Providers adopt different conventions for formatting tool schemas. For instance, OpenAI uses a format like this:
We can bind this model-specific format directly to the model as well if preferred. Here's an example:
from langchain_openai import ChatOpenAI
model = 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.
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