{"id":36461,"date":"2025-03-25T20:02:02","date_gmt":"2025-03-25T14:32:02","guid":{"rendered":"https:\/\/mobisoftinfotech.com\/resources\/?p=36461"},"modified":"2025-11-06T13:19:03","modified_gmt":"2025-11-06T07:49:03","slug":"conversational-analytics-sql-ai-agent-database","status":"publish","type":"post","link":"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/conversational-analytics-sql-ai-agent-database","title":{"rendered":"Conversational Analytics Tutorial: How to Implement SQL AI Agent that Speaks Database"},"content":{"rendered":"<p>AI agents are transforming how we engage with technology by efficiently analyzing data, making informed decisions, and automating complex processes with little human input. From virtual assistants like Siri and Alexa to self-driving cars and cutting-edge cybersecurity solutions, these intelligent systems enhance efficiency, precision, and adaptability across various industries. For businesses looking to explore<a href=\"https:\/\/mobisoftinfotech.com\/services\/artificial-intelligence\"> <strong>AI development services<\/strong><\/a>, these technologies can be key in shaping the future of their operations.<\/p>\n\n\n\n<p>In this blog, I\u2019ll guide you through building an SQLite AI agent that allows you to interact with an SQLite database using simple, natural language queries instead of writing complex SQL statements. This AI-powered agent will intelligently translate everyday language into SQL queries, making database interaction seamless for both developers and non-technical users, without the need to learn SQL syntax. We\u2019ll dive into the tools and technologies behind this project, focusing on how machine learning models can enhance the querying process and improve database management. If you want a strategic approach, consider exploring<a href=\"https:\/\/mobisoftinfotech.com\/services\/ai-strategy-consulting\"> <strong>AI strategy services<\/strong><\/a> to align your AI initiatives with broader business goals.<\/p>\n\n\n\n<p>To build this agent, we\u2019ll use the LangChain and Mistral 7B model running on Hugging Face, combining their strengths to transform natural language inputs into SQL queries, execute them, and fetch the results\u2014streamlining and speeding up your workflow. Let\u2019s dive into the process!<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 1: <strong>Create a New Project Directory<\/strong><\/strong><\/h2>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">mkdir sqlite_agent_project\ncd sqlite_agent_project<\/code><\/span><\/pre>\n\n\n<p><strong>Note:<\/strong> Ensure that the following prerequisites are installed on your Machine.&nbsp;&nbsp;<\/p>\n\n\n\n<p><strong>## Prerequisites<\/strong><\/p>\n\n\n\n<p>&#8211; Python 3.11 or higher<\/p>\n\n\n\n<p>&#8211; pip (Python package installer)<\/p>\n\n\n\n<p>&#8211; A HuggingFace account and API token<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/mobisoftinfotech.com\/services\/artificial-intelligence?utm_source=blog&amp;utm_medium=referral&amp;utm_campaign=conversational-analytics-sql-ai-agent-database-cta1\"><noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/most-of-businesses-adopting-ai.png\" alt=\"90% of businesses adopting AI: Don\u2019t miss out90% of businesses adopting AI: Don\u2019t miss out!!\" class=\"wp-image-36495\" title=\"90% of Businesses are Rushing to Adopt AI. You Should Too!\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20363%22%3E%3C%2Fsvg%3E\" alt=\"90% of businesses adopting AI: Don\u2019t miss out90% of businesses adopting AI: Don\u2019t miss out!!\" class=\"wp-image-36495 lazyload\" title=\"90% of Businesses are Rushing to Adopt AI. You Should Too!\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/most-of-businesses-adopting-ai.png\"><\/a><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 2: Create and Activate a Virtual Environment<\/strong><\/h2>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">&nbsp;python3 -m venv venv<\/code><\/span><\/pre>\n\n\n<ul class=\"wp-block-list\">\n<li>The above command creates a new virtual environment<\/li>\n\n\n\n<li>First venv is the Python module that creates virtual environments<\/li>\n\n\n\n<li>Second venv is the name of the directory where the environment will be created<\/li>\n\n\n\n<li>Creates an isolated Python environment with its own:\n<ul class=\"wp-block-list\">\n<li>Python interpreter<\/li>\n\n\n\n<li>pip package manager<\/li>\n\n\n\n<li>Standard library<\/li>\n\n\n\n<li>Site-packages directory<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">&nbsp;source venv\/bin\/activate<\/code><\/span><\/pre>\n\n\n<ul class=\"wp-block-list\">\n<li>The above&nbsp; command activates the virtual environment<\/li>\n\n\n\n<li>venv\/bin\/activate is the path to the activation script<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 3: <strong>Install the Required Dependencies<\/strong><\/strong><\/h2>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">pip install langchain langchain-community langchain-experimental langchain-huggingface python-dotenv sqlalchemy<\/code><\/span><\/pre>\n\n\n<p><strong>Here\u2019s a quick overview of the dependencies we&#8217;ll be using to build our SQLiteAgent:<\/strong><\/p>\n\n\n\n<p>1. <strong>LangChain Components<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>langchain<\/strong>: The main framework for building AI-driven applications, providing tools for natural language processing and interacting with various data sources, including SQL databases.