version bump

agent.py

@@ -167,30 +167,23 @@ def create_assistant_tools(cfg):
 
     class QueryCaselawArgs(BaseModel):
         query: str = Field(..., description="The user query.")
-        citations: Optional[str] = Field(default = None, 
-                                         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, 
                                      vectara_customer_id=cfg.customer_id, 
                                      vectara_corpus_id=cfg.corpus_id)
-    tools_factory = ToolsFactory()
-
+    summarizer = 'vectara-experimental-summary-ext-2023-12-11-med-omni'
     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.
-        """,
+        tool_description = "A tool for asking questions about case law in Alaska.",
         tool_args_schema = QueryCaselawArgs,
         reranker = "multilingual_reranker_v1", rerank_k = 100, 
         n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005,
         summary_num_results = 10,
-        vectara_summarizer = 'vectara-experimental-summary-ext-2023-12-11-med-omni',
+        vectara_summarizer = summarizer,
         include_citations = False,
     )
 
+    tools_factory = ToolsFactory()
     return (
         [ask_caselaw] +
         [tools_factory.create_tool(tool) for tool in [
@@ -207,6 +200,7 @@ def get_agent_config() -> OmegaConf:
     cfg = OmegaConf.create({
         'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']),
         'corpus_id': str(os.environ['VECTARA_CORPUS_ID']),
+        'corpus_key': str(os.environ['VECTARA_CORPUS_KEY']),
         'api_key': str(os.environ['VECTARA_API_KEY']),
         'examples': os.environ.get('QUERY_EXAMPLES', None),
         'demo_name': "legal-agent",
@@ -227,7 +221,7 @@ def initialize_agent(_cfg, update_func=None):
       For example you can include citations, decision date, or case name.
     - Citations include 3 components: volume number, reporter, and first page. 
       Here are some examples: '253 P.2d 136', '10 Alaska 11', '6 C.M.A. 3'
-      Never use your internal knowledge to contruct or guess what the citation is.
+    - Never use your internal knowledge to guess citations. Only use citations information provided by a tool or the user.
     - If two cases have conflicting rulings, assume that the case with the more current ruling date is correct.
     - If the response is based on cases that are older than 5 years, make sure to inform the user that the information may be outdated,
       since some case opinions may no longer apply in law.
@@ -248,6 +242,6 @@ def initialize_agent(_cfg, update_func=None):
         tools=create_assistant_tools(_cfg),
         topic="Case law in Alaska",
         custom_instructions=legal_assistant_instructions,
-        update_func=update_func
+        update_func=update_func,
     )
     return agent

app.py

@@ -1,159 +1,16 @@
-from PIL import Image
-import sys
+import streamlit as st
+from st_app import launch_bot
 import uuid
 
 import nest_asyncio
 import asyncio
 
-import streamlit as st
-from streamlit_pills import pills
-from streamlit_feedback import streamlit_feedback
-
-from vectara_agentic.agent import AgentStatusType
-
-from agent import initialize_agent, get_agent_config
-from utils import thumbs_feedback, escape_dollars_outside_latex, send_amplitude_data
-
-initial_prompt = "How can I help you today?"
-
 # Setup for HTTP API Calls to Amplitude Analytics
 if 'device_id' not in st.session_state:
     st.session_state.device_id = str(uuid.uuid4())
 
