How to contribute to the MindMeld platform: Note: this web client only works on Chrome browser. git clone mindmeld/mindmeld-uiįor detailed installation instructions, see Getting Started for UI. This web UI also serves as a debugging tool to step through the various stages of query processing by the MindMeld pipeline. You can use our sample web-based chat client interface to interact with any MindMeld application. To start with pre-built sample applications, see MindMeld Blueprints. This makes MindMeld ideally suited for applications which must demonstrate deep understanding of a large product catalog, content library, or FAQ database, for example.ĭifferently from cloud-based NLP services, which require that you forfeit your data, MindMeld was designed from the start to ensure that proprietary training data and models always remain within the control and ownership of your application.Īssuming you have pip installed with Python 3.6 or Python 3.7 and Elasticsearch running in the background: pip install mindmeldįor detailed installation instructions, see Getting Started. MindMeld is the only Conversational AI platform available today which supports custom knowledge base creation. Nearly all production conversational applications rely on a comprehensive knowledge base to enhance intelligence and utility. MindMeld provides end-to-end functionality including advanced NLP, QA, and DM, all three of which are required for production applications today. While conversational AI platforms available today typically provide natural language processing (NLP) support, few assist with question answering (QA) or dialogue management (DM). In contrast to machine learning toolkits which offer algorithms but little data, MindMeld provides not only state-of-the-art algorithms, but also functionality which streamlines the collection and management of large sets of custom training data. Unlike GUI-based tools typically too rigid to accommodate the functionality required by many applications, MindMeld provides powerful command-line utilities with the flexibility to accommodate nearly any product requirements. This has been achieved by following the architectural philosophy whose guiding principles are expressed in the table below. Over the course of these production deployments, MindMeld has evolved to be ideally suited for building production-quality, large-vocabulary language understanding capabilities for any custom application domain. MindMeld has been used for applications in dozens of different domains by some of the largest global organizations. Training data collection and management support To summarize, the functionality available in MindMeld includes:Īdvanced Natural Language Processing, consisting of The architecture of MindMeld is illustrated below. MindMeld is the only Conversational AI platform available today that provides tools and capabilities for every step in the workflow for a state-of-the-art conversational application. Evolved over several years of building and deploying dozens of the most advanced conversational experiences achievable, MindMeld is optimized for building advanced conversational assistants which demonstrate deep understanding of a particular use case or domain while providing highly useful and versatile conversational experiences. It is a Python-based machine learning framework which encompasses all of the algorithms and utilities required for this purpose. The MindMeld Conversational AI platform is among the most advanced AI platforms for building production-quality conversational applications. This repository contains the MindMeld Conversational AI Platform.
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