<\/li>\n\n\n\n<li><strong>langchain-community<\/strong>: A collection of community-contributed tools to extend the functionality of LangChain.<\/li>\n\n\n\n<li><strong>langchain-experimental<\/strong>: A package that includes cutting-edge features and tools that are still in development.<\/li>\n\n\n\n<li><strong>langchain-huggingface<\/strong>: A module that integrates LangChain with HuggingFace models, allowing us to use pre-trained models for language tasks.<\/li>\n<\/ul>\n\n\n\n<p><strong>2. Supporting Packages<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>python-dotenv<\/strong>: A package that helps manage environment variables, making it easier to handle configuration in different environments.<\/li>\n\n\n\n<li><strong>sqlalchemy<\/strong>: A powerful library for SQL database operations, enabling interaction with SQLite and other SQL databases.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 4: <strong>In the Project Directory, Create a .env File and Add Your HuggingFace API Token<\/strong><\/strong><\/h2>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">HUGGINGFACE_API_TOKEN=your_token_here<\/code><\/span><\/pre>\n\n\n<p>You can generate a token from<a href=\"https:\/\/huggingface.co\/settings\/tokens\" target=\"_blank\" rel=\"noreferrer noopener\"> Hugging Face Tokens<\/a>. Ensure the token has the following permissions:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Make calls to Inference Providers<br><\/li>\n\n\n\n<li>Make calls to your Inference Endpoints<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 5: <strong>Building the SQLite Agent Script<\/strong><\/strong><\/h2>\n\n\n\n<p>Create a file named sqlite_agent.py and insert the following code.<\/p>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">import sqlite3\n\nfrom typing import List, Dict, Any\n\nfrom langchain_huggingface import HuggingFaceEndpoint\n\nfrom langchain_community.utilities import SQLDatabase\n\nfrom langchain_experimental.sql import SQLDatabaseChain\n\nimport os\n\nfrom dotenv import load_dotenv\n\nclass SQLiteAgent:\n\n&nbsp;&nbsp;&nbsp;&nbsp;def __init__(self, db_path: str):\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.db_path = db_path\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Load the Environment variables from .env file\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;load_dotenv()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Initialize the LLM with HuggingFace\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.llm = HuggingFaceEndpoint(\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;repo_id=\"mistralai\/Mistral-7B-Instruct-v0.2\",\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;task=\"text-generation\",\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;temperature=0.1,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;max_new_tokens=250,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;do_sample=False,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;model_kwargs={\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"max_length\": 512\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;},\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;huggingfacehub_api_token=os.getenv(\"HUGGINGFACE_API_TOKEN\"),\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;client_options={\"timeout\": 60.0}\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Initialize the database\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.db = SQLDatabase.from_uri(f\"sqlite:\/\/\/{db_path}\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Create the chain\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.chain = SQLDatabaseChain.from_llm(\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;llm=self.llm,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;db=self.db,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;verbose=True\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;)\n\n&nbsp;&nbsp;&nbsp;&nbsp;def query(self, question: str) -&gt; str:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"\"\"Execute a natural language query on the database.\"\"\"\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;try:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;result = self.chain.invoke({\"query\": question})\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return f\"Result: {result&#091;'result']}\"\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;except Exception as e:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return f\"Error executing query: {str(e)}\"\n\n&nbsp;&nbsp;&nbsp;&nbsp;def get_table_info(self) -&gt; List&#091;Dict&#091;str, Any]]:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"\"\"Retrieve information about all the tables in the database.