strangely the pipeline we currently run doesnt take the full param into account, instead of using the Params pydantic, it search for a strange require_minimal
so I am going to paste the class def here
class Params(BaseModel):
"""
Evaluation parameters.
Example:
{
"evaluation_mode": "lenient",
"expected_type": "DFA",
"feedback_verbosity": "standard"
}
"""
# Evaluation mode
evaluation_mode: Literal["strict", "lenient", "partial"] = Field(
default="lenient",
description="strict: exact match, lenient: language equivalence, partial: partial credit"
)
# Expected automaton type
expected_type: Literal["DFA", "NFA", "any"] = Field(
default="any",
description="Expected automaton type"
)
# Feedback level
feedback_verbosity: Literal["minimal", "standard", "detailed"] = Field(
default="standard",
description="Level of feedback detail"
)
# Validation options
check_minimality: bool = Field(default=False, description="Check if FSA is minimal")
check_completeness: bool = Field(default=False, description="Check if DFA is complete")
# UI options
highlight_errors: bool = Field(default=True, description="Include element IDs for UI highlighting")
show_counterexample: bool = Field(default=True, description="Show counterexample if languages differ")
# Test generation
max_test_length: int = Field(default=10, ge=1, le=50, description="Max length for generated test strings")
is_dev: bool = Field(
default=False,
description="Flag indicating if running in development mode"
)
so here
- evaluation mode: this should do 1. decomposition and are_iso 2. accept same language 3. I dont know
- expected_type: we need some extra is_nfa and is_dfa functions
- feedback verbosity: honestly I have no idea how to do this
- check_minimality and check_completeness will be done in the next commit
- show_counterexamples: also need a helper
- max_test_length: what the hell is this
- is_dev: this is added by me incase I need som dev only stuff, but now seems useless
but anyways we should do this in the checkpoint2
strangely the pipeline we currently run doesnt take the full param into account, instead of using the Params pydantic, it search for a strange require_minimal
so I am going to paste the class def here
so here
but anyways we should do this in the checkpoint2