update to v0.1.16
Browse files- .gitignore +2 -1
- agent.py +6 -12
- app.py +1 -153
- requirements.txt +1 -1
- st_app.py +169 -0
.gitignore
CHANGED
@@ -11,6 +11,7 @@ core/__pycache__/
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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@@ -140,4 +141,4 @@ dmypy.json
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project.yaml
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.idea/
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-
ev_database.db
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*.so
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# Distribution / packaging
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+
*.db
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.Python
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build/
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develop-eggs/
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project.yaml
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.idea/
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+
ev_database.db
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agent.py
CHANGED
@@ -4,7 +4,7 @@ from pydantic import Field, BaseModel
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from omegaconf import OmegaConf
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from llama_index.core.utilities.sql_wrapper import SQLDatabase
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-
from sqlalchemy import create_engine
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from dotenv import load_dotenv
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load_dotenv(override=True)
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@@ -22,7 +22,6 @@ def create_assistant_tools(cfg):
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vectara_corpus_id=cfg.corpus_ids)
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summarizer = 'vectara-experimental-summary-ext-2023-12-11-med-omni'
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-
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ask_complaints = vec_factory.create_rag_tool(
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tool_name = "ask_complaints",
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tool_description = """
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@@ -32,9 +31,9 @@ def create_assistant_tools(cfg):
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tool_args_schema = QueryCFPBComplaints,
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reranker = "multilingual_reranker_v1", rerank_k = 100,
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n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005,
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-
summary_num_results =
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vectara_summarizer = summarizer,
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-
include_citations =
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)
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tools_factory = ToolsFactory()
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@@ -53,17 +52,12 @@ def create_assistant_tools(cfg):
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def initialize_agent(_cfg, update_func=None):
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cfpb_complaints_bot_instructions = """
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56 |
-
- You are a helpful research assistant,
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- For a query with multiple sub-questions, break down the query into the sub-questions,
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and make separate calls to the ask_complaints tool to answer each sub-question,
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then combine the answers to provide a complete response.
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-
- If you do not find an answer from one of the tools, try to use the other tools to answer the query.
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-
- Before answering any user query, use cfpb_describe_tables to understand schema of each table, and use get_sample_data
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-
to get sample data from each table in the database, so that you can understand NULL and unique values for each column.
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-
- Use the database tools (cfpb_load_data, cfpb_describe_tables and cfpb_list_tables) to answer analytical queries.
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-
- IMPORTANT: When using database_tools, always call the ev_load_sample_data tool with the table you want to query
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-
to understand the table structure, column naming, and values in the table. Never call the cfpb_load_data tool for a query until you have called cfpb_load_sample_data.
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-
- When providing links, try to put the name of the website or source of information for the displayed text. Don't just say 'Source'.
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- Never discuss politics, and always respond politely.
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"""
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from omegaconf import OmegaConf
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from llama_index.core.utilities.sql_wrapper import SQLDatabase
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+
from sqlalchemy import create_engine
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from dotenv import load_dotenv
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load_dotenv(override=True)
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vectara_corpus_id=cfg.corpus_ids)
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summarizer = 'vectara-experimental-summary-ext-2023-12-11-med-omni'
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ask_complaints = vec_factory.create_rag_tool(
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tool_name = "ask_complaints",
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tool_description = """
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tool_args_schema = QueryCFPBComplaints,
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reranker = "multilingual_reranker_v1", rerank_k = 100,
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n_sentences_before = 2, n_sentences_after = 2, lambda_val = 0.005,
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+
summary_num_results = 15,
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vectara_summarizer = summarizer,
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+
include_citations = True,
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)
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tools_factory = ToolsFactory()
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def initialize_agent(_cfg, update_func=None):
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cfpb_complaints_bot_instructions = """
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+
- You are a helpful research assistant,
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+
with expertise in finance and complaints from the CFPB (Consumer Financial Protection Bureau),
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+
in conversation with a user.
