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On line 586, the check_query function should use check_query_system_prompt. Instead, small mistake it is using the generate_query_system_prompt prompt which is obviously incorrect.
64 KiB
64 KiB
In [ ]:
%%capture --no-stderr
%pip install -U langgraph langchain_community "langchain[openai]"In [1]:
from langchain.chat_models import init_chat_model
llm = init_chat_model("openai:gpt-4.1")In [ ]:
import requests
url = "https://storage.googleapis.com/benchmarks-artifacts/chinook/Chinook.db"
response = requests.get(url)
if response.status_code == 200:
# Open a local file in binary write mode
with open("Chinook.db", "wb") as file:
# Write the content of the response (the file) to the local file
file.write(response.content)
print("File downloaded and saved as Chinook.db")
else:
print(f"Failed to download the file. Status code: {response.status_code}")In [2]:
from langchain_community.utilities import SQLDatabase
db = SQLDatabase.from_uri("sqlite:///Chinook.db")
print(f"Dialect: {db.dialect}")
print(f"Available tables: {db.get_usable_table_names()}")
print(f'Sample output: {db.run("SELECT * FROM Artist LIMIT 5;")}')Dialect: sqlite Available tables: ['Album', 'Artist', 'Customer', 'Employee', 'Genre', 'Invoice', 'InvoiceLine', 'MediaType', 'Playlist', 'PlaylistTrack', 'Track'] Sample output: [(1, 'AC/DC'), (2, 'Accept'), (3, 'Aerosmith'), (4, 'Alanis Morissette'), (5, 'Alice In Chains')]
In [3]:
from langchain_community.agent_toolkits import SQLDatabaseToolkit
toolkit = SQLDatabaseToolkit(db=db, llm=llm)
tools = toolkit.get_tools()
for tool in tools:
print(f"{tool.name}: {tool.description}\n")sql_db_query: Input to this tool is a detailed and correct SQL query, output is a result from the database. If the query is not correct, an error message will be returned. If an error is returned, rewrite the query, check the query, and try again. If you encounter an issue with Unknown column 'xxxx' in 'field list', use sql_db_schema to query the correct table fields. sql_db_schema: Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables. Be sure that the tables actually exist by calling sql_db_list_tables first! Example Input: table1, table2, table3 sql_db_list_tables: Input is an empty string, output is a comma-separated list of tables in the database. sql_db_query_checker: Use this tool to double check if your query is correct before executing it. Always use this tool before executing a query with sql_db_query!
In [4]:
from langgraph.prebuilt import create_react_agent
system_prompt = """
You are an agent designed to interact with a SQL database.
Given an input question, create a syntactically correct {dialect} query to run,
then look at the results of the query and return the answer. Unless the user
specifies a specific number of examples they wish to obtain, always limit your
query to at most {top_k} results.
You can order the results by a relevant column to return the most interesting
examples in the database. Never query for all the columns from a specific table,
only ask for the relevant columns given the question.
You MUST double check your query before executing it. If you get an error while
executing a query, rewrite the query and try again.
DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the
database.
To start you should ALWAYS look at the tables in the database to see what you
can query. Do NOT skip this step.
Then you should query the schema of the most relevant tables.
""".format(
dialect=db.dialect,
top_k=5,
)
agent = create_react_agent(
llm,
tools,
prompt=system_prompt,
)In [5]:
question = "Which sales agent made the most in sales in 2009?"
