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apppa.py
56 lines (46 loc) · 1.89 KB
/
apppa.py
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from flask import Flask, request, render_template_string
import pandas as pd
from some_gpt_library import GPT # Placeholder, replace with actual GPT library import
app = Flask(__name__)
# Load CSV files into pandas DataFrames
df1 = pd.read_csv('path/to/csv1.csv')
df2 = pd.read_csv('path/to/csv2.csv')
@app.route('/', methods=['GET', 'POST'])
def index():
if request.method == 'POST':
# Fetch details from form dropdowns
merchant_name = request.form.get('merchant_name')
peer_group_name = request.form.get('peer_group_name')
region = request.form.get('region')
kpi = request.form.get('kpi')
# Perform DA queries based on form values to get "ABC" and "XYZ"
abc, xyz = perform_da_queries(merchant_name, peer_group_name, region, kpi)
# Call GPT functions
gpt_result1 = gpt_call_function1(abc, xyz)
gpt_result2 = gpt_call_function2(abc, xyz)
return f'''
<p>ABC: {abc}, XYZ: {xyz}</p>
<p>GPT Result 1: {gpt_result1}</p>
<p>GPT Result 2: {gpt_result2}</p>
'''
else:
# Render the form on GET request
return render_template_string(open('index.html').read()) # Ensure 'index.html' is in the correct path
def perform_da_queries(merchant_name, peer_group_name, region, kpi):
# Placeholder for DA queries - replace with your actual logic
# Example:
abc = "Result for ABC based on input"
xyz = "Result for XYZ based on input"
return abc, xyz
def gpt_call_function1(abc, xyz):
# Placeholder for a GPT call - replace with actual implementation
# Example:
result = "GPT output based on ABC and XYZ"
return result
def gpt_call_function2(abc, xyz):
# Another placeholder for a different GPT call
# Example:
result = "Different GPT output based on ABC and XYZ"
return result
if __name__ == '__main__':
app.run(debug=True)