This is a Dialogue Understanding (DU) model developed by Rasa. It can be used to power assistants built with the Conversational AI with Language Models (CALM) approach developed by Rasa.

Model Details

Model Description

This model takes as input a transcript of an ongoing conversation between an AI assistant and a user, as well as structured information about the assistant's business logic. As output, it produces a short sequence of commands (typically 1-3) from the following list:

start flow flow_name
set slot slot_name slot_value
cancel flow
disambiguate flows flow_name1 flow_name2 ... flow_name_n
provide info
offtopic reply
hand over

Note that this model can only produce commands to be interpreted by Rasa. It cannot be used to generate arbitrary text.

The Command Generator translates user messages into this internal grammar, allowing CALM to progress the conversation.

Examples:

I want to transfer money

start flow transfer_money

I want to transfer $55 to John

start flow transfer_money
set slot recipient John
set slot amount 55

Developed by: Rasa Technologies
Model type: Text Generation
Language(s) (NLP): English
License: Apache 2.0
Finetuned from model [optional]: meta-llama/Llama-3.1-8B-Instruct

Uses

The Command Generator is used as part of an AI assistant developed with Rasa's CALM paradigm. Typical use cases include customer-facing chatbots, voice assistants, IVR systems, and internal chatbots in large organizations.

Direct Use

This model can be directly used as part of the command generator component if the flows of your CALM assistant are similar to flows used in the rasa-calm-demo assistant.

Downstream Use [optional]

The model can also be used as a base model to fine-tune further on your own assistant's data using the fine-tuning recipe feature available in rasa pro

Out-of-Scope Use

Since the model has been explicitly fine-tuned to output the grammar of commands, it shouldn't be used to generate any other free form content.

Bias, Risks, and Limitations

The Command Generator interprets conversations and translates user messages into commands. These commands are processed by Rasa to advance the conversations. This model does not generate text to be sent to and end user, and is incapable of generating problematic or harmful text.

However, as with any pre-trained model, its predictions are susceptible to bias. For example, the accuracy of the model varies with the language used. The authors have tested the performance on English but haven't tried the model in any other language.

Training Details

Training Data

Trained on the train split of rasa/command-generation-calm-v2.

Training Procedure

Trained using the notebook available here. Used a single A100 GPU with 40GB VRAM.

Evaluation

Testing Data, Factors & Metrics

Testing Data

Evaluated on the test split of rasa/command-generation-calm-v2.

Metrics

F1 score per command type (StartFlow, SetSlot, etc.) is the main metric chosen to evaluate the model on the test split. This helps us understand which commands the model has learnt well and the ones that the model needs more training on.

Results

To be added

Model Card Contact

If you have questions about the dataset, please reach out to us on the Rasa forum.

rasa/command-generator-llama-3.1-8b-instruct

Model Card for Command Generator