How to bind model-specific tools
Source: langchain

# How to bind model-specific toolsProviders adopt different conventions for formatting tool schemas. For instance, OpenAI uses a format like this:- `type`: The type of the tool. At the time of writing, this is always `"function"`.- `function`: An object containing tool parameters.- `function.name`: The name of the schema to output.- `function.description`: A high level description of the schema to output.- `function.parameters`: The nested details of the schema you want to extract, formatted as a [JSON schema](https://json-schema.org/) dict.We can bind this model-specific format directly to the model as well if preferred. Here's an example:```pythonfrom langchain_openai import ChatOpenAImodel = ChatOpenAI()model_with_tools = model.bind(    tools=[        {            "type": "function",            "function": {                "name": "multiply",                "description": "Multiply two integers together.",                "parameters": {                    "type": "object",                    "properties": {                        "a": {"type": "number", "description": "First integer"},                        "b": {"type": "number", "description": "Second integer"},                    },                    "required": ["a", "b"],                },            },        }    ])model_with_tools.invoke("Whats 119 times 8?")```    AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_mn4ELw1NbuE0DFYhIeK0GrPe', 'function': {'arguments': '{"a":119,"b":8}', 'name': 'multiply'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 62, 'total_tokens': 79}, 'model_name': 'gpt-3.5-turbo', 'system_fingerprint': 'fp_c2295e73ad', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-353e8a9a-7125-4f94-8c68-4f3da4c21120-0', tool_calls=[{'name': 'multiply', 'args': {'a': 119, 'b': 8}, 'id': 'call_mn4ELw1NbuE0DFYhIeK0GrPe'}])This is functionally equivalent to the `bind_tools()` method.