How can you build a conversational agent using Rasa NLU pipelines

Question

With the help of code, can you explain how you can build a conversational agent using Rasa NLU pipelines?

Answer 1

To build a conversational agent using Rasa NLU pipelines, define intents and entities, and configure a pipeline in the config.yml. Train the model and use it for prediction. 

Here are the steps you can refer to:

• Define Pipeline in config.yml
• Define Intents and Entities in nlu.yml
• Train and Run the Model
• Python Script for Interaction

Here are the code snippets for the above steps:

In the above code, we are using the following approaches:

• Pipeline Setup: Configure tokenization, featurization, and intent/entity classification.
• Training Data: Define intents and examples in nlu.yml.
• Usage: Train the model and use it to interpret user inputs for conversation.

Hence, by referring to the above, you can build a conversational agent using Rasa NLU pipelines.