sentence-transformers How to use itsanan/codebert-finetuned-crewai-base with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("itsanan/codebert-finetuned-crewai-base")
sentences = [
"How to implement __del__?",
"class SampleMultiCrewFlow(Flow[SimpleState]):\n @start()\n def first_crew(self):\n \"\"\"Run first crew.\"\"\"\n agent = Agent(\n role=\"first agent\",\n goal=\"first task\",\n backstory=\"first agent\",\n llm=mock_llm_1,\n )\n task = Task(\n description=\"First task\",\n expected_output=\"first result\",\n agent=agent,\n )\n crew = Crew(\n agents=[agent],\n tasks=[task],\n share_crew=True,\n )\n\n result = crew.kickoff()\n\n assert crew._execution_span is not None\n return str(result.raw)\n\n @listen(first_crew)\n def second_crew(self, first_result: str):\n \"\"\"Run second crew.\"\"\"\n agent = Agent(\n role=\"second agent\",\n goal=\"second task\",\n backstory=\"second agent\",\n llm=mock_llm_2,\n )\n task = Task(\n description=\"Second task\",\n expected_output=\"second result\",\n agent=agent,\n )\n crew = Crew(\n agents=[agent],\n tasks=[task],\n share_crew=True,\n )\n\n result = crew.kickoff()\n\n assert crew._execution_span is not None\n\n self.state.result = f\"{first_result} + {result.raw}\"\n return self.state.result",
"async def test_anthropic_async_with_tools():\n \"\"\"Test async call with tools.\"\"\"\n llm = AnthropicCompletion(model=\"claude-sonnet-4-0\")\n\n tools = [\n {\n \"type\": \"function\",\n \"function\": {\n \"name\": \"get_weather\",\n \"description\": \"Get the current weather for a location\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"location\": {\n \"type\": \"string\",\n \"description\": \"The city and state, e.g. San Francisco, CA\"\n }\n },\n \"required\": [\"location\"]\n }\n }\n }\n ]\n\n result = await llm.acall(\n \"What's the weather in San Francisco?\",\n tools=tools\n )\n logging.debug(\"result: %s\", result)\n\n assert result is not None\n assert isinstance(result, str)",
"def __del__(self):\n \"\"\"Cleanup connections on deletion.\"\"\"\n try:\n if self._connection_pool:\n for conn in self._connection_pool:\n try:\n conn.close()\n except Exception: # noqa: PERF203, S110\n pass\n if self._thread_pool:\n self._thread_pool.shutdown()\n except Exception: # noqa: S110\n pass"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
