midrees2806 commited on
Commit
db74279
·
verified ·
1 Parent(s): 337f6f4

Update rag.py

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Files changed (1) hide show
  1. rag.py +7 -16
rag.py CHANGED
@@ -7,7 +7,6 @@ import pandas as pd
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  from datasets import load_dataset, Dataset
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  from dotenv import load_dotenv
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  import random
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- import glob
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  # Load environment variables
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  load_dotenv()
@@ -37,23 +36,15 @@ UNMATCHED_RESPONSES = [
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  "We appreciate your question. It has been forwarded for further processing. Until it’s available here, feel free to visit the official UE website or use the contact options:\n\n📞 +92-42-99262231-33\n✉️ [email protected]\n🌐 https://ue.edu.pk"
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  ]
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- # Load multiple JSON datasets
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- dataset = []
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  try:
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- json_files = glob.glob('datasets/*.json')
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- for file_path in json_files:
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- with open(file_path, 'r', encoding='utf-8') as f:
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- data = json.load(f)
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- if isinstance(data, list):
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- for item in data:
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- if isinstance(item, dict) and 'Question' in item and 'Answer' in item:
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- dataset.append(item)
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- else:
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- print(f"Invalid entry in {file_path}: {item}")
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- else:
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- print(f"File {file_path} does not contain a list.")
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  except Exception as e:
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- print(f"Error loading datasets: {e}")
 
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  # Precompute embeddings
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  dataset_questions = [item.get("Question", "").lower().strip() for item in dataset]
 
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  from datasets import load_dataset, Dataset
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  from dotenv import load_dotenv
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  import random
 
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  # Load environment variables
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  load_dotenv()
 
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  "We appreciate your question. It has been forwarded for further processing. Until it’s available here, feel free to visit the official UE website or use the contact options:\n\n📞 +92-42-99262231-33\n✉️ [email protected]\n🌐 https://ue.edu.pk"
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  ]
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+ # Load local dataset
 
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  try:
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+ with open('dataset.json', 'r') as f:
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+ dataset = json.load(f)
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+ if not all(isinstance(item, dict) and 'Question' in item and 'Answer' in item for item in dataset):
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+ raise ValueError("Invalid dataset structure")
 
 
 
 
 
 
 
 
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  except Exception as e:
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+ print(f"Error loading dataset: {e}")
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+ dataset = []
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  # Precompute embeddings
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  dataset_questions = [item.get("Question", "").lower().strip() for item in dataset]