Dasha vs Haystack NLP Framework
Overview
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CLI (Node.js)
Manual
Detailed Comparison
Dasha is a conversational AI as a Service platform. Dasha lets you create conversational apps that are more human-like than ever before, quicker than ever before and quickly integrate them into your products. | Haystack is an open source NLP framework to interact with your data using Transformer models and LLMs (GPT-4, ChatGPT, etc.). It offers production-ready tools to build NLP backend services, e.g., question answering or semantic search. |
Declarative language for conversation design; VSCode extension; native STT, NLP, NLU, NLG and TTS; Support for external TTS; Voice over SIP Trunk; Node.js SDK; Voice over GRPC; Text over GRPC; API-first; Open developer platform; Unlimited conversational depth; High conversational concurrency; Robust digressions and intents for the human-like experience; Custom intents training | Question answering;
Semantic document search;
Latest models;
Vector databases;
Scalable pipelines; |
Statistics | |
GitHub Stars - | GitHub Stars 23.2K |
GitHub Forks - | GitHub Forks 2.5K |
Stacks 3 | Stacks 6 |
Followers 8 | Followers 12 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Dasha, Haystack NLP Framework?
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
NanoNets
Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
Inferrd
It is the easiest way to deploy Machine Learning models. Start deploying Tensorflow, Scikit, Keras and spaCy straight from your notebook with just one extra line.
Speechly
It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.
GraphLab Create
Building an intelligent, predictive application involves iterating over multiple steps: cleaning the data, developing features, training a model, and creating and maintaining a predictive service. GraphLab Create does all of this in one platform. It is easy to use, fast, and powerful.
MonkeyLearn
Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.
Jina
It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
Clever AI Humanizer
That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology
LangChain
It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
