Create app.py

app.py

@@ -0,0 +1,585 @@
+import os
+import pandas as pd
+import sqlite3
+import numpy as np
+import json
+import re
+from typing import List, Dict, Tuple
+from groq import Groq
+import gradio as gr
+from sklearn.metrics import accuracy_score
+import warnings
+warnings.filterwarnings('ignore')
+
+# ------------------------------
+# ✅ GROQ API KEY FROM ENVIRONMENT
+# ------------------------------
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+if not GROQ_API_KEY:
+    print("⚠️ WARNING: GROQ_API_KEY environment variable not set!")
+    print("Please add your Groq API key to your Hugging Face Space secrets.")
+    print("For demo purposes, the app will continue but API calls will fail.")
+    GROQ_API_KEY = "dummy-key-for-demo"
+
+# ------------------------------
+# SQL Converter Using Groq API
+# ------------------------------
+
+class EnhancedNL2SQLConverter:
+    def __init__(self, model_name: str = "llama3-70b-8192"):
+        self.model_name = model_name
+        self.client = None
+        
+        try:
+            if GROQ_API_KEY and GROQ_API_KEY != "dummy-key-for-demo":
+                self.client = Groq(api_key=GROQ_API_KEY)
+                print(f"✅ Successfully initialized Groq client with model: {self.model_name}")
+            else:
+                print("⚠️ Groq client not initialized - API key missing")
+        except Exception as e:
+            print(f"❌ Error initializing Groq client: {str(e)}")
+            self.client = None
+
+        self.default_schema = """
+        Table: employees
+        Columns:
+        - id (INTEGER) PRIMARY KEY
+        - name (TEXT) NOT NULL
+        - department (TEXT)
+        - salary (REAL)
+        - hire_date (TEXT)
+        - manager_id (INTEGER)
+        """
+
+    def generate_sql(self, query: str, schema: str = None) -> str:
+        try:
+            if not self.client:
+                return "ERROR: Groq API client not initialized. Please check your API key."
+            
+            schema_to_use = schema or self.default_schema
+
+            system_prompt = """You are an expert SQL query generator. Convert natural language questions to SQL queries based on the provided database schema.
+
+Rules:
+1. Only return the SQL query, nothing else
+2. Use proper SQL syntax
+3. Be precise with column names and table names
+4. Use appropriate WHERE clauses, JOINs, and aggregations as needed
+5. For date comparisons, use proper date format
+6. Don't include explanations, just the SQL query"""
+
+            user_prompt = f"""Database Schema:
+{schema_to_use}
+
+Natural Language Question: {query}
+
+Generate the SQL query:"""
+
+            chat_completion = self.client.chat.completions.create(
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": user_prompt}
+                ],
+                model=self.model_name,
+                temperature=0.1,
+                max_tokens=200
+            )
+
+            sql_query = chat_completion.choices[0].message.content.strip()
+            return self._clean_sql(sql_query)
+
+        except Exception as e:
+            print(f"Error generating SQL: {str(e)}")
+            return f"ERROR: Could not generate SQL query - {str(e)}"
+
+    def _clean_sql(self, sql: str) -> str:
+        sql = sql.strip()
+        sql = re.sub(r'```sql\n?', '', sql)
+        sql = re.sub(r'```\n?', '', sql)
+        sql = re.sub(r'^["\']|["\']$', '', sql)
+        sql = sql.rstrip(';')
+
+        sql_keywords = ['SELECT', 'INSERT', 'UPDATE', 'DELETE', 'CREATE', 'DROP', 'ALTER']
+        if not any(sql.upper().startswith(keyword) for keyword in sql_keywords):
+            for keyword in sql_keywords:
+                if keyword in sql.upper():
+                    sql = sql[sql.upper().find(keyword):]
+                    break
+        return sql
+
+# ------------------------------
