एपीआई के लिए फ़ंक्शन स्कीमा परिभाषित करना

from openai import OpenAI

client = OpenAI()

tools = [
    {
        'type': 'function',
        'function': {
            'name': 'get_current_weather',
            'description': 'Get the current weather in a given location.',
            'parameters': {
                'type': 'object',
                'properties': {
                    'location': {
                        'type': 'string',
                        'description': 'City and country, e.g. London, UK'
                    },
                    'unit': {
                        'type': 'string',
                        'enum': ['celsius', 'fahrenheit'],
                        'description': 'Temperature unit to use.'
                    }
                },
                'required': ['location']
            }
        }
    }
]

# A more complex schema with multiple types
create_event_tool = {
    'type': 'function',
    'function': {
        'name': 'create_calendar_event',
        'description': 'Create a new calendar event. Use when the user wants to schedule a meeting or appointment.',
        'parameters': {
            'type': 'object',
            'properties': {
                'title': {'type': 'string', 'description': 'Event title.'},
                'start_time': {'type': 'string', 'description': 'ISO 8601 datetime, e.g. 2024-03-15T14:00:00.'},
                'duration_minutes': {'type': 'integer', 'description': 'Duration in minutes.', 'minimum': 5},
                'attendees': {
                    'type': 'array',
                    'items': {'type': 'string'},
                    'description': 'List of email addresses of attendees.'
                },
                'location': {'type': 'string', 'description': 'Physical or virtual meeting location.'}
            },
            'required': ['title', 'start_time', 'duration_minutes']
        }
    }
}

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

print('Finish reason:', response.choices[0].finish_reason)
# 'tool_calls' means the model wants to call a function
# 'stop' means the model gave a regular text response

choice = response.choices[0].message
if response.choices[0].finish_reason == 'tool_calls':
    print('Model wants to call:', choice.tool_calls[0].function.name)

# Force the model to always call extract_contact
response = client.chat.completions.create(
    model='gpt-4o',
    messages=[{'role': 'user', 'content': 'Hi, I am John Smith, john@example.com, +1-555-0100.'}],
    tools=[extract_contact_tool],
    tool_choice={'type': 'function', 'function': {'name': 'extract_contact'}}
)
# With tool_choice forced, finish_reason will always be 'tool_calls'

classify_sentiment_tool = {
    'type': 'function',
    'function': {
        'name': 'classify_sentiment',
        'description': 'Classify the sentiment of a customer review.',
        'parameters': {
            'type': 'object',
            'properties': {
                'sentiment': {
                    'type': 'string',
                    'enum': ['positive', 'negative', 'neutral', 'mixed'],
                    'description': 'The sentiment classification.'
                },
                'confidence': {
                    'type': 'number',
                    'minimum': 0.0,
                    'maximum': 1.0,
                    'description': 'Model confidence from 0 to 1.'
                }
            },
            'required': ['sentiment', 'confidence']
        }
    }
}

extract_order_tool = {
    'type': 'function',
    'function': {
        'name': 'extract_order',
        'description': 'Extract order details from a customer email.',
        'parameters': {
            'type': 'object',
            'properties': {
                'customer': {
                    'type': 'object',
                    'properties': {
                        'name': {'type': 'string'},
                        'email': {'type': 'string', 'format': 'email'}
                    },
                    'required': ['name']
                },
                'items': {
                    'type': 'array',
                    'items': {
                        'type': 'object',
                        'properties': {
                            'product_id': {'type': 'string'},
                            'quantity': {'type': 'integer', 'minimum': 1}
                        },
                        'required': ['product_id', 'quantity']
                    }
                }
            },
            'required': ['customer', 'items']
        }
    }
}

from pydantic import BaseModel, Field
from typing import Optional, List

class ContactInfo(BaseModel):
    name: str = Field(description='Full name of the person.')
    email: Optional[str] = Field(None, description='Email address.')
    phone: Optional[str] = Field(None, description='Phone number in E.164 format.')
    company: Optional[str] = Field(None, description='Company or organization.')

# Auto-generate the JSON Schema
schema = ContactInfo.schema()

# Build the tool definition
extract_contact_tool = {
    'type': 'function',
    'function': {
        'name': 'extract_contact',
        'description': 'Extract contact information from text.',
        'parameters': schema
    }
}

strict_tool = {
    'type': 'function',
    'function': {
        'name': 'classify_ticket',
        'description': 'Classify a support ticket into category and priority.',
        'strict': True,  # Enable strict schema adherence
        'parameters': {
            'type': 'object',
            'additionalProperties': False,  # Required for strict mode
            'properties': {
                'category': {
                    'type': 'string',
                    'enum': ['billing', 'technical', 'account', 'other']
                },
                'priority': {
                    'type': 'string',
                    'enum': ['low', 'medium', 'high', 'urgent']
                }
            },
            'required': ['category', 'priority']
        }
    }
}