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Testing Chat Completion API Implementation in gpt4free

This test suite validates the chat completion functionality in the gpt4free library, testing both synchronous and asynchronous API implementations for generating responses. It demonstrates core message handling and streaming capabilities.

Test Coverage Overview

The test coverage focuses on two primary chat completion paths – synchronous streaming and asynchronous response generation.

Tests streaming response handling with poetry generation prompt
Validates asynchronous chat completion with basic greeting
Covers model selection and message formatting
Includes provider configuration options (commented examples)

Implementation Analysis

The testing approach employs both synchronous and asynchronous Python patterns to validate the g4f.ChatCompletion interface. It leverages Python’s asyncio framework for async testing, while using standard print statements for streaming output verification.

The implementation demonstrates proper async/await syntax and stream handling with flush controls for real-time output.

Technical Details

Uses Python’s built-in asyncio library
Implements sys.path manipulation for import resolution
Utilizes pathlib for cross-platform path handling
Tests against g4f.models.default configuration
Includes stream=True parameter testing

Best Practices Demonstrated

The test suite showcases several testing best practices including proper separation of synchronous and asynchronous test cases.

Clear test case isolation
Proper exception handling structure
Flexible provider configuration
Maintainable message formatting
Effective use of Python’s async features

xtekky/gpt4free

etc/testing/test_chat_completion.py

            
import sys
from pathlib import Path

sys.path.append(str(Path(__file__).parent.parent.parent))

import g4f, asyncio

print("create:", end=" ", flush=True)
for response in g4f.ChatCompletion.create(
    model=g4f.models.default,
    #provider=g4f.Provider.Bing,
    messages=[{"role": "user", "content": "write a poem about a tree"}],
    stream=True
):
    print(response, end="", flush=True)
print()

async def run_async():
    response = await g4f.ChatCompletion.create_async(
        model=g4f.models.default,
        #provider=g4f.Provider.Bing,
        messages=[{"role": "user", "content": "hello!"}],
    )
    print("create_async:", response)

asyncio.run(run_async())