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quotes = { "Arthur Ashe": "Start where you are, Use what you have, Do what you can.", "Steve Jobs": "Don’t watch the clock; do what it does. Keep going.", "Sam Levenson": "Don’t watch the clock; do what it does. Keep going.", " Robert Collier": "Success is the sum of small efforts, repeated day in and day out.", "Nelson Mandela": "It always seems impossible until it’s done.", "Mahatma Gandhi": "The future depends on what you do today.", "Zig Ziglar": "You don’t have to be great to start, but you have to start to be great.", "Dave": "Discipline is doing what needs to be done, even if you don’t want to do it.", "Suzy Kassem": "Doubt kills more dreams than failure ever will.", "Pablo Picasso": "Action is the foundational key to all success." } This is the func

When I need to pass some variables to an async move block, and these variables will still be used in the current scope, I have to rename these variables. May I have a better way to handle this situation? Below is a sample code: // conference_id and participants will be used in the next codes, so I can't directly move them to the async block, I have to rename them with the prefix '_' let _conference_id = conference_id.to_owned(); let _participants = participants.clone(); tokio::spawn(async move { let participants = _participants .read() .await .get(&_conference_id) .ok_or(MyError::new(500, "failed to get participants")); });

I'm trying to convert this list of polygons into a shapefile. I'd like each polygon to be its own feature in the shapefile. Everything I've tried has only exported one single polygon. Here is a google drive link to my list of polygons: https://drive.google.com/drive/folders/1T6IhI9f_o_CvoYiamgjFDmF37d6Vx-VA?usp=drive_link I'm not 100% sure what the polygons will look like, as I wrote a code to create them and need to plot them out to see if I have the correct output of polygons. Here is one example of code that leads to a shapefile with a single polygon in the output: # convert list to to sf object all_buffers_df <- as.data.frame(all_buffers) all_buffers_sf <- st_sf(all_buffers_df) # Write the sf object to a shapefile st_write(all_buffers_sf, output_shapefile) Thanks in advance.

I successfully uploaded my data to Google Drive via the API and set the permissions so that the image can be viewed by anyone with the link. However, when I try to display the image, it crashes. I've been trying for several days, but the result is still nothing. import { google } from "googleapis"; import { NextRequest, NextResponse } from "next/server"; import { Readable } from "stream"; const GOOGLE_SHEET_ID = process.env.GOOGLE_SHEET_ID!; const GOOGLE_CLIENT_EMAIL = process.env.GOOGLE_CLIENT_EMAIL!; const GOOGLE_PRIVATE_KEY = process.env.GOOGLE_PRIVATE_KEY!.replace( /\\n/g, "\n" ); const GOOGLE_DRIVE_FOLDER_ID = process.env.GOOGLE_DRIVE_FOLDER_ID!; export async function POST(req: NextRequest) { try { const formData = await req.formData(); const name = formData.get("name") as string; const email = formData.get("email") as string; const message = formData.get("message") as s

I'm new to python, and trying to figure out how to have it do some division in the end of my program. Eariler in the program, it asks the user for a number that can be divided by 20 as seen here: if int(Integer) % 20 == 0: True I then want later to have it take that number and divide it by 20. I figured I could do it using the following command: print(int(Integer // 20) However, I then get the following error message: TypeError: unsupported operand type(s) for //: 'str' and 'int' Is there another command I can use to have it do that division at the end and give me the output?

I have created a fastAPI web interface to a local RAG powered question answer system. I have a local vector database populated with proprietary information. I first take the user question from the webpage and use it to retrieve results from chroma DB. Then I feed those results in as the context of a prompt to a local instance of mistral 7B. I would like to enforce a specific format of response from the LLM. What I have read about outlines sounds great, but I have not been able to get it to work in the context of streaming the output from the LLM. Has anyone had success with this? I’m currently using pydantic to specify an output format to fastAPI and validate the LLM response through an expected JSON object structure. This is an improvement, but not all the way to the strict enforcement that outlines provides using regular expressions.

I'm using Vercel's AI SDK to generate streamed responses from various providers and models. While the streamText function allows setting maxTokens for output, I’m unsure how to control or limit the input tokens being sent. A few things I'm trying to figure out: Is there a built-in way to restrict input token count? Do I need to manually count tokens, especially when attaching previous conversation context or file content (PDFs, images, audio)? Does file content count toward input token limits, and how can I manage that efficiently? Some models have high token limits, but I want to control input usage to avoid unnecessary costs. Any tips or best practices would be really helpful!

I'm building my web app with Next.JS and React JS. I'm currently using middleware for some tasks like checking user's authentication while accessing the URL and refreshing tokens if needed. However, I notice one phenomenon that could negatively affect user experience while using the app: The thing is, let's say I click the button to navigate to another page, the app stay "frozen" for half of second or more (i guess it the time the middleware handle the stuffs since I already compiled that page previously). This makes me feel annoyed as an user I would like to ask for any advice for handling this issue? I prefer to flow where it go to the new route and there is a loading state before rendering. Please help me.

I am using Apache 2.4.37 on a fairly simple server that is just serving images. The human client that requested this service be setup with case insensitivity. Initially I implemented mod_speling like this: <IfModule mod_speling.c> CheckSpelling On CheckCaseOnly On </IfModule> And it seemed to work great! But we hit a snag. The crappy app (nuff said) this service was setup for chokes on 301 redirects and can’t be adjusted. So what I am looking for is a way via mod_rewrite to affect case insensitivity. Initially, I came across this Server Fault answer was that seemed ideal with his RewriteRule: RewriteEngine On RewriteMap lc int:tolower RewriteRule ^(.*) ${lc:$1} But it’s not appropriate in my setup because we use images with uppercase filenames and lower

I have a problem with implementing CustomUser in a Django App. My project is called "VendorManagement". My app is "VMP". In settings, I have AUTH_USER_MODEL = 'VMP.CustomUser' set. Here is my CustomUser Model: from django.db import models from django.conf import settings from django.contrib.auth.models import User, AbstractUser from django.utils.timezone import timedelta, now from django.core.exceptions import ValidationError # File validation function def validate_file_type(value): allowed_types = ["application/pdf", "application/msword", "application/vnd.openxmlformats-officedocument.wordprocessingml.document"] if value.content_type not in allowed_types: raise ValidationError("Only PDF and Word documents are allowed.") class CustomUser(AbstractUser): ROLE_CHOICES = [ ('vendor', 'Vendor'), ('customer', 'Customer'), ('admin