> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# SQLite
> Query and manage SQLite databases
## Overview
SQLite tool allows you to query and manage SQLite databases. No server required - perfect for local development and embedded applications.
The user asks a data question; the agent runs SQL against the database and returns rows.
```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
subgraph "SQLiteTool Flow"
User[👤 User] --> Agent[🤖 Agent]
Agent --> Tool[🔧 SQLiteTool]
Tool --> Result[✅ Result]
Result --> Agent
end
classDef agent fill:#8B0000,stroke:#7C90A0,color:#fff
classDef tool fill:#189AB4,stroke:#7C90A0,color:#fff
classDef output fill:#10B981,stroke:#7C90A0,color:#fff
class User,Agent agent
class Tool tool
class Result output
```
## Installation
```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install "praisonai[tools]"
```
No additional dependencies required - SQLite is built into Python!
## Quick Start
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import SQLiteTool
# Initialize
sqlite = SQLiteTool(path="mydata.db")
# Query
results = sqlite.query("SELECT * FROM users LIMIT 5")
print(results)
```
Use the same tool with an agent — see **Usage with Agent** below, or pass env vars and options from the sections above.
## Usage with Agent
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent
from praisonai_tools import SQLiteTool
sqlite = SQLiteTool(path="mydata.db")
agent = Agent(
name="DBAnalyst",
instructions="You are a database analyst. Use SQLite to query data.",
tools=[sqlite]
)
response = agent.chat("Show me all tables in the database")
print(response)
```
## Available Methods
### query(sql)
Execute a SQL query.
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import SQLiteTool
sqlite = SQLiteTool(path="mydata.db")
results = sqlite.query("SELECT * FROM users WHERE active = 1")
```
### execute(sql)
Execute a SQL statement (INSERT, UPDATE, DELETE, CREATE).
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sqlite.execute("CREATE TABLE IF NOT EXISTS users (id INTEGER PRIMARY KEY, name TEXT)")
sqlite.execute("INSERT INTO users (name) VALUES ('Alice')")
```
### list\_tables()
List all tables in the database.
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
tables = sqlite.list_tables()
```
## Configuration Options
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sqlite = SQLiteTool(
path="mydata.db", # Database file path
timeout=30 # Connection timeout
)
```
## Function-Based Usage
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import query_sqlite
# Quick query
results = query_sqlite("SELECT * FROM users", path="mydata.db")
```
## In-Memory Database
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# Use :memory: for temporary in-memory database
sqlite = SQLiteTool(path=":memory:")
sqlite.execute("CREATE TABLE test (id INTEGER, value TEXT)")
```
## Error Handling
```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonai_tools import SQLiteTool
sqlite = SQLiteTool(path="mydata.db")
result = sqlite.query("SELECT * FROM users")
if isinstance(result, dict) and "error" in result:
print(f"Error: {result['error']}")
else:
for row in result:
print(row)
```
## Common Errors
| Error | Cause | Solution |
| -------------------- | --------------------- | ----------------------- |
| `no such table` | Table doesn't exist | Create table first |
| `database is locked` | Concurrent access | Close other connections |
| `disk I/O error` | File permission issue | Check file permissions |
## How It Works
```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
participant User
participant Agent
participant Tool as Tool
participant Svc as SQLite
User->>Agent: Request
Agent->>Tool: Call tool
Tool->>Svc: Query
Svc-->>Tool: Data
Tool-->>Agent: Result
Agent-->>User: Response
```
***
## Best Practices
List tables and columns before querying so the agent writes valid SQL.
Bind values instead of string-formatting them to avoid SQL injection.
Add `LIMIT` so the agent works with a focused result set.
***
## Related Tools
PostgreSQL database
MySQL database
Analytics database