132 skills found · Page 1 of 5
fighting41love / FunNLP中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名人词库、诗词词库、医学词库、饮食词库、法律词库、汽车词库、动物词库、中文聊天语料、中文谣言数据、百度中文问答数据集、句子相似度匹配算法集合、bert资源、文本生成&摘要相关工具、cocoNLP信息抽取工具、国内电话号码正则匹配、清华大学XLORE:中英文跨语言百科知识图谱、清华大学人工智能技术系列报告、自然语言生成、NLU太难了系列、自动对联数据及机器人、用户名黑名单列表、罪名法务名词及分类模型、微信公众号语料、cs224n深度学习自然语言处理课程、中文手写汉字识别、中文自然语言处理 语料/数据集、变量命名神器、分词语料库+代码、任务型对话英文数据集、ASR 语音数据集 + 基于深度学习的中文语音识别系统、笑声检测器、Microsoft多语言数字/单位/如日期时间识别包、中华新华字典数据库及api(包括常用歇后语、成语、词语和汉字)、文档图谱自动生成、SpaCy 中文模型、Common Voice语音识别数据集新版、神经网络关系抽取、基于bert的命名实体识别、关键词(Keyphrase)抽取包pke、基于医疗领域知识图谱的问答系统、基于依存句法与语义角色标注的事件三元组抽取、依存句法分析4万句高质量标注数据、cnocr：用来做中文OCR的Python3包、中文人物关系知识图谱项目、中文nlp竞赛项目及代码汇总、中文字符数据、speech-aligner: 从“人声语音”及其“语言文本”产生音素级别时间对齐标注的工具、AmpliGraph: 知识图谱表示学习(Python)库：知识图谱概念链接预测、Scattertext 文本可视化(python)、语言/知识表示工具：BERT & ERNIE、中文对比英文自然语言处理NLP的区别综述、Synonyms中文近义词工具包、HarvestText领域自适应文本挖掘工具（新词发现-情感分析-实体链接等）、word2word：(Python)方便易用的多语言词-词对集：62种语言/3,564个多语言对、语音识别语料生成工具：从具有音频/字幕的在线视频创建自动语音识别(ASR)语料库、构建医疗实体识别的模型（包含词典和语料标注）、单文档非监督的关键词抽取、Kashgari中使用gpt-2语言模型、开源的金融投资数据提取工具、文本自动摘要库TextTeaser: 仅支持英文、人民日报语料处理工具集、一些关于自然语言的基本模型、基于14W歌曲知识库的问答尝试--功能包括歌词接龙and已知歌词找歌曲以及歌曲歌手歌词三角关系的问答、基于Siamese bilstm模型的相似句子判定模型并提供训练数据集和测试数据集、用Transformer编解码模型实现的根据Hacker News文章标题自动生成评论、用BERT进行序列标记和文本分类的模板代码、LitBank：NLP数据集——支持自然语言处理和计算人文学科任务的100部带标记英文小说语料、百度开源的基准信息抽取系统、虚假新闻数据集、Facebook: LAMA语言模型分析，提供Transformer-XL/BERT/ELMo/GPT预训练语言模型的统一访问接口、CommonsenseQA：面向常识的英文QA挑战、中文知识图谱资料、数据及工具、各大公司内部里大牛分享的技术文档 PDF 或者 PPT、自然语言生成SQL语句（英文）、中文NLP数据增强（EDA）工具、英文NLP数据增强工具 、基于医药知识图谱的智能问答系统、京东商品知识图谱、基于mongodb存储的军事领域知识图谱问答项目、基于远监督的中文关系抽取、语音情感分析、中文ULMFiT-情感分析-文本分类-语料及模型、一个拍照做题程序、世界各国大规模人名库、一个利用有趣中文语料库 qingyun 训练出来的中文聊天机器人、中文聊天机器人seqGAN、省市区镇行政区划数据带拼音标注、教育行业新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增广库、中文全词覆盖BERT及两份阅读理解数据、ConvLab：开源多域端到端对话系统平台、中文自然语言处理数据集、基于最新版本rasa搭建的对话系统、基于TensorFlow和BERT的管道式实体及关系抽取、一个小型的证券知识图谱/知识库、复盘所有NLP比赛的TOP方案、OpenCLaP：多领域开源中文预训练语言模型仓库、UER：基于不同语料+编码器+目标任务的中文预训练模型仓库、中文自然语言处理向量合集、基于金融-司法领域(兼有闲聊性质)的聊天机器人、g2pC：基于上下文的汉语读音自动标记模块、Zincbase 知识图谱构建工具包、诗歌质量评价/细粒度情感诗歌语料库、快速转化「中文数字」和「阿拉伯数字」、百度知道问答语料库、基于知识图谱的问答系统、jieba_fast 