for step in agent.stream(
{"messages": [{"role": "user", "content": question}]},
stream_mode="values",
):
step["messages"][-1].pretty_print()================================[1m Human Message [0m================================= Which sales agent made the most in sales in 2009? ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_list_tables (call_0MfnhUYmRNVe03m6fYClaoa0) Call ID: call_0MfnhUYmRNVe03m6fYClaoa0 Args: tool_input: =================================[1m Tool Message [0m================================= Name: sql_db_list_tables Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_schema (call_XwI6uES0HeZ2xCRxkkdWzB3I) Call ID: call_XwI6uES0HeZ2xCRxkkdWzB3I Args: table_names: Employee, Invoice, InvoiceLine =================================[1m Tool Message [0m================================= Name: sql_db_schema CREATE TABLE "Employee" ( "EmployeeId" INTEGER NOT NULL, "LastName" NVARCHAR(20) NOT NULL, "FirstName" NVARCHAR(20) NOT NULL, "Title" NVARCHAR(30), "ReportsTo" INTEGER, "BirthDate" DATETIME, "HireDate" DATETIME, "Address" NVARCHAR(70), "City" NVARCHAR(40), "State" NVARCHAR(40), "Country" NVARCHAR(40), "PostalCode" NVARCHAR(10), "Phone" NVARCHAR(24), "Fax" NVARCHAR(24), "Email" NVARCHAR(60), PRIMARY KEY ("EmployeeId"), FOREIGN KEY("ReportsTo") REFERENCES "Employee" ("EmployeeId") ) /* 3 rows from Employee table: EmployeeId LastName FirstName Title ReportsTo BirthDate HireDate Address City State Country PostalCode Phone Fax Email 1 Adams Andrew General Manager None 1962-02-18 00:00:00 2002-08-14 00:00:00 11120 Jasper Ave NW Edmonton AB Canada T5K 2N1 +1 (780) 428-9482 +1 (780) 428-3457 andrew@chinookcorp.com 2 Edwards Nancy Sales Manager 1 1958-12-08 00:00:00 2002-05-01 00:00:00 825 8 Ave SW Calgary AB Canada T2P 2T3 +1 (403) 262-3443 +1 (403) 262-3322 nancy@chinookcorp.com 3 Peacock Jane Sales Support Agent 2 1973-08-29 00:00:00 2002-04-01 00:00:00 1111 6 Ave SW Calgary AB Canada T2P 5M5 +1 (403) 262-3443 +1 (403) 262-6712 jane@chinookcorp.com */ CREATE TABLE "Invoice" ( "InvoiceId" INTEGER NOT NULL, "CustomerId" INTEGER NOT NULL, "InvoiceDate" DATETIME NOT NULL, "BillingAddress" NVARCHAR(70), "BillingCity" NVARCHAR(40), "BillingState" NVARCHAR(40), "BillingCountry" NVARCHAR(40), "BillingPostalCode" NVARCHAR(10), "Total" NUMERIC(10, 2) NOT NULL, PRIMARY KEY ("InvoiceId"), FOREIGN KEY("CustomerId") REFERENCES "Customer" ("CustomerId") ) /* 3 rows from Invoice table: InvoiceId CustomerId InvoiceDate BillingAddress BillingCity BillingState BillingCountry BillingPostalCode Total 1 2 2009-01-01 00:00:00 Theodor-Heuss-Straße 34 Stuttgart None Germany 70174 1.98 2 4 2009-01-02 00:00:00 Ullevålsveien 14 Oslo None Norway 0171 3.96 3 8 2009-01-03 00:00:00 Grétrystraat 63 Brussels None Belgium 1000 5.94 */ CREATE TABLE "InvoiceLine" ( "InvoiceLineId" INTEGER NOT NULL, "InvoiceId" INTEGER NOT NULL, "TrackId" INTEGER NOT NULL, "UnitPrice" NUMERIC(10, 2) NOT NULL, "Quantity" INTEGER NOT NULL, PRIMARY KEY ("InvoiceLineId"), FOREIGN KEY("TrackId") REFERENCES "Track" ("TrackId"), FOREIGN KEY("InvoiceId") REFERENCES "Invoice" ("InvoiceId") ) /* 3 rows from InvoiceLine table: InvoiceLineId InvoiceId TrackId UnitPrice Quantity 1 1 2 0.99 1 2 1 4 0.99 1 3 2 6 0.99 1 */ ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_schema (call_dHE5FKSycFhYIkdPKtpEk9rM) Call ID: call_dHE5FKSycFhYIkdPKtpEk9rM Args: table_names: Customer =================================[1m Tool Message [0m================================= Name: sql_db_schema CREATE TABLE "Customer" ( "CustomerId" INTEGER NOT NULL, "FirstName" NVARCHAR(40) NOT NULL, "LastName" NVARCHAR(20) NOT NULL, "Company" NVARCHAR(80), "Address" NVARCHAR(70), "City" NVARCHAR(40), "State" NVARCHAR(40), "Country" NVARCHAR(40), "PostalCode" NVARCHAR(10), "Phone" NVARCHAR(24), "Fax" NVARCHAR(24), "Email" NVARCHAR(60) NOT NULL, "SupportRepId" INTEGER, PRIMARY KEY ("CustomerId"), FOREIGN KEY("SupportRepId") REFERENCES "Employee" ("EmployeeId") ) /* 3 rows from Customer table: CustomerId FirstName LastName Company Address City State Country PostalCode Phone Fax Email SupportRepId 1 Luís Gonçalves Embraer - Empresa Brasileira de