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- For a query with multiple sub-questions, break down the query into the sub-questions,
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and make separate calls to the ask_complaints tool to answer each sub-question,
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then combine the answers to provide a complete response.
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- Never discuss politics, and always respond politely.
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"""
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app.py
CHANGED
@@ -1,166 +1,14 @@
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-
from PIL import Image
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import sys
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import os
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-
import uuid
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import streamlit as st
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-
from
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from streamlit_feedback import streamlit_feedback
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import nest_asyncio
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import asyncio
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-
from utils import thumbs_feedback, escape_dollars_outside_latex, send_amplitude_data
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-
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import sqlite3
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from datasets import load_dataset
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-
from vectara_agentic.agent import AgentStatusType
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-
from agent import initialize_agent, get_agent_config
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-
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-
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-
initial_prompt = "How can I help you today?"
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-
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-
# Setup for HTTP API Calls to Amplitude Analytics
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-
if 'device_id' not in st.session_state:
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-
st.session_state.device_id = str(uuid.uuid4())
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-
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-
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-
if "feedback_key" not in st.session_state:
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-
st.session_state.feedback_key = 0
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-
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-
def toggle_logs():
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-
st.session_state.show_logs = not st.session_state.show_logs
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-
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-
def show_example_questions():
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-
if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:
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-
selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
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-
if selected_example:
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-
st.session_state.ex_prompt = selected_example
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-
st.session_state.first_turn = False
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-
return True
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-
return False
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-
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-
def update_func(status_type: AgentStatusType, msg: str):
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-
if status_type != AgentStatusType.AGENT_UPDATE:
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-
output = f"{status_type.value} - {msg}"
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-
st.session_state.log_messages.append(output)
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-
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-
async def launch_bot():
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-
def reset():
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-
st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
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-
st.session_state.thinking_message = "Agent at work..."
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-
st.session_state.log_messages = []
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-
st.session_state.prompt = None
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-
st.session_state.ex_prompt = None
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-
st.session_state.first_turn = True
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-
st.session_state.show_logs = False
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-
if 'agent' not in st.session_state:
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-
st.session_state.agent = initialize_agent(cfg, update_func=update_func)
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-
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-
if 'cfg' not in st.session_state:
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-
cfg = get_agent_config()
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-
st.session_state.cfg = cfg
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-
st.session_state.ex_prompt = None
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-
example_messages = [example.strip() for example in cfg.examples.split(";")] if cfg.examples else []
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-
st.session_state.example_messages = [em for em in example_messages if len(em)>0]
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-
reset()
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-
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-
cfg = st.session_state.cfg
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-
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-
# left side content
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-
with st.sidebar:
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-
image = Image.open('Vectara-logo.png')
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-
st.image(image, width=175)
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-
st.markdown(f"## {cfg['demo_welcome']}")
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-
st.markdown(f"{cfg['demo_description']}")
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-
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st.markdown("\n\n")
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-
bc1, _ = st.columns([1, 1])
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with bc1:
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-
if st.button('Start Over'):
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reset()
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st.rerun()
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-
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st.divider()
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st.markdown(
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-
"## How this works?\n"
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"This app was built with [Vectara](https://vectara.com).\n\n"
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-
"It demonstrates the use of Agentic RAG functionality with Vectara"
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-
)
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-
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-