 if "feedback_key" not in st.session_state:
-        st.session_state.feedback_key = 0
-
-def toggle_logs():
-    st.session_state.show_logs = not st.session_state.show_logs
-
-def show_example_questions():        
-    if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:            
-        selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
-        if selected_example:
-            st.session_state.ex_prompt = selected_example
-            st.session_state.first_turn = False
-            return True
-    return False
-
-def update_func(status_type: AgentStatusType, msg: str):
-    if status_type != AgentStatusType.AGENT_UPDATE:
-        output = f"{status_type.value} - {msg}"
-        st.session_state.log_messages.append(output)
-
-async def launch_bot():
-    def reset():
-        st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
-        st.session_state.thinking_message = "Agent at work..."
-        st.session_state.log_messages = []
-        st.session_state.prompt = None
-        st.session_state.ex_prompt = None
-        st.session_state.first_turn = True
-        st.session_state.show_logs = False
-        if 'agent' not in st.session_state:
-            st.session_state.agent = initialize_agent(cfg, update_func=update_func)
-
-    if 'cfg' not in st.session_state:
-        cfg = get_agent_config()
-        st.session_state.cfg = cfg
-        st.session_state.ex_prompt = None
-        example_messages = [example.strip() for example in cfg.examples.split(";")] if cfg.examples else []
-        st.session_state.example_messages = [em for em in example_messages if len(em)>0]
-        reset()
-
-    cfg = st.session_state.cfg
-
-    # left side content
-    with st.sidebar:
-        image = Image.open('Vectara-logo.png')
-        st.image(image, width=175)
-        st.markdown(f"## {cfg['demo_welcome']}")
-        st.markdown(f"{cfg['demo_description']}")
-
-        st.markdown("\n\n")
-        bc1, _ = st.columns([1, 1])
-        with bc1:
-            if st.button('Start Over'):
-                reset()
-                st.rerun()
-
-        st.divider()
-        st.markdown(
-            "## How this works?\n"
-            "This app was built with [Vectara](https://vectara.com).\n\n"
-            "It demonstrates the use of Agentic RAG functionality with Vectara"
-        )
-
-    if "messages" not in st.session_state.keys():
-        reset()
-    
-    # Display chat messages
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"], avatar=message["avatar"]):
-            st.write(message["content"])
-
-    example_container = st.empty()
-    with example_container:
-        if show_example_questions():
-            example_container.empty()
-            st.session_state.first_turn = False
-            st.rerun()
-
-    # User-provided prompt
-    if st.session_state.ex_prompt:
-        prompt = st.session_state.ex_prompt
-    else:
-        prompt = st.chat_input()
-    if prompt:
-        st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑‍💻'})
-        st.session_state.prompt = prompt  # Save the prompt in session state
-        st.session_state.log_messages = []
-        st.session_state.show_logs = False
-        with st.chat_message("user", avatar='🧑‍💻'):
-            print(f"Starting new question: {prompt}\n")
-            st.write(prompt)
-        st.session_state.ex_prompt = None
-        
-    # Generate a new response if last message is not from assistant
-    if st.session_state.prompt:
-        with st.chat_message("assistant", avatar='🤖'):
-            with st.spinner(st.session_state.thinking_message):
-                res = st.session_state.agent.chat(st.session_state.prompt)
-                res = escape_dollars_outside_latex(res)
-            message = {"role": "assistant", "content": res, "avatar": '🤖'}
-            st.session_state.messages.append(message)
-            st.markdown(res)
-
-        send_amplitude_data(
-            user_query=st.session_state.messages[-2]["content"], 
-            bot_response=st.session_state.messages[-1]["content"],
-            demo_name=cfg['demo_name']
-        )
-
-        st.session_state.ex_prompt = None
-        st.session_state.prompt = None
-        st.session_state.first_turn = False
-        st.rerun()
-
-    # Record user feedback
-    if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != "How can I help you today?"):
-        streamlit_feedback(
-            feedback_type="thumbs", on_submit = thumbs_feedback, key = st.session_state.feedback_key,
-            kwargs = {"user_query": st.session_state.messages[-2]["content"],
-                      "bot_response": st.session_state.messages[-1]["content"],
-                      "demo_name": cfg["demo_name"]}
-        )
-
-    log_placeholder = st.empty()
-    with log_placeholder.container():
-        if st.session_state.show_logs:
-            st.button("Hide Logs", on_click=toggle_logs)
-            for msg in st.session_state.log_messages:
-                st.text(msg)
-        else:
-            if len(st.session_state.log_messages) > 0:
-                st.button("Show Logs", on_click=toggle_logs)
-
-    sys.stdout.flush()
+    st.session_state.feedback_key = 0
 
 if __name__ == "__main__":
     st.set_page_config(page_title="Legal Assistant", layout="wide")

requirements.txt

@@ -6,4 +6,4 @@ streamlit-feedback==0.1.3
 uuid==1.30
 langdetect==1.0.9
 langcodes==3.4.0
-vectara-agentic==0.1.15
+vectara-agentic==0.1.16