+# SQL Evaluator & Test Database
+# ------------------------------
+
+class SQLEvaluator:
+    def __init__(self):
+        self.db_path = "test_database.db"
+        self.setup_test_database()
+
+    def setup_test_database(self):
+        conn = sqlite3.connect(self.db_path)
+        cursor = conn.cursor()
+        
+        cursor.execute('''
+        CREATE TABLE IF NOT EXISTS employees (
+            id INTEGER PRIMARY KEY,
+            name TEXT NOT NULL,
+            department TEXT,
+            salary REAL,
+            hire_date TEXT,
+            manager_id INTEGER
+        )''')
+        
+        sample_data = [
+            (1, 'Alice Johnson', 'Engineering', 75000, '2022-01-15', None),
+            (2, 'Bob Smith', 'Sales', 65000, '2021-06-20', None),
+            (3, 'Charlie Brown', 'Engineering', 80000, '2020-03-10', 1),
+            (4, 'Diana Prince', 'HR', 60000, '2023-02-28', None),
+            (5, 'Eve Wilson', 'Sales', 70000, '2022-11-05', 2),
+            (6, 'Frank Miller', 'Engineering', 85000, '2019-08-12', 1),
+            (7, 'Grace Lee', 'Marketing', 55000, '2023-01-20', None),
+            (8, 'Henry Davis', 'Engineering', 72000, '2022-07-30', 1)
+        ]
+        
+        cursor.executemany('''
+        INSERT OR REPLACE INTO employees (id, name, department, salary, hire_date, manager_id)
+        VALUES (?, ?, ?, ?, ?, ?)''', sample_data)
+        
+        conn.commit()
+        conn.close()
+        print("✅ Test database initialized successfully")
+
+    def execute_sql(self, sql_query: str) -> Tuple[bool, any]:
+        try:
+            conn = sqlite3.connect(self.db_path)
+            cursor = conn.cursor()
+            cursor.execute(sql_query)
+
+            if sql_query.strip().upper().startswith('SELECT'):
+                results = cursor.fetchall()
+                columns = [description[0] for description in cursor.description]
+                conn.close()
+                return True, {'columns': columns, 'data': results}
+            else:
+                conn.commit()
+                conn.close()
+                return True, "Query executed successfully"
+        except Exception as e:
+            return False, str(e)
+
+# ------------------------------
+# Initialize components
+# ------------------------------
+try:
+    converter = EnhancedNL2SQLConverter()
+    evaluator = SQLEvaluator()
+    print("✅ Application components initialized successfully")
+except Exception as e:
+    print(f"❌ Error initializing components: {str(e)}")
+    converter = None
+    evaluator = SQLEvaluator()
+
+# ------------------------------
+# Enhanced UI Functions
+# ------------------------------
+
+def process_nl_query(nl_query: str) -> Tuple[str, str, str]:
+    """Process natural language query and return SQL + results"""
+    if not nl_query.strip():
+        return "", "", "⚠️ Please enter a natural language query."
+    
+    try:
+        if not converter:
+            return "", "", "❌ Error: SQL converter not initialized. Please check API configuration."
+        
+        generated_sql = converter.generate_sql(nl_query)
+        
+        if generated_sql.startswith("ERROR"):
+            return generated_sql, "", "❌ Failed to generate SQL query. Please check your API key."
+        
+        success, result = evaluator.execute_sql(generated_sql)
+        
+        if success and isinstance(result, dict):
+            df = pd.DataFrame(result['data'], columns=result['columns'])
+            if len(df) == 0:
+                formatted_output = "No results found."
+            else:
+                formatted_output = df.to_string(index=False)
+            return generated_sql, formatted_output, "✅ Query executed successfully!"
+        elif success:
+            return generated_sql, str(result), "✅ Query executed successfully!"