加速版的jieba、正则表达式教程、中文阅读理解数据集、基于BERT等最新语言模型的抽取式摘要提取、Python利用深度学习进行文本摘要的综合指南、知识图谱深度学习相关资料整理、维基大规模平行文本语料、StanfordNLP 0.2.0：纯Python版自然语言处理包、NeuralNLP-NeuralClassifier：腾讯开源深度学习文本分类工具、端到端的封闭域对话系统、中文命名实体识别：NeuroNER vs. BertNER、新闻事件线索抽取、2019年百度的三元组抽取比赛：“科学空间队”源码、基于依存句法的开放域文本知识三元组抽取和知识库构建、中文的GPT2训练代码、ML-NLP - 机器学习(Machine Learning)NLP面试中常考到的知识点和代码实现、nlp4han:中文自然语言处理工具集(断句/分词/词性标注/组块/句法分析/语义分析/NER/N元语法/HMM/代词消解/情感分析/拼写检查、XLM：Facebook的跨语言预训练语言模型、用基于BERT的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取、中文自然语言处理相关的开放任务-数据集-当前最佳结果、CoupletAI - 基于CNN+Bi-LSTM+Attention 的自动对对联系统、抽象知识图谱、MiningZhiDaoQACorpus - 580万百度知道问答数据挖掘项目、brat rapid annotation tool: 序列标注工具、大规模中文知识图谱数据：1.4亿实体、数据增强在机器翻译及其他nlp任务中的应用及效果、allennlp阅读理解:支持多种数据和模型、PDF表格数据提取工具 、 Graphbrain：AI开源软件库和科研工具，目的是促进自动意义提取和文本理解以及知识的探索和推断、简历自动筛选系统、基于命名实体识别的简历自动摘要、中文语言理解测评基准，包括代表性的数据集&基准模型&语料库&排行榜、树洞 OCR 文字识别 、从包含表格的扫描图片中识别表格和文字、语声迁移、Python口语自然语言处理工具集(英文)、 similarity：相似度计算工具包，java编写、海量中文预训练ALBERT模型 、Transformers 2.0 、基于大规模音频数据集Audioset的音频增强 、Poplar：网页版自然语言标注工具、图片文字去除，可用于漫画翻译 、186种语言的数字叫法库、Amazon发布基于知识的人-人开放领域对话数据集 、中文文本纠错模块代码、繁简体转换 、 Python实现的多种文本可读性评价指标、类似于人名/地名/组织机构名的命名体识别数据集 、东南大学《知识图谱》研究生课程(资料)、. 英文拼写检查库 、 wwsearch是企业微信后台自研的全文检索引擎、CHAMELEON：深度学习新闻推荐系统元架构 、 8篇论文梳理BERT相关模型进展与反思、DocSearch：免费文档搜索引擎、 LIDA：轻量交互式对话标注工具 、aili - the fastest in-memory index in the East 东半球最快并发索引 、知识图谱车音工作项目、自然语言生成资源大全 、中日韩分词库mecab的Python接口库、中文文本摘要/关键词提取、汉字字符特征提取器 (featurizer)，提取汉字的特征（发音特征、字形特征）用做深度学习的特征、中文生成任务基准测评 、中文缩写数据集、中文任务基准测评 - 代表性的数据集-基准(预训练)模型-语料库-baseline-工具包-排行榜、PySS3：面向可解释AI的SS3文本分类器机器可视化工具 、中文NLP数据集列表、COPE - 格律诗编辑程序、doccano：基于网页的开源协同多语言文本标注工具 、PreNLP：自然语言预处理库、简单的简历解析器，用来从简历中提取关键信息、用于中文闲聊的GPT2模型：GPT2-chitchat、基于检索聊天机器人多轮响应选择相关资源列表(Leaderboards、Datasets、Papers)、(Colab)抽象文本摘要实现集锦(教程 、词语拼音数据、高效模糊搜索工具、NLP数据增广资源集、微软对话机器人框架 、 GitHub Typo Corpus：大规模GitHub多语言拼写错误/语法错误数据集、TextCluster：短文本聚类预处理模块 Short text cluster、面向语音识别的中文文本规范化、BLINK：最先进的实体链接库、BertPunc：基于BERT的最先进标点修复模型、Tokenizer：快速、可定制的文本词条化库、中文语言理解测评基准，包括代表性的数据集、基准(预训练)模型、语料库、排行榜、spaCy 医学文本挖掘与信息提取 、 NLP任务示例项目代码集、 python拼写检查库、chatbot-list - 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、语音质量评价指标(MOSNet, BSSEval, STOI, PESQ, SRMR)、 用138GB语料训练的法文RoBERTa预训练语言模型 、BERT-NER-Pytorch：三种不同模式的BERT中文NER实验、无道词典 - 有道词典的命令行版本，支持英汉互查和在线查询、2019年NLP亮点回顾、 Chinese medical dialogue data 中文医疗对话数据集 、最好的汉字数字(中文数字)-阿拉伯数字转换工具、 基于百科知识库的中文词语多词义/义项获取与特定句子词语语义消歧、awesome-nlp-sentiment-analysis - 情感分析、情绪原因识别、评价对象和评价词抽取、LineFlow：面向所有深度学习框架的NLP数据高效加载器、中文医学NLP公开资源整理 、MedQuAD：(英文)医学问答数据集、将自然语言数字串解析转换为整数和浮点数、Transfer Learning in Natural Language Processing (NLP) 、面向语音识别的中文/英文发音辞典、Tokenizers：注重性能与多功能性的最先进分词器、CLUENER 细粒度命名实体识别 Fine Grained Named Entity Recognition、 基于BERT的中文命名实体识别、中文谣言数据库、NLP数据集/基准任务大列表、nlp相关的一些论文及代码, 包括主题模型、词向量(Word Embedding)、命名实体识别(NER)、文本分类(Text Classificatin)、文本生成(Text Generation)、文本相似性(Text Similarity)计算等，涉及到各种与nlp相关的算法，基于keras和tensorflow 、Python文本挖掘/NLP实战示例、 Blackstone：面向非结构化法律文本的spaCy pipeline和NLP模型通过同义词替换实现文本“变脸” 、中文 预训练 ELECTREA 模型: 基于对抗学习 pretrain Chinese Model 、albert-chinese-ner - 用预训练语言模型ALBERT做中文NER 、基于GPT2的特定主题文本生成/文本增广、开源预训练语言模型合集、多语言句向量包、编码、标记和实现：一种可控高效的文本生成方法、 英文脏话大列表 、attnvis：GPT2、BERT等transformer语言模型注意力交互可视化、CoVoST：Facebook发布的多语种语音-文本翻译语料库，包括11种语言(法语、德语、荷兰语、俄语、西班牙语、意大利语、土耳其语、波斯语、瑞典语、蒙古语和中文)的语音、文字转录及英文译文、Jiagu自然语言处理工具 - 以BiLSTM等模型为基础，提供知识图谱关系抽取 中文分词 词性标注 命名实体识别 情感分析 新词发现 关键词 文本摘要 文本聚类等功能、用unet实现对文档表格的自动检测，表格重建、NLP事件提取文献资源列表 、 金融领域自然语言处理研究资源大列表、CLUEDatasetSearch - 中英文NLP数据集：搜索所有中文NLP数据集，附常用英文NLP数据集 、medical_NER - 中文医学知识图谱命名实体识别 、(哈佛)讲因果推理的免费书、知识图谱相关学习资料/数据集/工具资源大列表、Forte：灵活强大的自然语言处理pipeline工具集 、Python字符串相似性算法库、PyLaia：面向手写文档分析的深度学习工具包、TextFooler：针对文本分类/推理的对抗文本生成模块、Haystack：灵活、强大的可扩展问答(QA)框架、中文关键短语抽取工具
RasaHQ / Rasa💬 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
adeshpande3 / Facebook Messenger BotFacebook chatbot that I trained to talk like me using Seq2Seq
enginebai / PyMessagerPython API to develop chatbot on Facebook Messenger Platform
urban-bot / Urban Bot🤖 The universal chatbot library based on React. Write once, launch Telegram, Discord, Facebook, ... every messenger with chatbots
abusufyanvu / 6S191 MIT DeepLearningMIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: introtodeeplearning-staff@mit.edu Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning
messenger4j / Messenger4jA Java library for building Chatbots on the Facebook Messenger Platform - easy and fast.
