Vish2005 commited on
Commit
369efb7
·
1 Parent(s): 0126820

Update app.py

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Files changed (1) hide show
  1. app.py +0 -97
app.py CHANGED
@@ -30,7 +30,6 @@ Our main method first asks the user for their openai key. Then we have some test
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  #imports
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  import pandas as pd
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- from textblob import TextBlob
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  import spacy
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  import tensorflow_hub as hub
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  from scipy.spatial import distance
@@ -51,11 +50,6 @@ customer = pd.read_csv('customer_data.csv')
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  order = pd.read_csv('order_data.csv')
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  service = pd.read_csv('cust_service_data.csv')
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- """# Spelling correction"""
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-
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- def correctSpelling(sentence):
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- return str(TextBlob(sentence).correct())
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-
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  """# Entity Extraction"""
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  # extract entities, label, label definition from natural language questions and append to dataframe
@@ -144,97 +138,6 @@ def query_to_SQL_to_MongoDB(query, key, organization):
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  SQL = response['choices'][0]['text'] # extract the outputted SQL Query
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  return complex_SQL_to_MongoDB(SQL)
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- #Example:
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-
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- '''
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- db.Customer.aggregate(
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-
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- {
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-
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- $lookup:
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-
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- {
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-
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- from: "Orders",
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- localField: "cust_id",
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- foreignField: "cust_id",
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- as: "Customer"
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-
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- }
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-
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- },
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-
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- {
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-
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- $group:
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-
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- {
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-
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- _id: "cust_name",
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- count: {$count : {}}
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-
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- }
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-
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- },
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-
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- {
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-
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- $sort:{count : -1}
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-
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- },
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-
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- {
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-
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- $limit: 1
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-
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- }
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-
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- )
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-
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-
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- '''
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-
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- '''
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- db.Customer.aggregate(
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- {
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- $lookup:
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- {
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- from : "Orders",
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- localField: "cust_id",
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- foreignField: "cust_id",
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- as: "Customer"
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-
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- }
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- },
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- {
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- $lookup:
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- {
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- from : "Driver",
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- localField: "driver_id",
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- foreignField: "driver_id",
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- as: "Customer"
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- }
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- },
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-
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- {
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- $match:
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- {
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-
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- $group:
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- {
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- _id: "c.cust_name",
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- count: {$count: {order_id}
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- }
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- }
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-
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- },
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- {
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- $sort: {count : -1}
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- },
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- { $limit : 1 }
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-
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- )
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- '''
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  keywords = {'INNER', 'FROM', 'WHERE', 'GROUP', 'BY', 'ON', 'SELECT', 'BETWEEN', 'LIMIT', 'AND', 'ORDER'}
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  #imports
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  import pandas as pd
 
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  import spacy
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  import tensorflow_hub as hub
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  from scipy.spatial import distance
 
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  order = pd.read_csv('order_data.csv')
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  service = pd.read_csv('cust_service_data.csv')
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  """# Entity Extraction"""
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  # extract entities, label, label definition from natural language questions and append to dataframe
 
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  SQL = response['choices'][0]['text'] # extract the outputted SQL Query
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  return complex_SQL_to_MongoDB(SQL)
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  keywords = {'INNER', 'FROM', 'WHERE', 'GROUP', 'BY', 'ON', 'SELECT', 'BETWEEN', 'LIMIT', 'AND', 'ORDER'}
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