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EigenData-CLI adds a chatbot layer on top of the EigenData framework. Instead of writing prompts and configuring agents directly, you interact with a conversational interface that translates your natural-language requests into the prompts that drive the orchestration layer. Every core feature follows the same interaction pattern: describe your task → guided parameter collection → review and confirm → execute. Every core feature follows the same interaction pattern: describe your task → guided parameter collection → review and confirm → execute.

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Describe your task

Start by telling the CLI what you want to do in plain language: 
eigendata> Generate 50 multi-turn function calling dialogs about laptop troubleshooting for HP support
The system analyzes your input and automatically extracts parameters like the domain, request description, sample count, and file paths. If you include enough detail, the system may have everything it needs in a single message.

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Guided parameter collection

If any required parameters are missing, the CLI asks for them conversationally. You respond in natural language, and the system extracts the relevant values from your reply:
EigenData-CLI chatbot collecting parameters through natural language conversation
The conversation continues until all required parameters are collected. You can provide optional parameters like reference_doc or data_language at any point during the conversation.

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Review and confirm

Once all parameters are ready, the CLI displays a configuration summary with source annotations showing where each value came from, and presents an action menu:
Configuration summary with source annotations and action menu
OptionDescription
1Run the task with current configuration
2Restart from scratch (pick a different task)
3Edit individual parameters interactively
Text inputType natural language to refine the configuration
You can also run tasks non-interactively using the /execute command with a YAML configuration file, or manage settings with /configure.