LangChain

用 `SQLDatabaseChain` 对数据库进行问答

此示例演示了使用 SQLDatabaseChain 对数据库进行问答。

在后台，LangChain 使用 SQLAlchemy 连接 SQL 数据库。因此，SQLDatabaseChain 可以与 SQLAlchemy 支持的任何 SQL 方言一起使用，例如 MS SQL、MySQL、MariaDB、PostgreSQL、Oracle SQL 和 SQLite。请参阅 SQLAlchemy 文档，了解有关连接到数据库的要求的更多信息。例如，连接到 MySQL 需要适当的连接器，如 PyMySQL。MySQL 连接的 URI 可能如下所示：mysql+pymysql://user:pass@some_mysql_db_address/db_name

此演示使用 SQLite 和示例 Chinook 数据库。要设置它，请按照 https://database.guide/2-sample-databases-sqlite/ (opens in a new tab) 上的说明，在此存储库的根目录下的 notebooks 文件夹中放置 .db 文件。

from langchain import OpenAI, SQLDatabase, SQLDatabaseChain

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.

db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)

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

> 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

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
)

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

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

> 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.

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

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

> 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.

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

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

> 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.

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:

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)

db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)

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

> 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.

可以将此信息作为字典提供，其中表名为键，表信息为值。例如，让我们为只有几列的 Track 表提供自定义定义和示例行：

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
*/"""
}

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
*/

注意，我们自定义的 Track 表定义和示例行覆盖了 sample_rows_in_table_info 参数。未被 custom_table_info 覆盖的表，在本例中为 Playlist，将像往常一样自动收集其表信息。

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

> 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#

用于查询 SQL 数据库的顺序链。

链如下：

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

在数据库中表的数量很多的情况下，这非常有用。

from langchain.chains import SQLDatabaseSequentialChain
db = SQLDatabase.from_uri("sqlite:///../../../../notebooks/Chinook.db")

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

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

> 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.'

PAL Multi Prompt Router

用 SQLDatabaseChain 对数据库进行问答