updates

agent.py

@@ -140,7 +140,7 @@ def create_assistant_tools(cfg):
     class QueryCaselawArgs(BaseModel):
         query: str = Field(..., description="The user query.")
         citations: Optional[str] = Field(default = None, 
-                                         description = "The citation of the case. Optional.", 
+                                         description = "The citations of the case. Optional.",
                                          examples = ['253 P.2d 136', '10 Alaska 11', '6 C.M.A. 3'])
 
     vec_factory = VectaraToolFactory(vectara_api_key=cfg.api_key, 
@@ -151,12 +151,9 @@ def create_assistant_tools(cfg):
     ask_caselaw = vec_factory.create_rag_tool(
         tool_name = "ask_caselaw",
         tool_description = """
+        Use this tool for general case law queries.
         Returns a response (str) to the user query base on case law in the state of Alaska.
         If 'citations' is provided, filters the response based on information from that case.
-        The response includes metadata about the case such as title/name the ruling, the court, 
-        the decision date, the judges, and the case citation. 
-        You can use case citations from the metadata as input to other tools.
-        Use this tool for general case law queries.
         """,
         tool_args_schema = QueryCaselawArgs,
         reranker = "multilingual_reranker_v1", rerank_k = 100, 

app.py

@@ -2,6 +2,8 @@ from PIL import Image
 import sys
 import uuid
 
+import nest_asyncio
+import asyncio
 
 import streamlit as st
 from streamlit_pills import pills
@@ -38,7 +40,7 @@ def update_func(status_type: AgentStatusType, msg: str):
         output = f"{status_type.value} - {msg}"
         st.session_state.log_messages.append(output)
 
-def launch_bot():
+async def launch_bot():
     def reset():
         st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
         st.session_state.thinking_message = "Agent at work..."
@@ -155,4 +157,5 @@ def launch_bot():
 
 if __name__ == "__main__":
     st.set_page_config(page_title="Legal Assistant", layout="wide")
-    launch_bot()
+    nest_asyncio.apply()
+    asyncio.run(launch_bot())

requirements.txt

@@ -6,4 +6,4 @@ streamlit-feedback==0.1.3
 uuid==1.30
 langdetect==1.0.9
 langcodes==3.4.0
-vectara-agentic==0.1.5
+vectara-agentic==0.1.6