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Genome06
Implement backend and frontend for Tech-Support AI, including intent classification and response generation
826af0d | import pandas as pd | |
| class KnowledgeBase: | |
| def __init__(self, data_source): | |
| """ | |
| data_source can be a local path (data/dataset.csv) or a raw URL from GitHub. | |
| """ | |
| print(f"Loading Knowledge Base from {data_source}...") | |
| self.df = pd.read_csv(data_source) | |
| # We only keep unique intent-response pairs to avoid redundancy | |
| self.kb = self.df[['intent', 'response']].drop_duplicates(subset=['intent']) | |
| print("✅ Knowledge Base loaded!") | |
| def get_base_response(self, intent): | |
| # Looking for the response corresponding to the predicted intent | |
| result = self.kb[self.kb['intent'] == intent]['response'] | |
| if not result.empty: | |
| return result.values[0] | |
| return "Sorry, no specific procedure found for this request." |