Aeronáutica S.A. Av. Brigadeiro Faria Lima, 2170 São José dos Campos SP Brazil 12227-000 +55 (12) 3923-5555 +55 (12) 3923-5566 luisg@embraer.com.br 3 2 Leonie Köhler None Theodor-Heuss-Straße 34 Stuttgart None Germany 70174 +49 0711 2842222 None leonekohler@surfeu.de 5 3 François Tremblay None 1498 rue Bélanger Montréal QC Canada H2G 1A7 +1 (514) 721-4711 None ftremblay@gmail.com 3 */ ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_query_checker (call_QPtWY5cUZWgWhr13Kz6eBJkU) Call ID: call_QPtWY5cUZWgWhr13Kz6eBJkU Args: query: SELECT e.EmployeeId, e.FirstName, e.LastName, SUM(i.Total) as TotalSales FROM Employee e JOIN Customer c ON e.EmployeeId = c.SupportRepId JOIN Invoice i ON c.CustomerId = i.CustomerId WHERE i.InvoiceDate BETWEEN '2009-01-01' AND '2009-12-31' GROUP BY e.EmployeeId, e.FirstName, e.LastName ORDER BY TotalSales DESC LIMIT 1; =================================[1m Tool Message [0m================================= Name: sql_db_query_checker ```sql SELECT e.EmployeeId, e.FirstName, e.LastName, SUM(i.Total) as TotalSales FROM Employee e JOIN Customer c ON e.EmployeeId = c.SupportRepId JOIN Invoice i ON c.CustomerId = i.CustomerId WHERE i.InvoiceDate BETWEEN '2009-01-01' AND '2009-12-31' GROUP BY e.EmployeeId, e.FirstName, e.LastName ORDER BY TotalSales DESC LIMIT 1; ``` ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_query (call_X747YMElSeY5D3CfhE6KzLUj) Call ID: call_X747YMElSeY5D3CfhE6KzLUj Args: query: SELECT e.EmployeeId, e.FirstName, e.LastName, SUM(i.Total) as TotalSales FROM Employee e JOIN Customer c ON e.EmployeeId = c.SupportRepId JOIN Invoice i ON c.CustomerId = i.CustomerId WHERE i.InvoiceDate BETWEEN '2009-01-01' AND '2009-12-31' GROUP BY e.EmployeeId, e.FirstName, e.LastName ORDER BY TotalSales DESC LIMIT 1; =================================[1m Tool Message [0m================================= Name: sql_db_query [(5, 'Steve', 'Johnson', 164.34)] ==================================[1m Ai Message [0m================================== The sales agent who made the most in sales in 2009 was Steve Johnson, with total sales of 164.34.
In [7]:
from typing import Literal
from langchain_core.messages import AIMessage
from langchain_core.runnables import RunnableConfig
from langgraph.graph import END, START, MessagesState, StateGraph
from langgraph.prebuilt import ToolNode
get_schema_tool = next(tool for tool in tools if tool.name == "sql_db_schema")
get_schema_node = ToolNode([get_schema_tool], name="get_schema")
run_query_tool = next(tool for tool in tools if tool.name == "sql_db_query")
run_query_node = ToolNode([run_query_tool], name="run_query")
# Example: create a predetermined tool call
def list_tables(state: MessagesState):
tool_call = {
"name": "sql_db_list_tables",
"args": {},
"id": "abc123",
"type": "tool_call",
}
tool_call_message = AIMessage(content="", tool_calls=[tool_call])
list_tables_tool = next(tool for tool in tools if tool.name == "sql_db_list_tables")
tool_message = list_tables_tool.invoke(tool_call)
response = AIMessage(f"Available tables: {tool_message.content}")
return {"messages": [tool_call_message, tool_message, response]}
# Example: force a model to create a tool call
def call_get_schema(state: MessagesState):
# Note that LangChain enforces that all models accept `tool_choice="any"`
# as well as `tool_choice=<string name of tool>`.
llm_with_tools = llm.bind_tools([get_schema_tool], tool_choice="any")
response = llm_with_tools.invoke(state["messages"])
return {"messages": [response]}
generate_query_system_prompt = """
You are an agent designed to interact with a SQL database.
Given an input question, create a syntactically correct {dialect} query to run,
then look at the results of the query and return the answer. Unless the user
specifies a specific number of examples they wish to obtain, always limit your
query to at most {top_k} results.
You can order the results by a relevant column to return the most interesting
examples in the database. Never query for all the columns from a specific table,
only ask for the relevant columns given the question.
DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.