progapandist / Rubotnik"Bot-end" Ruby framework to quickly build and launch a Facebook Messenger chatbot
conbus / Fbmq(Deprecated) Facebook Messenger Platform Python Library (Facebook Chatbot Library)
NishNishendanidu / Mtroid BotGENARATED BY NISHEN Mtroid whatsApp bot 🪀 Command:`setup `✨️ Description:` edit bot settings `⚠️️ Warn `🪀 Command:` install <br> `✨️ Description:` Install external plugins. <br> `⚠️️ Warn:` Get plugins only from https://t.me/AlphaXplugin. `🪀 Command:` plugin<br> `✨️ Description:` Shows the plugins you have installed. `🪀 Command:` remove<br> `✨️ Description:` Removes the plugin. `🪀 Command:` admin<br> `✨️ Description:` Admin menu. `🪀 Command:` ban <br> `✨️ Description:` Ban someone in the group. Reply to message or tag a person to use command. `🪀 Command:` gname <br> `✨️ Description:` Change group name. `🪀 Command:` gdesc<br> `✨️ Description:` Change group discription. `🪀 Command:` dis <br> `✨️ Description:` Disappearing message on/off. <br> `💡 Example:` .dis on/off `🪀 Command:` reset<br> `✨️ Description:` Reset group invitation link. `🪀 Command:` gpp<br> `✨️ Description:` Set group profile picture `🪀 Command:` add<br> `✨️ Description:` Adds someone to the group. `🪀 Command:` promote <br> `✨️ Description:` Makes any person an admin. `🪀 Command:` demote <br> `✨️ Description:` Takes the authority of any admin. `🪀 Command:` mute <br> `✨️ Description:` Mute the group chat. Only the admins can send a message. ⌨️ Example: .mute & .mute 5m etc `🪀 Command:` unmute <br> `✨️ Description:` Unmute the group chat. Anyone can send a message. `🪀 Command:` invite <br> `✨️ Description:` Provides the group's invitation link. `🪀 Command:` afk <br> `✨️ Description:` It makes you AFK - Away From Keyboard. `🪀 Command:` art pack<br> `✨️ Description:` Beautifull artpack with more than 100 messages. `🪀 Command:` aspm <br> `✨️ Description:` This command for any emergency situation about any kind of WhatsApp SPAM in Group `🪀 Command:` alag <br> `✨️ Description:` This command for any emergency situation about any kind of WhatsApp SPAM in Chat `🪀 Command:` linkblock <br> `✨️ Description:` Activates the block link tool. <br> `💡 Example:` .linkblock on / off `🪀 Command:` CrAsH<br> `✨️ Description:` send BUG VIRUS to group. `🪀 Command:` CrAsH high<br> `✨️ Description:` send BUG VIRUS to group untill you stop. `🪀 Command:` -carbon `🪀 Command:` clear<br> `✨️ Description:` Clears all the messages from the chat. `🪀 Command:` qr <br> `✨️ Description:` To create an qr code from the word you give. `🪀 Command:` bcode <br> `✨️ Description:` To create an barcode from the word you give. `🪀 Command:` compliment<br> `✨️ Description:` It sends complimentry sentenses. `🪀 Command:` toaudio<br> `✨️ Description:` Converts video to sound. `🪀 Command:` toimage<br> `✨️ Description:` Converts the sticker to a photo. `🪀 Command:` tovideo<br> `✨️ Description:` Converts animated stickers to video. `🪀 Command:` deepai<br> `✨️ Description:` Runs the most powerful artificial intelligence tools using artificial neural networks. `🪀 Command:` details<br> `✨️ Description:` Displays metadata data of group or person. `🪀 Command:` dict <br> `✨️ Description:` Use it as a dictionary. Eg: .dict enUS;lead For supporting languages send •.lngcode• `🪀 Command:` dst<br> `✨️ Description:` Download status you repled. `🪀 Command:` emedia<br> `✨️ Description:` It is a plugin with more than 25 media tools. `🪀 Command:` emoji <br> `✨️ Description:` You can get Emoji as image. `🪀 Command:` print <br> `✨️ Description:` Prints the inside of the file on the server. `🪀 Command:` bashmedia <br> `✨️ Description:` Sends audio, video and photos inside the server. <br> `💡 Example:` video.mp4 && media/gif/pic.mp4 `🪀 Command:` addserver<br> `✨️ Description:` Uploads image, audio or video to the server. `🪀 Command:` term <br> `✨️ Description:` Allows to run the command on the server's shell. `🪀 Command:` mediainfo<br> `✨️ Description:` Shows the technical information of the replied video. `🪀 Command:` pmsend <br> `✨️ Description:` Sends a private message to the replied person. `🪀 Command:` pmttssend <br> `✨️ Description:` Sends a private voice message to the respondent. `🪀 Command:` ffmpeg <br> `✨️ Description:` Applies the desired ffmpeg filter to the video. ⌨️ Example: .ffmpeg fade=in:0:30 `🪀 Command:` filter <br> `✨️ Description:` It adds a