st_app.py

@@ -0,0 +1,163 @@
+from PIL import Image
+import sys
+
+import streamlit as st
+from streamlit_pills import pills
+from streamlit_feedback import streamlit_feedback
+
+from utils import thumbs_feedback, escape_dollars_outside_latex, send_amplitude_data
+
+from vectara_agentic.agent import AgentStatusType
+from agent import initialize_agent, get_agent_config
+
+initial_prompt = "How can I help you today?"
+
+def toggle_logs():
+    st.session_state.show_logs = not st.session_state.show_logs
+
+def show_example_questions():        
+    if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:            
+        selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
+        if selected_example:
+            st.session_state.ex_prompt = selected_example
+            st.session_state.first_turn = False
+            return True
+    return False
+
+def update_func(status_type: AgentStatusType, msg: str):
+    if status_type != AgentStatusType.AGENT_UPDATE:
+        output = f"{status_type.value} - {msg}"
+        st.session_state.log_messages.append(output)
+
+async def launch_bot():
+    def reset():
+        st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
+        st.session_state.thinking_message = "Agent at work..."
+        st.session_state.log_messages = []
+        st.session_state.prompt = None
+        st.session_state.ex_prompt = None
+        st.session_state.first_turn = True
+        st.session_state.logs_enabled = False
+        st.session_state.show_logs = False
+        if 'agent' not in st.session_state:
+            st.session_state.agent = initialize_agent(cfg, update_func=update_func)
+        else:
+            st.session_state.agent.clear_memory()
+
+    if 'cfg' not in st.session_state:
+        cfg = get_agent_config()
+        st.session_state.cfg = cfg
+        st.session_state.ex_prompt = None
+        example_messages = [example.strip() for example in cfg.examples.split(";")] if cfg.examples else []
+        st.session_state.example_messages = [em for em in example_messages if len(em)>0]
+        reset()
+
+    cfg = st.session_state.cfg
+
+    # left side content
+    with st.sidebar:
+        image = Image.open('Vectara-logo.png')
+        st.image(image, width=175)
+        st.markdown(f"## {cfg['demo_welcome']}")
+        st.markdown(f"{cfg['demo_description']}")
+
+        st.markdown("\n\n")
+        bc1, bc2 = st.columns([1, 1])
+        with bc1:
+            if st.button('Start Over'):
+                reset()
+                st.rerun()
+        with bc2:  # Updated button for enabling/disabling logs
+            if st.session_state.logs_enabled:
+                if st.button('Disable Logs', key='disable_logs'):
+                    st.session_state.logs_enabled = False
+                    st.rerun()
+            else:
+                if st.button('Enable Logs', key='enable_logs'):
+                    st.session_state.logs_enabled = True
+                    st.rerun()
+
+        st.divider()
+        st.markdown(
+            "## How this works?\n"
+            "This app was built with [Vectara](https://vectara.com).\n\n"
+            "It demonstrates the use of Agentic RAG functionality with Vectara"
+        )
+
+    if "messages" not in st.session_state.keys():
+        reset()
+
+    # Display chat messages
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"], avatar=message["avatar"]):
+            st.write(message["content"])
+
+    example_container = st.empty()
+    with example_container:
+        if show_example_questions():
+            example_container.empty()
+            st.session_state.first_turn = False
+            st.rerun()
+
+    # User-provided prompt
+    if st.session_state.ex_prompt:
+        prompt = st.session_state.ex_prompt
+    else:
+        prompt = st.chat_input()
+    if prompt:
+        st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑‍💻'})
+        st.session_state.prompt = prompt  # Save the prompt in session state
+        st.session_state.log_messages = []
+        st.session_state.show_logs = False
+        with st.chat_message("user", avatar='🧑‍💻'):
+            print(f"Starting new question: {prompt}\n")
+            st.write(prompt)
+        st.session_state.ex_prompt = None
+        
+    # Generate a new response if last message is not from assistant
+    if st.session_state.prompt:
+        with st.chat_message("assistant", avatar='🤖'):
+            with st.spinner(st.session_state.thinking_message):
+                res = st.session_state.agent.chat(st.session_state.prompt)
+                res = escape_dollars_outside_latex(res)
+            message = {"role": "assistant", "content": res, "avatar": '🤖'}
+            st.session_state.messages.append(message)
+            st.markdown(res)
+
+        send_amplitude_data(
+            user_query=st.session_state.messages[-2]["content"], 
+            bot_response=st.session_state.messages[-1]["content"],
+            demo_name=cfg['demo_name']
+        )
+
+        st.session_state.ex_prompt = None
+        st.session_state.prompt = None
+        st.session_state.first_turn = False
+        st.rerun()
+
+    # Record user feedback
+    if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != initial_prompt):
+        if st.session_state.show_logs and st.session_state.logs_enabled:  # Only show logs if enabled
+            streamlit_feedback(
+                feedback_type="thumbs", on_submit=thumbs_feedback, key=st.session_state.feedback_key,
+                kwargs={"user_query": st.session_state.messages[-2]["content"],
+                        "bot_response": st.session_state.messages[-1]["content"],
+                        "demo_name": cfg["demo_name"]}
+            )
+
+    log_placeholder = st.empty()
+    with log_placeholder.container():
+        if st.session_state.logs_enabled:  # Show logs button only if log toggle is enabled
+            if st.session_state.show_logs:
+                st.button("Hide Logs", on_click=toggle_logs)
+                for msg in st.session_state.log_messages:
+                    if len(msg) > 100:  # Use text_area for longer messages
+                        st.text_area(label="Log", value=msg, height=100, disabled=True)
+                    else:
+                        st.text(msg)
+            else:
+                if len(st.session_state.log_messages) > 0:
+                    st.button("Show Logs", on_click=toggle_logs)
+
+
+    sys.stdout.flush()