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Cursor – Working with Context
Cursor – Working with Context
How to work with context in Cursor
Intent context defines what the user wants to get out of the model. For example, a system prompt usually serves as high-level instructions for how the user wants the model to behave. Most of the “prompting” done in Cursor is intent context. “Turn that button from blue to green” is an example of stated intent; it is prescriptive.
State context describes the state of the current world. Providing Cursor with error messages, console logs, images, and chunks of code are examples of context related to state. It is descriptive, not prescriptive.
Together, these two types of context work in harmony by describing the current state and desired future state, enabling Cursor to make useful coding suggestions.
·docs.cursor.com·
Cursor – Working with Context
SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models
SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models
In the digital era, the widespread use of APIs is evident. However, scalable utilization of APIs poses a challenge due to structure divergence observed in online API documentation. This underscores the need for automat…
·ar5iv.labs.arxiv.org·
SpeCrawler: Generating OpenAPI Specifications from API Documentation Using Large Language Models
Prompt and empower your LLM, the tidy way
Prompt and empower your LLM, the tidy way
The tidyprompt package allows users to prompt and empower their large language models (LLMs) in a tidy way. It provides a framework to construct LLM prompts using tidyverse-inspired piping syntax, with a library of pre-built prompt wrappers and the option to build custom ones. Additionally, it supports structured LLM output extraction and validation, with automatic feedback and retries if necessary. Moreover, it enables specific LLM reasoning modes, autonomous R function calling for LLMs, and compatibility with any LLM provider.
·tjarkvandemerwe.github.io·
Prompt and empower your LLM, the tidy way