gpt4free/etc/unittest/client.py
kqlio67 9def1aa71f
Update model configurations, provider implementations, and documentation (#2577)
* Update model configurations, provider implementations, and documentation

- Updated model names and aliases for Qwen QVQ 72B and Qwen 2 72B (@TheFirstNoob)
- Revised HuggingSpace class configuration, added default_image_model
- Added llama-3.2-70b alias for Llama 3.2 70B model in AutonomousAI
- Removed BlackboxCreateAgent class
- Added gpt-4o alias for Copilot model
- Moved api_key to Mhystical class attribute
- Added models property with default_model value for Free2GPT
- Simplified Jmuz class implementation
- Improved image generation and model handling in DeepInfra
- Standardized default models and removed aliases in Gemini
- Replaced model aliases with direct model list in GlhfChat (@TheFirstNoob)
- Removed trailing slash from image generation URL in PollinationsAI (https://github.com/xtekky/gpt4free/issues/2571)
- Updated llama and qwen model configurations
- Enhanced provider documentation and model details

* Removed from (g4f/models.py) 'Yqcloud' provider from Default due to error 'ResponseStatusError: Response 429: 文字过长,请删减后重试。'

* Update docs/providers-and-models.md

* refactor(g4f/Provider/DDG.py): Add error handling and rate limiting to DDG provider

- Add custom exception classes for rate limits, timeouts, and conversation limits
- Implement rate limiting with sleep between requests (0.75s minimum delay)
- Add model validation method to check supported models
- Add proper error handling for API responses with custom exceptions
- Improve session cookie handling for conversation persistence
- Clean up User-Agent string and remove redundant code
- Add proper error propagation through async generator

Breaking changes:
- New custom exceptions may require updates to error handling code
- Rate limiting affects request timing and throughput
- Model validation is now stricter

Related:
- Adds error handling similar to standard API clients
- Improves reliability and robustness of chat interactions

* Update g4f/models.py g4f/Provider/PollinationsAI.py

* Update g4f/models.py

* Restored provider which was not working and was disabled (g4f/Provider/DeepInfraChat.py)

* Fixing a bug with Streaming Completions

* Update g4f/Provider/PollinationsAI.py

* Update g4f/Provider/Blackbox.py g4f/Provider/DDG.py

* Added another model for generating images 'ImageGeneration2' to the 'Blackbox' provider

* Update docs/providers-and-models.md

* Update g4f/models.py g4f/Provider/Blackbox.py

* Added a new OIVSCode provider from the Text Models and Vision (Image Upload) model

* Update docs/providers-and-models.md

* docs: add Conversation Memory class with context handling requested by @TheFirstNoob

* Simplified README.md documentation added new docs/configuration.md documentation

* Update add README.md docs/configuration.md

* Update README.md

* Update docs/providers-and-models.md g4f/models.py g4f/Provider/PollinationsAI.py

* Added new model deepseek-r1 to Blackbox provider. @TheFirstNoob

* Fixed bugs and updated docs/providers-and-models.md etc/unittest/client.py g4f/models.py g4f/Provider/.

---------

Co-authored-by: kqlio67 <>
Co-authored-by: H Lohaus <hlohaus@users.noreply.github.com>
2025-01-24 03:47:57 +01:00

