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nileshhanotia
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Parent(s):
e266142
Create sql_generator.py
Browse files- sql_generator.py +67 -0
sql_generator.py
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import requests
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from config import ACCESS_TOKEN, SHOP_NAME
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class SQLGenerator:
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def __init__(self):
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self.model_name = "premai-io/prem-1B-SQL"
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self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
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self.model = AutoModelForCausalLM.from_pretrained(self.model_name)
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def generate_query(self, natural_language_query):
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schema_info = """
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CREATE TABLE products (
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id DECIMAL(8,2) PRIMARY KEY,
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title VARCHAR(255),
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body_html VARCHAR(255),
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vendor VARCHAR(255),
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product_type VARCHAR(255),
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created_at VARCHAR(255),
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handle VARCHAR(255),
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updated_at DATE,
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published_at VARCHAR(255),
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template_suffix VARCHAR(255),
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published_scope VARCHAR(255),
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tags VARCHAR(255),
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status VARCHAR(255),
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admin_graphql_api_id DECIMAL(8,2),
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variants VARCHAR(255),
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options VARCHAR(255),
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images VARCHAR(255),
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image VARCHAR(255)
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);
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"""
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prompt = f"""### Task: Generate a SQL query to answer the following question.
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### Database Schema:
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{schema_info}
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### Question: {natural_language_query}
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### SQL Query:"""
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inputs = self.tokenizer(prompt, return_tensors="pt", add_special_tokens=False).to(self.model.device)
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outputs = self.model.generate(
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inputs["input_ids"],
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max_length=256,
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do_sample=False,
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num_return_sequences=1,
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eos_token_id=self.tokenizer.eos_token_id,
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pad_token_id=self.tokenizer.pad_token_id
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)
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return self.tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
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def fetch_shopify_data(self, endpoint):
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headers = {
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'X-Shopify-Access-Token': ACCESS_TOKEN,
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'Content-Type': 'application/json'
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}
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url = f"https://{SHOP_NAME}/admin/api/2023-10/{endpoint}.json"
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response = requests.get(url, headers=headers)
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if response.status_code == 200:
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return response.json()
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else:
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print(f"Error fetching {endpoint}: {response.status_code} - {response.text}")
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return None
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