+        else:
+            return generated_sql, "", f"❌ Error executing query: {result}"
+            
+    except Exception as e:
+        return "", "", f"❌ Unexpected error: {str(e)}"
+
+def get_sample_queries():
+    return [
+        "Show all employees in the Engineering department",
+        "Find employees with salary greater than 70000",
+        "List all employees hired after 2022",
+        "Count employees by department",
+        "Show the highest paid employee in each department",
+        "Find employees who don't have a manager",
+        "Show average salary by department"
+    ]
+
+# ------------------------------
+# Beautiful Custom CSS
+# ------------------------------
+
+custom_css = """
+/* Main container styling */
+.gradio-container {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    min-height: 100vh;
+    font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif;
+}
+
+/* Header styling */
+.header-container {
+    background: rgba(255, 255, 255, 0.1);
+    backdrop-filter: blur(20px);
+    border-radius: 20px;
+    padding: 2rem;
+    margin-bottom: 2rem;
+    border: 1px solid rgba(255, 255, 255, 0.2);
+    box-shadow: 0 8px 32px rgba(31, 38, 135, 0.37);
+}
+
+/* Card styling */
+.card {
+    background: rgba(255, 255, 255, 0.95);
+    backdrop-filter: blur(20px);
+    border-radius: 16px;
+    padding: 1.5rem;
+    margin: 1rem 0;
+    border: 1px solid rgba(255, 255, 255, 0.3);
+    box-shadow: 0 8px 32px rgba(31, 38, 135, 0.15);
+    transition: all 0.3s ease;
+}
+
+.card:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 12px 40px rgba(31, 38, 135, 0.25);
+}
+
+/* Input styling */
+.gr-textbox {
+    border-radius: 12px !important;
+    border: 2px solid rgba(103, 126, 234, 0.3) !important;
+    background: rgba(255, 255, 255, 0.9) !important;
+    transition: all 0.3s ease !important;
+}
+
+.gr-textbox:focus {
+    border-color: #667eea !important;
+    box-shadow: 0 0 0 3px rgba(103, 126, 234, 0.1) !important;
+    transform: scale(1.02);
+}
+
+/* Button styling */
+.gr-button {
+    background: linear-gradient(45deg, #667eea, #764ba2) !important;
+    border: none !important;
+    border-radius: 12px !important;
+    padding: 12px 24px !important;
+    font-weight: 600 !important;
+    color: white !important;
+    transition: all 0.3s ease !important;
+    box-shadow: 0 4px 15px rgba(103, 126, 234, 0.4) !important;
+}
+
+.gr-button:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 8px 25px rgba(103, 126, 234, 0.6) !important;
+}
+
+.sample-btn {
+    background: linear-gradient(45deg, #f093fb, #f5576c) !important;
+    margin: 0.25rem !important;
+    font-size: 0.9rem !important;
+    padding: 8px 16px !important;
+}
+
+.sample-btn:hover {
+    background: linear-gradient(45deg, #f5576c, #f093fb) !important;
+}
+
+/* Results area styling */
+.results-container {
+    background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);
+    border-radius: 16px;
+    padding: 1.5rem;
+    margin-top: 1rem;
+}
+
+/* Status indicators */
+.status-success {
+    color: #10b981 !important;
+    font-weight: 600 !important;
+}
+
+.status-error {
+    color: #ef4444 !important;
+    font-weight: 600 !important;
+}
+
+.status-warning {
+    color: #f59e0b !important;
+    font-weight: 600 !important;
+}
+
+/* Schema box */
+.schema-box {
+    background: linear-gradient(135deg, #ffecd2 0%, #fcb69f 100%);
+    border-radius: 12px;
+    padding: 1rem;
+    font-family: 'Monaco', 'Consolas', monospace;
+    border-left: 4px solid #f59e0b;
+}
+
+/* Animation keyframes */
+@keyframes fadeInUp {
+    from {
+        opacity: 0;
+        transform: translateY(30px);
+    }
+    to {
+        opacity: 1;
+        transform: translateY(0);
+    }
+}
+
+.fade-in {
+    animation: fadeInUp 0.6s ease-out;
+}
+
+/* Responsive design */
+@media (max-width: 768px) {
+    .gradio-container {
+        padding: 1rem;
+    }
+    
+    .card {
+        padding: 1rem;
+        margin: 0.5rem 0;
+    }
+}
+
+/* Loading spinner */
+.loading {
+    display: inline-block;
+    width: 20px;
+    height: 20px;
+    border: 3px solid rgba(255,255,255,.3);
+    border-radius: 50%;
+    border-top-color: #fff;
+    animation: spin 1s ease-in-out infinite;
+}
+
+@keyframes spin {
+    to { transform: rotate(360deg); }
