test_llm.py 3.0 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104
  1. import os
  2. from collections.abc import Generator
  3. import pytest
  4. from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
  5. from core.model_runtime.entities.message_entities import (
  6. AssistantPromptMessage,
  7. SystemPromptMessage,
  8. UserPromptMessage,
  9. )
  10. from core.model_runtime.errors.validate import CredentialsValidateFailedError
  11. from core.model_runtime.model_providers.openrouter.llm.llm import OpenRouterLargeLanguageModel
  12. def test_validate_credentials():
  13. model = OpenRouterLargeLanguageModel()
  14. with pytest.raises(CredentialsValidateFailedError):
  15. model.validate_credentials(
  16. model="mistralai/mixtral-8x7b-instruct", credentials={"api_key": "invalid_key", "mode": "chat"}
  17. )
  18. model.validate_credentials(
  19. model="mistralai/mixtral-8x7b-instruct",
  20. credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"},
  21. )
  22. def test_invoke_model():
  23. model = OpenRouterLargeLanguageModel()
  24. response = model.invoke(
  25. model="mistralai/mixtral-8x7b-instruct",
  26. credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "completion"},
  27. prompt_messages=[
  28. SystemPromptMessage(
  29. content="You are a helpful AI assistant.",
  30. ),
  31. UserPromptMessage(content="Who are you?"),
  32. ],
  33. model_parameters={
  34. "temperature": 1.0,
  35. "top_k": 2,
  36. "top_p": 0.5,
  37. },
  38. stop=["How"],
  39. stream=False,
  40. user="abc-123",
  41. )
  42. assert isinstance(response, LLMResult)
  43. assert len(response.message.content) > 0
  44. def test_invoke_stream_model():
  45. model = OpenRouterLargeLanguageModel()
  46. response = model.invoke(
  47. model="mistralai/mixtral-8x7b-instruct",
  48. credentials={"api_key": os.environ.get("TOGETHER_API_KEY"), "mode": "chat"},
  49. prompt_messages=[
  50. SystemPromptMessage(
  51. content="You are a helpful AI assistant.",
  52. ),
  53. UserPromptMessage(content="Who are you?"),
  54. ],
  55. model_parameters={
  56. "temperature": 1.0,
  57. "top_k": 2,
  58. "top_p": 0.5,
  59. },
  60. stop=["How"],
  61. stream=True,
  62. user="abc-123",
  63. )
  64. assert isinstance(response, Generator)
  65. for chunk in response:
  66. assert isinstance(chunk, LLMResultChunk)
  67. assert isinstance(chunk.delta, LLMResultChunkDelta)
  68. assert isinstance(chunk.delta.message, AssistantPromptMessage)
  69. def test_get_num_tokens():
  70. model = OpenRouterLargeLanguageModel()
  71. num_tokens = model.get_num_tokens(
  72. model="mistralai/mixtral-8x7b-instruct",
  73. credentials={
  74. "api_key": os.environ.get("TOGETHER_API_KEY"),
  75. },
  76. prompt_messages=[
  77. SystemPromptMessage(
  78. content="You are a helpful AI assistant.",
  79. ),
  80. UserPromptMessage(content="Hello World!"),
  81. ],
  82. )
  83. assert isinstance(num_tokens, int)
  84. assert num_tokens == 21