Open-source alternatives to Chinese Medical Dialogue Data

DSTC8 Track 1 Task 1 End-to-End Multi-Domain Dialog Challenge Result:

English Version

Haystack is an orchestration framework designed for building complex search and generative AI pipelines. It functions as an agentic workflow engine, enabling the construction of automated sequences that allow AI agents to perform multi-step reasoning and data analysis. The framework utilizes a modular, component-based architecture that connects processing steps into directed acyclic graphs. By employing a provider-agnostic integration layer, it decouples core logic from specific external AI services and vector databases, allowing for the flexible exchange of underlying technologies. This desi

:fourleafclover: Another Chinese chatbot implemented in PyTorch, which is the sub-module of intelligent work order processing robot. 👩‍🔧

With the aim of building next generation virtual assistants that can handle multimodal inputs and perform multimodal actions, we introduce two new datasets (both in the virtual shopping domain), the annotation schema, the core technical tasks, and the baseline models. The code for the baselines and the datasets will be opensourced.

The Largest-scale Chinese Medical QA Dataset： with 26,000,000 question answer pairs.

Please see the readme file as well as our 2019 EMNLP paper linked here -->

:black_circle: A spaCy pipeline and model for NLP on unstructured legal text.

Researches for Natural Language Processing for Financial Domain

This project is an instruction tuning framework and synthetic data generator that uses high-capacity teacher models to produce instruction-following pairs for training smaller student models. It provides datasets and tools for supervised instruction tuning and reinforcement learning from human feedback. The framework specializes in cross-lingual tuning, offering high-quality instruction-following examples in English and Chinese to improve model generalization across different scripts. It includes a reward modeling tool for creating preference datasets and comparative ratings used to train rew

Leaderboards, Datasets and Papers for Multi-Turn Response Selection in Retrieval-Based Chatbots

小型金融知识图谱构建流程（neo4j / python / cypher / KG）

BELLE is a specialized implementation of Chinese conversational large language models, encompassing a full instruction tuning framework. It provides a pipeline for training, evaluating, and deploying models optimized for natural language understanding and dialogue tasks in the Chinese language. The project is distinguished by its integrated approach to model refinement, combining the curation of multi-million entry instruction datasets with a distributed training pipeline. This pipeline supports both full fine-tuning and low-rank adaptation to optimize conversational performance. The system

Crime assistant including crime type prediction and crime consult service based on nlp methods and crime kg,罪名法务智能项目,内容包括856项罪名知识图谱, 基于280万罪名训练库的罪名预测,基于20W法务问答对的13类问题分类与法律资讯问答功能.

chatbot based on music region using method including es and music kb.基于14W歌曲知识库的问答尝试，功能包括歌词接龙，已知歌词找歌曲以及歌曲歌手歌词三角关系的问答。

行业内关于智能客服、聊天机器人的应用和架构、算法分享和介绍

⚠ The content in this repo has been moved to https://github.com/microsoft/botframework-sdk ⚠

An Extensible Conversational Information Seeking Platform

:hospital: Medical Text Mining and Information Extraction with spaCy

We unified the interfaces of instruction-tuning data (e.g., CoT data), multiple LLMs and parameter-efficient methods (e.g., lora, p-tuning) together for easy use. We welcome open-source enthusiasts to initiate any meaningful PR on this repo and integrate as many LLM related technologies as possible. 我们打造了方便研究人员上手和使用大模型等微调平台，我们欢迎开源爱好者发起任何有意义的pr！

开源的金融投资数据提取工具，专注在各类网站上爬取数据，并通过简单易用的API方式使用

This project provides a comprehensive Chinese language corpus designed to support the training and fine-tuning of large language models. It serves as a structured natural language processing resource, offering a collection of text data that includes dialogue, customer service interactions, and creative writing. The dataset is organized into distinct thematic categories, allowing for targeted model development across specific conversational and narrative contexts. By providing information in standardized, schema-agnostic text formats, the collection ensures portability across various machine l

EMNLP 2024 中文领域心理健康对话大模型MeChat

Question Answering using Albert and Electra

Simple application using T5 base model fine tuned in Quora Question Pairs to generate paraphased questions.

Must-read Papers on Legal Intelligence