Improve Ax-cli Model Validation Error Messages

Nov 20, 2025 by Alex Johnson 47 views

Improving Model Validation Error Messages in ax-cli

When working with command-line interfaces (CLIs) like ax-cli, clear and helpful error messages are crucial for a positive user experience. A poorly designed error message can leave users frustrated and unsure of how to proceed, while a well-crafted message can guide them toward a quick resolution. This article delves into the issue of unhelpful model validation error messages in ax-cli and proposes several strategies to enhance them. By addressing the shortcomings of the current error messages, we can empower users to troubleshoot issues more effectively and improve their overall interaction with the tool.

The Problem: Unhelpful Error Messages

Currently, when a model fails validation in ax-cli, the error message provided is often vague and lacks sufficient information. For example, the message Unknown model "llama3.1:8b", using default: grok-code-fast-1 fails to explain why the model is unknown. Is it an unsupported model? Is there a typo in the model name? Does it belong to a different provider? Without these crucial details, users are left to guess the cause of the error, leading to a frustrating trial-and-error approach. This lack of clarity can significantly hinder productivity and make the CLI less user-friendly.

Key Issues with Current Error Messages

Lack of Explanation: The error message doesn't explain the reason behind the model validation failure. It simply states that the model is unknown without providing any context.
No Alternatives Suggested: The message doesn't offer suggestions for valid models or how to find a list of supported models. This forces users to search documentation or rely on guesswork.
Confusing Fallback Behavior: The CLI falls back to a completely different provider (e.g., switching from Ollama to grok-code-fast-1) without clear communication, which can lead to unexpected results and further confusion.
Missing Resolution Path: The error message doesn't provide actionable next steps or links to relevant documentation, leaving users unsure of how to resolve the issue.
Absence of Context: The message doesn't mention the configured provider or the source of the model name (e.g., command-line flag, configuration file), making it difficult to debug the problem.

Illustrative Example

Consider the following scenario:

$ ax-cli -m "llama3.1:8b" -p "test"
Unknown model "llama3.1:8b", using default: grok-code-fast-1

This error message raises several questions in the user's mind:

Why is the model unknown?
What models are supported?
How can I fix this issue?
Why is it using grok when I specified llama?

These questions highlight the critical need for more informative and actionable error messages.

Recommended Error Message Strategies

To address the shortcomings of the current error messages, several strategies can be implemented. These strategies focus on providing users with clear explanations, helpful suggestions, and actionable steps to resolve model validation issues.

Option 1: Helpful with Alternatives

This approach provides a clear error message that explains the issue and suggests alternative models. It also includes information about the current provider and how to access a list of supported models.

Error: Model "llama3.1:8b" is not supported

Your current provider: Z.AI (GLM Models)
Supported models for Z.AI:
  • glm-4.6 (recommended)
  • glm-4-air
  • glm-4-airx

To use Ollama models, run: ax-cli setup
For all providers: ax-cli models list --help

This error message clearly states that the model is not supported, identifies the current provider, lists supported models for that provider, and provides instructions on how to switch to a different provider or list all available models. This comprehensive approach significantly improves the user experience by offering immediate solutions.

Option 2: Provider-Aware

This strategy tailors the error message to the configured provider, providing context-specific information. It helps users understand that the issue might be related to the model's compatibility with the current provider.

Error: Model "llama3.1:8b" not available for current provider

Current configuration:
  Provider: Z.AI
  Base URL: https://api.z.ai/api/coding/paas/v4
  
Model "llama3.1:8b" looks like an Ollama model.
To use Ollama, configure with: ax-cli setup --provider ollama

Or specify different model: ax-cli -m glm-4.6 -p "test"

This error message not only states that the model is unavailable but also provides details about the current configuration, including the provider and base URL. It also suggests that the model might be intended for a different provider (Ollama) and provides instructions on how to switch providers or specify a different model.

Option 3: Smart Detection

This approach goes a step further by attempting to detect the user's intended model and suggesting possible alternatives. It leverages fuzzy matching or other techniques to provide intelligent suggestions, making it easier for users to correct typos or select the appropriate model.

Error: Model "llama3.1:8b" not recognized

Did you mean:
  • llama3.1 (from Ollama examples)
  • glm-4.6 (primary model for current provider)

Note: Ollama support is currently non-functional (see issue #1)
Use Z.AI models instead: glm-4.6, glm-4-air, glm-4-airx

By suggesting potential matches, this error message significantly reduces the effort required to troubleshoot the issue. It also provides additional context, such as noting that Ollama support is currently non-functional and recommending alternative models for the current provider.

Option 4: Educational

This strategy takes a more comprehensive approach by educating users about model naming conventions and provider-specific models. It provides a detailed explanation of the issue and offers a wide range of solutions.

