mwparserfromhell VS dify

There's also https://github.com/earwig/mwparserfromhell, if you don't want to roll your own.

In particular what you're looking at is not XML but wikitext. I found a discussion on stackoverflow about solving the same problem of getting text from wikitext. Seems like the most promising solution in Python since you already have the dump is to run each page through mwparserfromhell. According to the top stackoverflow answer you could use something like

Thank you so much! I was actually talking about the markup language within the text. Turns out it's proprietary to WikiMedia and user lowerthansound kindly suggested I use this: https://github.com/earwig/mwparserfromhell

This visual IDE for LLM pipelines was posted recently: https://github.com/langgenius/dify

See if it helps.

> https://github.com/langgenius/dify/blob/main/LICENSE

everyone is apparently a license pioneer

Xorbits Inference (Xinference) is an open-source platform to streamline the operation and integration of a wide array of AI models. With Xinference, you’re empowered to run inference using any open-source LLMs, embedding models, and multimodal models either in the cloud or on your own premises, and create robust AI-driven applications. It provides a RESTful API compatible with OpenAI API, Python SDK, CLI, and WebUI. Furthermore, it integrates third-party developer tools like LangChain, LlamaIndex, and Dify, facilitating model integration and development.

If you are looking to develop QnA or chat based apps then check out https://dify.ai. Do a quick check and see if it fit your requirements. You can integrate it with your app using the apis it provides

As an AI newbie, I used to find coding apps from scratch an absolute nightmare! The learning curve was steep as a ski slope, debugging took endless hours, and developing even a simple AI app nearly drove me insane! But since discovering Dify, it has totally revolutionized my life by enabling app development without any coding skills!