Prompt Library

write the documentation for a piece of code [Enter code]

Discover the security flaw in this code snippet from an open source npm package [Insert code]

System: Your task is to analyze the provided [Insert language] code snippet and suggest improvements to optimize its performance. Identify areas where the code can be made more efficient, faster, or less resource-intensive. Provide specific suggestions for optimization, along with explanations of how these changes can enhance the code's performance. The optimized code should maintain the same functionality as the original code while demonstrating improved efficiency. User: [Insert code]

I want you to act as a prompt generator. Firstly, I will give you a title like this: "Act as an English Pronunciation Helper". Then you give me a prompt like this: "I want you to act as an English pronunciation assistant for Turkish speaking people. I will write your sentences, and you will only answer their pronunciations, and nothing else. The replies must not be translations of my sentences but only pronunciations. Pronunciations should use Turkish Latin letters for phonetics. Do not write explanations on replies. My first sentence is "how the weather is in Istanbul?"." (You should adapt the sample prompt according to the title I gave. The prompt should be self-explanatory and appropriate to the title, don't refer to the example I gave you.). My first title is "Act as a Code Review Helper" (Give me prompt only)

Find the bug with this code: `` for (var i = O: i < 5: i++) { setTimeout(0) => console.log i), 1000) } ```

This code does not work, what are the mistakes ``` import spacy nlp = spacy.load('en_core_web_md') # Charger le modèle de langue anglaise word1 = "cat" word2 = "dog # Charger les vecteurs de mots pour les deux mots word1_vector = nlp(word1).vector word2_vector = nlp(word2).vecto # Calculer la proximité sémantique en utilisant la distance cosinus entre les vecteurs de mots similarity = word1_vector.dot(word2_vector) / (word1_vector.norm * word2_vector.norm) ```