Popular GitHub Repositories for Dialogue Summarization

A generative speech model for daily dialogue.

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

? Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

An open source library for deep learning end-to-end dialog systems and chatbots.

搜索所有中文NLP数据集，附常用英文NLP数据集

Module for automatic summarization of text documents and HTML pages.

AdalFlow: The library to build & auto-optimize LLM applications.

GPT2 for Chinese chitchat/用于中文闲聊的GPT2模型(实现了DialoGPT的MMI思想)

RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology.

文本挖掘和预处理工具（文本清洗、新词发现、情感分析、实体识别链接、关键词抽取、知识抽取、句法分析等），无监督或弱监督方法

mPLUG-Owl: The Powerful Multi-modal Large Language Model Family

Large-scale pretraining for dialogue

A modular RL library to fine-tune language models to human preferences

A Large-scale Chinese Short-Text Conversation Dataset and Chinese pre-training dialog models

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

CakeChat: Emotional Generative Dialog System

Efficient Retrieval Augmentation and Generation Framework

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

This repo contains implementation of different architectures for emotion recognition in conversations.