actually use a lark grammar

the example tests do check it!

Author: matthewfranglen

docs/models/openai.md

@@ -239,7 +239,18 @@ from pydantic_ai.models.openai import OpenAIResponsesModel
 from pydantic_ai.output import ToolOutput
 from pydantic_ai.tools import FunctionTextFormat
 
-sql_grammar_definition = '...'  # (1)!
+sql_grammar_definition = r'''
+start: select_stmt
+select_stmt: "SELECT" select_list "FROM" table ("WHERE" condition ("AND" condition)*)?
+select_list: "*" | column ("," column)*
+table: "users" | "orders"
+column: "id" | "user_id" | "name" | "age"
+condition: column ("=" | ">" | "<") (NUMBER | STRING)
+%import common.NUMBER
+%import common.ESCAPED_STRING -> STRING
+%import common.WS
+%ignore WS
+''' # (1)!
 def database_query(sql: str) -> str:
     return sql  # (2)!
 
@@ -248,7 +259,7 @@ model = OpenAIResponsesModel('gpt-5')
 agent = Agent(model, output_type=output_tool)
 ```
 
-1. An inline SQL grammar definition would be quite extensive and so it has been omitted, you can find an example SQL grammar [in the openai example](https://cookbook.openai.com/examples/gpt-5/gpt-5_new_params_and_tools#33-example---sql-dialect--ms-sql-vs-postgresql). There are also example grammars in the [lark repo](https://github.com/lark-parser/lark/blob/master/examples/composition/json.lark).
+1. An inline SQL grammar definition would be quite extensive and so this simplified version has been written, you can find an example SQL grammar [in the openai example](https://cookbook.openai.com/examples/gpt-5/gpt-5_new_params_and_tools#33-example---sql-dialect--ms-sql-vs-postgresql). There are also example grammars in the [lark repo](https://github.com/lark-parser/lark/blob/master/examples/composition/json.lark). Remember that a simpler grammar that matches your DDL will be easier for GPT-5 to work with and will result in fewer semantically invalid results.
 2. Returning the input directly might seem odd, remember that it has been constrained to the provided grammar. This can be useful if you want GPT-5 to generate content according to a grammar that you then use extensively through your program.
 
 ##### Best Practices