Struct rust_bert::pipelines::conversation::ConversationModel

pub struct ConversationModel { /* fields omitted */ }

Conversation model

Processes a ConversationManager and generate system responses for active conversations.

Implementations

impl ConversationModel

pub fn new(
    conversation_config: ConversationConfig
) -> Result<ConversationModel, RustBertError>

Build a new ConversationModel

Arguments

• conversation_config - ConversationConfig object containing the resource references (model, vocabulary, configuration), conversation options and device placement (CPU/GPU)

Example

use rust_bert::pipelines::conversation::ConversationModel;

let conversation_model = ConversationModel::new(Default::default())?;

pub fn generate_responses<'a>(
    &self,
    conversation_manager: &'a mut ConversationManager
) -> HashMap<&'a Uuid, &'a str>

Perform a multi-turn conversation based on user input

Arguments

• conversation_manager - &mut ConversationManager Conversation manager keeping track of active conversations

Returns

• HashMap<&Uuid, &str> Responses from the model for each active conversation, referenced by Uuid

Example

use rust_bert::pipelines::conversation::{ConversationManager, ConversationModel};
use rust_bert::pipelines::generation_utils::LanguageGenerator;
let model = ConversationModel::new(Default::default())?;

let mut conversation_manager = ConversationManager::new();
conversation_manager.create("Hello, how are you?");

let output = model.generate_responses(&mut conversation_manager);

pub fn encode_prompts(&self, texts: &[&str]) -> Vec<Vec<i64>>

Encodes prompts into Vectors of indices to be processed by the model. This method may be used to initialize the history of a conversation with a prior state.

Example:

use rust_bert::pipelines::conversation::{ConversationManager, ConversationModel};
use rust_bert::pipelines::generation_utils::LanguageGenerator;
let model = ConversationModel::new(Default::default())?;
let history = [
    "Going to the movies tonight - any suggestions?",
    "The Big Lebowski",
    "Is it an action movie?",
];
let encoded_history = model.encode_prompts(&history);