Cinematika 7B (alpha) (free)

Description

This model is under development. Check the OpenRouter Discord for updates.

Note: this is a free, rate-limited version of this model. Outputs may be cached. Read about rate limits here.

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?

Sure, here's an example of how you can use the marshmallow library to generate dataclasses from a JSON string:

from marshmallow import Schema, fields

class UserSchema(Schema):
first_name = fields.Str()
last_name = fields.Str()
date_of_birth = fields.Date()
orders = fields.List(fields.Nested('OrderSchema'))

class OrderSchema(Schema):
created = fields.DateTime()
amount = fields.Decimal()

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

print(user_schema.data)

This will create a UserSchema and an OrderSchema, which you can use to validate and serialize your data. The UserSchema has fields for the user's first name, last name, date of birth, and a list of OrderSchema objects, which represent the user's orders. The OrderSchema has fields for the order's creation date and amount.

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)

openai/gpt-4-0125-preview says: (2.0) ()

Evaluating the provided solution against the marking scheme reveals certain issues and misses in the necessary features:

  1. Dataclasses Definition (2 marks)
  2. The solution does not define any dataclasses for a person or an order. The given solution uses only marshmallow Schema classes without utilizing dataclasses.

  3. Score: 0/2

  4. Schema Classes Definition (2 marks)

  5. The solution correctly defines two schema classes, UserSchema for the person and OrderSchema for the order.

  6. Score: 2/2

  7. Date Format Specification for date_of_birth (1 mark)

  8. The schema entry for date_of_birth is using fields.Date() but does not specify the format. The correct way should have been fields.Date(format="%m/%d/%Y").

  9. Score: 0/1

  10. Decimal Field 'as_string' Requirement (1 mark)

  11. The solution uses fields.Decimal() for the amount field but does not set as_string=True. Thus, it does not ensure the amount field is serialized as a string.

  12. Score: 0/1

  13. Linking Schema with Dataclasses via @post_load Method (2 marks)

  14. The solution does not implement the @post_load method, which is necessary to convert the loaded data into instances of dataclasses.

  15. Score: 0/2

  16. Additional Considerations (2 marks)

  17. Parsing and handling potential errors or complex structures were not discussed. Also, no handling or demonstration of datetime or decimal precision which might be crucial in practical scenarios.
  18. Score: 0/2

Final evaluation based on the marking scheme gives the following score:

{
  "score": 2/10
}

The main areas of improvement are the implementation of actual dataclasses, utilizing @post_load to create instances from schemas, and ensuring that fields like dates and decimals are accurately formatted as per specification.

anthropic/claude-3.5-sonnet says: (4.0) (0.90¢)

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

  1. The solution defines two schema classes (UserSchema and OrderSchema), but it doesn't define any dataclasses. (1 mark out of 2)

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

  3. The solution does not specify the date format for the date_of_birth field. (0 marks)

  4. The decimal field is not specified with as_string=True. (0 marks)

  5. The solution does not include @post_load methods to link schemas with dataclasses. (0 marks)

  6. Additional points:

  7. The solution correctly uses nested schemas for the orders field.
  8. It demonstrates how to use the schema to load data.
    (1 mark out of 2)

Comments:
The solution provides a basic structure using marshmallow schemas, which is a good start. However, it misses several key requirements:
- It doesn't create dataclasses, only schema classes.
- It doesn't specify the required date format for date_of_birth.
- The decimal field is not configured with as_string=True.
- There's no implementation of @post_load methods to create dataclass instances.
- The solution doesn't show how to handle the specific date and datetime formats mentioned in the problem.

While the solution demonstrates a basic understanding of marshmallow, it needs significant improvements to fully meet the requirements.

Marks breakdown:

{
  "Dataclasses definition": 1,
  "Schema classes definition": 2,
  "Date format specification": 0,
  "Decimal field configuration": 0,
  "@post_load method implementation": 0,
  "Additional points": 1
}

Score:

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

Sure, here's an example of how you can use the marshmallow library to generate dataclasses from a JSON string:

from marshmallow import Schema, fields

class UserSchema(Schema):
first_name = fields.Str()
last_name = fields.Str()
date_of_birth = fields.Date()
orders = fields.List(fields.Nested('OrderSchema'))

class OrderSchema(Schema):
created = fields.DateTime()
amount = fields.Decimal()

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

print(user_schema.data)

This will create a UserSchema and an OrderSchema, which you can use to validate and serialize your data. The UserSchema has fields for the user's first name, last name, date of birth, and a list of OrderSchema objects, which represent the user's orders. The OrderSchema has fields for the order's creation date and amount.

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)

openai/gpt-4-0125-preview says: (2.0) ()

Evaluating the provided solution against the marking scheme reveals certain issues and misses in the necessary features:

  1. Dataclasses Definition (2 marks)
  2. The solution does not define any dataclasses for a person or an order. The given solution uses only marshmallow Schema classes without utilizing dataclasses.

  3. Score: 0/2

  4. Schema Classes Definition (2 marks)

  5. The solution correctly defines two schema classes, UserSchema for the person and OrderSchema for the order.

  6. Score: 2/2

  7. Date Format Specification for date_of_birth (1 mark)

  8. The schema entry for date_of_birth is using fields.Date() but does not specify the format. The correct way should have been fields.Date(format="%m/%d/%Y").

  9. Score: 0/1

  10. Decimal Field 'as_string' Requirement (1 mark)

  11. The solution uses fields.Decimal() for the amount field but does not set as_string=True. Thus, it does not ensure the amount field is serialized as a string.

  12. Score: 0/1

  13. Linking Schema with Dataclasses via @post_load Method (2 marks)

  14. The solution does not implement the @post_load method, which is necessary to convert the loaded data into instances of dataclasses.