filter. If someone writes your filter, it send the answer. If you just write .filter, it show's your filter list. `🪀 Command:` stop <br> `✨️ Description:` Stops the filter you added previously. `🪀 Command:` bgmlist<br> `✨️ Description:` Bgm List. `🪀 Command:` github <br> `✨️ Description:` It Send Github User Data. <br> `💡 Example:` .github WhatsApp `🪀 Command:` welcome<br> `✨️ Description:` It sets the welcome message. If you leave it blank it shows the welcome message. `🪀 Command:` goodbye<br> `✨️ Description:` Sets the goodbye message. If you leave blank, it show's the goodbye message. `🪀 Command:` help<br> `✨️ Description:` Gives information about using the bot from the Help menu. `🪀 Command:` varset <br> `✨️ Description:` Changes the text of modules like alive, afk etc.. `🪀 Command:` restart<br> `✨️ Description:` Restart bot. `🪀 Command:` poweroff<br> `✨️ Description:` Shutdown bot. `🪀 Command:` dyno<br> `✨️ Description:` Check heroku dyno usage `🪀 Command:` setvar <br> `✨️ Description:` Set heroku config var `🪀 Command:` delvar <br> `✨️ Description:` Delete heroku config var `🪀 Command:` getvar <br> `✨️ Description:` Get heroku config var `🪀 Command:` hpmod <br> `✨️ Description:` To get mod apps info. `🪀 Command:` insult<br> `✨️ Description:` It gives random insults. `🪀 Command:` locate<br> `✨️ Description:` It send your location. <br> `⚠️️ Warn:` Please open your location before using command! `🪀 Command:` logmsg<br> `✨️ Description:` Saves the message you reply to your private number. <br> `⚠️️ Warn:` Does not support animated stickers! `🪀 Command:` logomaker<br> `✨️ Description:` Shows logomaker tools with unlimited access. `🪀 Command:` meme <br> `✨️ Description:` Photo memes you replied to. `🪀 Command:` movie <br> `✨️ Description:` Shows movie info. `🪀 Command:` neko<br> `✨️ Description:` Replied messages will be added to nekobin.com. `🪀 Command:` song <br> `✨️ Description:` Uploads the song you wrote. `🪀 Command:` video <br> `✨️ Description:` Downloads video from YouTube. `🪀 Command:` fb <br> `✨️ Description:` Download video from facebook. `🪀 Command:` tiktok <br> `✨️ Description:` Download tiktok video. `🪀 Command:` notes<br> `✨️ Description:` Shows all your existing notes. `🪀 Command:` save <br> `✨️ Description:` Reply a message and type .save or just use .save <Your note> without replying `🪀 Command:` deleteNotes<br> `✨️ Description:` Deletes *all* your saved notes. `🪀 Command:` ocr <br> `✨️ Description:` Reads the text on the photo you have replied. `🪀 Command:` pinimg <br> `✨️ Description:` Downloas images from Pinterest. `🪀 Command:` playst <br> `✨️ Description:` Get app details from play store. `🪀 Command:` profile<br> `✨️ Description:` Profile menu. `🪀 Command:` getpp<br> `✨️ Description:` Get pofile picture. `🪀 Command:` setbio <br> `✨️ Description:` Set your about. `🪀 Command:` getbio<br> `✨️ Description:` Get user about. `🪀 Command:` archive<br> `✨️ Description:` Archive chat. `🪀 Command:` unarchive<br> `✨️ Description:` Unarchive chat. `🪀 Command:` pin<br> `✨️ Description:` Archive chat. `🪀 Command:` unpin<br> `✨️ Description:` Unarchive chat. `🪀 Command:` pp<br> `✨️ Description:` Makes the profile photo what photo you reply. `🪀 Command:` kickme<br> `✨️ Description:` It kicks you from the group you are using it in. `🪀 Command:` block <br> `✨️ Description:` Block user. `🪀 Command:` unblock <br> `✨️ Description:` Unblock user. `🪀 Command:` jid <br> `✨️ Description:` Giving user's JID. `🪀 Command:` rdmore <br> `✨️ Description:` Add readmore to your message >> Use # to get readmore. `🪀 Command:` removebg <br> `✨️ Description:` Removes the background of the photos. `🪀 Command:` report <br> `✨️ Description:` Sends reports to group admins. `🪀 Command:` roll<br> `✨️ Description:` Roll dice randomly. `🪀 Command:` scam <br> `✨️ Description:` Creates 5 minutes of fake actions. `🪀 Command:` scan <br> `✨️ Description:` Checks whether the entered number is registered on WhatApp. `🪀 Command:` trt<br> `✨️ Description:` It translates with Google Translate. You must reply any message. <br> `💡 Example:` .trt en si (From English to Sinhala) `🪀 Command:` antilink <br> `✨️ Description:` Activates the Antilink tool. <br> `💡 Example:` .antilink on / off `🪀 Command:` autobio <br> `✨️ Description:` Add live clock to your bio! <br> `💡 Example:` .autobio on / off `🪀 Command:` detectlang<br> `✨️ Description:` Guess the language of the replied message. `🪀 Command:` currency `🪀 Command:` tts <br> `✨️ Description:` It converts text to sound. `🪀 Command:` music <br> `✨️ Description:` Uploads the song you wrote. `🪀 Command:` smp3 <br> `✨️ Description:` Get song as a mp3 documet file `🪀 Command:` mp4 <br> `✨️ Description:` Downloads video from YouTube. `🪀 Command:` yt <br> `✨️ Description:` It searchs on YouTube. `🪀 Command:` wiki <br> `✨️ Description:` Searches query on Wikipedia. `🪀 Command:` img <br> `✨️ Description:` Searches for related pics on Google. `🪀 Command:` lyric <br> `✨️ Description:` Finds the lyrics of the song. `🪀 Command:` covid <br> `✨️ Description:` Shows the daily and overall covid table of more than 15 countries. `🪀 Command:` ss <br> `✨️ Description:` Takes a screenshot from the page in the given link. `🪀 Command:` simi <br> `✨️ Description:` Are you bored? ... Fool around with SimSimi. ... World first popular Chatbot for daily conversation. `🪀 Command:` spdf <br> `✨️ Description:` Site to pdf file. `🪀 Command:` insta <br> `✨️ Description:` Downloads videos or photos from Instagram. `🪀 Command:` animesay <br> `✨️ Description:` It writes the text inside the banner the anime girl is holding `🪀 Command:` changesay <br> `✨️ Description:` Turns the text into the change my mind poster. `🪀 Command:` trumpsay <br> `✨️ Description:` Converts the text to Trump's tweet. `🪀 Command:` audio spam<br> `✨️ Description:` Sends the replied audio as spam. `🪀 Command:` foto spam<br> `✨️ Description:` Sends the replied photo as spam. `🪀 Command:` sticker spam<br> `✨️ Description:` Convert the replied photo or video to sticker and send it as spam. `🪀 Command:` vid spam `🪀 Command:` killspam<br> `✨️ Description:` Stops spam command. `🪀 Command:` spam <br> `✨️ Description:` It spam until you stop it. ⌨️ Example: .spam test `🪀 Command:` spotify <br> `✨️ Description:` Get music details from spotify. `🪀 Command:` st<br> `✨️ Description:` It converts your replied photo or video to sticker. `🪀 Command:` sweather<br> `✨️ Description:` Gives you the weekly interpretations of space weather observations provided by the Space Weather Research Center (SWRC) for a p. `🪀 Command:` alive <br> `✨️ Description:` Does bot work? `🪀 Command:` sysd<br> `✨️ Description:` Shows the system properties. `🪀 Command:` tagadmin `🪀 Command:` tg <br> `✨️ Description:` Tags everyone in the group. `🪀 Command:` pmall<br> `✨️ Description:` Sends the replied message to all members in the group. `🪀 Command:` tblend <br> `✨️ Description:` Applies the selected TBlend effect to videos. `🪀 Command:` link<br> `✨️ Description:` The image you reply to uploads to telegra.ph and provides its link. `🪀 Command:` unvoice<br> `✨️ Description:` Converts audio to sound recording. `🪀 Command:` up<br> `✨️ Description:` Checks the update your bot. `🪀 Command:` up now<br> `✨️ Description:` It makes updates. `🪀 Command:` voicy<br> `✨️ Description:` It converts audio to text. `🪀 Command:` wp<br> `✨️ Description:` It sends high resolution wallpapers. `🪀 Command:` wame <br> `✨️ Description:` Get a link to the user chat. `🪀 Command:` weather <br> `✨️ Description:` Shows the weather. `🪀 Command:` speedtest <br> `✨️ Description:` Measures Download and Upload speed. <br> `💡 Example:` speedtest user // speedtest server `🪀 Command:` ping<br> `✨️ Description:` Measures your ping. `🪀 Command:` short <br> `✨️ Description:` Shorten the long link. `🪀 Command:` calc <br> `✨️ Description:` Performs simple math operations. `🪀 Command:` xapi<br> `✨️ Description:` Xteam API key info. `🪀 Command:` joke<br> `✨️ Description:` Send random jokes. `🪀 Command:` quote<br> `✨️ Description:` Send random quotes.
hult / Facebook Chatbot PythonA simple python chatbot for Facebook messenger
Chatbot-Taiwan / Meetups台灣聊天機器人社群 ➡️ https://www.facebook.com/groups/chatbot.tw
messenger4j / Messenger4j Spring Boot Quickstart TemplateTemplate for a Facebook Messenger Chatbot using Java, Spring Boot, and messenger4j. Write Chatbots within minutes 🔥
terrenjpeterson / CaloriecounterAWS Lex based chatbot that calculates calories based on different fast food restaurants. This was an entry for a coding challenge on DevPost, and is actively used on Facebook Messenger. The issues list is actively managed as what defects or improvements are found by real world usage.
