feature: Minor edits, transition to 4o

app.py

@@ -1,9 +1,6 @@
 import streamlit as st
 from annotated_text import annotated_text
 import pymongo
-
-# import language_tool_python
-import re
 from utils import (
     load_files,
     highlight_text,
@@ -13,15 +10,15 @@ from utils import (
     process_response,
 )
 from openai import OpenAI
-import json
 
 from const import (
     LIMITATIONS,
     GOAL,
     femi_color,
-    masc_color,
     femi_pro_color,
     masc_pro_color,
+    ageism_color,
+    ableism_color,
 )
 
 
@@ -60,7 +57,7 @@ if "login" not in st.session_state:
     else:
         reject_login()
 
-cols = st.columns([1, 2, 1])
+cols = st.columns([2, 3, 2])
 
 with cols[1]:
     st.header("Fairplay: bias advisor / attractiveness rating in job ads")
@@ -68,26 +65,31 @@ with cols[1]:
     for line in LIMITATIONS:
         st.write(line)
 
+st.divider()
+
 col1, col2, col3 = st.columns([1, 3, 1])
 with col2:
+    st.write("**Please enter your job ad text below** [including a job title]:")
     job_ad_field = st.text_area(
         label="Job ad text",
         value="Please paste here your input",
         max_chars=10000,
         key="input",
         height=500,
+        label_visibility="collapsed",
     )
     clicked = st.button("Analyze", key="analyze")
 
 if clicked:
     st.divider()
-    st.header("Results:")
-    col1, col2, col3 = st.columns([1, 3, 1])
+
+    col1, col2, col3 = st.columns([1, 2, 1])
     job_ad_split, metrics = highlight_text(job_ad_field, st.session_state.data)
     indices = get_indices(metrics)
     openai_params = construct_params(job_ad_field)
 
     with col2:
+        st.header("Results:")
         with st.container(border=True):
             minicols = st.columns([1, 1, 1, 2, 4])
 
@@ -97,7 +99,7 @@ if clicked:
 
         placeholder = st.empty()
 
-    col1, col2, col3 = st.columns([1, 3, 1])
+    col1, col2, col3 = st.columns([1, 2, 1])
 
     with col2:
         with st.container(border=True):
@@ -105,20 +107,18 @@ if clicked:
     with col3:
         with st.container(border=True):
             st.subheader("Color explanations:")
-            st.write("**Misspelled**")
-            annotated_text(("Misspelled", "", "#cccccc"))
             st.write(
                 "**Gendered Language** according to [https://psycnet.apa.org/record/2011-04642-001]"
             )
-            annotated_text(("Male root", "M", masc_pro_color))
-            annotated_text(("Female root", "F", femi_pro_color))
+            annotated_text(("Gender significant words", "F/M", femi_color))
             st.write("**Gendered pronouns**")
-            annotated_text(("Male Pronoun", "", masc_color))
-            annotated_text(("Female Pronoun", "", femi_color))
-            st.write("**Age discriminatory language**")
-            annotated_text(("Ageism", "", "#FFA500"))
-            st.write("**Ableist discriminatory language**")
-            annotated_text(("Ableism", "", "#E97451"))
+            annotated_text(("Female Pronoun", "", femi_pro_color), "/", ("Male Pronoun", "", masc_pro_color))
+            st.write("**Age discriminatory language** [In the near future]")
+            annotated_text(("Ageism", "", ageism_color))
+            st.write("**Ableist discriminatory language** [In the near future]")
+            annotated_text(("Ableism", "", ableism_color))
+            st.write("**Misspelled** [In the near future]")
+            annotated_text(("Misspelled", "", "#cccccc"))
 
     with placeholder.container(border=True):
         with st.spinner("Wait for it..."):
@@ -128,30 +128,29 @@ if clicked:
 
         minicols[2].metric("Diversity Statement", cleaned_response["answer_4"], None)
         minicols[3].metric("Target Age Group", cleaned_response["answer_6"], None)
-        ## Gendered jobtitles
+        # Gendered jobtitles
         st.write(f"**Presence of gendered jobtitles:** {cleaned_response['answer_3']}")
         if cleaned_response["answer_3"] == "Yes":
             st.write(cleaned_response["longer_answer_3"])
-        ## Explicit length of experience
+        # Explicit length of experience
         st.write(f"**Explicit strict requirements:** {cleaned_response['answer_1']}")
         if cleaned_response["answer_1"] == "Yes":
             st.write(f'\t{cleaned_response["longer_answer_1"]}')
-        ## Explicit length of experience
+        # Explicit length of experience
         st.write(f"**Family life challenges:** {cleaned_response['answer_2']}")
         if cleaned_response["answer_2"] == "Yes":
             st.write(f'\t{cleaned_response["longer_answer_2"]}')
 
-        ## Text level equivalent
+        # Text level equivalent
         st.write(f"**Text level equivalent:** {cleaned_response['answer_5']}")
 
-        ## Target Age group
+        # Target Age group
         st.write(f"**Target Age group:** {cleaned_response['longer_answer_6']}")
 
-        ## Diversity statement
+        # Diversity statement
         if cleaned_response["answer_4"] == "No":
             st.write(
                 f"\t**Diversity statement**: This ad could benefit from a diversity statement."
             )
-
-        ## Short report
-        st.write(cleaned_response["short_report"])
+        # Short report
+        st.write(f'**Short report:** {cleaned_response["short_report"]}')

const.py

@@ -12,5 +12,7 @@ LIMITATIONS = [
 
 masc_color = "#f6cefc"
 femi_color = "#f6cefc"
-masc_pro_color = "#89CFF0"
-femi_pro_color = "#F88379"
+masc_pro_color = "#FFAC1C"
+femi_pro_color = "#FFAC1C"
+ageism_color = "#ADD8E6"
+ableism_color = "#E97451"

utils.py

@@ -26,8 +26,8 @@ def _construct_message(job_ad_text) -> list:
 def construct_params(job_ad_text) -> dict:
     messages = _construct_message(job_ad_text)
     return {
-        "model": "gpt-3.5-turbo-0125",
-        # "model": "gpt-4o",
+        #"model": "gpt-3.5-turbo-0125",
+        "model": "gpt-4o",
         "messages": messages,
         "response_format": {"type": "json_object"},
         "n": 1,