upgrade to 0.2.0

agent.py

@@ -18,8 +18,7 @@ def create_assistant_tools(cfg):
         query: str = Field(description="The user query.")
 
     vec_factory_1 = VectaraToolFactory(vectara_api_key=cfg.api_keys[0],
-                                        vectara_customer_id=cfg.customer_id, 
-                                        vectara_corpus_id=cfg.corpus_ids[0])
+                                        vectara_corpus_key=cfg.corpus_keys[0])
     
     summarizer = 'vectara-experimental-summary-ext-2023-12-11-med-omni'
 
@@ -48,8 +47,7 @@ def create_assistant_tools(cfg):
     )
 
     vec_factory_2 = VectaraToolFactory(vectara_api_key=cfg.api_keys[1],
-                                       vectara_customer_id=cfg.customer_id,
-                                       vectara_corpus_id=cfg.corpus_ids[1])
+                                       vectara_corpus_key=cfg.corpus_keys[1])
     
 
     class QueryEVLaws(BaseModel):
@@ -119,8 +117,7 @@ def initialize_agent(_cfg, agent_progress_callback=None):
 
 def get_agent_config() -> OmegaConf:
     cfg = OmegaConf.create({
-        'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']),
-        'corpus_ids': str(os.environ['VECTARA_CORPUS_IDS']).split(','),
+        'corpus_keys': str(os.environ['VECTARA_CORPUS_KEYS']).split(','),
         'api_keys': str(os.environ['VECTARA_API_KEYS']).split(','),
         'examples': os.environ.get('QUERY_EXAMPLES', None),
         'demo_name': "ev-assistant",

requirements.txt

@@ -7,4 +7,4 @@ langdetect==1.0.9
 langcodes==3.4.0
 datasets==2.19.2
 uuid==1.30
-vectara-agentic==0.1.22
+vectara-agentic==0.2.0

st_app.py

@@ -134,8 +134,8 @@ async def launch_bot():
     if st.session_state.prompt:
         with st.chat_message("assistant", avatar='🤖'):
             st.session_state.status = st.status('Processing...', expanded=False)
-            res = st.session_state.agent.chat(st.session_state.prompt)
-            res = escape_dollars_outside_latex(res)
+            response = st.session_state.agent.chat(st.session_state.prompt)
+            res = escape_dollars_outside_latex(response.response)
             message = {"role": "assistant", "content": res, "avatar": '🤖'}
             st.session_state.messages.append(message)
             st.markdown(res)