Make structured output example output more complete

Signed-off-by: shen-shanshan <467638484@qq.com>

Author: shen-shanshan

examples/offline_inference/structured_outputs.py

@@ -15,6 +15,8 @@
 from vllm import LLM, SamplingParams
 from vllm.sampling_params import GuidedDecodingParams
 
+MAX_TOKENS = 50
+
 # Guided decoding by Choice (list of possible options)
 guided_decoding_params_choice = GuidedDecodingParams(choice=["Positive", "Negative"])
 sampling_params_choice = SamplingParams(guided_decoding=guided_decoding_params_choice)
@@ -23,7 +25,9 @@
 # Guided decoding by Regex
 guided_decoding_params_regex = GuidedDecodingParams(regex=r"\w+@\w+\.com\n")
 sampling_params_regex = SamplingParams(
-    guided_decoding=guided_decoding_params_regex, stop=["\n"]
+    guided_decoding=guided_decoding_params_regex,
+    stop=["\n"],
+    max_tokens=MAX_TOKENS,
 )
 prompt_regex = (
     "Generate an email address for Alan Turing, who works in Enigma."
@@ -48,7 +52,10 @@ class CarDescription(BaseModel):
 
 json_schema = CarDescription.model_json_schema()
 guided_decoding_params_json = GuidedDecodingParams(json=json_schema)
-sampling_params_json = SamplingParams(guided_decoding=guided_decoding_params_json)
+sampling_params_json = SamplingParams(
+    guided_decoding=guided_decoding_params_json,
+    max_tokens=MAX_TOKENS,
+)
 prompt_json = (
     "Generate a JSON with the brand, model and car_type of"
     "the most iconic car from the 90's"
@@ -64,7 +71,10 @@ class CarDescription(BaseModel):
 number ::= "1 " | "2 "
 """
 guided_decoding_params_grammar = GuidedDecodingParams(grammar=simplified_sql_grammar)
-sampling_params_grammar = SamplingParams(guided_decoding=guided_decoding_params_grammar)
+sampling_params_grammar = SamplingParams(
+    guided_decoding=guided_decoding_params_grammar,
+    max_tokens=MAX_TOKENS,
+)
 prompt_grammar = (
     "Generate an SQL query to show the 'username' and 'email'from the 'users' table."
 )