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from typing import Dict, List, Optional
import pytest
from pydantic import BaseModel, Field, ValidationError
from starfish.common.exceptions import PydanticParserError
from starfish.llm.parser.pydantic_parser import PydanticParser
# Define test Pydantic models for use in tests
class Address(BaseModel):
street: str = Field(..., description="Street name")
city: str = Field(..., description="City name")
zip_code: Optional[str] = Field(None, description="Zip code")
class Contact(BaseModel):
name: str = Field(..., description="Contact name")
phone: str = Field(..., description="Phone number")
email: Optional[str] = Field(None, description="Email address")
class Person(BaseModel):
name: str = Field(..., description="Person's name")
age: int = Field(..., description="Person's age")
address: Address = Field(..., description="Person's address")
contacts: List[Contact] = Field(default_factory=list, description="Person's contacts")
class Child(BaseModel):
name: str = Field(..., description="Child's name")
age: int = Field(..., description="Child's age")
hobbies: List[str] = Field(default_factory=list, description="Child's hobbies")
class Spouse(BaseModel):
name: str = Field(..., description="Spouse's name")
occupation: Optional[str] = Field(None, description="Spouse's occupation")
class Family(BaseModel):
spouse: Optional[Spouse] = Field(None, description="Spouse information")
children: List[Child] = Field(default_factory=list, description="Children information")
class PersonWithFamily(BaseModel):
name: str = Field(..., description="Person's name")
age: int = Field(..., description="Person's age")
family: Family = Field(..., description="Family information")
class FactsList(BaseModel):
facts: List[Dict[str, str]] = Field(..., description="A list of facts")
class Fact(BaseModel):
question: str = Field(..., description="The factual question generated")
answer: str = Field(..., description="The corresponding answer")
category: str = Field(..., description="A category for the fact")
class NestedFactsList(BaseModel):
facts: List[Fact] = Field(..., description="A list of facts")
class TestPydanticParser:
"""Test cases for the PydanticParser class."""
# ---------------------------------------------------------------------------
# Tests for schema conversion from Pydantic models
# ---------------------------------------------------------------------------
def test_to_json_schema_basic(self):
"""Test converting a basic Pydantic model to JSON schema."""
# Define a simple model for this test
class SimpleModel(BaseModel):
name: str = Field(..., description="Person's name")
age: int = Field(..., description="Person's age")
is_active: bool = Field(False, description="Activity status")
schema = PydanticParser.to_json_schema(SimpleModel)
# Check schema structure
assert schema["type"] == "object"
assert "properties" in schema
assert "name" in schema["properties"]
assert "age" in schema["properties"]
assert "is_active" in schema["properties"]
# Check property types
assert schema["properties"]["name"]["type"] == "string"
assert schema["properties"]["age"]["type"] == "integer"
assert schema["properties"]["is_active"]["type"] == "boolean"
# Check descriptions
assert schema["properties"]["name"]["description"] == "Person's name"
assert schema["properties"]["age"]["description"] == "Person's age"
assert schema["properties"]["is_active"]["description"] == "Activity status"
# Check required fields
assert "required" in schema
assert "name" in schema["required"]
assert "age" in schema["required"]
assert "is_active" not in schema["required"] # Has default value
def test_to_json_schema_nested_object(self):
"""Test converting a Pydantic model with nested models to JSON schema."""
schema = PydanticParser.to_json_schema(Person)
# Process the schema to resolve references
processed_schema = PydanticParser._process_schema_for_formatting(schema)
# Check root properties
assert "name" in processed_schema["properties"]
assert "age" in processed_schema["properties"]
assert "address" in processed_schema["properties"]
assert "contacts" in processed_schema["properties"]
# Check nested address properties
assert "properties" in processed_schema["properties"]["address"]
assert "street" in processed_schema["properties"]["address"]["properties"]
assert "city" in processed_schema["properties"]["address"]["properties"]
assert "zip_code" in processed_schema["properties"]["address"]["properties"]
# Check array of contacts properties
assert processed_schema["properties"]["contacts"]["type"] == "array"
assert "items" in processed_schema["properties"]["contacts"]
assert "properties" in processed_schema["properties"]["contacts"]["items"]
assert "name" in processed_schema["properties"]["contacts"]["items"]["properties"]
assert "phone" in processed_schema["properties"]["contacts"]["items"]["properties"]
assert "email" in processed_schema["properties"]["contacts"]["items"]["properties"]
def test_to_json_schema_deeply_nested(self):
"""Test converting a deeply nested Pydantic model hierarchy to JSON schema."""
