Create app.py

app.py

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+# Import required libraries
+import os
+import openai
+import streamlit as st
+import pandas as pd
+from sqlalchemy import create_engine, text
+from PIL import Image
+from dotenv import load_dotenv
+# Load environment variables from .env file
+load_dotenv()
+
+temp_db = create_engine('sqlite:///:memory:', echo=True)
+
+# Function to create table definition prompt
+def create_table_definition_prompt(col_input):
+    prompt = '''### sqlite SQL table, with its properties:
+#
+# Sales({})
+#
+'''.format(",".join(str(x) for x in col_input))
+    return prompt
+
+
+# Function to combine prompts
+def combine_prompts(col_input, query_prompt):
+    definition = create_table_definition_prompt(col_input)
+    query_init_string = f"### A query to answer: {query_prompt}\nSELECT"
+    return definition + query_init_string
+
+
+# Function to execute SQL query
+def get_sql(nlp_text, field_input):
+    print(nlp_text)
+    print(field_input)
+    response = openai.Completion.create(
+        model="text-davinci-003",
+        prompt=combine_prompts(field_input, nlp_text),
+        temperature=0,
+        max_tokens=150,
+        top_p=1.0,
+        frequency_penalty=0.0,
+        presence_penalty=0.0,
+        stop=["#", ";"]
+    )
+    query = response["choices"][0]["text"]
+    if query.startswith(" "):
+        query = "SELECT" + query
+    with temp_db.connect() as conn:
+        result = conn.execute(text(query))
+    return result.all()
+
+
+# Read CSV file into DataFrame
+def read_csv_file(uploaded_file):
+    try:
+        df = pd.read_csv(uploaded_file, encoding="latin1")
+        with temp_db.connect() as conn:
+            df.to_sql(name='Sales', con=conn, if_exists='replace', index=False)
+        return df
+    except Exception as e:
+        st.error(f"Error occurred while reading the CSV file: {str(e)}")
+        return None
+
+
+# Configure Streamlit page layout and title
+st.set_page_config(
+    page_title="Query Builder",
+    layout="wide",
+    page_icon=":bar_chart:"
+)
+
+# Set OpenAI API key
+api_key = os.getenv('OPENAI_API_KEY')
+#api_key = os.environ.get('OPENAI_API_KEY')
+openai.api_key = api_key
+
+# Add CSS styles
+st.markdown(
+    """
+    <style>
+    .front-page {
+        background-color: #f5f5f5;
+        padding: 20px;
+        border-radius: 10px;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+hide_streamlit_style = """
+<style>
+#MainMenu {visibility: hidden;}
+footer {visibility: hidden;}
+</style>
+"""
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)
+
+col1, col2 = st.columns([1, 2])
+with col1:
+    pass
+with col2:
+    image = Image.open('D:/vscode/qb/data/comsense-Logo2.png')
+    resized_image = image.resize((1200, 400))  # Adjust the size as per your requirement
+    st.image(resized_image, width=180)
+
+# Front page content
+st.title(":bar_chart: Query Builder")
+#st.markdown('<div class="front-page">', unsafe_allow_html=True)
+st.title("Please write your *Query* Here :arrow_down_small:")
+input_value = st.text_input("", " ")
+st.markdown('</div>', unsafe_allow_html=True)
+
+# Sidebar - CSV file upload
+uploaded_file = st.sidebar.file_uploader("Upload CSV File")
+
+# Process uploaded CSV file
+if uploaded_file is not None:
+    df = read_csv_file(uploaded_file)
+    if df is not None:
+        st.sidebar.dataframe(df)
+
+    # Execute SQL query and display result
+    if st.button("Run Query"):
+        if uploaded_file is not None and df is not None:
+            try:
+                field_input =df.columns
+                final_result = get_sql(input_value, field_input)
+                output_column, _ = st.columns(2)
+                with output_column:
+                    st.title("Output")
+                    if isinstance(final_result, list):
+                        final_result = pd.DataFrame(final_result)
+                    show_data = st.dataframe(final_result.style.set_properties(**{'font-size': '12px', 'text-align': 'center'}))
+            except Exception as e:
+               st.error("Please try again with simple sentence.")
+else:
+    st.warning("Please upload a valid CSV file first.")