langchain/docs/modules/chains/examples/sqlite.ipynb

SQL Chain example

This example demonstrates the use of the SQLDatabaseChain for answering questions over a database.

Under the hood, LangChain uses SQLAlchemy to connect to SQL databases. The SQLDatabaseChain can therefore be used with any SQL dialect supported by SQLAlchemy, such as MS SQL, MySQL, MariaDB, PostgreSQL, Oracle SQL, and SQLite. Please refer to the SQLAlchemy documentation for more information about requirements for connecting to your database. For example, a connection to MySQL requires an appropriate connector such as PyMySQL. A URI for a MySQL connection might look like: mysql+pymysql://user:pass@some_mysql_db_address/db_name

This demonstration uses SQLite and the example Chinook database. To set it up, follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the .db file in a notebooks folder at the root of this repository.

In [1]:

from langchain import OpenAI, SQLDatabase, SQLDatabaseChain

In [2]:

db = SQLDatabase.from_uri("sqlite:///../../../../notebooks/Chinook.db")
llm = OpenAI(temperature=0)

NOTE: For data-sensitive projects, you can specify return_direct=True in the SQLDatabaseChain initialization to directly return the output of the SQL query without any additional formatting. This prevents the LLM from seeing any contents within the database. Note, however, the LLM still has access to the database scheme (i.e. dialect, table and key names) by default.

In [3]:

db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)

In [4]:

db_chain.run("How many employees are there?")

Out [4]:

> Entering new SQLDatabaseChain chain...
How many employees are there? 
SQLQuery:

/Users/harrisonchase/workplace/langchain/langchain/sql_database.py:120: SAWarning: Dialect sqlite+pysqlite does *not* support Decimal objects natively, and SQLAlchemy must convert from floating point - rounding errors and other issues may occur. Please consider storing Decimal numbers as strings or integers on this platform for lossless storage.
  sample_rows = connection.execute(command)

 SELECT COUNT(*) FROM Employee;
SQLResult: [(8,)]
Answer: There are 8 employees.
> Finished chain.

' There are 8 employees.'

Customize Prompt

You can also customize the prompt that is used. Here is an example prompting it to understand that foobar is the same as the Employee table

In [5]:

from langchain.prompts.prompt import PromptTemplate

_DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer.
Use the following format:

Question: "Question here"
SQLQuery: "SQL Query to run"
SQLResult: "Result of the SQLQuery"
Answer: "Final answer here"

Only use the following tables:

{table_info}

If someone asks for the table foobar, they really mean the employee table.

Question: {input}"""
PROMPT = PromptTemplate(
    input_variables=["input", "table_info", "dialect"], template=_DEFAULT_TEMPLATE
)

In [6]:

db_chain = SQLDatabaseChain(llm=llm, database=db, prompt=PROMPT, verbose=True)

In [7]:

db_chain.run("How many employees are there in the foobar table?")

Out [7]:

> Entering new SQLDatabaseChain chain...
How many employees are there in the foobar table? 
SQLQuery: SELECT COUNT(*) FROM Employee;
SQLResult: [(8,)]
Answer: There are 8 employees in the foobar table.
> Finished chain.

' There are 8 employees in the foobar table.'

Return Intermediate Steps

You can also return the intermediate steps of the SQLDatabaseChain. This allows you to access the SQL statement that was generated, as well as the result of running that against the SQL Database.

In [8]:

db_chain = SQLDatabaseChain(
    llm=llm, database=db, prompt=PROMPT, verbose=True, return_intermediate_steps=True
)

In [9]:

result = db_chain("How many employees are there in the foobar table?")
result["intermediate_steps"]

Out [9]:

> Entering new SQLDatabaseChain chain...
How many employees are there in the foobar table? 
SQLQuery: SELECT COUNT(*) FROM Employee;
SQLResult: [(8,)]
Answer: There are 8 employees in the foobar table.
> Finished chain.

[' SELECT COUNT(*) FROM Employee;', '[(8,)]']

Choosing how to limit the number of rows returned

If you are querying for several rows of a table you can select the maximum number of results you want to get by using the 'top_k' parameter (default is 10). This is useful for avoiding query results that exceed the prompt max length or consume tokens unnecessarily.

