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Fix variable name inconsistency in SQL agent tutorial #1552

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Nov 20, 2025
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Fix variable name inconsistency in SQL agent tutorial #1552

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14 changes: 7 additions & 7 deletions src/oss/langgraph/sql-agent.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -169,7 +169,7 @@ Use the `SQLDatabase` wrapper available in the `langchain_community` package to
```python
from langchain_community.agent_toolkits import SQLDatabaseToolkit

toolkit = SQLDatabaseToolkit(db=db, llm=llm)
toolkit = SQLDatabaseToolkit(db=db, llm=model)

tools = toolkit.get_tools()

Expand Down Expand Up @@ -304,7 +304,7 @@ def list_tables(state: MessagesState):
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")
llm_with_tools = model.bind_tools([get_schema_tool], tool_choice="any")
response = llm_with_tools.invoke(state["messages"])

return {"messages": [response]}
Expand Down Expand Up @@ -335,7 +335,7 @@ def generate_query(state: MessagesState):
}
# 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])
llm_with_tools = model.bind_tools([run_query_tool])
response = llm_with_tools.invoke([system_message] + state["messages"])

return {"messages": [response]}
Expand Down Expand Up @@ -369,7 +369,7 @@ def check_query(state: MessagesState):
# 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")
llm_with_tools = model.bind_tools([run_query_tool], tool_choice="any")
response = llm_with_tools.invoke([system_message, user_message])
response.id = state["messages"][-1].id

Expand Down Expand Up @@ -407,7 +407,7 @@ async function listTables(state: typeof MessagesAnnotation.State) {

// Example: force a model to create a tool call
async function callGetSchema(state: typeof MessagesAnnotation.State) {
const llmWithTools = llm.bindTools([getSchemaTool], {
const llmWithTools = model.bindTools([getSchemaTool], {
tool_choice: "any",
});
const response = await llmWithTools.invoke(state.messages);
Expand Down Expand Up @@ -435,7 +435,7 @@ async function generateQuery(state: typeof MessagesAnnotation.State) {
const systemMessage = new SystemMessage(generateQuerySystemPrompt);
// We do not force a tool call here, to allow the model to
// respond naturally when it obtains the solution.
const llmWithTools = llm.bindTools([queryTool]);
const llmWithTools = model.bindTools([queryTool]);
const response = await llmWithTools.invoke([systemMessage, ...state.messages]);

return { messages: [response] };
Expand Down Expand Up @@ -469,7 +469,7 @@ async function checkQuery(state: typeof MessagesAnnotation.State) {
}
const toolCall = lastMessage.tool_calls[0];
const userMessage = new HumanMessage(toolCall.args.query);
const llmWithTools = llm.bindTools([queryTool], {
const llmWithTools = model.bindTools([queryTool], {
tool_choice: "any",
});
const response = await llmWithTools.invoke([systemMessage, userMessage]);
Expand Down