Google: Gemma 7B (nitro)

Description

Gemma by Google is an advanced, open-source language model family, leveraging the latest in decoder-only, text-to-text technology. It offers English language capabilities across text generation tasks like question answering, summarization, and reasoning. The Gemma 7B variant is comparable in performance to leading open source models.

Usage of Gemma is subject to Google's Gemma Terms of Use.

Note: this is a higher-throughput version of Gemma 7B. It may have higher prices and slightly different outputs.

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?

Response 1 (3.0)

import datetime
import decimal
from marshmallow import Schema, fields

class Order(Schema):
    created = fields.Datetime()
    amount = fields.Decimal()

class Person(Schema):
    first_name = fields.Str()
    last_name = fields.Str()
    date_of_birth = fields.Date()
    orders = fields.List(Order)


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

person_schema.load(person_data)

print(person_schema.data)

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: (3.0) (0.84¢)

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

The solution does not define any dataclasses. It only defines Schema classes. (0/2 marks)
The solution defines two schema classes: Order and Person. (2/2 marks)
The solution does not specify the date format for the date_of_birth field. (0/1 mark)
The decimal field is not specified with as_string=True. (0/1 mark)
The solution does not use @post_load method to link schema and dataclasses. (0/2 marks)
Additional observations:
The solution imports necessary libraries.
It demonstrates how to use the schema to load data.
However, it incorrectly tries to access person_schema.data which is not a valid attribute.
(1/2 marks)

Comments:
The solution provides a basic structure using Marshmallow schemas, but it misses several key requirements. It doesn't use dataclasses, doesn't specify the required date format, doesn't set the decimal field as a string, and doesn't use @post_load to create dataclass instances. The attempt to print person_schema.data at the end is incorrect; after loading, you would typically access the deserialized data directly from the result of load().

Here's the breakdown of marks:

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

Final score:

{
  "scores": [0, 2, 0, 0, 0, 1],
  "total_score": 3
}

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

The provided solution attempts to use the Marshmallow library to parse and validate JSON data into Python objects. However, there are several essential aspects and errors in the implementation that need to be addressed based on the requirements and marking scheme:

Dataclasses Definition: The solution uses Schema classes instead of dataclass for Person and Order. This is a major misalignment with the requirement to define two dataclasses (-2 marks).
Schema Classes Definition: While schema classes have been defined (Person, Order), they are incorrectly implemented as Schema instead of extending them via proper decorator use or the appropriate linkage with actual data classes (-1 mark).
Specifying Date Format: The date_of_birth field is expected to be specified with the format "%m/%d/%Y". This format is notably absent in the definition of fields.Date() (-1 mark).
Decimal Field Handling: The amount should have as_string=True to ensure that the decimal field does not lose precision when serialized. This is not specified in the fields.Decimal() (-1 mark).
Linking Schema and Dataclasses with @post_load: No @post_load method is implemented in either schema class, which is essential for creating actual instances of the defined dataclasses from the parsed data (-2 marks).
Additional Considerations:
Error in the serialization: The print statement attempts to access .data on the result of person_schema.load(person_data), which is incorrect usage since loading will return the deserialized data directly. This confusion indicates an error in understanding how Marshmallow handles data handling (-1 mark).
Decimals and datetimes conversion appropriate handling (fields settings) are missing, nothing handled for ensuring encoding/decoding respects the precision and formats required. (-1 mark)

Given the missed requirements and incorrect implementations, the solution does not fully satisfy the problem's demands.

{
  "score": 1
}

Response 2 (2.0)

import datetime
import marshmallow

class User(marshmallow.Schema):
    first_name = marshmallow.fields.Str()
    last_name = marshmallow.fields.Str()
    date_of_birth = marshmallow.fields.Date(required=True)
    orders = marshmallow.fields.List(OrderedDict(items=[
        marshmallow.fields.Str('created'),
        marshmallow.fields.Decimal('amount')
    ]))

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

user = User.from_dict(data)

print(user.date_of_birth)  # Output: 1977-03-16
print(user.orders[0]['created'])  # Output: 2024-01-25 15:00:04
print(user.orders[0]['amount'])  # Output: 100.0

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: (2.0) (0.86¢)

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

The solution does not define any dataclasses. It only defines a schema class for the user. (0/2 marks)
The solution defines one schema class (User), but not for the order. (1/2 marks)
The solution does not specify the date format for the date_of_birth field. (0/1 mark)
The decimal field is not specified with as_string=True. (0/1 mark)
There is no @post_load method to link schema and dataclasses. (0/2 marks)
Additional observations:
The solution uses marshmallow for schema definition, which is correct.
It attempts to handle nested order data, but the implementation is incorrect.
The example usage shows an attempt to use the schema, but it's not correct as marshmallow doesn't have a from_dict method.
(1/2 marks)

Here's the breakdown of marks:

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

Score summary:

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

Comments:
The solution shows some understanding of using marshmallow for schema definition, but it falls short in many aspects. It doesn't use dataclasses, doesn't properly handle nested structures, and doesn't implement the required date and decimal field specifications. The attempt to use the schema is also incorrect. The solution needs significant improvements to meet the requirements of the problem.