Error: Unknown model "llama3.1:8b"

Model naming format varies by provider:
  Z.AI:      glm-4.6, glm-4-air
  xAI:       grok-code-fast-1
  OpenAI:    gpt-4-turbo, gpt-4
  Anthropic: claude-3-5-sonnet-20241022
  Ollama:    llama3.1:8b, qwen2.5:7b (currently broken)

Your provider (Z.AI) supports: glm-4.6, glm-4-air, glm-4-airx
Specify with: --model glm-4.6

See: ax-cli models list
Docs: https://github.com/defai-digital/ax-cli#models

This error message provides a wealth of information, including model naming formats for various providers, supported models for the current provider, and instructions on how to specify a model. It also includes links to additional resources, such as the ax-cli models list command and relevant documentation. This educational approach empowers users to understand the underlying issues and resolve them independently.

Best Practices for Error Messages

Regardless of the specific strategy employed, good error messages should adhere to certain best practices. These practices ensure that error messages are clear, helpful, and actionable.

Key Principles of Effective Error Messages

Explain what went wrong: Clearly state the issue, such as "Model not supported for provider."
Show why it happened: Provide context, such as "llama3.1:8b is Ollama format, you have Z.AI configured."
Suggest how to fix: Offer solutions, such as "Use glm-4.6 or run setup to change provider."
Provide examples: List valid models or commands.
Link to documentation: Point users to relevant documentation for more information.

By adhering to these principles, error messages can transform from frustrating roadblocks into helpful guides.

Additional Improvements for Enhanced User Experience

Beyond the core error message content, additional improvements can further enhance the user experience. These improvements focus on providing context and progressive disclosure of information.

Providing Context in Errors

Including context about the user's attempted command and configuration can significantly aid in troubleshooting. This context helps users understand the specific circumstances that led to the error.

Attempted command:
  ax-cli -m "llama3.1:8b" -p "test"
  
Configuration:
  Provider: Z.AI
  Source: ~/.ax-cli/config.json
  
Problem:
  Model "llama3.1:8b" is not valid for Z.AI provider

This detailed information allows users to quickly identify the source of the problem and take appropriate action.

Progressive Disclosure of Information

Progressive disclosure involves presenting information in layers, starting with a basic error message for a quick scan and then providing more details in a verbose mode. This approach caters to both novice and advanced users.

Basic error message:

Error: Model "llama3.1:8b" not supported. Use glm-4.6 instead.

Verbose mode (using --verbose flag):

$ ax-cli -m "llama3.1:8b" -p "test" --verbose

Error: Model validation failed

Details:
  Requested model: llama3.1:8b
  Model source: Command line flag (-m)
  Current provider: Z.AI (GLM Models)
  Provider base URL: https://api.z.ai/api/coding/paas/v4
  
Reason:
  Model "llama3.1:8b" uses Ollama naming convention (name:tag)
  but current provider is Z.AI which uses different format
  
Valid models for Z.AI:
  • glm-4.6       - Latest model with 32K context (recommended)
  • glm-4-air     - Faster inference
  • glm-4-airx    - Extended context
  
Solutions:
  1. Use Z.AI model: ax-cli -m glm-4.6 -p "test"
  2. Switch to Ollama: ax-cli setup (choose Ollama provider)
  3. List all models: ax-cli models list
  
Documentation:
  https://github.com/defai-digital/ax-cli#model-selection

The verbose mode provides a comprehensive overview of the issue, including details about the requested model, provider configuration, reason for the failure, valid models, solutions, and documentation links. This layered approach ensures that users can access the level of detail they need without being overwhelmed.

Learning from Other CLIs

Examining how other CLIs handle error messages can provide valuable insights. Good examples from other tools, such as Docker and NPM, can serve as inspiration for improving ax-cli error messages.

Examples from Docker and NPM

Docker:

Unable to find image 'unknown:latest' locally
docker: Error response from daemon: pull access denied for unknown,
repository does not exist or may require 'docker login'

See 'docker run --help'.

This error message clearly explains what happened, suggests a resolution, and links to help documentation.

NPM:

npm ERR! 404 Not Found - GET https://registry.npmjs.org/unknownpackage
npm ERR! 404
npm ERR! 404  'unknownpackage@latest' is not in this registry.
npm ERR! 404
npm ERR! 404 Note that you can also install from a
npm ERR! 404 tarball, folder, http url, or git url.

This error message clearly states the issue and suggests alternative approaches.

By analyzing these examples, we can identify best practices and apply them to ax-cli error messages.

Conclusion

Improving model validation error messages in ax-cli is crucial for enhancing the user experience. By providing clear explanations, helpful suggestions, and actionable steps, we can empower users to troubleshoot issues more effectively and improve their overall interaction with the tool. The strategies outlined in this article, including providing alternatives, tailoring messages to the provider, implementing smart detection, and offering educational content, can significantly enhance the usability of ax-cli. Embracing best practices for error message design and learning from other CLIs will further contribute to a more user-friendly and efficient command-line experience.

For more information on error message best practices, consider exploring resources from trusted websites like the Interaction Design Foundation. This can offer additional insights into crafting user-friendly error messages.