141 lines
6.9 KiB
Python

from __future__ import annotations
import unittest
from g4f.errors import ModelNotFoundError
from g4f.client import Client, AsyncClient, ChatCompletion, ChatCompletionChunk, get_model_and_provider
from g4f.Provider.Copilot import Copilot
from g4f.models import gpt_4o
from .mocks import AsyncGeneratorProviderMock, ModelProviderMock, YieldProviderMock
DEFAULT_MESSAGES = [{'role': 'user', 'content': 'Hello'}]
class AsyncTestPassModel(unittest.IsolatedAsyncioTestCase):
async def test_response(self):
client = AsyncClient(provider=AsyncGeneratorProviderMock)
response = await client.chat.completions.create(DEFAULT_MESSAGES, "")
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("Mock", response.choices[0].message.content)
async def test_pass_model(self):
client = AsyncClient(provider=ModelProviderMock)
response = await client.chat.completions.create(DEFAULT_MESSAGES, "Hello")
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("Hello", response.choices[0].message.content)
async def test_max_tokens(self):
client = AsyncClient(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = await client.chat.completions.create(messages, "Hello", max_tokens=1)
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How ", response.choices[0].message.content)
response = await client.chat.completions.create(messages, "Hello", max_tokens=2)
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How are ", response.choices[0].message.content)
async def test_max_stream(self):
client = AsyncClient(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = await client.chat.completions.create(messages, "Hello", stream=True)
async for chunk in response:
chunk: ChatCompletionChunk = chunk
self.assertIsInstance(chunk, ChatCompletionChunk)
if chunk.choices[0].delta.content is not None:
self.assertIsInstance(chunk.choices[0].delta.content, str)
messages = [{'role': 'user', 'content': chunk} for chunk in ["You ", "You ", "Other", "?"]]
response = await client.chat.completions.create(messages, "Hello", stream=True, max_tokens=2)
response_list = []
async for chunk in response:
response_list.append(chunk)
self.assertEqual(len(response_list), 3)
for chunk in response_list:
if chunk.choices[0].delta.content is not None:
self.assertEqual(chunk.choices[0].delta.content, "You ")
async def test_stop(self):
client = AsyncClient(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = await client.chat.completions.create(messages, "Hello", stop=["and"])
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How are you?", response.choices[0].message.content)
class TestPassModel(unittest.TestCase):
def test_response(self):
client = Client(provider=AsyncGeneratorProviderMock)
response = client.chat.completions.create(DEFAULT_MESSAGES, "")
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("Mock", response.choices[0].message.content)
def test_pass_model(self):
client = Client(provider=ModelProviderMock)
response = client.chat.completions.create(DEFAULT_MESSAGES, "Hello")
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("Hello", response.choices[0].message.content)
def test_max_tokens(self):
client = Client(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = client.chat.completions.create(messages, "Hello", max_tokens=1)
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How ", response.choices[0].message.content)
response = client.chat.completions.create(messages, "Hello", max_tokens=2)
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How are ", response.choices[0].message.content)
def test_max_stream(self):
client = Client(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = client.chat.completions.create(messages, "Hello", stream=True)
for chunk in response:
self.assertIsInstance(chunk, ChatCompletionChunk)
if chunk.choices[0].delta.content is not None:
self.assertIsInstance(chunk.choices[0].delta.content, str)
messages = [{'role': 'user', 'content': chunk} for chunk in ["You ", "You ", "Other", "?"]]
response = client.chat.completions.create(messages, "Hello", stream=True, max_tokens=2)
response_list = list(response)
self.assertEqual(len(response_list), 3)
for chunk in response_list:
if chunk.choices[0].delta.content is not None:
self.assertEqual(chunk.choices[0].delta.content, "You ")
def test_stop(self):
client = Client(provider=YieldProviderMock)
messages = [{'role': 'user', 'content': chunk} for chunk in ["How ", "are ", "you", "?"]]
response = client.chat.completions.create(messages, "Hello", stop=["and"])
self.assertIsInstance(response, ChatCompletion)
self.assertEqual("How are you?", response.choices[0].message.content)
def test_model_not_found(self):
def run_exception():
client = Client()
client.chat.completions.create(DEFAULT_MESSAGES, "Hello")
self.assertRaises(ModelNotFoundError, run_exception)
def test_best_provider(self):
not_default_model = "gpt-4o"
model, provider = get_model_and_provider(not_default_model, None, False)
self.assertTrue(hasattr(provider, "create_completion"))
self.assertEqual(model, not_default_model)
def test_default_model(self):
default_model = ""
model, provider = get_model_and_provider(default_model, None, False)
self.assertTrue(hasattr(provider, "create_completion"))
self.assertEqual(model, default_model)
def test_provider_as_model(self):
provider_as_model = Copilot.__name__
model, provider = get_model_and_provider(provider_as_model, None, False)
self.assertTrue(hasattr(provider, "create_completion"))
self.assertIsInstance(model, str)
self.assertEqual(model, Copilot.default_model)
def test_get_model(self):
model, provider = get_model_and_provider(gpt_4o.name, None, False)
self.assertTrue(hasattr(provider, "create_completion"))
self.assertEqual(model, gpt_4o.name)
if __name__ == '__main__':
unittest.main()