Creating the agent

1. Go to studio.uipath.com.
2. Select Create New button, then select Agent.
3. Select the agent type:
   • Autonomous: Create an agent that acts independently to complete a given task.
   • Conversational (Preview): Create an assistant that interacts with users through real-time dialogie.
4. If you want to create your agent from scratch, select Start fresh.
5. If you want to generate your agent using Autopilot (Preview), describe the agent you want the create in the available message box, then select Generate Agent. Be as specific as possible, so that Autopilot can efficiently generate an agent.
6. The new solution opens, with the Agent designer canvas displayed.

7. When configuring your agent, you can choose between two design modes: the traditional Form view and the Flow view (Preview). Both modes share the same underlying agent definition and remain fully synchronized, so you can switch between them at any time without losing data.

   Use Form view for a structured, step-by-step configuration experience, or switch to Flow view for a visual, node-based layout that lets you see how your agent’s components connect and interact.

Build an agent using Flow view (Preview)

1. Open your agent project in Studio Web.
2. In the top-right corner of the design-time canvas, select the Flow (Preview) option from the authoring mode toggle.

   • The Flow canvas opens, displaying the agent structure as nodes.

   • You can switch back to Form view at any time. All changes are saved and translated automatically between the two modes.

3. Configure the Agent node:
   • Open the Prompt section on the right to define your system and user prompts. For conversational agents, this section is simplified and only the system prompt is shown.
   • Open the Schema section on the left to define input and output arguments in the Data Manager panel.
   • Open the Properties panel to choose and configure your LLM:
     • Select a model from the available dropdown list. Models are provisioned through UiPath AI Trust Layer. To learn how to use a custom model, refer to Configuring LLMs.
     • Configure the Temperature and Max. tokens per response fields:
       • Temperature determines the creativity factor of the LLM generation. You can set a value between 0 (Precise) and 1 (Creative).
       • Max. tokens per response refers to the maximum number of tokens to generate with the agent's response.
4. Add context, tools, and escalations. After completing the agent nodes, three new node types become available:
   • Context: Select a Context Grounding index and adjust its search parameters. For details, refer to Contexts.
   • Tools: Open the command palette, search for a deployed tool, and add it to your canvas. You can further configure each tool once added. For details, refer to Tools.
   • Escalations: Add a human-in-the-loop node that connects to the existing escalation configuration experience. For details, refer to Escalations and Agent Memory.
5. Access additional options by selecting the ⋮ (More actions) menu on a tool node. The following actions are available:
   • Add breakpoint – Inserts a breakpoint at the tool node. When the agent is debugged, execution pauses just before this tool runs, allowing you to inspect its inputs, outputs, and trace data. Breakpoints are useful for verifying tool logic and debugging errors during design-time testing.
   • Add guardrail – Opens the Guardrail configuration window, where you can define rules that restrict or monitor how the tool is used at runtime.
   • Disable – Temporarily disables the selected tool node from agent execution. Disabled tools remain on the canvas but are skipped during runtime and debugging, allowing you to test or refine the agent’s behavior without permanently removing the tool.
     
     

     

     
     
6. Debug your agent.
   • Select Debug to run your agent in design time.
   • As the agent executes, nodes light up in sequence to show the execution flow.
   • If you run simulations, nodes appear in a different color to indicate mocked data or tool calls.
   • For conversational agents, a persistent chat window allows you to test exchanges; each message triggers a debug run that displays highlights across the connected nodes.
   • You can also set breakpoints on specific nodes to pause execution and inspect inputs, outputs, and trace data.
7. Save and publish your changes.
   • All updates in Flow view are stored automatically and remain synchronized with Form view.
   • When ready, publish the agent to make it available for testing and deployment.

Build an agent using Form view (Default)

1. From the Project Explorer panel on the left, access the agent Definition, Evaluation sets, and Evaluators.
   Figure 1. The Agent inside a Solution
   

   

   
   
   1. The Definition panel is where you design and define the core elements of an agent. The definition contains the following sections: General, Tools, Contexts, and Escalations.
      • Use the General section to define the prompts for your agent.
      • Use the Tools section to connect runtime tools, like Integration Service connectors or published automations.
      • Use the Contexts section to link knowledge sources using Context Grounding indexes to give your agent relevant data access.
      • Use the Escalations section to set up human-in-the-loop fallbacks and enable Agent Memory to persist interactions and help calibrate future agent escalations.
   2. The Evaluation sets panel is where you create evaluations and store results. Evaluations objectively measure your agent's output and assess whether or not it is consistent with your objectives. For details, refer to Evaluations.
   3. The Evaluators panel is where you create and manage the evaluators used in evaluations.
2. First, select your agent under Project Explorer. Right-click to select Rename, and give your agent a unique name.The agent name helps to identify the agent across projects.
3. Next, access the Properties panel from the right-hand side menu to select the large language model you want to use with your agent.
   1. Select a model from the available dropdown list. Models are provisioned through UiPath AI Trust Layer. For details, refer to Configuring LLMs.
   2. Configure the Temperature and Max. tokens per response fields:
   • Temperature determines the creativity factor of the LLM generation. You can set a value between 0 (Precise) and 1 (Creative).
   • Max. tokens per response refers to the maximum number of tokens to generate with the agent's response.
   Figure 2. Configuring the model settings
   

   

   
   
4. In the agent Definition panel, provide your agent with a System prompt and a User prompt.Add a well-structured prompt to give your agent instructions for what it should do, and constraints it should follow. For details, refer to Prompts.
5. Use the Data Manager panel to define the agent input and output arguments used in the prompts.
   Figure 3. Input arguments in the Data Manager panel
   

   

   
   
6. In the Tools section, select Add tool to add any tools your agent can use during execution.These can be a set of Integration Service activities, existing agents, and published automations to which you have access. Each tool must have a detailed description that helps inform the agent how and when to use this tool. For details, refer to Tools.
7. (Optional) In the Contexts section, select Add context to give the agent access to Context Grounding indexes.Choose an existing index available in your tenant, or select Create new to create a new index directly in Orchestrator. For details, refer to Contexts.
8. (Optional) In the Escalations section, select Add escalation to add a human in the loop through an escalation app and enable Agent Memory.Adding an escalation allows your agent to involve a human to review, approve, or update output as it is running. For details, refer to Escalations and Agent Memory.