output formatting, and conversation flow.
Agent Training
Enhance the agent’s effectiveness and accuracy through continuous training. This process involves three steps.
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Upload Training Data: Provide sample conversations, intents, user queries, or other relevant datasets to train the agent.
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Run Training: Trigger the training process to allow the system to learn from the provided data and optimzied agent response.
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Evaluate Performance: Test the trained agent in simulated or real scenarios, analyze results, and iterate on the model to ensure performance meets expectations.