Struct rust_bert::pipelines::conversation::ConversationModel

pub struct ConversationModel { /* private fields */ }

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 new_with_tokenizer( conversation_config: ConversationConfig, tokenizer: TokenizerOption ) -> Result<ConversationModel, RustBertError>

Build a new ConversationModel with a provided tokenizer.

Arguments

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

Example

use rust_bert::pipelines::common::{ModelType, TokenizerOption};
use rust_bert::pipelines::conversation::ConversationModel;
let tokenizer = TokenizerOption::from_file(
    ModelType::GPT2,
    "path/to/vocab.json",
    Some("path/to/merges.txt"),
    false,
    None,
    None,
)?;
let conversation_model = ConversationModel::new_with_tokenizer(Default::default(), tokenizer)?;

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

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);