Computer Use Component
Use the Computer Use component to give your agent a powerful, AI-driven virtual computer. It can execute complex, multi-step tasks described in natural language—from researching topics on the web to analyzing data—all without writing a single line of code.
What You’ll Configure
- How It Works
- Define the Task (Prompt)
- Provide Inputs
- Handle Outputs
- Best Practices & Limitations
- Troubleshooting Tips
- What to Try Next
Step 1: How It Works
The Computer Use component functions as a virtual computer operated by an advanced AI model. When you provide a natural language prompt, the AI formulates an execution plan. This plan may involve using various tools like web search, data calculation, or text analysis to fulfill your request. The final result is then structured and returned as an output.
Step 2: Define the Task (Prompt)
This is the core of the component. You provide a clear, natural language instruction that tells the AI computer what you want it to accomplish.
Setting | Description |
---|---|
Prompt | The primary instruction that guides the AI computer's operations. You can connect this to outputs from other components to dynamically generate tasks. |
Example Prompts:
- "Search for the current weather in New York and extract the temperature and conditions."
- "Find the latest stock price for Microsoft and calculate the 7-day average."
- "Look up population data for the top 10 most populous cities in California and create a summary table."
Step 3: Provide Inputs
You can make your prompts dynamic by adding custom inputs.
Input | Description |
---|---|
Prompt | The default input for your main instruction. |
Custom Inputs | Click the + icon to add new inputs (e.g., location , company_name ). You can then reference these in your prompt using {{variable}} syntax to make your tasks reusable and dynamic. |
Step 4: Handle Outputs
The component provides a single, comprehensive Output
and allows you to define custom outputs to easily extract specific pieces of data.
Output | Description |
---|---|
Output | The default output containing the complete, structured results of the executed tasks. |
Custom Outputs | Click the + icon to add new outputs that extract specific data from the main Output (e.g., temperature , stock_price ). SmythOS automatically understands that these custom outputs are parsing the default Output , so no complex expression is needed. |
Step 5: Best Practices & Limitations
- Be Specific: Provide clear, detailed instructions for best results. Instead of "find company info," try "Find the founding date and current CEO of Microsoft."
- Start Simple: Begin with straightforward, single-step tasks and gradually increase complexity as you get a feel for how the component interprets prompts.
- Test Iteratively: Run your prompt in Debug Mode and refine it based on the output to improve accuracy.
- Create Dedicated Outputs: Set up specific custom outputs for each data element you need. This makes your workflow much cleaner than trying to parse a single large JSON object downstream.
Step 6: Troubleshooting Tips
Step 7: What to Try Next
- Feed the raw
Output
into a GenAI LLM Component to have it write a narrative summary of the structured data. - Use this component as a more powerful alternative to the basic Web Search Component for complex research tasks that require multiple steps.
- Use a JSON Filter Component to further refine or clean the structured
Output
before passing it to other parts of your workflow.