- 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" |
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{ | |
"embeddings": [ | |
{ | |
"tensorName": "My tensor", | |
"tensorShape": [ | |
1000, | |
50 | |
], | |
"tensorPath": "https://gist.githubusercontent.com/duarteocarmo/d15f3d8a062640649e0dbd280eb62e0b/raw/9fbabadefaa7d6b2a1a9792f8c3dbe0e74828b53/corona_128.tsv" | |
} |
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0.265047 | 0.402412 | 0.04394 | 0.232379 | -0.178385 | -0.251961 | 0.033933 | 0.004331000000000001 | 0.269349 | 0.276781 | 0.62878 | 0.038244 | 0.018466 | 0.277584 | 0.291458 | 0.226978 | -0.308167 | 0.21948499999999999 | -0.21985100000000002 | -0.056057 | -0.211689 | 0.141289 | 0.465743 | -0.23253800000000002 | -0.380131 | 0.171227 | 0.410419 | 0.256002 | -0.5630649999999999 | 0.268669 | 0.175975 | 0.31272 | 0.126661 | 0.24339299999999997 | -0.068918 | 0.518714 | 0.3942 | 0.013861000000000002 | -0.24618299999999999 | 0.006409999999999999 | -0.347699 | 0.708418 | 0.16986099999999998 | 0.181118 | 0.30225 | 0.41640900000000003 | 0.15104700000000001 | 0.227142 | 0.083771 | -0.031074 | -0.435808 | -0.18545799999999998 | -0.132331 | 0.30448600000000003 | 0.121923 | -0.318643 | -0.02396 | 0.045665 | -0.094992 | 0.46035 | -0.35325700000000004 | 0.138192 | 0.28922 | -0.586064 | -0.11838699999999999 | -0.201355 | 0.14893 | -0.661425 | 0.757174 | 0.35458 | 0.102619 | -0.017088 | -0.057553999999999994 | -0.238733 | 0.22670900000000002 | 0.120297 | 0.024797 | 0.125356 | -0.131823 | -0.102591 | 0.128919 | -0.331512 | 0.396284 | -0.658933 | -0.017664 | 0.464 | 0.087157 | -0.170877 | -0.331757 | 0. |
---|
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import tweepy | |
import datetime | |
NO_ACTIVITY_FOR = 30 | |
UNFOLLOW_COUNTER = 0 | |
PROCESSED_USERS = 0 | |
# get these at: https://developer.twitter.com/en/apps | |
access_token = "" | |
access_token_secret = "" |
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import subprocess | |
import sys | |
import papermill as papermill | |
REMOTE_FOLDER = "your cloud folder name" | |
LOCAL_FOLDER = "your local folder name" | |
TEMPLATE_NOTEBOOK = "template_notebook.ipynb" | |
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