from donew import DO
from pydantic import BaseModel, Field
from donew.new import LiteLLMModel
    
class Answer(BaseModel):
    word: str = Field(description="The word to check")
    count: int = Field(description="The answer number")
 
doer = DO.New(model=LiteLLMModel(model_id="ollama/qwen2.5-coder:3b")})
result = doer.envision(Answer).enact("how many r's are in the word strawberry?")
assert result.count == 3
print(result)

from donew import DO
from pydantic import BaseModel, Field
from donew.new import LiteLLMModel
 
class Countries(BaseModel):
    countries: List[str] = Field(description="The list of countries whose names begin with 'B' and do not contain the letter 'E'. The names are sorted and each starts with a capital letter.")
 
doer = DO.New(model=LiteLLMModel(model_id="ollama/qwen2.5-coder:3b"))
result = doer.envision(Countries).enact("fullfill the task")
 
reference_list = ["Bahamas", "Bahrain", "Barbados", "Bhutan", "Bolivia", "Botswana", "Brazil", "Bulgaria", "Burkina Faso", "Burundi"]
assert result.countries == reference_list
print(result)

from donew import DO
from pydantic import BaseModel, Field
from donew.new import LiteLLMModel
 
class WeatherData(BaseModel):
    """Current weather information"""
    temperature: float = Field(description="Current temperature in Celsius")
    conditions: str = Field(description="Current weather conditions (e.g., sunny, rainy)")
    humidity: Optional[float] = Field(description="Current humidity percentage")
    wind_speed: Optional[float] = Field(description="Current wind speed in km/h")
 
doer = DO.New(
    model = LiteLLMModel(model_id="gpt-4o") # use e.g. from dotenv import load_dotenv
)
result = doer.realm([BROWSE]).envision(WeatherData).enact(
    "Get the current weather for the given parameters",
    city="Berlin, Germany"
)
 
assert isinstance(result, WeatherData)
assert result.temperature is not None  # Ensure we got a temperature
print(result.model_dump_json(indent=2))
return result