\"\"\"\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;try:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;with sqlite3.connect(self.db_path) as conn:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor = conn.cursor()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor.execute(\"SELECT name FROM sqlite_master WHERE type='table';\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;tables = cursor.fetchall()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_info = &#091;]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;for table in tables:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_name = table&#091;0]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor.execute(f\"PRAGMA table_info({table_name});\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;columns = cursor.fetchall()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_info.append({\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"table_name\": table_name,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"columns\": &#091;col&#091;1] for col in columns]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;})\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return table_info\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;except Exception as e:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(f\"Error getting table info: {str(e)}\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;return &#091;]\n\nif __name__ == \"__main__\":\n\n&nbsp;&nbsp;&nbsp;&nbsp;# Initialize the agent with the existing database\n\n&nbsp;&nbsp;&nbsp;&nbsp;db_path = 'employee_database.db'\n\n&nbsp;&nbsp;&nbsp;&nbsp;if not os.path.exists(db_path):\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(f\"Error: Database file '{db_path}' not found!\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(\"Please make sure the employee_database.db file exists in the current directory.\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;exit(1)\n\n&nbsp;&nbsp;&nbsp;&nbsp;# Initialize the agent\n\n&nbsp;&nbsp;&nbsp;&nbsp;agent = SQLiteAgent(db_path)\n\n&nbsp;&nbsp;&nbsp;&nbsp;# Display table information\n\n&nbsp;&nbsp;&nbsp;&nbsp;table_info = agent.get_table_info()\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"\\nAvailable tables in the database:\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;for table in table_info:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(f\"\\nTable: {table&#091;'table_name']}\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(\"Columns:\", \", \".join(table&#091;'columns']))\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"\\nSQLite Agent initialized! You can ask questions about the database.\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"\\nExample questions:\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"- What is the average salary in the Engineering department?\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"- Who are all the employees in the Marketing department?\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"- What is the total number of employees?\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;print(\"\\nType 'exit' to quit.\\n\")\n\n&nbsp;&nbsp;&nbsp;&nbsp;while True:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;question = input(\"Your question: \")\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;if question.lower() == 'exit':\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;break\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;result = agent.query(question)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;print(result)<\/code><\/span><\/pre>\n\n\n<p>If you want to learn more about building AI agents, check out this<a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/build-ai-agents-crewai-framework\"> <strong>AI Agent Framework Tutorial: Building AI Agents using CrewAI<\/strong><\/a> for an in-depth look.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Let&#8217;s understand the code and see how our agent functions.<\/strong><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>The Imports and Their Purposes<\/strong><\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li><code>import sqlite3<\/code> \u2013 Handles SQLite database operations.<\/li>\n\n\n\n<li><code>from typing import List, Dict, Any<\/code> \u2013 Provides type hints for better code readability.<\/li>\n\n\n\n<li><code>from langchain_huggingface import HuggingFaceEndpoint<\/code> \u2013 Integrates Hugging Face models.<\/li>\n\n\n\n<li><code>from langchain_community.utilities import SQLDatabase<\/code> \u2013 Offers database utility functions.<\/li>\n\n\n\n<li><code>from langchain_experimental.sql import SQLDatabaseChain<\/code> \u2013 Manages SQL chain processing.<\/li>\n\n\n\n<li><code>import os<\/code> \u2013 Supports file and path operations.<\/li>\n\n\n\n<li><code>from dotenv import load_dotenv<\/code> \u2013 Manages environment variables.