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

The provided solution seems to attempt to define a serialization/deserialization behavior using the Marshmallow library for a JSON structure provided in the problem. Let's evaluate it based on the given marking scheme:

Defining Dataclasses: The solution does not define any data classes. The User class is defined as a Marshmallow Schema, not as a Python dataclass. The described order structure is also not defined as a dataclass.
Score: 0/2
Defining Schema Classes: The User class is defined as a schema correctly, but no separate schema is defined for orders; instead, an attempt is made to define it inline within the User schema.
Score: 1/2
Specifying Date Format for date_of_birth: The date_of_birth field does not specify the format "%m/%d/%Y" as required. It only states that it is a date field.
Score: 0/1
Decimal Field as_string=True: The solution does not specify as_string=True for the Decimal field, which is necessary to maintain it as a string in the output.
Score: 0/1
Using @post_load method to Link Schema and Dataclasses: No @post_load methods are used in the provided solution. Moreover, no dataclasses are defined to link with the schemas.
Score: 0/2
Additional Considerations:
The use of OrderedDict in the orders field is incorrect and not valid syntax in Marshmallow for defining fields within a list.
No correct handling or definition for the Order schema or dataclass.
Error in attempt to deserialize data with non-existent from_dict method on the User schema instance.
Score: 0/2

Overall Evaluation:
- The solution misses key requirements from the problem statement.
- The implementation has several syntax and conceptual errors, such as the misuse of Marshmallow's schema definitions and the lack of required marshmallow features.
- It appears to have significant gaps in understanding both Python dataclasses and the correct usage of the Marshmallow library.

Final Score:

{
  "score": 1
}

Response 3 (3.0)

import datetime
import decimal
from marshmallow import Schema, fields

class Order(Schema):
    created = fields.Datetime()
    amount = fields.Decimal()

class User(Schema):
    first_name = fields.Str()
    last_name = fields.Str()
    date_of_birth = fields.Date()
    orders = fields.List(Order())

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

# Instantiate the schema and bind the JSON data
user_schema = User().load(user_data)

# Print the results
print(user_schema)

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: (3.0) (0.92¢)

Let's evaluate this solution based on the provided marking scheme:

The solution does not define any dataclasses. It only defines Schema classes. (0/2 marks)
The solution correctly defines two schema classes: Order and User. (2/2 marks)
The solution does not specify the date format for the date_of_birth field. (0/1 mark)
The decimal field is not specified with as_string=True. (0/1 mark)
The solution does not use @post_load decorators to link schema classes with dataclasses. (0/2 marks)
Additional observations:
The solution correctly uses marshmallow's Schema and fields.
It demonstrates how to create a JSON dictionary and load it using the schema.
However, it doesn't fully meet the requirements of using dataclasses and specific field configurations.
(1/2 marks)

Breakdown of marks:

{
  "Dataclasses definition": 0,
  "Schema classes definition": 2,
  "Date format specification": 0,
  "Decimal field configuration": 0,
  "Schema and dataclass linking": 0,
  "Additional observations": 1
}

Score:

{
  "scores": [0, 2, 0, 0, 0, 1],
  "total_score": 3
}

Comments:
The solution partially addresses the problem by defining schema classes using marshmallow. However, it falls short in several key areas:
1. It doesn't use dataclasses as required.
2. It doesn't specify the required date format for date_of_birth.
3. It doesn't configure the decimal field with as_string=True.
4. It doesn't use @post_load decorators to link schemas with dataclasses.

To improve, the solution should incorporate dataclasses, add the specified configurations for date and decimal fields, and use @post_load decorators to create instances of the dataclasses from the loaded data.

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

The provided solution attempts to use the marshmallow library to parse and validate data, but there are a number of critical issues in relation to the provided problem description and requirements:

Dataclasses Definition: The solution does not implement Python dataclasses (@dataclass) for encapsulating User and Order data. Instead, it defines these entities using Schema classes, which are part of the marshmallow library intended for schema definition and not data encapsulation in the form of dataclasses. There was a requirement to define two dataclasses, but it wasn't done (-2 marks).
Schema Classes Definition: While the solution correctly creates User and Order as instances of Schema, it misuses the purpose of these classes. They should primarily define the structure and validation, yet no specific validation like date formats or decimal precision is set up correctly (-1 mark).
Date Format Specification: The solution doesn't specify the format for the date_of_birth field, which should be handled with the format (%m/%d/%Y). This is a requirement to correctly parse the string date from JSON into a Python date object. It leaves room for potential errors during date parsing (-1 mark).
Decimal Field Handling: The amount field is marked as a Decimal type, but it does not specify as_string=True which was required to ensure that the decimal value is treated correctly as a string when rendering back to JSON or keeping the precision intact (-1 mark).
Linking Schema and Dataclasses: The solution does not implement the @post_load method, which is necessary for converting loaded data into instances of the defined dataclasses. This step is critical for the proper usage of dataclasses together with schemas in marshmallow (-2 marks).
Additional considerations: The code does not effectively handle the nesting of orders' data within the user data properly (the fields.List should point to a schema instance, not a class). Additional aspects such as error handling or proper object instantiation for the nested structure are also not covered (-2 marks).

Based on these points, the solution significantly deviates from the requirements, lacking crucial implementations for a correct and functional use of marshmallow with dataclasses in Python.

{
  "score": 1
}

1.00	0.79	0.90
0.79	1.00	0.86
0.90	0.86	1.00

Google: Gemma 7B (nitro)

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