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[Misc] refactor examples for the structured outputs
Signed-off-by: reidliu41 <reid201711@gmail.com>
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‎examples/online_serving/openai_chat_completion_structured_outputs.py‎

Lines changed: 117 additions & 77 deletions
Original file line numberDiff line numberDiff line change
@@ -1,43 +1,49 @@
11
# SPDX-License-Identifier: Apache-2.0
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"""
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To run this example, you need to start the vLLM server:
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```bash
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vllm serve Qwen/Qwen2.5-3B-Instruct
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```
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"""
29

310
from enum import Enum
411

512
from openai import BadRequestError, OpenAI
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from pydantic import BaseModel
714

8-
client = OpenAI(
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base_url="http://localhost:8000/v1",
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api_key="-",
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)
1215

1316
# Guided decoding by Choice (list of possible options)
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completion = client.chat.completions.create(
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model="Qwen/Qwen2.5-3B-Instruct",
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messages=[{
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"role": "user",
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"content": "Classify this sentiment: vLLM is wonderful!"
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}],
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extra_body={"guided_choice": ["positive", "negative"]},
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)
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print(completion.choices[0].message.content)
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def guided_choice_completion(client: OpenAI, model: str):
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completion = client.chat.completions.create(
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model=model,
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messages=[{
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"role": "user",
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"content": "Classify this sentiment: vLLM is wonderful!"
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}],
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extra_body={"guided_choice": ["positive", "negative"]},
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)
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return completion.choices[0].message.content
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2328

2429
# Guided decoding by Regex
25-
prompt = ("Generate an email address for Alan Turing, who works in Enigma."
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"End in .com and new line. Example result:"
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"alan.turing@enigma.com\n")
28-
29-
completion = client.chat.completions.create(
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model="Qwen/Qwen2.5-3B-Instruct",
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messages=[{
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"role": "user",
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"content": prompt,
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}],
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extra_body={
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"guided_regex": r"\w+@\w+\.com\n",
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"stop": ["\n"]
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},
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)
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print(completion.choices[0].message.content)
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def guided_regex_completion(client: OpenAI, model: str):
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prompt = ("Generate an email address for Alan Turing, who works in Enigma."
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"End in .com and new line. Example result:"
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"alan.turing@enigma.com\n")
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35+
completion = client.chat.completions.create(
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model=model,
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messages=[{
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"role": "user",
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"content": prompt,
40+
}],
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extra_body={
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"guided_regex": r"\w+@\w+\.com\n",
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"stop": ["\n"]
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},
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)
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return completion.choices[0].message.content
4147

4248

4349
# Guided decoding by JSON using Pydantic schema
@@ -54,66 +60,100 @@ class CarDescription(BaseModel):
5460
car_type: CarType
5561

5662

57-
json_schema = CarDescription.model_json_schema()
58-
59-
prompt = ("Generate a JSON with the brand, model and car_type of"
60-
"the most iconic car from the 90's")
61-
completion = client.chat.completions.create(
62-
model="Qwen/Qwen2.5-3B-Instruct",
63-
messages=[{
64-
"role": "user",
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"content": prompt,
66-
}],
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extra_body={"guided_json": json_schema},
68-
)
69-
print(completion.choices[0].message.content)
63+
def guided_json_completion(client: OpenAI, model: str):
64+
json_schema = CarDescription.model_json_schema()
7065

71-
# Guided decoding by Grammar
72-
simplified_sql_grammar = """
73-
root ::= select_statement
66+
prompt = ("Generate a JSON with the brand, model and car_type of"
67+
"the most iconic car from the 90's")
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completion = client.chat.completions.create(
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model=model,
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messages=[{
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"role": "user",
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"content": prompt,
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}],
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extra_body={"guided_json": json_schema},
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)
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return completion.choices[0].message.content
7477

