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Base

For the given query including a meal description, calculate the amount of carbohydrates in grams. If the serving size of any item in the
meal is not specified, assume it is a single standard serving based on common nutritional guidelines (e.g., USDA).
Respond with a dictionary object containing the total carbohydrates in grams as follows:
{{"total_carbohydrates": total grams of carbohydrates for the serving}}
For the total carbohydrates, respond with just the numeric amount of carbohydrates without extra text. If you don't know the answer,
respond with:
{{"total_carbohydrates": -1}}.

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# requires-python = ">=3.13"
# /// script
# dependencies = [
# "pydantic",
# "feedparser",
# "tqdm",
# "litellm",
# ]
# ///

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# /// script
# dependencies = [
#   "transformers",
#   "torch",
#   "accelerate",
#   "matplotlib",
# ]
# ///
# Notes: Mostly stolen from https://github.com/open-thought/tiny-grpo
# Run with uv run gpt_grpo.py 

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• Most things by Jason Liu are great
• Arcturus labs has some good writing on the topic
• Simon Willison's entries are always worth a skim/read
• LLM Engineer's handbook from Paul Iusztin and Maxime Labonne
• I'm currently reading relevant search
• Handling vision in RAG
• This talk by Ben Clavié
• Most of these talks from Parlance labs
• Evaluate rag with RAGAS
• This blog post by Goku Mohandas

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import streamlit as st
from litellm import completion, stream_chunk_builder
from loguru import logger
import json
import plotly.express as px
from enum import Enum

MODEL = "gpt-4o-mini"

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import pandas


def remove_bad_cols(dataframe):
    return df.drop(
        labels=df.columns.difference(["passengerid", "price_paid"]), axis=1
    )


def add_inflation_to_price(dataframe):

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delivery-85367.icu                                                             
% IANA WHOIS server
% for more information on IANA, visit http://www.iana.org
% This query returned 1 object

refer:        whois.nic.icu

domain:       ICU

organisation: Shortdot SA

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// Variables used by Scriptable.
// These must be at the very top of the file. Do not edit.
// icon-color: deep-green; icon-glyph: user-md;
// change "country" to a value from https://coronavirus-19-api.herokuapp.com/countries/
// teste
const country = "Portugal"
const url = `https://coronavirus-19-api.herokuapp.com/countries/${country}`
const req = new Request(url)
const res = await req.loadJSON()

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{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        27378,
        128
      ],
      "tensorPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128.tsv",
      "metadataPath": "https://opera-nora-vos.dataverz.com/upload-json/upload/corona_128_metadata.tsv"