Reddit Sentiment Analysis Y4 v3.0.0
|
Classes | |
class | SearchHistory |
Functions | |
get_utc_plus_one () | |
fetch_comments_from_posts (search_term, subreddit='all', sort_order='default', time_filter='all', comment_sort_order='top', max_comments=1000, max_comments_per_post=75) | |
preprocess_text (text) | |
predict_sentiment (text) | |
interpret_sentiment (positive_percentage) | |
convert_to_html_list (text) | |
prepare_comments_for_gpt (comments, max_tokens=16385, prompt_type='default') | |
chatgpt_sentiment_analysis (comments, prompt_type) | |
save_sentiment_pie_chart (positive_percentage, image_path) | |
save_word_cloud (comments, image_path) | |
fetch_comments (search_term, subreddit='all', limit=5) | |
home () | |
generate_prompt () | |
validate_search_term () | |
landing () | |
history () | |
Variables | |
app = Flask(__name__) | |
secret_key | |
db = SQLAlchemy(app) | |
model = DistilBertForSequenceClassification.from_pretrained('C:\\Users\\35387\\Desktop\\app1\\distilbert_sentiment_analysis') | |
tokenizer = DistilBertTokenizerFast.from_pretrained('C:\\Users\\35387\\Desktop\\app1\\distilbert_sentiment_analysis_tokenizer') | |
debug | |
app.fetch_comments | ( | search_term, | |
subreddit = 'all', | |||
limit = 5 ) |
app.fetch_comments_from_posts | ( | search_term, | |
subreddit = 'all', | |||
sort_order = 'default', | |||
time_filter = 'all', | |||
comment_sort_order = 'top', | |||
max_comments = 1000, | |||
max_comments_per_post = 75 ) |
app.prepare_comments_for_gpt | ( | comments, | |
max_tokens = 16385, | |||
prompt_type = 'default' ) |
app.save_sentiment_pie_chart | ( | positive_percentage, | |
image_path ) |
app.model = DistilBertForSequenceClassification.from_pretrained('C:\\Users\\35387\\Desktop\\app1\\distilbert_sentiment_analysis') |
app.reddit |