A collection of large datasets for conversational response selection. This repository provides tools to create reproducible datasets for training and evaluating models of conversational response.

Serve gen AI models, including open source and third-party models such as Meta Llama, Anthropic Claude, OpenAI GPT, and more. Build and deploy your own agents, including tool …

6 days ago · In one interaction, a model may need to perform intent classification, entity recognition, sentiment analysis, and track the dialogue state. Therefore, the dataset must …

Mar 21, 2025 · In this paper, we present ConvoGen: an innovative framework for generating synthetic conversational data using multi-agent systems. Our method leverages few-shot …

Apr 11, 2025 · A conversational AI solution must comply with laws such as GDPR, HIPAA, and others that govern how data is stored, processed, and transferred. Rasa supports fully on …

Dec 22, 2022 · As you start designing your conversational AI, the following aspects should be decided and detailed in advance to avoid any gaps and surprises later. User Interface. The …

There are 3 main architectural approaches for developing conversational AI systems: Hybrid systems that combine the NLU and LLM components to get the best of both worlds: the control …

May 13, 2024 · Data augmentation (DA) is an affective approach to alleviate the data scarcity problem in conversational systems. This tutorial provides a comprehensive and up-to-date …

Sep 28, 2023 · After considering the market opportunities and the business value of conversational AI systems, we will explain the additional "machinery" in terms of data, LLM …

Train dialogue models using domain-specific datasets and prompt examples. Customize chatbot behavior, tone, and context handling for natural, multi-turn conversations. Use real-time testing …