Tinkprocodes / Fca UnofficialThis repo is a fork from main repo and will usually have new features bundled faster than main repo (and maybe bundle some bugs, too). # Unofficial Facebook Chat API <img alt="version" src="https://img.shields.io/github/package-json/v/ProCoderMew/fca-unofficial?label=github&style=flat-square"> Facebook now has an official API for chat bots [here](https://developers.facebook.com/docs/messenger-platform). This API is the only way to automate chat functionalities on a user account. We do this by emulating the browser. This means doing the exact same GET/POST requests and tricking Facebook into thinking we're accessing the website normally. Because we're doing it this way, this API won't work with an auth token but requires the credentials of a Facebook account. _Disclaimer_: We are not responsible if your account gets banned for spammy activities such as sending lots of messages to people you don't know, sending messages very quickly, sending spammy looking URLs, logging in and out very quickly... Be responsible Facebook citizens. See [below](#projects-using-this-api) for projects using this API. ## Install If you just want to use fca-unofficial, you should use this command: ```bash npm install procodermew/fca-unofficial ``` It will download `fca-unofficial` from NPM repositories ## Testing your bots If you want to test your bots without creating another account on Facebook, you can use [Facebook Whitehat Accounts](https://www.facebook.com/whitehat/accounts/). ## Example Usage ```javascript const login = require("fca-unofficial"); // Create simple echo bot login({email: "FB_EMAIL", password: "FB_PASSWORD"}, (err, api) => { if(err) return console.error(err); api.listen((err, message) => { api.sendMessage(message.body, message.threadID); }); }); ``` Result: <img width="517" alt="screen shot 2016-11-04 at 14 36 00" src="https://cloud.githubusercontent.com/assets/4534692/20023545/f8c24130-a29d-11e6-9ef7-47568bdbc1f2.png"> ## Documentation You can see it [here](DOCS.md). ## Main Functionality ### Sending a message #### api.sendMessage(message, threadID[, callback][, messageID]) Various types of message can be sent: * *Regular:* set field `body` to the desired message as a string. * *Sticker:* set a field `sticker` to the desired sticker ID. * *File or image:* Set field `attachment` to a readable stream or an array of readable streams. * *URL:* set a field `url` to the desired URL. * *Emoji:* set field `emoji` to the desired emoji as a string and set field `emojiSize` with size of the emoji (`small`, `medium`, `large`) Note that a message can only be a regular message (which can be empty) and optionally one of the following: a sticker, an attachment or a url. __Tip__: to find your own ID, you can look inside the cookies. The `userID` is under the name `c_user`. __Example (Basic Message)__ ```js const login = require("fca-unofficial"); login({email: "FB_EMAIL", password: "FB_PASSWORD"}, (err, api) => { if(err) return console.error(err); var yourID = "000000000000000"; var msg = "Hey!"; api.sendMessage(msg, yourID); }); ``` __Example (File upload)__ ```js const login = require("fca-unofficial"); login({email: "FB_EMAIL", password: "FB_PASSWORD"}, (err, api) => { if(err) return console.error(err); // Note this example uploads an image called image.jpg var yourID = "000000000000000"; var msg = { body: "Hey!", attachment: fs.createReadStream(__dirname + '/image.jpg') } api.sendMessage(msg, yourID); }); ``` ------------------------------------ ### Saving session. To avoid logging in every time you should save AppState (cookies etc.) to a file, then you can use it without having password in your scripts. __Example__ ```js const fs = require("fs"); const login = require("fca-unofficial"); var credentials = {email: "FB_EMAIL", password: "FB_PASSWORD"}; login(credentials, (err, api) => { if(err) return console.error(err); fs.writeFileSync('appstate.json', JSON.stringify(api.getAppState())); }); ``` Alternative: Use [c3c-fbstate](https://github.com/c3cbot/c3c-fbstate) to get fbstate.json (appstate.json) ------------------------------------ ### Listening to a chat #### api.listen(callback) Listen watches for messages sent in a chat. By default this won't receive events (joining/leaving a chat, title change etc…) but it can be activated with `api.setOptions({listenEvents: true})`. This will by default ignore messages sent by the current account, you can enable listening to your own messages with `api.setOptions({selfListen: true})`. __Example__ ```js const fs = require("fs"); const login = require("fca-unofficial"); // Simple echo bot. It will repeat everything that you say. // Will stop when you say '/stop' login({appState: JSON.parse(fs.readFileSync('appstate.json', 'utf8'))}, (err, api) => { if(err) return console.error(err); api.setOptions({listenEvents: true}); var stopListening = api.listenMqtt((err, event) => { if(err) return console.error(err); api.markAsRead(event.threadID, (err) => { if(err) console.error(err); }); switch(event.type) { case "message": if(event.body === '/stop') { api.sendMessage("Goodbye…", event.threadID); return stopListening(); } api.sendMessage("TEST BOT: " + event.body, event.threadID); break; case "event": console.log(event); break; } }); }); ``` ## FAQS 1. How do I run tests? > For tests, create a `test-config.json` file that resembles `example-config.json` and put it in the `test` directory. From the root >directory, run `npm test`. 