""".format(
dialect=db.dialect,
top_k=5,
)
def generate_query(state: MessagesState):
system_message = {
"role": "system",
"content": generate_query_system_prompt,
}
# We do not force a tool call here, to allow the model to
# respond naturally when it obtains the solution.
llm_with_tools = llm.bind_tools([run_query_tool])
response = llm_with_tools.invoke([system_message] + state["messages"])
return {"messages": [response]}
check_query_system_prompt = """
You are a SQL expert with a strong attention to detail.
Double check the {dialect} query for common mistakes, including:
- Using NOT IN with NULL values
- Using UNION when UNION ALL should have been used
- Using BETWEEN for exclusive ranges
- Data type mismatch in predicates
- Properly quoting identifiers
- Using the correct number of arguments for functions
- Casting to the correct data type
- Using the proper columns for joins
If there are any of the above mistakes, rewrite the query. If there are no mistakes,
just reproduce the original query.
You will call the appropriate tool to execute the query after running this check.
""".format(dialect=db.dialect)
def check_query(state: MessagesState):
system_message = {
"role": "system",
"content": check_query_system_prompt,
}
# Generate an artificial user message to check
tool_call = state["messages"][-1].tool_calls[0]
user_message = {"role": "user", "content": tool_call["args"]["query"]}
llm_with_tools = llm.bind_tools([run_query_tool], tool_choice="any")
response = llm_with_tools.invoke([system_message, user_message])
response.id = state["messages"][-1].id
return {"messages": [response]}In [8]:
def should_continue(state: MessagesState) -> Literal[END, "check_query"]:
messages = state["messages"]
last_message = messages[-1]
if not last_message.tool_calls:
return END
else:
return "check_query"
builder = StateGraph(MessagesState)
builder.add_node(list_tables)
builder.add_node(call_get_schema)
builder.add_node(get_schema_node, "get_schema")
builder.add_node(generate_query)
builder.add_node(check_query)
builder.add_node(run_query_node, "run_query")
builder.add_edge(START, "list_tables")
builder.add_edge("list_tables", "call_get_schema")
builder.add_edge("call_get_schema", "get_schema")
builder.add_edge("get_schema", "generate_query")
builder.add_conditional_edges(
"generate_query",
should_continue,
)
builder.add_edge("check_query", "run_query")
builder.add_edge("run_query", "generate_query")
agent = builder.compile()In [9]:
from IPython.display import Image, display
from langchain_core.runnables.graph import CurveStyle, MermaidDrawMethod, NodeStyles
display(Image(agent.get_graph().draw_mermaid_png()))In [10]:
question = "Which sales agent made the most in sales in 2009?"
for step in agent.stream(
{"messages": [{"role": "user", "content": question}]},
stream_mode="values",
):
step["messages"][-1].pretty_print()================================[1m Human Message [0m================================= Which sales agent made the most in sales in 2009? ==================================[1m Ai Message [0m================================== Available tables: Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_schema (call_rMs3sF1HVcAGggGf89ZNvtLE) Call ID: call_rMs3sF1HVcAGggGf89ZNvtLE Args: table_names: Employee,Invoice,Customer =================================[1m Tool Message [0m================================= Name: sql_db_schema CREATE TABLE "Customer" ( "CustomerId" INTEGER NOT NULL, "FirstName" NVARCHAR(40) NOT NULL, "LastName" NVARCHAR(20) NOT NULL, "Company" NVARCHAR(80), "Address" NVARCHAR(70), "City" NVARCHAR(40), "State" NVARCHAR(40), "Country" NVARCHAR(40), "PostalCode" NVARCHAR(10), "Phone" NVARCHAR(24), "Fax" NVARCHAR(24), "Email" NVARCHAR(60) NOT NULL, "SupportRepId" INTEGER, PRIMARY KEY ("CustomerId"), FOREIGN