In [10]:

db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True, top_k=3)

In [11]:

db_chain.run("What are some example tracks by composer Johann Sebastian Bach?")

Out [11]:

> Entering new SQLDatabaseChain chain...
What are some example tracks by composer Johann Sebastian Bach? 
SQLQuery: SELECT Name, Composer FROM Track WHERE Composer LIKE '%Johann Sebastian Bach%' LIMIT 3;
SQLResult: [('Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace', 'Johann Sebastian Bach'), ('Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria', 'Johann Sebastian Bach'), ('Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude', 'Johann Sebastian Bach')]
Answer: Some example tracks by composer Johann Sebastian Bach are 'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace', 'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria', and 'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude'.
> Finished chain.

' Some example tracks by composer Johann Sebastian Bach are \'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace\', \'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria\', and \'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude\'.'

Adding example rows from each table

Sometimes, the format of the data is not obvious and it is optimal to include a sample of rows from the tables in the prompt to allow the LLM to understand the data before providing a final query. Here we will use this feature to let the LLM know that artists are saved with their full names by providing two rows from the Track table.

In [12]:

db = SQLDatabase.from_uri(
    "sqlite:///../../../../notebooks/Chinook.db",
    include_tables=[
        "Track"
    ],  # we include only one table to save tokens in the prompt :)
    sample_rows_in_table_info=2,
)

The sample rows are added to the prompt after each corresponding table's column information:

In [13]:

print(db.table_info)

CREATE TABLE "Track" (
	"TrackId" INTEGER NOT NULL, 
	"Name" NVARCHAR(200) NOT NULL, 
	"AlbumId" INTEGER, 
	"MediaTypeId" INTEGER NOT NULL, 
	"GenreId" INTEGER, 
	"Composer" NVARCHAR(220), 
	"Milliseconds" INTEGER NOT NULL, 
	"Bytes" INTEGER, 
	"UnitPrice" NUMERIC(10, 2) NOT NULL, 
	PRIMARY KEY ("TrackId"), 
	FOREIGN KEY("MediaTypeId") REFERENCES "MediaType" ("MediaTypeId"), 
	FOREIGN KEY("GenreId") REFERENCES "Genre" ("GenreId"), 
	FOREIGN KEY("AlbumId") REFERENCES "Album" ("AlbumId")
)
/*
2 rows from Track table:
TrackId	Name	AlbumId	MediaTypeId	GenreId	Composer	Milliseconds	Bytes	UnitPrice
1	For Those About To Rock (We Salute You)	1	1	1	Angus Young, Malcolm Young, Brian Johnson	343719	11170334	0.99
2	Balls to the Wall	2	2	1	None	342562	5510424	0.99
*/

/home/jon/projects/langchain/langchain/sql_database.py:135: SAWarning: Dialect sqlite+pysqlite does *not* support Decimal objects natively, and SQLAlchemy must convert from floating point - rounding errors and other issues may occur. Please consider storing Decimal numbers as strings or integers on this platform for lossless storage.
  sample_rows = connection.execute(command)

In [14]:

db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)

In [15]:

db_chain.run("What are some example tracks by Bach?")

Out [15]:

> Entering new SQLDatabaseChain chain...
What are some example tracks by Bach? 
SQLQuery: SELECT Name FROM Track WHERE Composer LIKE '%Bach%' LIMIT 5;
SQLResult: [('American Woman',), ('Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace',), ('Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria',), ('Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude',), ('Toccata and Fugue in D Minor, BWV 565: I. Toccata',)]
Answer: Some example tracks by Bach are 'American Woman', 'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace', 'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria', 'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude', and 'Toccata and Fugue in D Minor, BWV 565: I. Toccata'.
> Finished chain.

' Some example tracks by Bach are \'American Woman\', \'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace\', \'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria\', \'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude\', and \'Toccata and Fugue in D Minor, BWV 565: I. Toccata\'.'

Custom Table Info

In some cases, it can be useful to provide custom table information instead of using the automatically generated table definitions and the first sample_rows_in_table_info sample rows. For example, if you know that the first few rows of a table are uninformative, it could help to manually provide example rows that are more diverse or provide more information to the model. It is also possible to limit the columns that will be visible to the model if there are unnecessary columns.

