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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from categories.fluency import *"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sentence: caveman speak weird few word good\n"
]
}
],
"source": [
"s = input(\"Enter a sentence: \") # Prompt the user to enter a sentence\n",
"\n",
"if s == \"\":\n",
" s = \"The cat sat the quickly up apples banana.\"\n",
"\n",
"print(\"Sentence:\", s) # Print the input sentence\n",
"\n",
"err = grammar_errors(s) # Call the function to execute the grammar error checking\n",
"flu = pseudo_perplexity(s, threshold=3.25) # Call the function to execute the fluency checking"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This sentence does not start with an uppercase letter.: caveman speak\n",
"Perplexity 4.2750282429106585 over threshold 3.25: caveman\n",
"Perplexity 5.191700905668536 over threshold 3.25: few\n",
"Perplexity 3.8370066187600944 over threshold 3.25: good\n"
]
}
],
"source": [
"combined_err = err[\"errors\"] + flu[\"errors\"] # Combine the error counts from both functions\n",
"\n",
"for e in combined_err:\n",
" substr = \" \".join(s.split(\" \")[e[\"start\"]:e[\"end\"]+1])\n",
" print(f\"{e['message']}: {substr}\") # Print the error messages\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"100.0 80.14\n",
"Fluency Score: 90.07\n"
]
}
],
"source": [
"fluency_score = 0.5 * err[\"score\"] + 0.5 * flu[\"score\"] # Calculate the fluency score\n",
"print(err[\"score\"], flu[\"score\"]) # Print the individual scores\n",
"print(\"Fluency Score:\", fluency_score) # Print the fluency score"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "teach-bs",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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