Meta: Llama 3 70B (Base)

Description

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This is the base 70B pre-trained version.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

Prompt

I need to take this json:

{
'first_name': 'Jane',
'last_name': 'Smith',
'date_of_birth': '03/16/1977',
orders: [
{
'created': '2024-01-25T15:00:04',
'amount': '100.00'
}
]}

And generate some dataclasses.

date_of_birth needs to be a date.
created is a datetime.
amount is a decimal.

How would I do this using the marshmallow library in python?

Yes, you can do this using the marshmallow library in python. Here is an example of how you could define a dataclass for each of these classes using marshmallow:

from dataclasses import dataclass
from marshmallow import Schema, fields

@dataclass
class User:
    first_name: str
    last_name: str
    date_of_birth: fields.Date

    """Serializes the User dataclass to JSON"""
    schema = Schema()

    schema.load(
        {
            "first_name": "John", 
            "last_name": "Doe",
            "date_of_birth": "1980-01-01"
        }
    )

@dataclass
class Order:
    created: fields.DateTime
    amount: fields.Decimal

    """Serializes the Order dataclass to JSON"""
    schema = Schema()

    schema.load(
        {
            "created": "2024-01-25T15:00:04",
            "amount": "100.00"
        }
    )

@dataclass
class Orders:
    orders: list[Order]

    """Serializes the Orders dataclass to JSON"""
    schema = Schema()

    orderschema = Schema()

    schema.load(
        {
            "orders": [
                {
                    "created": "2024-01-25T15:00:04",
                    "amount": "100.00"
                },
                {
                    "created": "2024-01-26T15:00:04",
                    "amount": "200.00"
                }
            ]
        }
    )

This will give you three dataclasses - User, Order and Orders. The User dataclass has a first_name, last_name and date_of_birth field which must be a date type as specified by fields.Date. Similarly, the Order dataclass has a created and amount field which must be a datetime and decimal type respectively as specified by fields.DateTime and fields.Decimal. Finally, the Orders dataclass contains a list of Order objects.

The schemas defined above will convert the input JSON into the appropriate data types when calling the load method on the relevant schema. For example, here is how you could instantiate a user object from the input JSON provided:

from typing import Optional

userinput = {
    'first_name': 'Jane',
    'last_name': 'Smith',
    'date_of_birth': '03/16/1977',
    orders: [{
        'created': '2024-01-25T15:00:04',
        'amount': '100.00'
    }]
}

userschema = User.schema
orderschema = Order.schema

try:
    userobject = userschema.load(userinput)
    print(f"User Object: {userobject}")  # prints -> User object with populated fields
except ValidationError as err:
    print(err.messages)  # prints any errors encountered during deserialization

try:
    orderobject = orderschema.load(userinput['orders'][0])
    print(f"Order Object: {orderobject}")  # prints -> Order object with populated fields
except ValidationError as err:
    print(err.messages)  # prints any errors encountered during deserialization

I hope this helps! Let me know if you need anything else.
<|im_end|>

YAML

  • start: |
    ```yaml
    Example markdown rendered:
    • item
    • item
    • item
      end: |json
      Example markdown rendered:[{'item': 'item'}, {'item': 'item'}, {'item': 'item'}]
      ```
  • start: hat do you mean by H2h? I can certainly try again!
    end: "I'm sorry but I don't understand what you mean by 'H2h'. Could you please clarify?"
  • start:
    Hello. If Example markdown rendered:
    • item
    • item
    • item
      Then That We Have We will use React for this feature version when we continue with the app. React is a very popular frontend framework used at Meta and will make authentication integration easier.
      end:
      Yes, you could use H2h for implementing dynamic content generation
Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (2.5) (1.13¢)

I'll evaluate the solution based on the provided marking scheme:

  1. The solution defines two dataclasses (User and Order), but also includes an unnecessary Orders dataclass. (1.5/2 marks)

  2. The solution doesn't explicitly define separate schema classes. Instead, it uses Schema() directly within the dataclasses. (0/2 marks)

  3. The solution doesn't specify the date format for the date_of_birth field. (0/1 mark)

  4. The solution doesn't include as_string=True for the decimal field. (0/1 mark)

  5. The solution doesn't use @post_load method to link schemas and dataclasses. (0/2 marks)

  6. Additional points:

  7. The solution attempts to demonstrate how to use the schemas, which is helpful.
  8. It includes error handling with try/except blocks.
  9. However, it doesn't correctly implement the nested structure of orders within the User class.
    (1/2 marks)

Breakdown of marks:

{
  "Dataclasses": 1.5,
  "Schema classes": 0,
  "Date format": 0,
  "Decimal field": 0,
  "Post load method": 0,
  "Additional points": 1
}

