sentence-transformers How to use itsanan/codebert-embed-crewai-base with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("itsanan/codebert-embed-crewai-base")
sentences = [
"Explain the test_code_docs_search_tool logic",
"def test_anthropic_call_with_interceptor_tracks_requests(self) -> None:\n \"\"\"Test that interceptor tracks Anthropic API requests.\"\"\"\n interceptor = AnthropicTestInterceptor()\n llm = LLM(model=\"anthropic/claude-3-5-haiku-20241022\", interceptor=interceptor)\n\n # Make a simple completion call\n result = llm.call(\n messages=[{\"role\": \"user\", \"content\": \"Say 'Hello World' and nothing else\"}]\n )\n\n # Verify custom headers were added\n for request in interceptor.outbound_calls:\n assert \"X-Anthropic-Interceptor\" in request.headers\n assert request.headers[\"X-Anthropic-Interceptor\"] == \"anthropic-test-value\"\n assert \"X-Request-ID\" in request.headers\n assert request.headers[\"X-Request-ID\"] == \"test-request-456\"\n\n # Verify response was tracked\n for response in interceptor.inbound_calls:\n assert \"X-Response-Tracked\" in response.headers\n assert response.headers[\"X-Response-Tracked\"] == \"true\"\n\n # Verify result is valid\n assert result is not None\n assert isinstance(result, str)\n assert len(result) > 0",
"def on_inbound(self, message: httpx.Response) -> httpx.Response:\n \"\"\"Pass through inbound response.\n\n Args:\n message: The inbound response.\n\n Returns:\n The response unchanged.\n \"\"\"\n return message",
"def test_code_docs_search_tool(mock_adapter):\n mock_adapter.query.return_value = \"test documentation\"\n\n docs_url = \"https://crewai.com/any-docs-url\"\n search_query = \"test documentation\"\n tool = CodeDocsSearchTool(docs_url=docs_url, adapter=mock_adapter)\n result = tool._run(search_query=search_query)\n assert \"test documentation\" in result\n mock_adapter.add.assert_called_once_with(docs_url, data_type=DataType.DOCS_SITE)\n mock_adapter.query.assert_called_once_with(\n search_query, similarity_threshold=0.6, limit=5\n )\n\n mock_adapter.query.reset_mock()\n mock_adapter.add.reset_mock()\n\n tool = CodeDocsSearchTool(adapter=mock_adapter)\n result = tool._run(docs_url=docs_url, search_query=search_query)\n assert \"test documentation\" in result\n mock_adapter.add.assert_called_once_with(docs_url, data_type=DataType.DOCS_SITE)\n mock_adapter.query.assert_called_once_with(\n search_query, similarity_threshold=0.6, limit=5\n )"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