KEY("SupportRepId") REFERENCES "Employee" ("EmployeeId") ) /* 3 rows from Customer table: CustomerId FirstName LastName Company Address City State Country PostalCode Phone Fax Email SupportRepId 1 Luís Gonçalves Embraer - Empresa Brasileira de Aeronáutica S.A. Av. Brigadeiro Faria Lima, 2170 São José dos Campos SP Brazil 12227-000 +55 (12) 3923-5555 +55 (12) 3923-5566 luisg@embraer.com.br 3 2 Leonie Köhler None Theodor-Heuss-Straße 34 Stuttgart None Germany 70174 +49 0711 2842222 None leonekohler@surfeu.de 5 3 François Tremblay None 1498 rue Bélanger Montréal QC Canada H2G 1A7 +1 (514) 721-4711 None ftremblay@gmail.com 3 */ CREATE TABLE "Employee" ( "EmployeeId" INTEGER NOT NULL, "LastName" NVARCHAR(20) NOT NULL, "FirstName" NVARCHAR(20) NOT NULL, "Title" NVARCHAR(30), "ReportsTo" INTEGER, "BirthDate" DATETIME, "HireDate" DATETIME, "Address" NVARCHAR(70), "City" NVARCHAR(40), "State" NVARCHAR(40), "Country" NVARCHAR(40), "PostalCode" NVARCHAR(10), "Phone" NVARCHAR(24), "Fax" NVARCHAR(24), "Email" NVARCHAR(60), PRIMARY KEY ("EmployeeId"), FOREIGN KEY("ReportsTo") REFERENCES "Employee" ("EmployeeId") ) /* 3 rows from Employee table: EmployeeId LastName FirstName Title ReportsTo BirthDate HireDate Address City State Country PostalCode Phone Fax Email 1 Adams Andrew General Manager None 1962-02-18 00:00:00 2002-08-14 00:00:00 11120 Jasper Ave NW Edmonton AB Canada T5K 2N1 +1 (780) 428-9482 +1 (780) 428-3457 andrew@chinookcorp.com 2 Edwards Nancy Sales Manager 1 1958-12-08 00:00:00 2002-05-01 00:00:00 825 8 Ave SW Calgary AB Canada T2P 2T3 +1 (403) 262-3443 +1 (403) 262-3322 nancy@chinookcorp.com 3 Peacock Jane Sales Support Agent 2 1973-08-29 00:00:00 2002-04-01 00:00:00 1111 6 Ave SW Calgary AB Canada T2P 5M5 +1 (403) 262-3443 +1 (403) 262-6712 jane@chinookcorp.com */ CREATE TABLE "Invoice" ( "InvoiceId" INTEGER NOT NULL, "CustomerId" INTEGER NOT NULL, "InvoiceDate" DATETIME NOT NULL, "BillingAddress" NVARCHAR(70), "BillingCity" NVARCHAR(40), "BillingState" NVARCHAR(40), "BillingCountry" NVARCHAR(40), "BillingPostalCode" NVARCHAR(10), "Total" NUMERIC(10, 2) NOT NULL, PRIMARY KEY ("InvoiceId"), FOREIGN KEY("CustomerId") REFERENCES "Customer" ("CustomerId") ) /* 3 rows from Invoice table: InvoiceId CustomerId InvoiceDate BillingAddress BillingCity BillingState BillingCountry BillingPostalCode Total 1 2 2009-01-01 00:00:00 Theodor-Heuss-Straße 34 Stuttgart None Germany 70174 1.98 2 4 2009-01-02 00:00:00 Ullevålsveien 14 Oslo None Norway 0171 3.96 3 8 2009-01-03 00:00:00 Grétrystraat 63 Brussels None Belgium 1000 5.94 */ ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_query (call_TQyoJSV78xEWHqc69PiYHjdS) Call ID: call_TQyoJSV78xEWHqc69PiYHjdS Args: query: SELECT e.FirstName, e.LastName, SUM(i.Total) as TotalSales FROM Employee e JOIN Customer c ON e.EmployeeId = c.SupportRepId JOIN Invoice i ON c.CustomerId = i.CustomerId WHERE strftime('%Y', i.InvoiceDate) = '2009' GROUP BY e.EmployeeId ORDER BY TotalSales DESC LIMIT 1; ==================================[1m Ai Message [0m================================== Tool Calls: sql_db_query (call_tSQOuxc7iQ1jvLzXSofCqK4V) Call ID: call_tSQOuxc7iQ1jvLzXSofCqK4V Args: query: SELECT e.FirstName, e.LastName, SUM(i.Total) as TotalSales FROM Employee e JOIN Customer c ON e.EmployeeId = c.SupportRepId JOIN Invoice i ON c.CustomerId = i.CustomerId WHERE strftime('%Y', i.InvoiceDate) = '2009' GROUP BY e.EmployeeId ORDER BY TotalSales DESC LIMIT 1; =================================[1m Tool Message [0m================================= Name: sql_db_query [('Steve', 'Johnson', 164.34)] ==================================[1m Ai Message [0m================================== The sales agent who made the most in sales in 2009 was Steve Johnson, with total sales of 164.34.