+}
+"""
+
+# ------------------------------
+# Enhanced Gradio Interface
+# ------------------------------
+
+with gr.Blocks(css=custom_css, title="AI-Powered NL2SQL Converter", theme=gr.themes.Glass()) as iface:
+    # Header Section
+    with gr.Row(elem_classes="header-container fade-in"):
+        gr.HTML("""
+        <div style="text-align: center; color: white;">
+            <h1 style="font-size: 3rem; margin-bottom: 0.5rem; background: linear-gradient(45deg, #fff, #f0f0f0); -webkit-background-clip: text; -webkit-text-fill-color: transparent;">
+                🚀 AI-Powered NL2SQL Converter
+            </h1>
+            <p style="font-size: 1.2rem; opacity: 0.9; margin-bottom: 1rem;">
+                Transform natural language into powerful SQL queries using Groq's advanced AI
+            </p>
+            <div style="display: flex; justify-content: center; gap: 2rem; margin-top: 1rem;">
+                <div style="text-align: center;">
+                    <div style="font-size: 2rem;">🤖</div>
+                    <div style="font-size: 0.9rem; opacity: 0.8;">AI-Powered</div>
+                </div>
+                <div style="text-align: center;">
+                    <div style="font-size: 2rem;">⚡</div>
+                    <div style="font-size: 0.9rem; opacity: 0.8;">Lightning Fast</div>
+                </div>
+                <div style="text-align: center;">
+                    <div style="font-size: 2rem;">🎯</div>
+                    <div style="font-size: 0.9rem; opacity: 0.8;">Precise Results</div>
+                </div>
+            </div>
+        </div>
+        """)
+    
+    # Database Schema Section
+    with gr.Row(elem_classes="card fade-in"):
+        gr.HTML("""
+        <div class="schema-box">
+            <h3 style="color: #d97706; margin-bottom: 1rem;">📊 Database Schema</h3>
+            <div style="background: rgba(255,255,255,0.7); padding: 1rem; border-radius: 8px;">
+                <strong>employees</strong> table:<br>
+                • <code>id</code> (INTEGER) - Primary Key<br>
+                • <code>name</code> (TEXT) - Employee Name<br>
+                • <code>department</code> (TEXT) - Department<br>
+                • <code>salary</code> (REAL) - Salary Amount<br>
+                • <code>hire_date</code> (TEXT) - Hiring Date<br>
+                • <code>manager_id</code> (INTEGER) - Manager Reference
+            </div>
+        </div>
+        """)
+    
+    # Main Input Section
+    with gr.Row(elem_classes="card fade-in"):
+        with gr.Column(scale=3):
+            nl_input = gr.Textbox(
+                label="💬 Ask your question in plain English",
+                placeholder="e.g., Show me all engineers earning more than $75,000",
+                lines=3,
+                elem_classes="main-input"
+            )
+            
+            with gr.Row():
+                submit_btn = gr.Button(
+                    "🔮 Generate & Execute SQL", 
+                    variant="primary",
+                    size="lg",
+                    elem_classes="main-button"
+                )
+                clear_btn = gr.Button(
+                    "🗑️ Clear", 
+                    variant="secondary",
+                    size="lg"
+                )
+        
+        with gr.Column(scale=2):
+            gr.HTML("<h3 style='color: #667eea; margin-bottom: 1rem;'>🎯 Try These Examples</h3>")
+            
+            sample_queries = get_sample_queries()
+            for i, query in enumerate(sample_queries):
+                sample_btn = gr.Button(
+                    f"💡 {query}",
+                    variant="secondary",
+                    size="sm",
+                    elem_classes="sample-btn"
+                )
+                sample_btn.click(
+                    lambda q=query: q,
+                    outputs=nl_input
+                )
+    
+    # Results Section
+    with gr.Row(elem_classes="results-container fade-in"):
+        with gr.Column():
+            gr.HTML("<h3 style='color: #6366f1; margin-bottom: 1rem;'>📝 Generated SQL Query</h3>")
+            sql_output = gr.Code(
+                label="",
+                language="sql",
+                lines=4,
+                interactive=False,
+                elem_classes="sql-output"