if "messages" not in st.session_state.keys():
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reset()
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-
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-
# Display chat messages
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-
for message in st.session_state.messages:
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-
with st.chat_message(message["role"], avatar=message["avatar"]):
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-
st.write(message["content"])
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-
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-
example_container = st.empty()
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-
with example_container:
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-
if show_example_questions():
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-
example_container.empty()
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-
st.session_state.first_turn = False
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-
st.rerun()
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-
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# User-provided prompt
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-
if st.session_state.ex_prompt:
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prompt = st.session_state.ex_prompt
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-
else:
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prompt = st.chat_input()
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-
if prompt:
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st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑💻'})
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-
st.session_state.prompt = prompt # Save the prompt in session state
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-
st.session_state.log_messages = []
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-
st.session_state.show_logs = False
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-
with st.chat_message("user", avatar='🧑💻'):
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print(f"Starting new question: {prompt}\n")
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st.write(prompt)
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st.session_state.ex_prompt = None
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-
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# Generate a new response if last message is not from assistant
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if st.session_state.prompt:
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-
with st.chat_message("assistant", avatar='🤖'):
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-
with st.spinner(st.session_state.thinking_message):
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-
res = st.session_state.agent.chat(st.session_state.prompt)
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-
res = escape_dollars_outside_latex(res)
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-
message = {"role": "assistant", "content": res, "avatar": '🤖'}
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-
st.session_state.messages.append(message)
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-
st.markdown(res)
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-
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-
send_amplitude_data(
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-
user_query=st.session_state.messages[-2]["content"],
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-
bot_response=st.session_state.messages[-1]["content"],
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-
demo_name=cfg['demo_name']
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-
)
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-
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-
st.session_state.ex_prompt = None
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-
st.session_state.prompt = None
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-
st.session_state.first_turn = False
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-
st.rerun()
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-
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-
# Record user feedback
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-
if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != initial_prompt):
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-
streamlit_feedback(
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-
feedback_type="thumbs", on_submit = thumbs_feedback, key = st.session_state.feedback_key,
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-
kwargs = {"user_query": st.session_state.messages[-2]["content"],
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-
"bot_response": st.session_state.messages[-1]["content"],
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-
"demo_name": cfg["demo_name"]}
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)
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-
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log_placeholder = st.empty()
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with log_placeholder.container():
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-
if st.session_state.show_logs:
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-
st.button("Hide Logs", on_click=toggle_logs)
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-
for msg in st.session_state.log_messages:
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st.text(msg)
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else:
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if len(st.session_state.log_messages) > 0:
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st.button("Show Logs", on_click=toggle_logs)
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-
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-
sys.stdout.flush()
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-
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def setup_db():
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db_path = 'cfpb_database.db'
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conn = sqlite3.connect(db_path)
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import os
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import streamlit as st
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+
from st_app import launch_bot
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import nest_asyncio
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import asyncio
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import sqlite3
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from datasets import load_dataset
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12 |
def setup_db():
|
13 |
db_path = 'cfpb_database.db'
|
14 |
conn = sqlite3.connect(db_path)
|
requirements.txt
CHANGED
@@ -7,4 +7,4 @@ langdetect==1.0.9
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|
7 |
langcodes==3.4.0
|
8 |
datasets==2.19.2
|
9 |
uuid==1.30
|
10 |
-
vectara-agentic==0.1.
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|
7 |
langcodes==3.4.0
|
8 |
datasets==2.19.2
|
9 |
uuid==1.30
|
10 |
+
vectara-agentic==0.1.16
|
st_app.py
ADDED
@@ -0,0 +1,169 @@
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|
1 |
+
from PIL import Image
|
2 |
+
import sys
|
3 |
+
import uuid
|
4 |
+
|
5 |
+
import streamlit as st
|
6 |
+
from streamlit_pills import pills
|
7 |
+
from streamlit_feedback import streamlit_feedback
|
8 |
+
|
9 |
+
from utils import thumbs_feedback, escape_dollars_outside_latex, send_amplitude_data
|
10 |
+
|
11 |
+
from vectara_agentic.agent import AgentStatusType
|
12 |
+
from agent import initialize_agent, get_agent_config
|
13 |
+
|
14 |
+
initial_prompt = "How can I help you today?"
