Gensim
spaCy
FastText
NLTK
TensorFlow
Google Cloud Natural Language API
Keras
Amazon Comprehend
rasa NLU
Dialogflow
Microsoft Bot Framework
Wit.ai
Botpress
Amazon Lex
Chatfuel
Voiceflow
Gensim rasa NLUBased on our record, rasa NLU should be more popular than Gensim. It has been mentiond 22 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝. - Source: dev.to / over 1 year ago
Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling. Source: over 1 year ago
Here we have to install the gensim library in a jupyter notebook to be able to use it in our project, consider the code below;. - Source: dev.to / almost 2 years ago
TextRank will work without any problems. Https://radimrehurek.com/gensim/. Source: about 2 years ago
For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use. - Source: dev.to / over 2 years ago
Beyond raw language models, NLP engines like Rasa and Dialogflow offer frameworks for designing, building, and improving conversational flows. They help in intent recognition, entity extraction, and dialogue management, which are crucial for a coherent conversation structure. - Source: dev.to / about 1 month ago
There are frameworks out there for doing that kind of thing, see https://rasa.com/ for example. It's not using any LLMs at the moment, just BERT and DIET mostly but it's highly customizable and you could likely bring in an LLM for doing some interesting things to handle more complex messages from users. - Source: Hacker News / 11 months ago
Chatbot frameworks: Utilize chatbot frameworks such as Botpress, Rasa, or Microsoft Bot Framework to streamline development. - Source: dev.to / about 1 year ago
Rasa is a popular tool used right now to build these applications. If you're looking for a serious turn-key solution I would check out Vectara. Source: about 1 year ago
Another example is RASA, one of the most popular platforms for creating conversational AI assistants. On the accepted AI quality scale, RASA reaches levels 3 and 4. It means that the "robot" not only understands humans with high accuracy in a given contextual field but also learns to recognize contradictions and ulterior motives. - Source: dev.to / over 1 year ago
spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
Dialogflow - Conversational UX Platform. (ex API.ai)
FastText - Library for efficient text classification and representation learning
Microsoft Bot Framework - Framework to build and connect intelligent bots.
NLTK - NLTK is a platform for building Python programs to work with human language data.
Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...
