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Overview

Function calling lets you define tools that the model can invoke. When the model decides to call a tool, it returns a structured JSON response that you execute in your application and feed back to the model.

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Basic Example

from openai import OpenAI
import json

client = OpenAI(
    api_key="sk-samurai-YOUR_KEY",
    base_url="https://api.samuraiapi.in/v1"
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get the current weather for a city",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "The city name, e.g. 'London'"
                    },
                    "unit": {
                        "type": "string",
                        "enum": ["celsius", "fahrenheit"],
                        "description": "Temperature unit"
                    }
                },
                "required": ["city"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "What's the weather in Tokyo?"}],
    tools=tools,
    tool_choice="auto"
)

message = response.choices[0].message

# Check if the model called a tool
if message.tool_calls:
    tool_call = message.tool_calls[0]
    args = json.loads(tool_call.function.arguments)
    print(f"Called: {tool_call.function.name}({args})")
    # => Called: get_weather({'city': 'Tokyo'})

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Multi-Step Tool Use

After receiving a tool call, execute it and send the result back: 
# Step 1: Model requests tool call (see above)
# Step 2: Execute your function
def get_weather(city: str, unit: str = "celsius"):
    return {"city": city, "temperature": 22, "unit": unit, "condition": "Sunny"}

result = get_weather(**args)

# Step 3: Send result back to model
messages = [
    {"role": "user", "content": "What's the weather in Tokyo?"},
    message,  # assistant message with tool_calls
    {
        "role": "tool",
        "tool_call_id": tool_call.id,
        "content": json.dumps(result)
    }
]

final_response = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    tools=tools
)
print(final_response.choices[0].message.content)
# => "The weather in Tokyo is currently 22°C and Sunny."

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tool_choice Options

ValueBehavior
"auto"Model decides whether to call a tool
"none"Model never calls tools
"required"Model must call at least one tool
{"type": "function", "function": {"name": "X"}}Force a specific function