+            )
+            
+            status_output = gr.HTML(
+                "<div style='padding: 1rem; text-align: center; font-size: 1.1rem;'>Ready to process your query! 🚀</div>"
+            )
+    
+    with gr.Row(elem_classes="card fade-in"):
+        gr.HTML("<h3 style='color: #059669; margin-bottom: 1rem;'>📊 Query Results</h3>")
+        results_output = gr.Code(
+            label="",
+            lines=12,
+            interactive=False,
+            elem_classes="results-output"
+        )
+    
+    # Footer Section
+    with gr.Row(elem_classes="card fade-in"):
+        gr.HTML("""
+        <div style="text-align: center; padding: 1rem;">
+            <h3 style="color: #667eea; margin-bottom: 1rem;">🔍 About This Application</h3>
+            <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 1rem; margin-top: 1rem;">
+                <div style="background: linear-gradient(135deg, #667eea, #764ba2); color: white; padding: 1rem; border-radius: 12px;">
+                    <h4>🤖 AI Model</h4>
+                    <p>Powered by Groq's Llama3-70B for intelligent SQL generation</p>
+                </div>
+                <div style="background: linear-gradient(135deg, #f093fb, #f5576c); color: white; padding: 1rem; border-radius: 12px;">
+                    <h4>💾 Database</h4>
+                    <p>SQLite with sample employee data for testing and learning</p>
+                </div>
+                <div style="background: linear-gradient(135deg, #a8edea, #fed6e3); color: #374151; padding: 1rem; border-radius: 12px;">
+                    <h4>✨ Features</h4>
+                    <p>Natural language processing, SQL execution, and formatted results</p>
+                </div>
+            </div>
+            <div style="margin-top: 2rem; padding: 1rem; background: rgba(103, 126, 234, 0.1); border-radius: 12px;">
+                <h4 style="color: #667eea;">💡 Pro Tips for Better Results</h4>
+                <ul style="text-align: left; display: inline-block; color: #4b5563;">
+                    <li>Be specific and clear in your questions</li>
+                    <li>Use column names mentioned in the schema</li>
+                    <li>Try the sample queries to understand the format</li>
+                    <li>Use natural language - no need for technical jargon</li>
+                </ul>
+            </div>
+        </div>
+        """)
+    
+    # Event Handlers with Enhanced Feedback
+    def enhanced_process(query):
+        if not query.strip():
+            return "", "<div class='status-warning'>⚠️ Please enter a question first!</div>", ""
+        
+        # Show loading state
+        loading_html = "<div class='status-info'>🔄 Processing your query... <span class='loading'></span></div>"
+        
+        try:
+            sql, results, status = process_nl_query(query)
+            
+            # Enhanced status formatting
+            if "successfully" in status.lower():
+                status_html = f"<div class='status-success'>{status}</div>"
+            elif "error" in status.lower() or "failed" in status.lower():
+                status_html = f"<div class='status-error'>{status}</div>"
+            else:
+                status_html = f"<div class='status-warning'>{status}</div>"
+            
+            return sql, status_html, results
+            
+        except Exception as e:
+            return "", f"<div class='status-error'>❌ Unexpected error: {str(e)}</div>", ""
+    
+    def clear_all():
+        return "", "", "<div style='padding: 1rem; text-align: center; font-size: 1.1rem;'>Ready to process your query! 🚀</div>", ""
+    
+    # Connect events
+    submit_btn.click(
+        fn=enhanced_process,
+        inputs=[nl_input],
+        outputs=[sql_output, status_output, results_output]
+    )
+    
+    nl_input.submit(
+        fn=enhanced_process,
+        inputs=[nl_input],
+        outputs=[sql_output, status_output, results_output]
+    )
+    
+    clear_btn.click(
+        fn=clear_all,
+        outputs=[nl_input, sql_output, status_output, results_output]
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    print("🚀 Launching Enhanced NL2SQL Application...")
+    iface.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,
+        show_error=True
+    )