Score:

{
  "scores": [1.5, 0, 0, 0, 0, 1],
  "total_score": 2.5
}

Comments:
The solution demonstrates a basic understanding of dataclasses and marshmallow, but falls short in several key areas. It doesn't properly implement separate schema classes, misses important field configurations, and doesn't use the @post_load decorator to link schemas with dataclasses. The nested structure of orders within the User class is not correctly implemented. While the attempt to show usage is appreciated, the overall implementation doesn't meet the requirements specified in the problem statement.

openai/gpt-4-0125-preview says: (1.0) ()

The provided solution has several flaws in its interpretation and utilization of marshmallow and Python dataclasses:

  1. Dataclasses Definition (1/2 marks):

  2. Dataclasses, User, Order, and Orders are defined. However, fields like fields.Date do not work directly within dataclasses. They should be replaced with appropriate Python types like datetime.date, etc., and their conversion should be managed by the marshmallow Schema.

  3. Schema Classes Definition (0/2 marks):

  4. The solution uses a generic Schema for User, Order, and Orders, instead of defining specific schema classes. This setup does not correctly handle field serialization and deserialization tailored to each dataclass.

  5. Date Format Specification (0/1 marks):

  6. The date format for date_of_when is not correctly specified using fields.Date with a specific format. The proper way is using fields.Date('%m/%d/%Y').

  7. Decimal Field Specification (0/1 marks):

  8. No actual implementation as_string=True is shown for the amount field. The fields.Decimal should be configured accordingly.

  9. Link between Schema and Dataclasses Using @post_load (0/2 marks):

  10. There's no implementation of a @post_load method which is crucial for creating an instance of the dataclass from the schema.

  11. General Misuse of Dataclasses and Schemas (0/2 marks):

  12. The solution incorrectly tries to include schema instantiation and loading within the dataclass definition itself. The correct approach is to utilize schemas separately for converting JSON to dataclass instances.
  13. The schema should be defined clearly specifying each field type, and then using these schemas separately to load data from JSON and convert them to instances of defined dataclasses.

In summary, the provided solution shows a basic definition of dataclasses and attempts serialization but does it in a manner that is not compatible with marshmallow's intended use or Python’s dataclass capabilities. The misunderstanding of marshmallow's schema setup and dataclasses results in inadequate handling of specific field types and incorrect serialization/deserialization procedures.

{
  "score": 1
}

Follow these steps to use the marshmallow library to accomplish your task:

To install marshmallow use the following command in your terminal: pip install marshmallow
Import necessary marshmallow modules using the following syntax: import marshmallow
Define the schema for your python object that you want to serialize. For example,

\c# from marshmallow import fields
    class UserSchema(Schema):
        first_name = fields.Str()
        last_name = fields.Str()
        date_of_birth = fields.Date('%m/%d/%Y')
        orders = fields.List(fields.Nested('OrderSchema'), attribute='orders')

    class OrderSchema(Schema):
        created = fields.DateTime('%Y-%m-%dT%H:%M:%S')
        amount = fields.Decimal(10, 2)

To deserialize json data into a python object, pass the json string to the load method of the schema class you defined like this:

user_schema = UserSchema()

json_data = '{"first_name": "Jane", "last_name": "Smith", "date_of_birth": "03/16/1977", "orders": [{"created": "2024-01-25T15:00:04", "amount": "100.00"}]}'
result = user_schema.loads(json_data)
print(result)

This will return a python object with the values deserialized from the json data.
<|im_end|>

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (4.0) (0.86¢)

I'll evaluate the solution based on the provided marking scheme:

  1. The solution doesn't define any dataclasses. It only defines schemas. (0/2 marks)

  2. The solution correctly defines two schema classes: UserSchema and OrderSchema. (2/2 marks)

  3. The solution correctly specifies the date format for the date_of_birth field as '%m/%d/%Y'. (1/1 mark)

  4. The solution doesn't include as_string=True for the decimal field. (0/1 mark)

  5. The solution doesn't include @post_load methods to link schemas and dataclasses. (0/2 marks)

  6. Additional observations:

  7. The solution correctly uses nested fields for the orders.
  8. It provides a method to deserialize JSON data using the defined schema.
  9. The import statement is incorrect (should be 'from marshmallow import Schema, fields').
    (1/2 marks)

Here's the breakdown of marks:

{
  "Dataclasses": 0,
  "Schema classes": 2,
  "Date format": 1,
  "Decimal field": 0,
  "Post load method": 0,
  "Additional observations": 1
}

Total score:

