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import streamlit as st | |
import datasets | |
from datasets import load_dataset | |
import pandas as pd | |
from streamlit.components.v1 import html | |
from streamlit import markdown | |
import re | |
import os | |
import time | |
import json | |
st.title('StackOverflow Question Demo') | |
library = st.radio('Select a library', ('numpy', 'tensorflow+ pytorch', 'scipy', 'scikit-learn', 'pandas')) | |
question_path = './{}.txt'.format(library) | |
# loading stackoverflow questions. | |
# using huggingface load_dataset function. | |
# not done yet | |
#@st.cache | |
#def load_data(path): | |
# return load_dataset('text', data_files = path, cache_dir = './data') | |
intro = {'numpy': ''' | |
#### Setup | |
temperature = 0.7, topP = 0.95, turns = 10 | |
#### Prompt: | |
Problem: | |
…… | |
A: | |
<code> | |
…… | |
###BEGIN SOLUTION | |
[insert] | |
###END SOLUTION | |
… | |
</code> | |
A0: change example | |
A1: change logits(decimal places, array, etc) | |
A2: change output type (array -> dict, etc) | |
A3: analogy | |
A4: dimension(index) involved | |
A5: inverted operation | |
A6: order | |
A7: ±condition/operation | |
combinations involved, only show the highest level. | |
''', | |
'scipy': | |
''' | |
#### Setup | |
temperature = 0.7, topP = 0.95, 10 attempts. | |
#### Prompt: | |
Problem: | |
…… | |
A: | |
<code> | |
…… | |
###BEGIN SOLUTION | |
[insert] | |
###END SOLUTION | |
… | |
</code> | |
Origin: original question from stackoverflow(might be specified or simplified) | |
Function: Let model fill in a function. | |
A1: paraphrasing, seems not effective to Codex. | |
A2: change example | |
A3: analogy(min->max, column->row, etc) | |
A6: result type constraint. | |
A7: ±condition/operation | |
''' | |
} | |
hyper_links = {'numpy':'https://docs.google.com/document/d/1WjMXfe-zV5VvKfbUnyxauTBciPB1Bp82baaIrG3XffM/edit#', | |
'scipy': 'https://docs.google.com/document/d/1u_rGiLrLbH9Ac_OueTbmDFyLlWOtB0U56Ertp8ggW1Q/edit'} | |
st.write(intro[library]) | |
st.write('If the demo seems a little confusing, feel free to check the document.', hyper_links[library]) | |
dataset = [] | |
#dataset = load_data(question_path) | |
with open(question_path) as f: | |
lines = f.readlines() | |
question = '' | |
temp = {} | |
tag = '' | |
for line in lines: | |
if line == 'Origin:\n' or line == 'Function:\n' or re.match(r'A\d:\n', line): | |
if not tag: | |
tag = line[:-2] | |
else: | |
temp[tag] = question | |
question = '' | |
tag = line[:-2] | |
elif re.match(r'\d*\.\n', line): | |
if tag: | |
temp[tag] = question | |
dataset.append(temp) | |
question = '' | |
tag = '' | |
temp = {} | |
else: | |
if tag: | |
question += line + '\n' | |
temp[tag] = question | |
dataset.append(temp) | |
# Select index | |
number = st.number_input("Insert a index: range from", | |
min_value = 0, max_value = len(dataset) - 1) | |
st.write('The current index is ', number) | |
data_index = int(number) | |
# Selece modification | |
options = tuple(dataset[data_index].keys()) | |
modification = st.radio('Modification:', | |
options = options | |
) | |
st.write(dataset[data_index][modification]) | |