File size: 1,709 Bytes
ebeaa49 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
{
"model_type": "custom",
"model_name": "Product-Review-Grader",
"description": "A model that analyzes product reviews, generates summaries, extracts pros and cons, and assigns grades based on sentiment.",
"schema": {
"preprocessing": {
"stopwords": [
"the", "is", "in", "at", "on", "a", "an", "and", "or", "for", "to", "of", "with", "that", "by", "it"
],
"text_cleaning": "removes numbers, punctuation, and extra spaces, converts to lowercase"
},
"task": {
"name": "sentiment_analysis_and_grading",
"description": "Generates sentiment analysis and grades for product reviews using a fine-tuned Gemini model.",
"input": {
"review_text": "A string representing a product review."
},
"output": {
"sentiment_label": ["POSITIVE", "NEUTRAL", "NEGATIVE"],
"grade": "A float number from 1 to 5 representing the grade."
}
},
"summarization": {
"input": "Text from multiple reviews combined into a single string.",
"output": "A summarized string of the main points of the reviews."
},
"pros_and_cons_extraction": {
"input": "Text from multiple reviews combined into a single string.",
"output": {
"pros": "A string with pros extracted from the text.",
"cons": "A string with cons extracted from the text."
}
},
"parameters": {
"min_raters": 35,
"weighting_formula": "Weighted average combining product rating and global average rating."
}
},
"dependencies": {
"libraries": [
"streamlit",
"pandas",
"google-generativeai",
"os",
"json",
"re"
],
"python_version": "3.10"
}
}
|