schema = PydanticParser.to_json_schema(PersonWithFamily)
# Process the schema to resolve references
processed_schema = PydanticParser._process_schema_for_formatting(schema)
# Check first level nesting
assert "family" in processed_schema["properties"]
assert "properties" in processed_schema["properties"]["family"]
# Check second level nesting - spouse and children
family_props = processed_schema["properties"]["family"]["properties"]
assert "spouse" in family_props
assert "children" in family_props
# Check that the schema was processed appropriately
# Even if the exact structure varies, we need to ensure the schema contains
# all the necessary information for generating valid instructions
children_prop = family_props["children"]
assert children_prop["type"] == "array"
assert "items" in children_prop
# ---------------------------------------------------------------------------
# Tests for format instructions generation
# ---------------------------------------------------------------------------
def test_get_format_instructions_basic(self):
"""Test generating format instructions for a basic model."""
class SimpleModel(BaseModel):
name: str = Field(..., description="Person's name")
age: int = Field(..., description="Person's age")
instructions = PydanticParser.get_format_instructions(SimpleModel)
# Check basic elements
assert "[" in instructions
assert "]" in instructions
assert '"name": ""' in instructions
assert '"age": number' in instructions
assert "Person's name (required)" in instructions
assert "Person's age (required)" in instructions
def test_get_format_instructions_nested(self):
"""Test generating format instructions for a model with nested objects."""
instructions = PydanticParser.get_format_instructions(Person)
# Check nested object formatting
assert '"address": {' in instructions
assert '"street": ""' in instructions
assert '"city": ""' in instructions
assert '"zip_code": ""' in instructions
assert "Street name (required)" in instructions
assert "City name (required)" in instructions
assert "Zip code (optional)" in instructions
# Check array of objects formatting
assert '"contacts": [' in instructions
assert '"name": ""' in instructions # Multiple occurrences
assert '"phone": ""' in instructions
assert '"email": ""' in instructions
assert "Contact name (required)" in instructions
assert "Phone number (required)" in instructions
assert "Email address (optional)" in instructions
def test_get_format_instructions_deeply_nested(self):
"""Test generating format instructions for deeply nested models."""
instructions = PydanticParser.get_format_instructions(PersonWithFamily)
# Check family nested object
assert '"family": {' in instructions
# Adjust the test to check for just the key presence without checking exact formatting
assert '"spouse"' in instructions
assert '"children"' in instructions
# Check for name field presence in the output
assert '"name"' in instructions
# Less strict checks for description content
assert "name" in instructions # Just check that "name" is mentioned somewhere
assert "age" in instructions
assert "hobbies" in instructions
def test_nested_fact_model(self):
"""Test specific case for NestedFactsList model."""
instructions = PydanticParser.get_format_instructions(NestedFactsList)
# Check facts array structure
assert '"facts": [' in instructions
# Check fact object properties
assert '"question": ""' in instructions
assert '"answer": ""' in instructions
assert '"category": ""' in instructions
# Check descriptions
assert "The factual question generated (required)" in instructions
assert "The corresponding answer (required)" in instructions
assert "A category for the fact (required)" in instructions
# ---------------------------------------------------------------------------
# Tests for parsing LLM output to Pydantic models
# ---------------------------------------------------------------------------
def test_parse_dict_or_list_single(self):
"""Test parsing a single dictionary to a Pydantic model."""
data = {"name": "John Doe", "age": 35, "address": {"street": "123 Main St", "city": "Anytown", "zip_code": "12345"}}
person = PydanticParser.parse_dict_or_list(data, Person)
assert isinstance(person, Person)
assert person.name == "John Doe"
assert person.age == 35
assert person.address.street == "123 Main St"
assert person.address.city == "Anytown"
assert person.address.zip_code == "12345"
assert isinstance(person.address, Address)
assert len(person.contacts) == 0
def test_parse_dict_or_list_list(self):
"""Test parsing a list of dictionaries to a list of Pydantic models."""
data = [{"name": "Alice", "phone": "555-1234"}, {"name": "Bob", "phone": "555-5678", "email": "[email protected]"}]
contacts = PydanticParser.parse_dict_or_list(data, Contact)
assert isinstance(contacts, list)
assert len(contacts) == 2
assert all(isinstance(contact, Contact) for contact in contacts)
assert contacts[0].name == "Alice"
assert contacts[0].phone == "555-1234"
assert contacts[0].email is None
assert contacts[1].name == "Bob"
assert contacts[1].phone == "555-5678"
assert contacts[1].email == "[email protected]"
def test_parse_dict_or_list_validation_error(self):
"""Test validation errors in parse_dict_or_list."""
