updates for HHEM

agent.py

@@ -33,7 +33,7 @@ tickers = {
     "STT": "State Street",
     "BK": "Bank of New York Mellon",
 }
-years = list(range(2015, 2025))
+years = list(range(2015, 2026))
 initial_prompt = "How can I help you today?"
 
 
@@ -206,6 +206,6 @@ def get_agent_config() -> OmegaConf:
         'examples': os.environ.get('QUERY_EXAMPLES', None),
         'demo_name': "finance-chat",
         'demo_welcome': "Financial Assistant demo.",
-        'demo_description': f"This assistant can help you with any questions about the financials of several companies:\n\n **{companies}**.\n"
+        'demo_description': f"This assistant can help you with any questions about the financials of several companies:\n\n **{companies}**.\n",
     })
     return cfg

requirements.txt

@@ -5,5 +5,5 @@ streamlit_feedback==0.1.3
 uuid==1.30
 langdetect==1.0.9
 langcodes==3.4.0
-vectara-agentic==0.2.16
+vectara-agentic==0.2.21
 torch==2.6.0

st_app.py

@@ -147,6 +147,11 @@ async def launch_bot():
             st.session_state.status = st.status('Processing...', expanded=False)
             response = await st.session_state.agent.achat(st.session_state.prompt)
             res = escape_dollars_outside_latex(response.response)
+            fcs = None
+            try:
+                fcs = response.metadata.get('fcs', None)
+            except Exception as e:
+                pass
 
             #from vectara_agentic.sub_query_workflow import SequentialSubQuestionsWorkflow
             #response = await st.session_state.agent.run(inputs=SequentialSubQuestionsWorkflow.InputsModel(query=st.session_state.prompt))
@@ -158,8 +163,10 @@ async def launch_bot():
             #res = await st.session_state.agent.astream_chat(st.session_state.prompt)
             #response = ''.join([token async for token in res.async_response_gen()])
             #res = escape_dollars_outside_latex(response)
-
-            message = {"role": "assistant", "content": res, "avatar": '🤖'}
+            if fcs is not None:
+                message = {"role": "assistant", "content": res + f"\n\n**Factual Consistency Score**: {fcs}", "avatar": '🤖'}
+            else:
+                message = {"role": "assistant", "content": res, "avatar": '🤖'}
             st.session_state.messages.append(message)
 
         send_amplitude_data(