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