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import os |
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import streamlit as st |
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from transformers import AutoTokenizer |
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from snowflake.ml.utils.connection_params import SnowflakeLoginOptions |
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from langchain_community.utilities import SQLDatabase |
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from langchain.llms import HuggingFaceHub |
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from langchain.chains import create_sql_query_chain |
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@st.cache_resource(show_spinner="Connecting...") |
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def getSession(): |
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pars = SnowflakeLoginOptions("test_conn") |
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pars["account"] ="ap20346.ap-south-1" |
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pars["user"] = "Vassist" |
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pars["password"]= "Vassist@123" |
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pars["role"]= "ACCOUNTADMIN" |
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pars["warehouse"] = "COMPUTE_WH" |
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pars["database"] = "SNOWFLAKE_SAMPLE_DATA" |
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pars["schema"] = "TPCH_SF1" |
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session = Session.builder.configs(pars).create() |
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url = (f"snowflake://{pars['user']}:{pars['password']}@{pars['account']}" |
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+ f"/{pars['database']}/{pars['schema']}" |
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+ f"?warehouse={pars['warehouse']}&role={pars['role']}") |
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db = SQLDatabase.from_uri(url) |
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os.environ["HUGGINGFACEHUB_API_TOKEN"] ='HUGGINGFACEHUB_API_TOKEN' |
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llm = HuggingFaceHub(repo_id= "ravithejakandi/Sf-Arctic-Demo-Enu") |
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chain = create_sql_query_chain(llm, db) |
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return session, db, chain |
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st.title("SQL Query Generator") |
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st.write("Returns and runs queries from questions in natural language.") |
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session, db, chain = getSession() |
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question = st.sidebar.text_area("Ask a question:", |
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value="Show me the total number of entries in the first table") |
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sql = chain.invoke({"question": question}).rstrip(';') |
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tabQuery, tabData, tabLog = st.tabs(["Query", "Data", "Log"]) |
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tabQuery.code(sql, language="sql") |
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tabData.dataframe(session.sql(sql)) |
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tabLog.code(db.table_info, language="sql") |
