Add topology calculation

app.py

@@ -1,10 +1,10 @@
 import streamlit as st
 import os
 import google.generativeai as genai
-GOOGLE_API_KEY= 'AIzaSyC0T2fN5Dga-6nkPc6HYV7-bDZskqgALX0' #os.getenv('GEMINI_API_KEY')
+GOOGLE_API_KEY= os.getenv('GEMINI_API_KEY')
 genai.configure(api_key=GOOGLE_API_KEY)
 model = genai.GenerativeModel(model_name = "gemini-pro")
-from utils import findTop3MoneyNeeds
+from utils import findTop3MoneyNeeds, findTop3Topologies
 
 
 # Create a banner using Markdown
@@ -24,6 +24,7 @@ st.markdown(
 
 selectedCity = st.selectbox("Please select the City and the Bank Product for Your Proposition.", ["CharlesTown", "Limburg"])
 selectedProduct = st.selectbox("Please select the Product", ["Current", "Mortage", "Credit Card", "Crypto"])
+subscriberTakeOut = st.text_area("Please enter your subscriber take out")
 moneyNeeds = st.text_area("Describe money needs of your target audience. For example do they spend a lot on education, healthcare, gym, eating out etc.")
 customerExperience = st.text_area("Describe the customer experience needs of your target audience.")
 sutainabilityNeeds = st.text_area("Describe the sutainability needs of your target audience.")
@@ -46,7 +47,7 @@ Question: what is the key demographic behaviour?
 Answer: They want connect on Social Media sites
 Question: Prime Money Attitudes?
 Answer: They want great deals and want to manage things independantly
-Question: Brand needs?
+Question: Brand needs?sss
 Answer: They want the brand to be fun and positive
 
 Analyse this proposition and score it on the below criteria based upon its popularity within the audience 'Living of today'
@@ -74,13 +75,20 @@ Only show the table and conclusion remarks if the proposition suits the target a
 {{0}}
 '''
 
+CharlesTownDemographic = '''CharlesTown city people are Living for today people mostly with a population of 10000. Out of this 65% are between the age of 18-25.'''
+LimburgTownDemographic = '''Limburg city people are young families people mostly with a population of 20000. Out of this 65% are between the age of 30-45. Most of them have kids aged between 0-15'''
+
+demographic = ''
 if selectedCity:
     if selectedCity == 'CharlesTown':
-        st.write('''{} city people are Living for today people mostly with a population of 10000. Out of this 65% are between the age of 18-25.'''.format(selectedCity))
+
+        st.write(CharlesTownDemographic)
+        demographic = CharlesTownDemographic
     
     if selectedCity == 'Limburg':
-        st.write('''{} city people are young families people mostly with a population of 20000. Out of this 65% are between the age of 30-45. Most of 
-        them have kids aged between 0-15'''.format(selectedCity))
+        st.write(LimburgTownDemographic)
+        demographic = LimburgTownDemographic
+
 if submit_button:
     proposal = '''Given proposal is for the city {} with product {}. The propsal is as below.
     {}'''
@@ -90,11 +98,19 @@ if submit_button:
     
     topMoneyNeeds, topMoneyNeedsDict = findTop3MoneyNeeds(moneyNeeds)
 
+    matchingTopologies, topologies = findTop3Topologies(proposal, demographic)
+
     response = model.generate_content([pre_prompt.format(proposal)])
     st.write("As per your money needs your product is mostly targeting the below spending patterns",)
     
     for idx, need in enumerate(topMoneyNeeds):
         st.write("{}. {}".format(idx+1, need))
+
+
+    st.write("As per your demographic and your proposition here are the three topologies you are targeting",)
+    
+    for idx, topology in enumerate(matchingTopologies):
+        st.write("{}. {}".format(idx+1, topology))
     
     #st.write(response.text)
 

utils.py

@@ -2,6 +2,7 @@ from db import fetch_db_rows_as_dicts
 import google.generativeai as genai
 import json
 import os
+import pandas as pd
 
 GOOGLE_API_KEY=os.getenv('GEMINI_API_KEY')
 genai.configure(api_key=GOOGLE_API_KEY)
@@ -109,28 +110,50 @@ def findTop3Needs(proposition, moneyNeeds):
     return obj['matches']
 
 
-def findTop3Topologies(proposition):
-    topologies, rows = fetch_db_rows_as_dicts('topologies.sqlite', 'topologies')
+def findTop3Topologies(proposition, demographic):
+
+    topologies = pd.read_csv('topologies_desc.csv',  encoding = "ISO-8859-1")
+
+    topologies = topologies.dropna(axis=1, how='all')
+    
+    topologyAttributes = topologies['Column1']
+    topologyNames = list(topologies.columns)
+    topologyNames.remove('Column1')
+
+    #print(" topologyNames = {} ", topologyNames)
+    
+    topologyDetails = {}
+
+    for name in topologyNames:
+        topologyDetails[name] = {}
+        for attribute in topologyAttributes:
+            topologyDetails[name][attribute] = topologies[name][pd.Index(topologies['Column1']).get_loc(attribute)]
+            
+    prompt = '''You have these listed topology names of a demographic in comma separated values below
+    {}
+
+    Now for each of these above topologies here are the details
+    {}
+
+    Now given a proposition details below
     
-    topologiesDict = transform_to_dict_of_dicts(topologies, rows)
-    print(topologiesDict)
-    # prompt = '''You have these listed needs of customers
-    # {}
+    {}
 
-    # Now given a proposition 
-    # "{}" 
+    and given a demographic details below
+
+    {}
     
-    # Find the best 3 strings out of the list which matches this proposition. Return output strictly only in json under a list called matches
-    # '''
+    Find the best 3 common strings out of the topology names which matches the proposition and the demographic the most. Return output strictly only in json under a list called matches
+    '''
 
-    # moneyNeedsPrompt = prompt.format(moneyNeedsString, proposition)
-    # response = model.generate_content([moneyNeedsPrompt])
-    # output = response.text
-    # output = output.replace('```json', '')
-    # output = output.replace('```', '')
-    # obj = load_json_from_string(output)
-    # print(obj)
-    # return obj['matches']
+    topologyPrompt = prompt.format(", ".join(topologyNames), str(topologyDetails), proposition, demographic)
+    response = model.generate_content([topologyPrompt])
+    output = response.text
+    output = output.replace('```json', '')
+    output = output.replace('```', '')
+    obj = load_json_from_string(output)
+    print(obj)
+    return obj['matches'], topologies
 
 
 def findTop3Needs(proposition, moneyNeeds):
@@ -156,7 +179,11 @@ def findTop3Needs(proposition, moneyNeeds):
     return obj['matches']
 
 
-#findTop3Topologies('We have a product for family people giving them discounts and low interest loans for home appliances. They can pay us back in small instalments over the course of 4 years')
+# findTop3Topologies('We have a product for family people giving them discounts and low interest loans for home appliances. They can pay us back in small instalments over the course of 4 years',
+#                    'CharlesTown city people are young families people mostly with a population of 20000. Out of this 65% are between the age of 30-45. Most of them have kids aged between 0-15')
+
 #findTop3MoneyNeeds('We have a product for family people giving them discounts and low interest loans for home appliances. They can pay us back in small instalments over the course of 4 years')
 
 #We provide a credit card which gives 10% discount on purchasing home appliances and also provides low interest rates based loans
+
+# subscriber take out