  15. Score: 0/2

  16. Additional Considerations (2 marks)

  17. Parsing and handling potential errors or complex structures were not discussed. Also, no handling or demonstration of datetime or decimal precision which might be crucial in practical scenarios.
  18. Score: 0/2

Final evaluation based on the marking scheme gives the following score:

{
  "score": 2/10
}

The main areas of improvement are the implementation of actual dataclasses, utilizing @post_load to create instances from schemas, and ensuring that fields like dates and decimals are accurately formatted as per specification.

anthropic/claude-3.5-sonnet says: (4.0) (0.90¢)

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

  1. The solution defines two schema classes (UserSchema and OrderSchema), but it doesn't define any dataclasses. (1 mark out of 2)

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

  3. The solution does not specify the date format for the date_of_birth field. (0 marks)

  4. The decimal field is not specified with as_string=True. (0 marks)

  5. The solution does not include @post_load methods to link schemas with dataclasses. (0 marks)

  6. Additional points:

  7. The solution correctly uses nested schemas for the orders field.
  8. It demonstrates how to use the schema to load data.
    (1 mark out of 2)

Comments:
The solution provides a basic structure using marshmallow schemas, which is a good start. However, it misses several key requirements:
- It doesn't create dataclasses, only schema classes.
- It doesn't specify the required date format for date_of_birth.
- The decimal field is not configured with as_string=True.
- There's no implementation of @post_load methods to create dataclass instances.
- The solution doesn't show how to handle the specific date and datetime formats mentioned in the problem.

While the solution demonstrates a basic understanding of marshmallow, it needs significant improvements to fully meet the requirements.

Marks breakdown:

{
  "Dataclasses definition": 1,
  "Schema classes definition": 2,
  "Date format specification": 0,
  "Decimal field configuration": 0,
  "@post_load method implementation": 0,
  "Additional points": 1
}

Score:

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

Sure, here's an example of how you can use the marshmallow library to generate dataclasses from a JSON string:

from marshmallow import Schema, fields

class UserSchema(Schema):
first_name = fields.Str()
last_name = fields.Str()
date_of_birth = fields.Date()
orders = fields.List(fields.Nested('OrderSchema'))

class OrderSchema(Schema):
created = fields.DateTime()
amount = fields.Decimal()

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

print(user_schema.data)

This will create a UserSchema and an OrderSchema, which you can use to validate and serialize your data. The UserSchema has fields for the user's first name, last name, date of birth, and a list of OrderSchema objects, which represent the user's orders. The OrderSchema has fields for the order's creation date and amount.

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)

openai/gpt-4-0125-preview says: (2.0) ()

Evaluating the provided solution against the marking scheme reveals certain issues and misses in the necessary features:

  1. Dataclasses Definition (2 marks)
  2. The solution does not define any dataclasses for a person or an order. The given solution uses only marshmallow Schema classes without utilizing dataclasses.

  3. Score: 0/2

  4. Schema Classes Definition (2 marks)

  5. The solution correctly defines two schema classes, UserSchema for the person and OrderSchema for the order.

  6. Score: 2/2

  7. Date Format Specification for date_of_birth (1 mark)

  8. The schema entry for date_of_birth is using fields.Date() but does not specify the format. The correct way should have been fields.Date(format="%m/%d/%Y").

  9. Score: 0/1

  10. Decimal Field 'as_string' Requirement (1 mark)

  11. The solution uses fields.Decimal() for the amount field but does not set as_string=True. Thus, it does not ensure the amount field is serialized as a string.

  12. Score: 0/1

  13. Linking Schema with Dataclasses via @post_load Method (2 marks)

  14. The solution does not implement the @post_load method, which is necessary to convert the loaded data into instances of dataclasses.

  15. Score: 0/2

  16. Additional Considerations (2 marks)

  17. Parsing and handling potential errors or complex structures were not discussed. Also, no handling or demonstration of datetime or decimal precision which might be crucial in practical scenarios.
  18. Score: 0/2

Final evaluation based on the marking scheme gives the following score:

{
  "score": 2/10
}

The main areas of improvement are the implementation of actual dataclasses, utilizing @post_load to create instances from schemas, and ensuring that fields like dates and decimals are accurately formatted as per specification.

anthropic/claude-3.5-sonnet says: (4.0) (0.90¢)

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

  1. The solution defines two schema classes (UserSchema and OrderSchema), but it doesn't define any dataclasses. (1 mark out of 2)

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

  3. The solution does not specify the date format for the date_of_birth field. (0 marks)

  4. The decimal field is not specified with as_string=True. (0 marks)

  5. The solution does not include @post_load methods to link schemas with dataclasses. (0 marks)

  6. Additional points:

  7. The solution correctly uses nested schemas for the orders field.
  8. It demonstrates how to use the schema to load data.
    (1 mark out of 2)

Comments:
The solution provides a basic structure using marshmallow schemas, which is a good start. However, it misses several key requirements:
- It doesn't create dataclasses, only schema classes.
- It doesn't specify the required date format for date_of_birth.
- The decimal field is not configured with as_string=True.
- There's no implementation of @post_load methods to create dataclass instances.
- The solution doesn't show how to handle the specific date and datetime formats mentioned in the problem.

While the solution demonstrates a basic understanding of marshmallow, it needs significant improvements to fully meet the requirements.

Marks breakdown:

{
  "Dataclasses definition": 1,
  "Schema classes definition": 2,
  "Date format specification": 0,
  "Decimal field configuration": 0,
  "@post_load method implementation": 0,
  "Additional points": 1
}

Score:

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