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Class Definition and HuggingFace Model Setup<\/strong><\/h4>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">class SQLiteAgent:\n\n&nbsp;&nbsp;&nbsp;&nbsp;def __init__(self, db_path: str):\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.db_path = db_path\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Load the Environment variables from .env file\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;load_dotenv()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;# Initialize the LLM with HuggingFace\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;self.llm = HuggingFaceEndpoint(\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;repo_id=\"mistralai\/Mistral-7B-Instruct-v0.2\",\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;task=\"text-generation\",\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;temperature=0.1,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;max_new_tokens=250,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;do_sample=False,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;model_kwargs={\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;\"max_length\": 512\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;},\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;huggingfacehub_api_token=os.getenv(\"HUGGINGFACE_API_TOKEN\"),\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;client_options={\"timeout\": 60.0}\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;)\n\n...<\/code><\/span><\/pre>\n\n\n<p><strong>In the above code block, we perform the following operations:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Load environment variables from the <code>.env<\/code> file.<\/li>\n\n\n\n<li>Initialize the LLM using Hugging Face.<\/li>\n\n\n\n<li>Set the model to <code>Mistral-7B-Instruct-v0.2<\/code>.<\/li>\n\n\n\n<li>Define parameters to control the model&#8217;s behavior:\n<ul class=\"wp-block-list\">\n<li>Perform a text generation task<\/li>\n\n\n\n<li>Set a low temperature (0.1) for precision<\/li>\n\n\n\n<li>Limit the generation to a maximum of 250 new tokens<\/li>\n\n\n\n<li>Disable sampling for consistency<\/li>\n\n\n\n<li>Set a total length limit of 512 tokens.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>Retrieve and set <code>huggingfacehub_api_token<\/code> value from the .env file.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Initialize the Database and Chain setup&nbsp;<\/strong><\/h4>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-1\" data-shcb-language-name=\"PHP\" data-shcb-language-slug=\"php\"><span><code class=\"hljs language-php\"><span class=\"hljs-comment\"># Initialize the database<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">self<\/span>.db = SQLDatabase.from_uri(f<span class=\"hljs-string\">\"sqlite:\/\/\/{db_path}\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\"># Create the chain<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">self<\/span>.chain = SQLDatabaseChain.from_llm(\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;llm=<span class=\"hljs-keyword\">self<\/span>.llm,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;db=<span class=\"hljs-keyword\">self<\/span>.db,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;verbose=<span class=\"hljs-keyword\">True<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;)&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-1\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">PHP<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">php<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>In the above code block, we are initializing the database and creating the processing chain.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Query Method<\/strong><\/h4>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-2\" data-shcb-language-name=\"PHP\" data-shcb-language-slug=\"php\"><span><code class=\"hljs language-php\">def query(<span class=\"hljs-keyword\">self<\/span>, question: str) -&gt; str:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-string\">\"\"<\/span><span class=\"hljs-string\">\"Execute a natural language query on the database.\"<\/span><span class=\"hljs-string\">\"\"<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">try<\/span>:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;result = <span class=\"hljs-keyword\">self<\/span>.chain.invoke({<span class=\"hljs-string\">\"query\"<\/span>: question})\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">return<\/span> f<span class=\"hljs-string\">\"Result: {result&#091;'result']}\"<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;except <span class=\"hljs-keyword\">Exception<\/span> <span class=\"hljs-keyword\">as<\/span> e:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">return<\/span> f<span class=\"hljs-string\">\"Error executing query: {str(e)}\"<\/span>&nbsp;&nbsp;&nbsp;&nbsp;<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-2\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">PHP<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">php<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>The query method takes a natural language question and processes it by sending it to the AI model, which converts the question into SQL. The SQL query is then executed on the database, and the result is returned.<\/p>\n\n\n\n<p><strong>The flow is as follows:<\/strong> Question \u2192 AI \u2192 SQL \u2192 Database \u2192 Answer.