This information can be provided as a dictionary with table names as the keys and table information as the values. For example, let's provide a custom definition and sample rows for the Track table with only a few columns:

In [16]:

custom_table_info = {
    "Track": """CREATE TABLE Track (
	"TrackId" INTEGER NOT NULL, 
	"Name" NVARCHAR(200) NOT NULL,
	"Composer" NVARCHAR(220),
	PRIMARY KEY ("TrackId")
)
/*
3 rows from Track table:
TrackId	Name	Composer
1	For Those About To Rock (We Salute You)	Angus Young, Malcolm Young, Brian Johnson
2	Balls to the Wall	None
3	My favorite song ever	The coolest composer of all time
*/"""
}

In [17]:

db = SQLDatabase.from_uri(
    "sqlite:///../../../../notebooks/Chinook.db",
    include_tables=["Track", "Playlist"],
    sample_rows_in_table_info=2,
    custom_table_info=custom_table_info,
)

print(db.table_info)

CREATE TABLE "Playlist" (
	"PlaylistId" INTEGER NOT NULL, 
	"Name" NVARCHAR(120), 
	PRIMARY KEY ("PlaylistId")
)
/*
2 rows from Playlist table:
PlaylistId	Name
1	Music
2	Movies
*/

CREATE TABLE Track (
	"TrackId" INTEGER NOT NULL, 
	"Name" NVARCHAR(200) NOT NULL,
	"Composer" NVARCHAR(220),
	PRIMARY KEY ("TrackId")
)
/*
3 rows from Track table:
TrackId	Name	Composer
1	For Those About To Rock (We Salute You)	Angus Young, Malcolm Young, Brian Johnson
2	Balls to the Wall	None
3	My favorite song ever	The coolest composer of all time
*/

Note how our custom table definition and sample rows for Track overrides the sample_rows_in_table_info parameter. Tables that are not overridden by custom_table_info, in this example Playlist, will have their table info gathered automatically as usual.

In [18]:

db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)
db_chain.run("What are some example tracks by Bach?")

Out [18]:

> Entering new SQLDatabaseChain chain...
What are some example tracks by Bach? 
SQLQuery: SELECT Name, Composer FROM Track WHERE Composer LIKE '%Bach%' LIMIT 5;
SQLResult: [('American Woman', 'B. Cummings/G. Peterson/M.J. Kale/R. Bachman'), ('Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace', 'Johann Sebastian Bach'), ('Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria', 'Johann Sebastian Bach'), ('Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude', 'Johann Sebastian Bach'), ('Toccata and Fugue in D Minor, BWV 565: I. Toccata', 'Johann Sebastian Bach')]
Answer: Some example tracks by Bach are 'American Woman', 'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace', 'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria', 'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude', and 'Toccata and Fugue in D Minor, BWV 565: I. Toccata'.
> Finished chain.

' Some example tracks by Bach are \'American Woman\', \'Concerto for 2 Violins in D Minor, BWV 1043: I. Vivace\', \'Aria Mit 30 Veränderungen, BWV 988 "Goldberg Variations": Aria\', \'Suite for Solo Cello No. 1 in G Major, BWV 1007: I. Prélude\', and \'Toccata and Fugue in D Minor, BWV 565: I. Toccata\'.'

SQLDatabaseSequentialChain

Chain for querying SQL database that is a sequential chain.

The chain is as follows:

1. Based on the query, determine which tables to use.
2. Based on those tables, call the normal SQL database chain.

This is useful in cases where the number of tables in the database is large.

In [20]:

from langchain.chains import SQLDatabaseSequentialChain

db = SQLDatabase.from_uri("sqlite:///../../../../notebooks/Chinook.db")

In [21]:

chain = SQLDatabaseSequentialChain.from_llm(llm, db, verbose=True)

In [22]:

chain.run("How many employees are also customers?")

Out [22]:

> Entering new SQLDatabaseSequentialChain chain...
Table names to use:
['Customer', 'Employee']

> Entering new SQLDatabaseChain chain...
How many employees are also customers? 
SQLQuery: SELECT COUNT(*) FROM Employee INNER JOIN Customer ON Employee.EmployeeId = Customer.SupportRepId;
SQLResult: [(59,)]
Answer: 59 employees are also customers.
> Finished chain.

> Finished chain.

' 59 employees are also customers.'

In [ ]: