Question 1

How do I handle API errors with wit-ruby?

Accepted Answer

The library doesn't provide built-in error handling; you'll need to wrap calls in rescue blocks for network issues or Wit.ai errors. Check the Wit.ai API docs for specific error codes and implement retry logic manually.

Question 2

Integrating wit-ruby into a Ruby on Rails application

Accepted Answer

You can add the gem to your Gemfile and initialize the client in controllers or services. However, there are no pre-built Rails integrations, so you'll need to manage tokens and responses within your application logic, potentially using background jobs for async processing.

Question 3

Wit.ai or Dialogflow for Ruby: which one should I choose?

Accepted Answer

Wit.ai is better for teams already invested in its ecosystem or needing Facebook integration, while Dialogflow might offer more features out-of-the-box. wit-ruby simplifies Wit.ai use in Ruby, but Dialogflow has its own SDKs; consider factors like pricing, language support, and customization needs.

Question 4

How to programmatically train intents with wit-ruby

Accepted Answer

Use the post_utterances method with a payload containing text, intent, and entities. First, create intents and entities via CRUD methods, then feed training data as shown in the README example for utterance payloads.

Question 5

Is wit-ruby suitable for production use at scale?

Accepted Answer

It can be used in production, but you must handle Wit.ai's rate limits and potential latency. Implement caching, monitor API usage, and consider async processing to avoid bottlenecks, as the SDK doesn't optimize for high throughput.

Question 6

What are the rate limits for Wit.ai API with wit-ruby?

Accepted Answer

Rate limits are set by Wit.ai, not the SDK. Refer to Wit.ai's documentation for current limits on requests per minute; wit-ruby doesn't throttle calls, so you need to manage pacing in your code to avoid hitting barriers.

wit-ruby

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