Implementation:ThreeSR Awesome Inference Time Scaling Config Function

Page Metadata
Knowledge Sources	Awesome-Inference-Time-Scaling
Domains	CLI Design, Configuration Management, Python Scripting
Last Updated	2026-02-14 00:00 GMT

Overview

Concrete tool for parsing command-line arguments provided by the config() function in fetch_semantic_info.py.

Description

The config() function creates an argparse.ArgumentParser instance, defines the --paper_name argument with a default value of "Inference-Time Scaling", parses the command-line arguments, and returns the resulting argparse.Namespace object. This function is the sole entry point for runtime configuration in the repository and is called at the top of the __main__ block.

Usage

Import or call this function when:

• Running fetch_semantic_info.py from the command line to fetch papers
• You need to override the default search query with a custom paper name
• Integrating the script into a CI/CD pipeline or automation workflow where the search term varies

Code Reference

Source Location: fetch_semantic_info.py, lines 14-20

Function Signature:

def config() -> argparse.Namespace

Import Statement:

from fetch_semantic_info import config

Source Code:

def config() -> argparse.Namespace:
    parser = argparse.ArgumentParser(
        description="Fetch Paper Data and update the README.md paper list"
    )
    parser.add_argument("--paper_name", type=str, default="Inference-Time Scaling")
    args = parser.parse_args()
    return args

Dependencies:

• argparse (Python standard library)

I/O Contract

Inputs:

Parameter	Type	Default	Description
--paper_name	str	"Inference-Time Scaling"	The search query string passed to the Semantic Scholar API to find relevant papers

Note: This function takes no explicit parameters. It reads from sys.argv via argparse.

Outputs:

Field	Type	Description
args.paper_name	str	The paper name or search query to use for the Semantic Scholar search

The return type is argparse.Namespace, which exposes each defined argument as an attribute.

Usage Examples

Example 1: Default invocation (no arguments)

python fetch_semantic_info.py
# Uses default paper_name="Inference-Time Scaling"

Example 2: Custom paper name

python fetch_semantic_info.py --paper_name "Chain of Thought Reasoning"

Example 3: Programmatic usage

import sys
# Simulate command-line arguments for testing
sys.argv = ["fetch_semantic_info.py", "--paper_name", "Reward Modeling"]

from fetch_semantic_info import config

args = config()
print(args.paper_name)  # Output: "Reward Modeling"

Example 4: Viewing the help text

python fetch_semantic_info.py --help
# Output:
# usage: fetch_semantic_info.py [-h] [--paper_name PAPER_NAME]
#
# Fetch Paper Data and update the README.md paper list
#
# optional arguments:
#   -h, --help            show this help message and exit
#   --paper_name PAPER_NAME

Related Pages

• Principle:ThreeSR_Awesome_Inference_Time_Scaling_CLI_Configuration -- The principle of CLI Configuration that this function implements
• Environment:ThreeSR_Awesome_Inference_Time_Scaling_Python_Runtime_Environment