108 lines
3.0 KiB
Python
108 lines
3.0 KiB
Python
import streamlit as st
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import time
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from backend import orquestrador
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import boto3
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from boto3.dynamodb.conditions import Key
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# Configure the page - MUST BE FIRST
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st.set_page_config(
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page_title="Chatbot",
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page_icon="💬",
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layout="centered"
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)
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session = boto3.Session()
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dynamodb = boto3.resource("dynamodb", region_name=orquestrador.REGION)
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def list_bases():
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table = dynamodb.Table("poc_dnx_monthly_summary")
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response = table.query(
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IndexName="item_type_index",
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KeyConditionExpression=Key("item_type").eq("contexto")
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)
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return [item["id"].removesuffix("_contexto") for item in response.get("Items", [])]
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# Model selection with session state persistence
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MODELS = [
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"anthropic.claude-haiku-4-5-20251001-v1:0",
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"anthropic.claude-sonnet-4-5-20250929-v1:0",
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"meta.llama4-maverick-17b-instruct-v1:0",
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"meta.llama4-scout-17b-instruct-v1:0",
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"amazon.nova-lite-v1:0",
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"amazon.nova-pro-v1:0",
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"amazon.nova-2-lite-v1:0"
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]
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selected_value = st.selectbox(
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"Selecione o modelo:",
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MODELS,
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key="selected_model"
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)
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BASES = list_bases()
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BASES.sort()
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base = st.selectbox(
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"Selecione a base:",
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BASES,
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key="selected_base"
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)
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# Initialize chat history in session state
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if "messages" not in st.session_state:
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st.session_state.messages = []
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# Display title
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st.title("💬 Chatbot")
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# Display chat history
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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# Chat input
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if prompt := st.chat_input("Type your message here..."):
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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# Display user message
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with st.chat_message("user"):
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st.markdown(prompt)
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# Display assistant response
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with st.chat_message("assistant"):
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message_placeholder = st.empty()
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# Simulate streaming response (replace with actual API call)
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result = orquestrador.main(prompt,str(st.session_state.messages),selected_value,base)
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full_response = result["response"]
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# Simulate typing effect
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displayed_response = ""
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for char in full_response:
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displayed_response += char
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message_placeholder.markdown(displayed_response + "▌")
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time.sleep(0.01)
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message_placeholder.markdown(full_response)
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st.caption(f"Tokens: {result['input_tokens']} in / {result['output_tokens']} out / {result['total_tokens']} total")
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# Add assistant response to chat history
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st.session_state.messages.append({"role": "assistant", "content": full_response})
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# Add a sidebar with options
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with st.sidebar:
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st.header("Options")
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if st.button("Clear Chat History"):
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st.session_state.messages = []
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st.rerun()
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st.divider()
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st.markdown("""
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### How to use:
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1. Type your message in the input box
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2. Press Enter or click Send
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3. View the conversation history
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""") |