[Bug Fix]: Fix test cases and update version to 0.1.93 (#1303)
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@@ -97,7 +97,6 @@ class BaseLlmConfig(BaseConfig):
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endpoint: Optional[str] = None,
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model_kwargs: Optional[dict[str, Any]] = None,
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local: Optional[bool] = False,
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base_url: Optional[str] = None,
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):
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"""
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Initializes a configuration class instance for the LLM.
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@@ -172,7 +171,6 @@ class BaseLlmConfig(BaseConfig):
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self.endpoint = endpoint
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self.model_kwargs = model_kwargs
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self.local = local
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self.base_url = base_url
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if isinstance(prompt, str):
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prompt = Template(prompt)
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@@ -1,6 +1,6 @@
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[tool.poetry]
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name = "embedchain"
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version = "0.1.92"
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version = "0.1.93"
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description = "Simplest open source retrieval(RAG) framework"
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authors = [
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"Taranjeet Singh <taranjeet@embedchain.ai>",
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@@ -30,6 +30,7 @@ def mock_data():
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@pytest.fixture
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def mock_answer_relevance_metric(monkeypatch):
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monkeypatch.setenv("OPENAI_API_KEY", "test_api_key")
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monkeypatch.setenv("OPENAI_API_BASE", "test_api_base")
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metric = AnswerRelevance()
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return metric
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@@ -73,6 +73,7 @@ def test_get_llm_model_answer_without_system_prompt(config, mocker):
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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)
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@@ -98,6 +99,7 @@ def test_get_llm_model_answer_with_tools(config, mocker, mock_return, expected):
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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)
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mocked_convert_to_openai_tool.assert_called_once_with({"test": "test"})
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mocked_json_output_tools_parser.assert_called_once()
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@@ -14,6 +14,7 @@ from embedchain.vectordb.chroma import ChromaDB
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@pytest.fixture
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def app():
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os.environ["OPENAI_API_KEY"] = "test_api_key"
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os.environ["OPENAI_API_BASE"] = "test_api_base"
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return App()
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@@ -26,6 +26,7 @@ class TestFactories:
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def test_llm_factory_create(self, provider_name, config_data, expected_class):
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os.environ["ANTHROPIC_API_KEY"] = "test_api_key"
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os.environ["OPENAI_API_KEY"] = "test_api_key"
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os.environ["OPENAI_API_BASE"] = "test_api_base"
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llm_instance = LlmFactory.create(provider_name, config_data)
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assert isinstance(llm_instance, expected_class)
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