Instructions to use anaghaj111/codebert-base-code-embed-mrl-langchain-langgraph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anaghaj111/codebert-base-code-embed-mrl-langchain-langgraph with sentence-transformers:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("anaghaj111/codebert-base-code-embed-mrl-langchain-langgraph")

sentences = [
    "Explain the __init__ logic",
    "async def test_handler_with_async_execution() -> None:\n    \"\"\"Test handler works correctly with async tool execution.\"\"\"\n\n    @tool\n    def async_add(a: int, b: int) -> int:\n        \"\"\"Async add two numbers.\"\"\"\n        return a + b\n\n    def modifying_handler(\n        request: ToolCallRequest,\n        execute: Callable[[ToolCallRequest], ToolMessage | Command],\n    ) -> ToolMessage | Command:\n        \"\"\"Handler that modifies arguments.\"\"\"\n        # Add 10 to both arguments using override method\n        modified_call = {\n            **request.tool_call,\n            \"args\": {\n                **request.tool_call[\"args\"],\n                \"a\": request.tool_call[\"args\"][\"a\"] + 10,\n                \"b\": request.tool_call[\"args\"][\"b\"] + 10,\n            },\n        }\n        modified_request = request.override(tool_call=modified_call)\n        return execute(modified_request)\n\n    tool_node = ToolNode([async_add], wrap_tool_call=modifying_handler)\n\n    result = await tool_node.ainvoke(\n        {\n            \"messages\": [\n                AIMessage(\n                    \"adding\",\n                    tool_calls=[\n                        {\n                            \"name\": \"async_add\",\n                            \"args\": {\"a\": 1, \"b\": 2},\n                            \"id\": \"call_13\",\n                        }\n                    ],\n                )\n            ]\n        },\n        config=_create_config_with_runtime(),\n    )\n\n    tool_message = result[\"messages\"][-1]\n    assert isinstance(tool_message, ToolMessage)\n    # Original: 1 + 2 = 3, with modifications: 11 + 12 = 23\n    assert tool_message.content == \"23\"",
    "def __init__(self) -> None:\n        self.loads: set[str] = set()\n        self.stores: set[str] = set()",
    "class InternalServerError(APIStatusError):\n    pass"
]
embeddings = model.encode(sentences)

similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4]

Notebooks
Google Colab
Kaggle

anaghaj111 commited on Jan 26

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