75-
select_statement ::= "SELECT " column " from " table " where " condition
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77-
column ::= "col_1 " | "col_2 "
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# Guided decoding by Grammar
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def guided_grammar_completion(client: OpenAI, model: str):
81+
simplified_sql_grammar = """
82+
root ::= select_statement
7883
79-
table ::= "table_1 " | "table_2 "
84+
select_statement ::= "SELECT " column " from " table " where " condition
8085
81-
condition ::= column "= " number
86+
column ::= "col_1 " | "col_2 "
8287
83-
number ::= "1 " | "2 "
84-
"""
88+
table ::= "table_1 " | "table_2 "
8589
86-
prompt = ("Generate an SQL query to show the 'username' and 'email'"
87-
"from the 'users' table.")
88-
completion = client.chat.completions.create(
89-
model="Qwen/Qwen2.5-3B-Instruct",
90-
messages=[{
91-
"role": "user",
92-
"content": prompt,
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}],
94-
extra_body={"guided_grammar": simplified_sql_grammar},
95-
)
96-
print(completion.choices[0].message.content)
90+
condition ::= column "= " number
9791
98-
# Extra backend options
99-
prompt = ("Generate an email address for Alan Turing, who works in Enigma."
100-
"End in .com and new line. Example result:"
101-
"alan.turing@enigma.com\n")
92+
number ::= "1 " | "2 "
93+
"""
10294

103-
try:
104-
# The no-fallback option forces vLLM to use xgrammar, so when it fails
105-
# you get a 400 with the reason why
95+
prompt = ("Generate an SQL query to show the 'username' and 'email'"
96+
"from the 'users' table.")
10697
completion = client.chat.completions.create(
107-
model="Qwen/Qwen2.5-3B-Instruct",
98+
model=model,
10899
messages=[{
109100
"role": "user",
110101
"content": prompt,
111102
}],
112-
extra_body={
113-
"guided_regex": r"\w+@\w+\.com\n",
114-
"stop": ["\n"],
115-
"guided_decoding_backend": "xgrammar:no-fallback"
116-
},
103+
extra_body={"guided_grammar": simplified_sql_grammar},
104+
)
105+
return completion.choices[0].message.content
106+
107+
108+
# Extra backend options
109+
def extra_backend_options_completion(client: OpenAI, model: str):
110+
prompt = ("Generate an email address for Alan Turing, who works in Enigma."
111+
"End in .com and new line. Example result:"
112+
"alan.turing@enigma.com\n")
113+
114+
try:
115+
# The no-fallback option forces vLLM to use xgrammar, so when it fails
116+
# you get a 400 with the reason why
117+
completion = client.chat.completions.create(
118+
model=model,
119+
messages=[{
120+
"role": "user",
121+
"content": prompt,
122+
}],
123+
extra_body={
124+
"guided_regex": r"\w+@\w+\.com\n",
125+
"stop": ["\n"],
126+
"guided_decoding_backend": "xgrammar:no-fallback"
127+
},
128+
)
129+
return completion.choices[0].message.content
130+
except BadRequestError as e:
131+
print("This error is expected:", e)
132+
133+
134+
def main():
135+
client: OpenAI = OpenAI(
136+
base_url="http://localhost:8000/v1",
137+
api_key="-",
117138
)
118-
except BadRequestError as e:
119-
print("This error is expected:", e)
139+
140+
model = "Qwen/Qwen2.5-3B-Instruct"
141+
142+
print("Guided Choice Completion:")
143+
print(guided_choice_completion(client, model))
144+
145+
print("\nGuided Regex Completion:")
146+
print(guided_regex_completion(client, model))
147+
148+
print("\nGuided JSON Completion:")
149+
print(guided_json_completion(client, model))
150+
151+
print("\nGuided Grammar Completion:")
152+
print(guided_grammar_completion(client, model))
153+
154+
print("\nExtra Backend Options Completion:")
155+
print(extra_backend_options_completion(client, model))
156+
157+
158+
if __name__ == "__main__":
159+
main()

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