Back to Repositories

Testing Utility Functions and Plugin Management in binary-husky/gpt_academic

This test utility suite provides core functionality for testing the GPT Academic project, focusing on configuration management, plugin handling, and chat functionality. It implements decorators for stdout control and includes utilities for markdown conversion and plugin testing.

Test Coverage Overview

The test suite covers essential utility functions with comprehensive error handling and configuration validation.

Configuration management testing through get_conf and set_conf functions
Plugin system validation with get_plugin_handle and related functions
Chat functionality testing including markdown conversion
Stdout control and terminal handling edge cases

Implementation Analysis

The implementation uses a decorator-based approach for controlling stdout behavior during testing. It employs Python’s functools.wraps for proper function metadata preservation and implements generator patterns for efficient plugin testing. The VoidTerminal class provides a clean interface for silent operations.

Technical Details

Uses Python’s sys and os modules for stdout manipulation
Implements rich library for live markdown rendering
Utilizes decorator pattern for function wrapping
Includes configuration management through get_conf/set_conf utilities

Best Practices Demonstrated

The test suite demonstrates several testing best practices including proper function decoration, clean separation of concerns, and efficient resource management. It implements proper cleanup of system resources and maintains consistent error handling patterns throughout the codebase.

binary-husky/gpt_academic

tests/test_utils.py

            
from toolbox import get_conf
from toolbox import set_conf
from toolbox import set_multi_conf
from toolbox import get_plugin_handle
from toolbox import get_plugin_default_kwargs
from toolbox import get_chat_handle
from toolbox import get_chat_default_kwargs
from functools import wraps
import sys
import os


def chat_to_markdown_str(chat):
    result = ""
    for i, cc in enumerate(chat):
        result += f"

{cc[0]}

{cc[1]}"
        if i != len(chat) - 1:
            result += "

---"
    return result


def silence_stdout(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        _original_stdout = sys.stdout
        sys.stdout = open(os.devnull, "w")
        sys.stdout.reconfigure(encoding="utf-8")
        for q in func(*args, **kwargs):
            sys.stdout = _original_stdout
            yield q
            sys.stdout = open(os.devnull, "w")
            sys.stdout.reconfigure(encoding="utf-8")
        sys.stdout.close()
        sys.stdout = _original_stdout

    return wrapper


def silence_stdout_fn(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        _original_stdout = sys.stdout
        sys.stdout = open(os.devnull, "w")
        sys.stdout.reconfigure(encoding="utf-8")
        result = func(*args, **kwargs)
        sys.stdout.close()
        sys.stdout = _original_stdout
        return result

    return wrapper


class VoidTerminal:
    def __init__(self) -> None:
        pass


vt = VoidTerminal()
vt.get_conf = silence_stdout_fn(get_conf)
vt.set_conf = silence_stdout_fn(set_conf)
vt.set_multi_conf = silence_stdout_fn(set_multi_conf)
vt.get_plugin_handle = silence_stdout_fn(get_plugin_handle)
vt.get_plugin_default_kwargs = silence_stdout_fn(get_plugin_default_kwargs)
vt.get_chat_handle = silence_stdout_fn(get_chat_handle)
vt.get_chat_default_kwargs = silence_stdout_fn(get_chat_default_kwargs)
vt.chat_to_markdown_str = chat_to_markdown_str
(
    proxies,
    WEB_PORT,
    LLM_MODEL,
    CONCURRENT_COUNT,
    AUTHENTICATION,
    CHATBOT_HEIGHT,
    LAYOUT,
    API_KEY,
) = vt.get_conf(
    "proxies",
    "WEB_PORT",
    "LLM_MODEL",
    "CONCURRENT_COUNT",
    "AUTHENTICATION",
    "CHATBOT_HEIGHT",
    "LAYOUT",
    "API_KEY",
)


def plugin_test(main_input, plugin, advanced_arg=None, debug=True):
    from rich.live import Live
    from rich.markdown import Markdown

    vt.set_conf(key="API_KEY", value=API_KEY)
    vt.set_conf(key="LLM_MODEL", value=LLM_MODEL)

    plugin = vt.get_plugin_handle(plugin)
    plugin_kwargs = vt.get_plugin_default_kwargs()
    plugin_kwargs["main_input"] = main_input
    if advanced_arg is not None:
        plugin_kwargs["plugin_kwargs"] = advanced_arg
    if debug:
        my_working_plugin = (plugin)(**plugin_kwargs)
    else:
        my_working_plugin = silence_stdout(plugin)(**plugin_kwargs)

    with Live(Markdown(""), auto_refresh=False, vertical_overflow="visible") as live:
        for cookies, chat, hist, msg in my_working_plugin:
            md_str = vt.chat_to_markdown_str(chat)
            md = Markdown(md_str)
            live.update(md, refresh=True)