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Table Information Method<\/strong><\/h4>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-3\" data-shcb-language-name=\"PHP\" data-shcb-language-slug=\"php\"><span><code class=\"hljs language-php\">def get_table_info(<span class=\"hljs-keyword\">self<\/span>) -&gt; <span class=\"hljs-keyword\">List<\/span>&#091;Dict&#091;str, Any]]:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-string\">\"\"<\/span><span class=\"hljs-string\">\"Retrieve information about all the tables in the database.\"<\/span><span class=\"hljs-string\">\"\"<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">try<\/span>:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;with sqlite3.connect(<span class=\"hljs-keyword\">self<\/span>.db_path) <span class=\"hljs-keyword\">as<\/span> conn:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor = conn.cursor()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor.execute(<span class=\"hljs-string\">\"SELECT name FROM sqlite_master WHERE type='table';\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;tables = cursor.fetchall()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_info = &#091;]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">for<\/span> table in tables:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_name = table&#091;<span class=\"hljs-number\">0<\/span>]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;cursor.execute(f<span class=\"hljs-string\">\"PRAGMA table_info({table_name});\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;columns = cursor.fetchall()\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;table_info.append({\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-string\">\"table_name\"<\/span>: table_name,\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-string\">\"columns\"<\/span>: &#091;col&#091;<span class=\"hljs-number\">1<\/span>] <span class=\"hljs-keyword\">for<\/span> col in columns]\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;})\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">return<\/span> table_info\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;except <span class=\"hljs-keyword\">Exception<\/span> <span class=\"hljs-keyword\">as<\/span> e:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(f<span class=\"hljs-string\">\"Error getting table info: {str(e)}\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">return<\/span> &#091;]<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-3\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">PHP<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">php<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>The get_table_info method performs the following tasks<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Analyzes the database structure&nbsp;<\/li>\n\n\n\n<li>Displays available tables and columns<\/li>\n\n\n\n<li>Guides users on what can be queried<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Main Execution Block and User Interface Setup<\/strong><\/h4>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-4\" data-shcb-language-name=\"PHP\" data-shcb-language-slug=\"php\"><span><code class=\"hljs language-php\"><span class=\"hljs-keyword\">if<\/span> __name__ == <span class=\"hljs-string\">\"__main__\"<\/span>:\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\"># Initialize the agent with the existing database<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;db_path = <span class=\"hljs-string\">'employee_database.db'<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">if<\/span> not os.path.exists(db_path):\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(f<span class=\"hljs-string\">\"Error: Database file '{db_path}' not found!\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"Please make sure the employee_database.db file exists in the current directory.\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">exit<\/span>(<span class=\"hljs-number\">1<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\"># Initialize the agent<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;agent = SQLiteAgent(db_path)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-comment\"># Get and display table information<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;table_info = agent.get_table_info()\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"\\nAvailable tables in the database:\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">for<\/span> table in table_info:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(f<span class=\"hljs-string\">\"\\nTable: {table&#091;'table_name']}\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"Columns:\"<\/span>, <span class=\"hljs-string\">\", \"<\/span>.join(table&#091;<span class=\"hljs-string\">'columns'<\/span>]))\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"\\nSQLite Agent initialized! You can ask questions about the database.\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"\\nExample questions:\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"- What is the average salary in the Engineering department?\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"- Who are all the employees in the Marketing department?