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Based on our record, Hugging Face seems to be a lot more popular than rasa NLU. While we know about 254 links to Hugging Face, we've tracked only 22 mentions of rasa NLU. 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.
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 / 3 months 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 / about 1 year 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: over 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
We will use the OpenAI embeddings API to convert the content of the blog posts into vector embeddings. You will need to sign up for an API key on the OpenAI website to use the API. You will need to provide your credit card information as there is a cost associated with using the API. You can review the pricing on the OpenAI website. There are alternatives to generate embeddings. Hugging Face provides... - Source: dev.to / 2 days ago
Hugging-face 🤗 is a repository to host all the LLM models available in the world. https://huggingface.co/. - Source: dev.to / 10 days ago
HuggingFaceEmbeddings is a function that we use for converting our documents to vector which is called embedding, you can use any embedding model from huggingface, it will load the model on your local computer and create embeddings(you can use external api/service to create embeddings), then we just pass this to context and create index and store them into folder so we can reuse them and don't need to recalculate it. - Source: dev.to / about 1 month ago
The only requirement for this tutorial is to have an Hugging Face account. In order to get it:. - Source: dev.to / about 2 months ago
Finally, you'll need to download a compatible language model and copy it to the ~/llama.cpp/models directory. Head over to Hugging Face and search for a GGUF-formatted model that fits within your device's available RAM. I'd recommend starting with TinyLlama-1.1B. - Source: dev.to / about 2 months ago
Dialogflow - Conversational UX Platform. (ex API.ai)
Replika - Your Ai friend
Microsoft Bot Framework - Framework to build and connect intelligent bots.
LangChain - Framework for building applications with LLMs through composability
Botpress - Open-source platform for developers to build high-quality digital assistants
Haystack NLP Framework - Haystack is an open source NLP framework to build applications with Transformer models and LLMs.