|
15 |
+
|
16 |
+
# Setup for HTTP API Calls to Amplitude Analytics
|
17 |
+
if 'device_id' not in st.session_state:
|
18 |
+
st.session_state.device_id = str(uuid.uuid4())
|
19 |
+
|
20 |
+
|
21 |
+
if "feedback_key" not in st.session_state:
|
22 |
+
st.session_state.feedback_key = 0
|
23 |
+
|
24 |
+
def toggle_logs():
|
25 |
+
st.session_state.show_logs = not st.session_state.show_logs
|
26 |
+
|
27 |
+
def show_example_questions():
|
28 |
+
if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:
|
29 |
+
selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
|
30 |
+
if selected_example:
|
31 |
+
st.session_state.ex_prompt = selected_example
|
32 |
+
st.session_state.first_turn = False
|
33 |
+
return True
|
34 |
+
return False
|
35 |
+
|
36 |
+
def update_func(status_type: AgentStatusType, msg: str):
|
37 |
+
if status_type != AgentStatusType.AGENT_UPDATE:
|
38 |
+
output = f"{status_type.value} - {msg}"
|
39 |
+
st.session_state.log_messages.append(output)
|
40 |
+
|
41 |
+
async def launch_bot():
|
42 |
+
def reset():
|
43 |
+
st.session_state.messages = [{"role": "assistant", "content": initial_prompt, "avatar": "🦖"}]
|
44 |
+
st.session_state.thinking_message = "Agent at work..."
|
45 |
+
st.session_state.log_messages = []
|
46 |
+
st.session_state.prompt = None
|
47 |
+
st.session_state.ex_prompt = None
|
48 |
+
st.session_state.first_turn = True
|
49 |
+
st.session_state.logs_enabled = False
|
50 |
+
st.session_state.show_logs = False
|
51 |
+
if 'agent' not in st.session_state:
|
52 |
+
st.session_state.agent = initialize_agent(cfg, update_func=update_func)
|
53 |
+
else:
|
54 |
+
st.session_state.agent.clear_memory()
|
55 |
+
|
56 |
+
if 'cfg' not in st.session_state:
|
57 |
+
cfg = get_agent_config()
|
58 |
+
st.session_state.cfg = cfg
|
59 |
+
st.session_state.ex_prompt = None
|
60 |
+
example_messages = [example.strip() for example in cfg.examples.split(";")] if cfg.examples else []
|
61 |
+
st.session_state.example_messages = [em for em in example_messages if len(em)>0]
|
62 |
+
reset()
|
63 |
+
|
64 |
+
cfg = st.session_state.cfg
|
65 |
+
|
66 |
+
# left side content
|
67 |
+
with st.sidebar:
|
68 |
+
image = Image.open('Vectara-logo.png')
|
69 |
+
st.image(image, width=175)
|
70 |
+
st.markdown(f"## {cfg['demo_welcome']}")
|
71 |
+
st.markdown(f"{cfg['demo_description']}")
|
72 |
+
|
73 |
+
st.markdown("\n\n")
|
74 |
+
bc1, bc2 = st.columns([1, 1])
|
75 |
+
with bc1:
|
76 |
+
if st.button('Start Over'):
|
77 |
+
reset()
|
78 |
+
st.rerun()
|
79 |
+
with bc2: # Updated button for enabling/disabling logs
|
80 |
+
if st.session_state.logs_enabled:
|
81 |
+
if st.button('Disable Logs', key='disable_logs'):
|
82 |
+
st.session_state.logs_enabled = False
|
83 |
+
st.rerun()
|
84 |
+
else:
|
85 |
+
if st.button('Enable Logs', key='enable_logs'):
|
86 |
+
st.session_state.logs_enabled = True
|
87 |
+
st.rerun()
|
88 |
+
|
89 |
+
st.divider()
|
90 |
+
st.markdown(
|
91 |
+
"## How this works?\n"
|
92 |
+
"This app was built with [Vectara](https://vectara.com).\n\n"
|
93 |
+
"It demonstrates the use of Agentic RAG functionality with Vectara"
|
94 |