\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"- What is the total number of employees?\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(<span class=\"hljs-string\">\"\\nType 'exit' to quit.\\n\"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">while<\/span> <span class=\"hljs-keyword\">True<\/span>:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;question = input(<span class=\"hljs-string\">\"Your question: \"<\/span>)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">if<\/span> question.lower() == <span class=\"hljs-string\">'exit'<\/span>:\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">break<\/span>\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;result = agent.query(question)\n\n&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<span class=\"hljs-keyword\">print<\/span>(result)<\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-4\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">PHP<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">php<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p><strong>The above code block is our main function, which performs the below-mentioned tasks:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Initializes the employee_database, an SQLite database that is generated using the <a href=\"https:\/\/pypi.org\/project\/Faker\/\">Faker <\/a>Python package.<\/li>\n\n\n\n<li>Verifies if the database exists, ensuring that the required SQLite database is available for operations.<\/li>\n\n\n\n<li>Initializes an SQLite AI agent responsible for interacting with the database and processing queries.<\/li>\n\n\n\n<li>Displays the schema of the database, including available tables and columns, to guide users in constructing valid queries.<\/li>\n\n\n\n<li>It begins an interactive question-and-answer loop, allowing users to submit queries and receive responses based on the database content.<\/li>\n<\/ul>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-sql-agent-for-database-analytics.png\" alt=\"AI SQL Agent for Conversational Analytics\" class=\"wp-image-36497\" title=\"AI SQL Agent for SQL Database Analytics\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20363%22%3E%3C%2Fsvg%3E\" alt=\"AI SQL Agent for Conversational Analytics\" class=\"wp-image-36497 lazyload\" title=\"AI SQL Agent for SQL Database Analytics\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-sql-agent-for-database-analytics.png\"><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Step 6: <strong>Running and Executing the SQLite Agent<\/strong><\/strong><\/h2>\n\n\n\n<p>Once you&#8217;ve completed the previous steps, your project directory structure should appear as follows:<\/p>\n\n\n\n<p>sqlite_agent_project\/<\/p>\n\n\n\n<p>\u251c\u2500\u2500 sqlite_agent.py<\/p>\n\n\n\n<p>\u251c\u2500\u2500 .env<\/p>\n\n\n\n<p>\u2514\u2500\u2500 employee_database.db&nbsp;<\/p>\n\n\n\n<p>\u2514\u2500\u2500 venv<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Activate the virtual environment by executing the below command in your project directory<\/li>\n<\/ul>\n\n\n<pre class=\"wp-block-code\"><span><code class=\"hljs\">&nbsp;source venv\/bin\/activate<\/code><\/span><\/pre>\n\n\n<ul class=\"wp-block-list\">\n<li>Run the Agent<\/li>\n<\/ul>\n\n\n<pre class=\"wp-block-code\" aria-describedby=\"shcb-language-5\" data-shcb-language-name=\"CSS\" data-shcb-language-slug=\"css\"><span><code class=\"hljs language-css\">&nbsp;<span class=\"hljs-selector-tag\">python3<\/span> <span class=\"hljs-selector-tag\">sqlite_agent<\/span><span class=\"hljs-selector-class\">.py<\/span><\/code><\/span><small class=\"shcb-language\" id=\"shcb-language-5\"><span class=\"shcb-language__label\">Code language:<\/span> <span class=\"shcb-language__name\">CSS<\/span> <span class=\"shcb-language__paren\">(<\/span><span class=\"shcb-language__slug\">css<\/span><span class=\"shcb-language__paren\">)<\/span><\/small><\/pre>\n\n\n<p>After running the agent, it will show the available tables and their columns in the SQLite database, along with example questions you can ask. And just like that, our AI-powered agent is up and running!<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"550\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-sql-agent-up-and-running-database.png\" alt=\"AI-powered SQL AI agent successfully running and analyzing database\" class=\"wp-image-36489\" title=\"AI-Powered SQL AI Agent is Now Running\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"550\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20550%22%3E%3C%2Fsvg%3E\" alt=\"AI-powered SQL AI agent successfully running and analyzing database\" class=\"wp-image-36489 lazyload\" title=\"AI-Powered SQL AI Agent is Now Running\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-sql-agent-up-and-running-database.png\"><\/figure>\n\n\n\n<p>Let&#8217;s give our agent a test run&#8230;<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-running-sql-queries.png\" alt=\"AI-powered agent executing SQL queries in the database\" class=\"wp-image-36491\" title=\"AI-Powered Agent Executing SQL Querie\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20604%22%3E%3C%2Fsvg%3E\" alt=\"AI-powered