wehub-resource-sync
195 lines
9.2 KiB
Python
195 lines
9.2 KiB
Python
from scrapegraphai.helpers.models_tokens import models_tokens
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class TestModelsTokens:
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"""Test suite for verifying the models_tokens dictionary content and structure."""
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def test_openai_tokens(self):
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"""Test that the 'openai' provider exists and its tokens are valid positive integers."""
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openai_models = models_tokens.get("openai")
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assert openai_models is not None, (
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"'openai' key should be present in models_tokens"
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)
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for model, token in openai_models.items():
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assert isinstance(model, str), "Model name should be a string"
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assert isinstance(token, int), "Token limit should be an integer"
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assert token > 0, "Token limit should be positive"
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def test_azure_openai_tokens(self):
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"""Test that the 'azure_openai' provider exists and its tokens are valid."""
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azure_models = models_tokens.get("azure_openai")
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assert azure_models is not None, "'azure_openai' key should be present"
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for model, token in azure_models.items():
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assert isinstance(model, str), "Model name should be a string"
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assert isinstance(token, int), "Token limit should be an integer"
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def test_google_providers(self):
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"""Test that Google provider dictionaries ('google_genai' and 'google_vertexai') contain expected entries."""
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google_genai = models_tokens.get("google_genai")
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google_vertexai = models_tokens.get("google_vertexai")
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assert google_genai is not None, "'google_genai' key should be present"
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assert google_vertexai is not None, "'google_vertexai' key should be present"
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# Check a specific key from google_genai
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assert "gemini-pro" in google_genai, (
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"'gemini-pro' should be in google_genai models"
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)
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# Validate token values types
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for provider in [google_genai, google_vertexai]:
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for token in provider.values():
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assert isinstance(token, int), "Token limit must be an integer"
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def test_non_existent_provider(self):
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"""Test that a non-existent provider returns None."""
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assert models_tokens.get("non_existent") is None, (
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"Non-existent provider should return None"
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)
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def test_total_model_keys(self):
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"""Test that the total number of models across all providers is above an expected count."""
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total_keys = sum(len(details) for details in models_tokens.values())
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assert total_keys > 20, "Expected more than 20 total model tokens defined"
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def test_specific_token_value(self):
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"""Test specific expected token value for a known model."""
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openai = models_tokens.get("openai")
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# Verify that the token limit for "gpt-4" is 8192 as defined
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assert openai.get("gpt-4") == 8192, "Expected token limit for gpt-4 to be 8192"
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def test_non_empty_model_keys(self):
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"""Ensure that model token names are non-empty strings."""
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for provider, model_dict in models_tokens.items():
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for model in model_dict.keys():
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assert model != "", (
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f"Model name in provider '{provider}' should not be empty."
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)
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def test_token_limits_range(self):
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"""Test that token limits for all models fall within a plausible range (e.g., 1 to 300000)."""
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for provider, model_dict in models_tokens.items():
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for model, token in model_dict.items():
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assert 1 <= token <= 1100000, (
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f"Token limit for {model} in provider {provider} is out of plausible range."
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)
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def test_provider_structure(self):
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"""Test that every provider in models_tokens has a dictionary as its value."""
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for provider, models in models_tokens.items():
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assert isinstance(models, dict), (
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f"Provider {provider} should map to a dictionary, got {type(models).__name__}"
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)
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def test_non_empty_provider(self):
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"""Test that each provider dictionary is not empty."""
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for provider, models in models_tokens.items():
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assert len(models) > 0, (
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f"Provider {provider} should contain at least one model."
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)
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def test_specific_model_token_values(self):
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"""Test specific expected token values for selected models from various providers."""
