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alejandro
commited on
Commit
·
c796379
1
Parent(s):
ec96023
feat: create chain that returns sql query
Browse files- src/app.py +64 -4
src/app.py
CHANGED
@@ -1,13 +1,57 @@
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import streamlit as st
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from langchain_community.utilities import SQLDatabase
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def initialize_database(host, port, username, password, database):
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db_uri = f"mysql+mysqlconnector://{username}:{password}@{host}:{port}/{database}"
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return SQLDatabase.from_uri(db_uri)
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st.set_page_config(initial_sidebar_state="expanded", page_title="Chat with a MySQL Database", page_icon=":speech_balloon:")
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with st.sidebar:
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st.title("Chat with a MySQL Database")
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st.write("This is a simple chat application allows you to chat with a MySQL database.")
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if st.button("Connect"):
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with st.spinner("Connecting to the database..."):
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db = initialize_database(
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username=st.session_state.username,
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password=st.session_state.password,
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host=st.session_state.name,
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port=st.session_state.port,
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database=st.session_state.database
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)
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st.
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user_query = st.chat_input("Type a message...")
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if user_query != "":
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-
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import streamlit as st
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from langchain_community.utilities import SQLDatabase
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.runnables import RunnablePassthrough
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage, AIMessage
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from dotenv import load_dotenv
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def initialize_database(host, port, username, password, database):
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db_uri = f"mysql+mysqlconnector://{username}:{password}@{host}:{port}/{database}"
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return SQLDatabase.from_uri(db_uri)
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def get_response(user_query, chat_history, db):
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from langchain_core.prompts import ChatPromptTemplate
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template = """
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Based on the table schema below, write a SQL query that would answer the user's question.
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{schema}
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Question: {question}
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SQL Query:
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"""
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prompt = ChatPromptTemplate.from_template(template)
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llm = ChatOpenAI()
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def get_schema(_):
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return db.get_table_info()
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sql_chain = (
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RunnablePassthrough.assign(schema=get_schema)
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| prompt
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| llm.bind(stop="\nSQL Result:")
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| StrOutputParser()
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)
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return sql_chain.invoke({
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"question": user_query
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})
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load_dotenv()
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st.set_page_config(initial_sidebar_state="expanded", page_title="Chat with a MySQL Database", page_icon=":speech_balloon:")
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if 'chat_history' not in st.session_state:
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st.session_state.chat_history = [
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AIMessage(content="")
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]
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if 'db' not in st.session_state:
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st.session_state.db = None
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with st.sidebar:
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st.title("Chat with a MySQL Database")
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st.write("This is a simple chat application allows you to chat with a MySQL database.")
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if st.button("Connect"):
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with st.spinner("Connecting to the database..."):
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st.session_state.db = initialize_database(
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username=st.session_state.username,
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password=st.session_state.password,
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host=st.session_state.name,
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port=st.session_state.port,
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database=st.session_state.database
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)
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if st.session_state.db is not None:
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st.success("Connected to the database!")
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user_query = st.chat_input("Type a message...")
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if user_query is not None and user_query != "":
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st.session_state.chat_history.append(HumanMessage(content=user_query))
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with st.chat_message("Human"):
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st.markdown(user_query)
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with st.chat_message("AI"):
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response = get_response(
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user_query,
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st.session_state.chat_history,
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st.session_state.db
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)
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print(f"Response generated: {response}")
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st.markdown(response)
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st.session_state.chat_history.append(AIMessage(content=response))
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