agent executing SQL queries in the database\" class=\"wp-image-36491 lazyload\" title=\"AI-Powered Agent Executing SQL Querie\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-running-sql-queries.png\"><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-entering-sql-database-chain.png\" alt=\"AI agent entering SQL database chain for analysis\" class=\"wp-image-36500\" title=\"AI Agent Entering SQL Database Chain\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20604%22%3E%3C%2Fsvg%3E\" alt=\"AI agent entering SQL database chain for analysis\" class=\"wp-image-36500 lazyload\" title=\"AI Agent Entering SQL Database Chain\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-entering-sql-database-chain.png\"><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"542\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-finished-sql-database-chain.png\" alt=\"AI agent entering SQL database chain for analysis\" class=\"wp-image-36492\" title=\"AI Agent Entering SQL Database Chain\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"542\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20542%22%3E%3C%2Fsvg%3E\" alt=\"AI agent entering SQL database chain for analysis\" class=\"wp-image-36492 lazyload\" title=\"AI Agent Entering SQL Database Chain\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-agent-finished-sql-database-chain.png\"><\/figure>\n\n\n\n<p><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-powered-agent-operational.png\" alt=\"AI-powered SQL agent successfully up and operational\" class=\"wp-image-36494\" title=\"AI-Powered SQL AI Agent is Operational\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"604\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20604%22%3E%3C%2Fsvg%3E\" alt=\"AI-powered SQL agent successfully up and operational\" class=\"wp-image-36494 lazyload\" title=\"AI-Powered SQL AI Agent is Operational\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/ai-powered-agent-operational.png\"><\/figure>\n\n\n\n<p><strong>Note:<\/strong> The agent uses the Mistral 7B Model running on Hugging Face for natural language processing. While this implementation is free to use, it requires a HuggingFace API token. The model may have rate limits or usage restrictions based on your HuggingFace account type.<\/p>\n\n\n\n<p>For those interested in expanding their knowledge of building AI agents, I highly recommend checking out this video tutorial on<a href=\"https:\/\/www.youtube.com\/watch?v=w_w8Hq5zEpo\" target=\"_blank\" rel=\"noreferrer noopener\"><strong> creating AI agents using the Crew AI framework<\/strong>.<\/a> This video is perfect for beginners and anyone looking to improve their automation skills, providing a step-by-step guide on how to create intelligent AI agents.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Summing It Up<\/strong><\/h2>\n\n\n\n<p>I hope you enjoyed the SQLite AI agent tutorial, which provides an intelligent interface that bridges natural language and databases. This allows users to query SQLite databases using plain English. Powered by the Mistral-7B AI model, it automatically converts natural language questions into SQL queries, executes them, and returns results in a human-readable format. You can download the script <a href=\"https:\/\/github.com\/mobisoftinfotech\/sqlite-natural-language-query-agent\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>here<\/strong><\/a><strong>.<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/mobisoftinfotech.com\/contact-us?utm_source=blog&amp;utm_medium=referral&amp;utm_campaign=conversational-analytics-sql-ai-agent-database-cta2\"><noscript><img decoding=\"async\" width=\"800\" height=\"340\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/build-next-big-idea-right-tech.jpg\" alt=\"Build your next big idea with the right AI technology\" class=\"wp-image-36496\" title=\"Your Next Big Idea Needs the Right Tech. Let\u2019s Build It!\"><\/noscript><img decoding=\"async\" width=\"800\" height=\"340\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20800%20340%22%3E%3C%2Fsvg%3E\" alt=\"Build your next big idea with the right AI technology\" class=\"wp-image-36496 lazyload\" title=\"Your Next Big Idea Needs the Right Tech. Let\u2019s Build It!\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2025\/03\/build-next-big-idea-right-tech.jpg\"><\/a><\/figure>\n\n\n<div class=\"related-posts-section\"><h2>Related Posts<\/h2><ul class=\"related-posts-list\"><li><a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/build-ai-agents-crewai-framework\">AI Agent Framework Tutorial: Building AI Agents using CrewAI<\/a><\/li><li><a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/custom-ai-agent-development-crew-ai-framework\">Custom AI Agent Development: How To Create AI Agents With Crew AI Agent Framework With Function Calling Support<\/a><\/li><li><a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/cloud-vs-dedicated-gpu-hosting-providers\">Cloud vs. Dedicated GPU Hosting: Top Providers Reviewed for AI &amp; ML Projects<\/a><\/li><li><a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/ai-customer-support-automation-guide-faqs-chatbots\">AI