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Update app_utils.py
Browse files- app_utils.py +9 -8
app_utils.py
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@@ -4,6 +4,10 @@ Financial Chatbot Utilities
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Core functionality for RAG-based financial chatbot
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"""
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import os
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import re
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import nltk
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@@ -26,20 +30,17 @@ from sentence_transformers import CrossEncoder
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from sklearn.metrics.pairwise import cosine_similarity
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# Initialize NLTK stopwords
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nltk.download('stopwords')
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stop_words = set(stopwords.words('english'))
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# mount
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import sys
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sys.path.append('/mount/src/gen_ai_dev')
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# Configuration
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DATA_PATH = "./Infy financial report/"
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DATA_FILES = ["INFY_2022_2023.pdf", "INFY_2023_2024.pdf"]
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EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
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LLM_MODEL = "gpt2" # Or "distilgpt2" # Or "HuggingFaceH4/zephyr-7b-beta" or "microsoft/phi-2"
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# Environment settings
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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Core functionality for RAG-based financial chatbot
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"""
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# mount
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import sys
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sys.path.append('/home/user/app')
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import os
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import re
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import nltk
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from sklearn.metrics.pairwise import cosine_similarity
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# Initialize NLTK stopwords
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# nltk.download('stopwords')
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# stop_words = set(stopwords.words('english'))
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nltk.data.path.append('./nltk_data') # Point to local NLTK data
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stop_words = set(nltk.corpus.stopwords.words('english'))
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# Configuration
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DATA_PATH = "./Infy financial report/"
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DATA_FILES = ["INFY_2022_2023.pdf", "INFY_2023_2024.pdf"]
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EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
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LLM_MODEL = "microsoft/phi-1.5" # or "gpt2" # Or "distilgpt2" # Or "HuggingFaceH4/zephyr-7b-beta" or "microsoft/phi-2"
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# Environment settings
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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