2. Why doesn't `sendMessage` always work when I'm logged in as a page? > Pages can't start conversations with users directly; this is to prevent pages from spamming users. 3. What do I do when `login` doesn't work? > First check that you can login to Facebook using the website. If login approvals are enabled, you might be logging in incorrectly. For how to handle login approvals, read our docs on [`login`](DOCS.md#login). 4. How can I avoid logging in every time? Can I log into a previous session? > We support caching everything relevant for you to bypass login. `api.getAppState()` returns an object that you can save and pass into login as `{appState: mySavedAppState}` instead of the credentials object. If this fails, your session has expired. 5. Do you support sending messages as a page? > Yes, set the pageID option on login (this doesn't work if you set it using api.setOptions, it affects the login process). > ```js > login(credentials, {pageID: "000000000000000"}, (err, api) => { … } > ``` 6. I'm getting some crazy weird syntax error like `SyntaxError: Unexpected token [`!!! > Please try to update your version of node.js before submitting an issue of this nature. We like to use new language features. 7. I don't want all of these logging messages! > You can use `api.setOptions` to silence the logging. You get the `api` object from `login` (see example above). Do > ```js > api.setOptions({ > logLevel: "silent" > }); > ``` <a name="projects-using-this-api"></a> ## Projects using this API: - [c3c](https://github.com/lequanglam/c3c) - A bot that can be customizable using plugins. Support Facebook & Discord. - [Miraiv2](https://github.com/miraiPr0ject/miraiv2) - A simple Facebook Messenger Bot made by CatalizCS and SpermLord. ## Projects using this API (original repository, facebook-chat-api): - [Messer](https://github.com/mjkaufer/Messer) - Command-line messaging for Facebook Messenger - [messen](https://github.com/tomquirk/messen) - Rapidly build Facebook Messenger apps in Node.js - [Concierge](https://github.com/concierge/Concierge) - Concierge is a highly modular, easily extensible general purpose chat bot with a built in package manager - [Marc Zuckerbot](https://github.com/bsansouci/marc-zuckerbot) - Facebook chat bot - [Marc Thuckerbot](https://github.com/bsansouci/lisp-bot) - Programmable lisp bot - [MarkovsInequality](https://github.com/logicx24/MarkovsInequality) - Extensible chat bot adding useful functions to Facebook Messenger - [AllanBot](https://github.com/AllanWang/AllanBot-Public) - Extensive module that combines the facebook api with firebase to create numerous functions; no coding experience is required to implement this. - [Larry Pudding Dog Bot](https://github.com/Larry850806/facebook-chat-bot) - A facebook bot you can easily customize the response - [fbash](https://github.com/avikj/fbash) - Run commands on your computer's terminal over Facebook Messenger - [Klink](https://github.com/KeNt178/klink) - This Chrome extension will 1-click share the link of your active tab over Facebook Messenger - [Botyo](https://github.com/ivkos/botyo) - Modular bot designed for group chat rooms on Facebook - [matrix-puppet-facebook](https://github.com/matrix-hacks/matrix-puppet-facebook) - A facebook bridge for [matrix](https://matrix.org) - [facebot](https://github.com/Weetbix/facebot) - A facebook bridge for Slack. - [Botium](https://github.com/codeforequity-at/botium-core) - The Selenium for Chatbots - [Messenger-CLI](https://github.com/AstroCB/Messenger-CLI) - A command-line interface for sending and receiving messages through Facebook Messenger. - [AssumeZero-Bot](https://github.com/AstroCB/AssumeZero-Bot) – A highly customizable Facebook Messenger bot for group chats. - [Miscord](https://github.com/Bjornskjald/miscord) - An easy-to-use Facebook bridge for Discord. - [chat-bridge](https://github.com/rexx0520/chat-bridge) - A Messenger, Telegram and IRC chat bridge. - [messenger-auto-reply](https://gitlab.com/theSander/messenger-auto-reply) - An auto-reply service for Messenger. - [BotCore](https://github.com/AstroCB/BotCore) – A collection of tools for writing and managing Facebook Messenger bots. - [mnotify](https://github.com/AstroCB/mnotify) – A command-line utility for sending alerts and notifications through Facebook Messenger.
chief-nerd / WitAI Facebook Messenger Chatbot BoilerplateWit AI and Facebook Messenger Chatbot Boilerplate
lvklabs / ChatbotChatbot is an open source platform to create Facebook and Gtalk/Gmail chatbots
pmuens / Serverless Facebook Messenger BotServerless Chatbot for the Facebook Messenger platform
simonprickett / BartfbchatbotFacebook Messenger Chatbot for BART.
BlondelSeumo / Social Media Marketing PlatformMainly this is a visual drag and drop Flow Builder based chatbot for Facebook Messenger and Instagram DM. It also comprises a feature for auto comment, auto-reply to comment, and private reply for Facebook and Instagram. Besides, It has a feature for posting on Facebook, Instagram, and others. True, it has an SMS and Email marketing service. On the other hand, it has a full-featured Ecommerce that can live inside Facebook Messenger, Instagram DM, and on web browsers. And finally, it is a self-hosted white label multi-user SaaS application. In one word, it is an all-in-one marketing solution for your business.