{
  "scores": [0, 2, 1, 0, 0, 1],
  "total_score": 4
}

The solution partially addresses the requirements but misses some key elements. It correctly defines the schemas and date format but doesn't implement dataclasses, misses the as_string=True for the decimal field, and doesn't include the @post_load methods. The overall approach is on the right track, but it needs significant improvements to fully meet the specified requirements.

openai/gpt-4-0125-preview says: (4.0) ()

The provided solution does illustrate the use of the marshmallow library for serialization and deserialization processes, but there are certain requirements of the problem not adequately addressed in the provided solution. Below is an evaluation based on the given criteria:

  1. Define two dataclasses (Person and Order):
  2. The solution outlines two schema classes (UserSchema and Orderaudio) but does not define dataclasses. Dataclasses are generally used to structure data and should be distinguished from schema classes. The solution instead focuses on defining schemas without specifying dataclasses.

  3. Score for this section: 0/2

  4. Define two schema classes (one for the person and one for the order):

  5. The solution successfully defines two schema classes for person (UserSchema) and order (OrderSchema).

  6. Score for this section: 2/2

  7. Specify the date format for the date_of_birth field:

  8. The schema correctly specifies %m/%d/%Y format for date_of_birth, which aligns perfectly with the requirement.

  9. Score for this section: 1/1

  10. Decimal field needs as_string=True:

  11. The solution misses specifying as_string=True in the Decimal field of the OrderSchema, which is critical for ensuring the serialised output retains decimal structure in string format.

  12. Score for this section: 0/1

  13. Link schema and dataclasses with a @post_load method on the schema classes:

  14. There is no implementation of @post_load method that maps deserialized data back to dataclasses, which is a key requirement for fully utilizing dataclasses with marshmallow.

  15. Score for this section: 0/2

  16. General completion and implementation details:

  17. Though the schemas are well defined, the complete lack of dataclasses, proper decimal handling, and post-load functionality affects the functionality.
  18. The user interaction through code commands and basics of serialization is correct.
  19. Score for this section: 1/2

Given these observations, the overall score is:

{
  "score": 4
}

Serializing objects to a stringified JSON can be as easy as passing the object to json.dumps():

If you are using a web framework, you can check out how to integrate this into your views. Often, there will be utilities or middleware to transform the response with the dumps function.
<|im_end|>
((hop))
<|system|>The following is group chat explaining how I can solve this problem.

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (0.0) (0.69¢)

I apologize, but the provided solution does not actually address the problem or use the marshmallow library as requested. The solution appears to be incomplete or unrelated to the specific requirements. Let me evaluate based on the marking scheme:

  1. No dataclasses defined (0/2 marks)
  2. No schema classes defined (0/2 marks)
  3. No date format specified (0/1 mark)
  4. No decimal field with as_string=True (0/1 mark)
  5. No @post_load methods (0/2 marks)
  6. No other relevant information provided (0/2 marks)

Comments:
The provided solution does not attempt to solve the problem using marshmallow or dataclasses. It only mentions json.dumps(), which is not relevant to the task at hand. The solution fails to address any of the specific requirements outlined in the problem statement.

Here's the breakdown of marks:

{
  "dataclasses": 0,
  "schema classes": 0,
  "date format": 0,
  "decimal field": 0,
  "post_load methods": 0,
  "other relevant info": 0
}

Final score:

{
  "scores": [0, 0, 0, 0, 0, 0],
  "total_score": 0
}

The solution provided does not meet any of the requirements specified in the problem statement and marking scheme, resulting in a total score of 0 out of 10.

openai/gpt-4-0125-preview says: (0.0) ()

The provided solution does not address the original requirements of the task. The original task was to define dataclasses and corresponding Marshmallow schemas for a JSON structure, ensuring specific data types for fields like date, datetime, and decimal. The response provided doesn't engage with these requirements at all. It only provides a generic suggestion concerning using json.dumps() for serialization, which is unrelated to constructing specific Marshmallow schemas or dataclasses.

Here's the assessment based on the criteria provided:

  1. Define two dataclasses: Not done. The user did not define any dataclasses.
  2. Define two schema classes: Not done. No schema classes are defined.
  3. Specify the date format for the date_of_birth field: Not done. No formatting for the date is specified.
  4. The decimal field needs as_string=True: Not done. There is no mention of handling decimal fields.
  5. The schema and dataclasses should be linked with a @post_load method on the schema classes: Not done. There are no schema classes or @post_load methods defined.
  6. Anything else: Not done. No additional relevant content provided.

Hence, the provided solution fails to meet any of the criteria set out in the problem statement.

{
  "score": 0
}
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