in Customer Support: The Complete Guide to Automation from FAQs to Chatbots<\/a><\/li><\/ul><\/div>\n\n\n<div class=\"modern-author-card\">\n    <div class=\"author-card-content\">\n        <div class=\"author-info-section\">\n            <div class=\"author-avatar\">\n                <noscript><img decoding=\"async\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2023\/08\/prashant.png\" alt=\"Prashant Telangi\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"Prashant Telangi\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2023\/08\/prashant.png\" class=\" lazyload\">\n            <\/div>\n            <div class=\"author-details\">\n                <h3 class=\"author-name\">Prashant Telangi<\/h3>\n                <p class=\"author-title\">Head of Technology, Mobile<\/p>\n                <a href=\"javascript:void(0);\" class=\"read-more-link read-more-btn\" onclick=\"toggleAuthorBio(this); return false;\">Read more <noscript><img decoding=\"async\" src=\"\/assets\/images\/blog\/Vector.png\" alt=\"expand\" class=\"read-more-arrow down-arrow\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"expand\" class=\"read-more-arrow down-arrow lazyload\" data-src=\"\/assets\/images\/blog\/Vector.png\"><\/a>\n                <div class=\"author-bio-expanded\">\n                    <p>Prashant Telangi brings over 15 years of experience in Mobile Technology, He is currently serving as Head of Technology, Mobile at <a href=\"https:\/\/mobisoftinfotech.com\" target=\"_blank\">Mobisoft Infotech<\/a>. With a proven history in IT and services, he is a skilled, passionate developer specializing in Mobile Applications. His strong engineering background underscores his commitment to crafting innovative solutions in the ever-evolving tech landscape.<\/p>\n                    <div class=\"author-social-links\"><div class=\"social-icon\"><a href=\"https:\/\/www.linkedin.com\/in\/prashant-telangi-83816918\/\" target=\"_blank\" rel=\"nofollow noopener\"><i class=\"icon-sprite linkedin\"><\/i><\/a>\n                     <a href=\"https:\/\/twitter.com\/PrashantAnna\" target=\"_blank\" rel=\"nofollow noopener\"><i class=\"icon-sprite twitter\"><\/i><\/a>\n                     <a href=\"https:\/\/www.facebook.com\/prashant.telangi\/\" target=\"_blank\" rel=\"nofollow noopener\"><i class=\"icon-sprite facebook\"><\/i><\/a><\/div><\/div>\n                    <a href=\"javascript:void(0);\" class=\"read-more-link read-less-btn\" onclick=\"toggleAuthorBio(this); return false;\" style=\"display: none;\">Read less <noscript><img decoding=\"async\" src=\"\/assets\/images\/blog\/Vector.png\" alt=\"collapse\" class=\"read-more-arrow up-arrow\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"collapse\" class=\"read-more-arrow up-arrow lazyload\" data-src=\"\/assets\/images\/blog\/Vector.png\"><\/a>\n                <\/div>\n            <\/div>\n        <\/div>\n        <div class=\"share-section\">\n            <span class=\"share-label\">Share Article<\/span>\n            <div class=\"social-share-buttons\">\n                <a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https%3A%2F%2Fmobisoftinfotech.com%2Fresources%2Fblog%2Fai-machine-learning%2Fconversational-analytics-sql-ai-agent-database\" target=\"_blank\" class=\"share-btn facebook-share\"><i class=\"fa fa-facebook-f\"><\/i><\/a>\n                <a href=\"https:\/\/www.linkedin.com\/sharing\/share-offsite\/?url=https%3A%2F%2Fmobisoftinfotech.com%2Fresources%2Fblog%2Fai-machine-learning%2Fconversational-analytics-sql-ai-agent-database\" target=\"_blank\" class=\"share-btn linkedin-share\"><i class=\"fa fa-linkedin\"><\/i><\/a>\n            <\/div>\n        <\/div>\n    <\/div>\n<\/div>\n\n\n\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Article\",\n  \"mainEntityOfPage\": {\n    \"@type\": \"WebPage\",\n    \"@id\": \"https:\/\/mobisoftinfotech.com\/resources\/blog\/ai-machine-learning\/conversational-analytics-sql-ai-agent-database\"\n  },\n  \"headline\": \"Conversational Analytics Tutorial: How to implement SQL AI Agent that Speaks Database\",\n  \"description\": \"Learn how to implement SQL AI agents for conversational analytics in database management. 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His strong engineering background underscores his commitment to crafting innovative solutions in the ever-evolving tech landscape.\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"Mobisoft Infotech\",\n    \"logo\": {\n      \"@type\": \"ImageObject\",\n      \"url\": \"https:\/\/mobisoftinfotech.com\/assets\/images\/mshomepage\/MI_Logo-white.svg\",\n      \"width\": 600,\n      \"height\": 60\n    }\n  },\n  \"datePublished\": \"2025-03-25\",\n  \"dateModified\": \"2025-03-25\"\n}\n<\/script>\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Organization\",\n  \"name\": \"Mobisoft Infotech\",\n  \"url\": \"https:\/\/mobisoftinfotech.com\/\",\n  \"logo\": \"https:\/\/mobisoftinfotech.com\/assets\/images\/MI_Logo.svg\",\n  \"sameAs\": [\n    \"https:\/\/www.facebook.com\/pages\/Mobisoft-Infotech\/131035500270720\",\n    \"https:\/\/twitter.com\/MobisoftInfo\",\n    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