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(venv) john@Johns-MacBook-Air agent_dialog % python -i AgentDialog.py | |
John: Hello Robin, I was thinking about going hiking today. Are you interested in joining me? | |
Robin: Hello John, hiking sounds like a great idea! I was actually hoping to go biking today, but a hike could be a nice compromise. Where were you thinking of hiking? | |
John: That's great to hear, Robin! I was thinking of hitting the trails at the Green Mountain Forest. There are some fantastic views and the terrain is just right for a good day's hike. How does that sound to you? | |
Robin: Green Mountain Forest sounds wonderful, John! I've heard the trails there are quite scenic. And you're right, it seems like the perfect place for a good day's hike. Let's do it! What time were you thinking of starting? | |
John: I'm glad you're on board, Robin! How about we start early to make the most of the day? Meeting at 8:00 AM would give us plenty of time to enjoy the trails. Does that work for you? | |
Robin: That sounds like a plan, John! Meeting at 8:00 AM works for |
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import aiohttp | |
import asyncio | |
http_status_codes = { | |
100: "Continue", | |
101: "Switching Protocols", | |
102: "Processing", | |
200: "OK", | |
201: "Created", | |
202: "Accepted", |
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from jinja2 import Template | |
from jinja2 import Environment, meta | |
class Question: | |
"""This class reprsents a question sent to an LLM (or human). | |
It uses the jinja2 templating language to generate the prompt. | |
For details on jinja2: https://jinja.palletsprojects.com/en/3.0.x/ | |
This templating language gives us lots of flexibility in how we ask questions. | |
""" | |
def __init__(self, template_string): |
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# Find all your R files & get just the package names, uniquely | |
find ../analysis/ -name *R -print0 | xargs -0 grep -h 'library*' | sed 's/library//g' | sed 's/#//g' | sed 's/ //g' | sort | uniq|\ | |
sed 's/(//g' | sed 's/)//g' > package_list.txt | |
# Install each package | |
cat package_list.txt | xargs -I {} Rscript -e 'install.packages("{}")' |
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#!/usr/bin/Rscript --vanilla | |
suppressPackageStartupMessages({ | |
library(magrittr) | |
library(dplyr) | |
library(foreign) | |
library(plm) | |
library(reshape2) | |
library(stargazer) | |
library(ggplot2) |
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project_name = hot_towel | |
ts := $(shell /bin/date "+%Y-%m-%d---%H-%M-%S") | |
params = | |
# DONE | |
params += params_exp_details.tex | |
params_exp_details.tex: ../analysis/params_exp_details.R | |
cd ../analysis && ./params_exp_details.R |
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library(XML) | |
library(ggplot2) | |
df <- readHTMLTable("http://projects.dailycal.org/paychecker/departments/")[[1]] | |
DeMoney <- function(x) as.numeric(gsub(",", "", gsub("\\$", "", as.character(x)))) | |
money.columns <- c("All", "Professor", "Associate professor", "Assistant professor", | |
"Lecturer") |
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library(geofacet) # my forked version | |
library(ggplot2) | |
library(jsonlite) | |
library(ggrepel) | |
# grab top cities | |
cities <- fromJSON("https://gist.githubusercontent.com/Miserlou/c5cd8364bf9b2420bb29/raw/2bf258763cdddd704f8ffd3ea9a3e81d25e2c6f6/cities.json") | |
n <- 50 | |
x <- cities$longitude[1:n] |
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library(lfe) | |
library(stargazer) | |
set.seed(6152011) | |
# Number of cities | |
L <- 1000 | |
# Number of industries | |
K <- 3 |
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SimExperiment <- function(num.groups, sample.size, beta, randomize.by.group = FALSE){ | |
"Simulate running an analysis of the experiment with linear regression" | |
df <- CreateClusteredData(num.groups, sample.size, beta, randomize.by.group = randomize.by.group) | |
m <- lm(y ~ trt, data = df) | |
c(as.numeric(coef(m)[2]), as.numeric(sqrt(diag(vcov(m))[2]))) | |
} |
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