<s>[INST] I want to write a language server vscode extension, it should handle .dws files. Please outline, what is necessary to achieve this goal. [/INST] Here is a general outline for writing a language server for .dws files in Visual Studio Code:

    Familiarize yourself with the language server protocol (LSP): The LSP is a protocol for language-agnostic development tools to communicate with code editors. You will need to understand how LSP works to write a language server that can be used by VSCode.

    Choose a programming language: You will need to choose a programming language in which to write the language server. Some popular options include JavaScript, TypeScript, and Python.

    Set up the development environment: You will need to install VSCode and its extension development tools, as well as a language-specific development environment.

    Write the language server: You will need to write code to parse .dws files, provide diagnostics and suggestions, and perform other language-specific tasks.

    Package and publish the extension: You will need to package your language server as a VSCode extension and publish it in the VSCode marketplace so that users can install and use it.

    Test and refine: You will need to test the language server to ensure it works as expected, and refine it based on feedback from users.

Note: This is a high-level outline, and the specifics of writing a language server will depend on the programming language you choose and the complexity of your .dws language.</s>\ <s>[INST] Okay, I'll keep this in mind. Are there any tools that can help me with parsing the text, such as existing libraries? [/INST] Yes, there are several libraries and tools that can help with parsing text. Some of the most popular ones include:

1.  Natural Language Toolkit (NLTK) - an open-source library for NLP in Python
2.  spaCy - an open-source library for NLP in Python
3.  Stanford Parser - a Java-based parser developed by Stanford NLP Group
4.  CoreNLP - an NLP library developed by Stanford NLP Group
5.  Gensim - an open-source library for topic modeling in Python

These libraries provide a variety of tools and techniques for text parsing, including tokenization, part-of-speech tagging, parsing, named entity recognition, and more.</s>