fix risk networks rerun and file download names

app/util/ui_components.py

@@ -79,7 +79,7 @@ def generative_ai_component(system_prompt_var, variables):
     with b2:
         message = f'AI input uses {tokens}/{util.AI_API.max_input_tokens} ({round(ratio, 2)}%) of token limit'
         if ratio <= 100:
-            st.success(message)
+            st.info(message)
         else:
             st.warning(message)
     return generate, messages, reset_prompt
@@ -470,7 +470,8 @@ def convert(x):
     else:
         st.warning('Generate final dataset to continue.')
 
-def validate_ai_report(messages, result):
-    st.status('Validating AI report and generating groundedness score...', expanded=False, state='running')
+def validate_ai_report(messages, result, show_status = True):
+    if show_status:
+        st.status('Validating AI report and generating groundedness score...', expanded=False, state='running')
     validation, messages_to_llm = util.AI_API.validate_report(messages, result)
     return re.sub(r"```json\n|\n```", "", validation), messages_to_llm

app/workflows/record_matching/variables.py

@@ -18,4 +18,6 @@ def __init__(self, prefix):
         self.matching_sentence_pair_embedding_threshold = SessionVariable(0.05, prefix)
         self.matching_last_sentence_pair_embedding_threshold = SessionVariable(0.05, prefix)
         self.matching_evaluations = SessionVariable(pl.DataFrame(), prefix)
+        self.matching_report_validation = SessionVariable({}, prefix)
+        self.matching_report_validation_messages = SessionVariable('', prefix)
         self.matching_system_prompt = SessionVariable(prompts.list_prompts, prefix)

app/workflows/record_matching/workflow.py

@@ -1,4 +1,6 @@
 # Copyright (c) 2024 Microsoft Corporation. All rights reserved.
+import json
+import pandas as pd
 import streamlit as st
 import polars as pl
 
@@ -327,13 +329,19 @@ def att_ui(i):
             prefix = '```\nGroup ID,Relatedness,Explanation\n'
             placeholder = st.empty()
             gen_placeholder = st.empty()
+            get_current_time = pd.Timestamp.now().strftime('%Y%m%d%H%M%S')
+
             if generate:
                 for messages in batch_messages:
                     response = util.AI_API.generate_text_from_message_list(messages, placeholder, prefix=prefix)
                     if len(response.strip()) > 0:
                         prefix = prefix + response + '\n'
                 result = prefix.replace('```\n', '').strip()
                 sv.matching_evaluations.value = pl.read_csv(io.StringIO(result))
+
+                validation, messages_to_llm = util.ui_components.validate_ai_report(messages, sv.matching_evaluations.value)
+                sv.matching_report_validation.value = json.loads(validation)
+                sv.matching_report_validation_messages.value = messages_to_llm
                 st.rerun()
             else:
                 if len(sv.matching_evaluations.value) == 0:
@@ -342,4 +350,17 @@ def att_ui(i):
             if len(sv.matching_evaluations.value) > 0:
                 st.dataframe(sv.matching_evaluations.value.to_pandas(), height=700, use_container_width=True, hide_index=True)
                 jdf = sv.matching_matches_df.value.join(sv.matching_evaluations.value, on='Group ID', how='inner')
-                st.download_button('Download AI match report', data=jdf.write_csv(), file_name='record_groups_evaluated.csv', mime='text/csv')
+                st.download_button('Download AI match report', data=jdf.write_csv(), file_name='record_groups_evaluated.csv', mime='text/csv')
+
+                if sv.matching_report_validation.value != {}:
+                    validation_status = st.status(label=f"LLM faithfulness score: {sv.matching_report_validation.value['score']}/5", state='complete')
+                    with validation_status:
+                        st.write(sv.matching_report_validation.value['explanation'])
+
+                    if sv_home.mode.value == 'dev':
+                        obj = json.dumps({
+                            "message": sv.matching_report_validation_messages.value,
+                            "result": sv.matching_report_validation.value,
+                            "report": sv.matching_evaluations.value
+                        }, indent=4)
+                        st.download_button('Download validation prompt', use_container_width=True, data=str(obj), file_name=f'matching_{get_current_time}_messages.json', mime='text/json')

app/workflows/risk_networks/workflow.py

@@ -502,27 +502,33 @@ def create():
                 gen_placeholder = st.empty()
                 get_current_time = pd.Timestamp.now().strftime('%Y%m%d%H%M%S')
 
+                generated = False
                 if generate:
+                    generated = True
                     result = util.AI_API.generate_text_from_message_list(
                         placeholder=report_placeholder,
                         messages=messages,
                         prefix=''
                     )
                     sv.network_report.value = result
+                    validation_status = st.status('Validating AI report and generating groundedness score...', expanded=False, state='running')
 
-                    validation, messages_to_llm = util.ui_components.validate_ai_report(messages, result)
+                    validation, messages_to_llm = util.ui_components.validate_ai_report(messages, result, False)
                     sv.network_report_validation.value = json.loads(validation)
                     sv.network_report_validation_messages.value = messages_to_llm
-                    st.rerun()
                 else:
                     if len(sv.network_report.value) == 0:
                         gen_placeholder.warning('Press the Generate button to create an AI report for the current network.')
-                report_placeholder.markdown(sv.network_report.value)
+                report_data = sv.network_report.value
+                report_placeholder.markdown(report_data)
 
                 util.ui_components.report_download_ui(sv.network_report, 'network_report')
 
                 if sv.network_report_validation.value != {}:
-                        validation_status = st.status(label=f"LLM faithfulness score: {sv.network_report_validation.value['score']}/5", state='complete')
+                        if generated:
+                            validation_status.update(label=f"LLM faithfulness score: {sv.network_report_validation.value['score']}/5", state='complete')
+                        else:
+                            validation_status = st.status(label=f"LLM faithfulness score: {sv.network_report_validation.value['score']}/5", state='complete')
                         with validation_status:
                             st.write(sv.network_report_validation.value['explanation'])