# Missing required field
data = {"name": "John"}
with pytest.raises(ValidationError):
PydanticParser.parse_dict_or_list(data, Contact)
# Wrong type for field
data = {"name": "John", "phone": 12345}
with pytest.raises(ValidationError):
PydanticParser.parse_dict_or_list(data, Contact)
def test_parse_llm_output_basic(self):
"""Test parsing LLM output into a basic Pydantic model."""
text = '{"name": "Alice", "phone": "555-1234"}'
result = PydanticParser.parse_llm_output(text, Contact)
assert isinstance(result, Contact)
assert result.name == "Alice"
assert result.phone == "555-1234"
assert result.email is None
def test_parse_llm_output_nested(self):
"""Test parsing LLM output into a nested Pydantic model structure."""
text = """
{
"name": "John Smith",
"age": 42,
"address": {
"street": "123 Main St",
"city": "Anytown"
},
"contacts": [
{
"name": "Jane Smith",
"phone": "555-1234",
"email": "[email protected]"
},
{
"name": "Bob Jones",
"phone": "555-5678"
}
]
}
"""
result = PydanticParser.parse_llm_output(text, Person)
assert isinstance(result, Person)
assert result.name == "John Smith"
assert result.age == 42
assert result.address.street == "123 Main St"
assert result.address.city == "Anytown"
assert len(result.contacts) == 2
assert result.contacts[0].name == "Jane Smith"
assert result.contacts[0].phone == "555-1234"
assert result.contacts[0].email == "[email protected]"
assert result.contacts[1].name == "Bob Jones"
assert result.contacts[1].phone == "555-5678"
assert result.contacts[1].email is None
def test_parse_llm_output_with_markdown_code_blocks(self):
"""Test parsing LLM output with markdown formatting."""
text = """
Here's the information you requested:
```json
{
"name": "John Smith",
"age": 42,
"address": {
"street": "123 Main St",
"city": "Anytown"
}
}
```
Is there anything else you need?
"""
result = PydanticParser.parse_llm_output(text, Person)
assert isinstance(result, Person)
assert result.name == "John Smith"
assert result.age == 42
assert result.address.street == "123 Main St"
assert result.address.city == "Anytown"
def test_parse_llm_output_error_handling(self):
"""Test error handling in parse_llm_output."""
# Missing required field
text = '{"name": "John"}'
# Should raise error in strict mode
with pytest.raises(PydanticParserError):
PydanticParser.parse_llm_output(text, Person, strict=True)
# Should return None in non-strict mode
result = PydanticParser.parse_llm_output(text, Person, strict=False)
assert result is None
def test_parse_llm_output_with_wrapper(self):
"""Test parsing with a JSON wrapper key."""
text = """
{
"results": [
{
"name": "John Doe",
"phone": "555-1234"
},
{
"name": "Jane Smith",
"phone": "555-5678",
"email": "[email protected]"
}
]
}
"""
result = PydanticParser.parse_llm_output(text, Contact, json_wrapper_key="results")
assert isinstance(result, list)
assert len(result) == 2
assert all(isinstance(item, Contact) for item in result)
assert result[0].name == "John Doe"
assert result[1].name == "Jane Smith"
assert result[1].email == "[email protected]"
def test_nested_facts_list_parsing(self):
"""Test parsing the specific NestedFactsList example."""
text = """
{
"facts": [
{
"question": "What is the tallest building in New York?",
"answer": "One World Trade Center",
"category": "Architecture"
},
{
"question": "What is the largest park in New York?",
"answer": "Pelham Bay Park",
"category": "Geography"
}
]
}
"""
result = PydanticParser.parse_llm_output(text, NestedFactsList)
assert isinstance(result, NestedFactsList)
assert len(result.facts) == 2
assert all(isinstance(fact, Fact) for fact in result.facts)
assert result.facts[0].question == "What is the tallest building in New York?"
assert result.facts[0].answer == "One World Trade Center"
assert result.facts[0].category == "Architecture"
assert result.facts[1].question == "What is the largest park in New York?"
assert result.facts[1].answer == "Pelham Bay Park"
assert result.facts[1].category == "Geography"
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