+
)
|
95 |
+
|
96 |
+
if "messages" not in st.session_state.keys():
|
97 |
+
reset()
|
98 |
+
|
99 |
+
# Display chat messages
|
100 |
+
for message in st.session_state.messages:
|
101 |
+
with st.chat_message(message["role"], avatar=message["avatar"]):
|
102 |
+
st.write(message["content"])
|
103 |
+
|
104 |
+
example_container = st.empty()
|
105 |
+
with example_container:
|
106 |
+
if show_example_questions():
|
107 |
+
example_container.empty()
|
108 |
+
st.session_state.first_turn = False
|
109 |
+
st.rerun()
|
110 |
+
|
111 |
+
# User-provided prompt
|
112 |
+
if st.session_state.ex_prompt:
|
113 |
+
prompt = st.session_state.ex_prompt
|
114 |
+
else:
|
115 |
+
prompt = st.chat_input()
|
116 |
+
if prompt:
|
117 |
+
st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑💻'})
|
118 |
+
st.session_state.prompt = prompt # Save the prompt in session state
|
119 |
+
st.session_state.log_messages = []
|
120 |
+
st.session_state.show_logs = False
|
121 |
+
with st.chat_message("user", avatar='🧑💻'):
|
122 |
+
print(f"Starting new question: {prompt}\n")
|
123 |
+
st.write(prompt)
|
124 |
+
st.session_state.ex_prompt = None
|
125 |
+
|
126 |
+
# Generate a new response if last message is not from assistant
|
127 |
+
if st.session_state.prompt:
|
128 |
+
with st.chat_message("assistant", avatar='🤖'):
|
129 |
+
with st.spinner(st.session_state.thinking_message):
|
130 |
+
res = st.session_state.agent.chat(st.session_state.prompt)
|
131 |
+
res = escape_dollars_outside_latex(res)
|
132 |
+
message = {"role": "assistant", "content": res, "avatar": '🤖'}
|
133 |
+
st.session_state.messages.append(message)
|
134 |
+
st.markdown(res)
|
135 |
+
|
136 |
+
send_amplitude_data(
|
137 |
+
user_query=st.session_state.messages[-2]["content"],
|
138 |
+
bot_response=st.session_state.messages[-1]["content"],
|
139 |
+
demo_name=cfg['demo_name']
|
140 |
+
)
|
141 |
+
|
142 |
+
st.session_state.ex_prompt = None
|
143 |
+
st.session_state.prompt = None
|
144 |
+
st.session_state.first_turn = False
|
145 |
+
st.rerun()
|
146 |
+
|
147 |
+
# Record user feedback
|
148 |
+
if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != initial_prompt):
|
149 |
+
if st.session_state.show_logs and st.session_state.logs_enabled: # Only show logs if enabled
|
150 |
+
streamlit_feedback(
|
151 |
+
feedback_type="thumbs", on_submit=thumbs_feedback, key=st.session_state.feedback_key,
|
152 |
+
kwargs={"user_query": st.session_state.messages[-2]["content"],
|
153 |
+
"bot_response": st.session_state.messages[-1]["content"],
|
154 |
+
"demo_name": cfg["demo_name"]}
|
155 |
+
)
|
156 |
+
|
157 |
+
log_placeholder = st.empty()
|
158 |
+
with log_placeholder.container():
|
159 |
+
if st.session_state.logs_enabled: # Show logs button only if log toggle is enabled
|
160 |
+
if st.session_state.show_logs:
|
161 |
+
st.button("Hide Logs", on_click=toggle_logs)
|
162 |
+
for msg in st.session_state.log_messages:
|
163 |
+
st.text(msg)
|
164 |
+
else:
|
165 |
+
if len(st.session_state.log_messages) > 0:
|
166 |
+
st.button("Show Logs", on_click=toggle_logs)
|
167 |
+
|
168 |
+
|
169 |
+
sys.stdout.flush()
|