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# Verify a token for a selected model from the 'openai' provider
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openai = models_tokens.get("openai")
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assert openai.get("gpt-3.5-turbo-0125") == 16385, (
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"Expected token limit for gpt-3.5-turbo-0125 in openai to be 16385"
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)
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# Verify a token for a selected model from the 'azure_openai' provider
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azure = models_tokens.get("azure_openai")
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assert azure.get("gpt-3.5") == 4096, (
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"Expected token limit for gpt-3.5 in azure_openai to be 4096"
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)
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# Verify a token for a selected model from the 'anthropic' provider
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anthropic = models_tokens.get("anthropic")
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assert anthropic.get("claude_instant") == 100000, (
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"Expected token limit for claude_instant in anthropic to be 100000"
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)
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def test_providers_count(self):
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"""Test that the total number of providers is as expected (at least 15)."""
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assert len(models_tokens) >= 15, (
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"Expected at least 15 providers in models_tokens"
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)
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def test_non_existent_model(self):
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"""Test that a non-existent model within a valid provider returns None."""
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openai = models_tokens.get("openai")
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assert openai.get("non_existent_model") is None, (
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"Non-existent model should return None from a valid provider."
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)
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def test_no_whitespace_in_model_names(self):
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"""Test that model names do not contain leading or trailing whitespace."""
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for provider, model_dict in models_tokens.items():
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for model in model_dict.keys():
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# Assert that stripping whitespace does not change the model name
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assert model == model.strip(), (
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f"Model name '{model}' in provider '{provider}' contains leading or trailing whitespace."
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)
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def test_specific_models_additional(self):
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"""Test specific token values for additional models across various providers."""
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# Check some models in the 'ollama' provider
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ollama = models_tokens.get("ollama")
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assert ollama.get("llama2") == 4096, (
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"Expected token limit for 'llama2' in ollama to be 4096"
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)
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assert ollama.get("llama2:70b") == 4096, (
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"Expected token limit for 'llama2:70b' in ollama to be 4096"
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)
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# Check a specific model from the 'mistralai' provider
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mistralai = models_tokens.get("mistralai")
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assert mistralai.get("open-codestral-mamba") == 256000, (
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"Expected token limit for 'open-codestral-mamba' in mistralai to be 256000"
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)
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# Check a specific model from the 'deepseek' provider
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deepseek = models_tokens.get("deepseek")
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assert deepseek.get("deepseek-chat") == 28672, (
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"Expected token limit for 'deepseek-chat' in deepseek to be 28672"
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)
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# Check a model from the 'ernie' provider
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ernie = models_tokens.get("ernie")
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assert ernie.get("ernie-bot") == 4096, (
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"Expected token limit for 'ernie-bot' in ernie to be 4096"
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)
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def test_nvidia_specific(self):
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"""Test specific token value for 'meta/codellama-70b' in the nvidia provider."""
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nvidia = models_tokens.get("nvidia")
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assert nvidia is not None, "'nvidia' provider should exist"
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# Verify token for 'meta/codellama-70b' equals 16384 as defined in the nvidia dictionary
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assert nvidia.get("meta/codellama-70b") == 16384, (
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"Expected token limit for 'meta/codellama-70b' in nvidia to be 16384"
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)
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def test_groq_specific(self):
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"""Test specific token value for 'claude-3-haiku-20240307\'' in the groq provider."""
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groq = models_tokens.get("groq")
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assert groq is not None, "'groq' provider should exist"
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# Note: The model name has an embedded apostrophe at the end in its name.
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assert groq.get("claude-3-haiku-20240307'") == 8192, (
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"Expected token limit for 'claude-3-haiku-20240307\\'' in groq to be 8192"
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)
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def test_togetherai_specific(self):
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"""Test specific token value for 'meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo' in the toghetherai provider."""
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togetherai = models_tokens.get("toghetherai")
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assert togetherai is not None, "'toghetherai' provider should exist"
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expected = 128000
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model_name = "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo"
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assert togetherai.get(model_name) == expected, (
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f"Expected token limit for '{model_name}' in toghetherai to be {expected}"
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)
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def test_ernie_all_values(self):
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"""Test that all models in the 'ernie' provider have token values exactly 4096."""
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ernie = models_tokens.get("ernie")
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assert ernie is not None, "'ernie' provider should exist"
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for model, token in ernie.items():
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assert token == 4096, (
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f"Expected token limit for '{model}' in ernie to be 4096, got {token}"
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)
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