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Update app.py
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app.py
CHANGED
@@ -3,8 +3,8 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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from datasets import load_dataset
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from difflib import get_close_matches
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# Load the
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# Load tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
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@@ -17,7 +17,7 @@ def find_closest_match(query, dataset):
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def generate_sql_from_user_input(query):
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# Find the closest match in the dataset
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matched_query = find_closest_match(query,
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if not matched_query:
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return "No close match found in the dataset.", ""
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@@ -33,8 +33,8 @@ interface = gr.Interface(
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fn=generate_sql_from_user_input,
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inputs=gr.Textbox(label="Enter your natural language query"),
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outputs=[gr.Textbox(label="Matched Query from Dataset"), gr.Textbox(label="Generated SQL Query")],
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title="NL to SQL with T5 using
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description="This model finds the closest match in the
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)
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# Launch the app
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from datasets import load_dataset
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from difflib import get_close_matches
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# Load the Spider dataset
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spider_dataset = load_dataset("spider", split='train[:100]') # Increase the number of examples for better matching
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# Load tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-wikiSQL")
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def generate_sql_from_user_input(query):
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# Find the closest match in the dataset
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matched_query = find_closest_match(query, spider_dataset)
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if not matched_query:
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return "No close match found in the dataset.", ""
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fn=generate_sql_from_user_input,
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inputs=gr.Textbox(label="Enter your natural language query"),
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outputs=[gr.Textbox(label="Matched Query from Dataset"), gr.Textbox(label="Generated SQL Query")],
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title="NL to SQL with T5 using Spider Dataset",
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description="This model finds the closest match in the Spider dataset for your query and generates the corresponding SQL."
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)
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# Launch the app
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