youngkingdom/vllm
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Convert examples to ruff-format (#18400)

Browse Source 
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-05-26 17:57:54 +01:00
committed by GitHub
parent e7523c2e03
commit 27bebcd897
83 changed files with 2529 additions and 2405 deletions
Download Patch File Download Diff File Expand all files Collapse all files

43
examples/offline_inference/structured_outputs.py
View File

@ -1,9 +1,9 @@
# SPDX-License-Identifier: Apache-2.0
"""
This file demonstrates the example usage of guided decoding
to generate structured outputs using vLLM. It shows how to apply
different guided decoding techniques such as Choice, Regex, JSON schema,
and Grammar to produce structured and formatted results
This file demonstrates the example usage of guided decoding
to generate structured outputs using vLLM. It shows how to apply
different guided decoding techniques such as Choice, Regex, JSON schema,
and Grammar to produce structured and formatted results
based on specific prompts.
"""
@ -15,20 +15,20 @@ from vllm import LLM, SamplingParams
from vllm.sampling_params import GuidedDecodingParams
# 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)
guided_decoding_params_choice = GuidedDecodingParams(choice=["Positive", "Negative"])
sampling_params_choice = SamplingParams(guided_decoding=guided_decoding_params_choice)
prompt_choice = "Classify this sentiment: vLLM is wonderful!"
# 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"]
)
prompt_regex = (
"Generate an email address for Alan Turing, who works in Enigma."
"End in .com and new line. Example result:"
"alan.turing@enigma.com\n")
"alan.turing@enigma.com\n"
)
# Guided decoding by JSON using Pydantic schema
@ -47,10 +47,11 @@ 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)
prompt_json = ("Generate a JSON with the brand, model and car_type of"
"the most iconic car from the 90's")
sampling_params_json = SamplingParams(guided_decoding=guided_decoding_params_json)
prompt_json = (
"Generate a JSON with the brand, model and car_type of"
"the most iconic car from the 90's"
)
# Guided decoding by Grammar
simplified_sql_grammar = """
@ -61,12 +62,11 @@ table ::= "table_1 " | "table_2 "
condition ::= column "= " number
number ::= "1 " | "2 "
"""
guided_decoding_params_grammar = GuidedDecodingParams(
grammar=simplified_sql_grammar)
sampling_params_grammar = SamplingParams(
guided_decoding=guided_decoding_params_grammar)
prompt_grammar = ("Generate an SQL query to show the 'username' and 'email'"
"from the 'users' table.")
guided_decoding_params_grammar = GuidedDecodingParams(grammar=simplified_sql_grammar)
sampling_params_grammar = SamplingParams(guided_decoding=guided_decoding_params_grammar)
prompt_grammar = (
"Generate an SQL query to show the 'username' and 'email'from the 'users' table."
)
def format_output(title: str, output: str):
@ -90,8 +90,7 @@ def main():
json_output = generate_output(prompt_json, sampling_params_json, llm)
format_output("Guided decoding by JSON", json_output)
grammar_output = generate_output(prompt_grammar, sampling_params_grammar,
llm)
grammar_output = generate_output(prompt_grammar, sampling_params_grammar, llm)
format_output("Guided decoding by Grammar", grammar_output)