feat: moved configuration params into answer

Author: HarrySu123

evaluation_function/evaluation.py

@@ -622,20 +622,54 @@ def _ok() -> Result:
     def _err(msg: str) -> Result:
         return Result(is_correct=False, feedback_items=[("error", msg)])
 
-    # ── parse params FIRST — directed/weighted/multigraph live here ─────
+    # ── parse answer FIRST — evaluation_type and graph flags now live here ─────
+
+    answer_dict = _to_dictish(answer) or {}
+
+    if is_frontend_format(answer_dict):
+        parsed_graph = parse_frontend_graph(answer_dict)
+        answer_dict = {"graph": parsed_graph.model_dump()}
 
-    raw_params = _to_dictish(params) or {}
     try:
-        p = EvaluationParams.model_validate(raw_params)
+        ans = Answer.model_validate(answer_dict)
     except ValidationError as e:
-        return _err(
-            "Invalid params schema. Expected e.g. "
-            "{'evaluation_type': 'connectivity'|'bipartite'|'graph_coloring'|...}. "
-            f"Error: {e}"
-            f"response: {response}"
-            f"answer: {answer}"
-            f"params: {params}"
-        )
+        return _err(f"Invalid answer schema: {e}")
+
+    # ── extract evaluation params from answer ─────────────────────────────
+    # All evaluation configuration now comes from the answer object
+    
+    eval_params_dict = {}
+    
+    # Get evaluation_type from answer (required)
+    if ans.evaluation_type:
+        eval_params_dict['evaluation_type'] = ans.evaluation_type
+    elif 'evaluation_type' in answer_dict:
+        eval_params_dict['evaluation_type'] = answer_dict['evaluation_type']
+    else:
+        return _err("evaluation_type is required in answer object")
+    
+    # Get graph structure flags from answer (with defaults)
+    eval_params_dict['directed'] = ans.directed if ans.directed is not None else False
+    eval_params_dict['weighted'] = ans.weighted if ans.weighted is not None else False
+    eval_params_dict['multigraph'] = ans.multigraph if ans.multigraph is not None else False
+    
+    # Get optional evaluation sub-params from answer
+    for key in ['connectivity', 'bipartite', 'graph_coloring', 'cycle_detection', 
+                'isomorphism', 'feedback_level', 'tolerance']:
+        value = getattr(ans, key, None)
+        if value is not None:
+            eval_params_dict[key] = value
+    
+    # Set defaults for feedback_level and tolerance if not provided
+    if 'feedback_level' not in eval_params_dict:
+        eval_params_dict['feedback_level'] = 'standard'
+    if 'tolerance' not in eval_params_dict:
+        eval_params_dict['tolerance'] = 1e-9
+    
+    try:
+        p = EvaluationParams.model_validate(eval_params_dict)
+    except ValidationError as e:
+        return _err(f"Invalid evaluation parameters in answer: {e}")
 
     # ── parse response (student's graph) ─────────────────────────────────
 
@@ -650,22 +684,9 @@ def _err(msg: str) -> Result:
     except ValidationError as e:
         return _err(f"Invalid response schema: {e}")
 
-    # ── parse answer (teacher's reference) ───────────────────────────────
-
-    answer_dict = _to_dictish(answer) or {}
-
-    if is_frontend_format(answer_dict):
-        parsed_graph = parse_frontend_graph(answer_dict)
-        answer_dict = {"graph": parsed_graph.model_dump()}
-
-    try:
-        ans = Answer.model_validate(answer_dict)
-    except ValidationError as e:
-        return _err(f"Invalid answer schema: {e}")
-
     # ── resolve graphs and stamp params flags ─────────────────────────────
-    # directed/weighted/multigraph come exclusively from params — never from
-    # the student or teacher payload.
+    # directed/weighted/multigraph come exclusively from answer object — never from
+    # the student response payload.
 
     student_graph: Graph = resp.graph
     if student_graph is None:

evaluation_function/schemas/params.py

@@ -75,7 +75,7 @@ class TraversalParams(BaseModel):
 class EvaluationParams(BaseModel):
     evaluation_type: EvaluationType = Field(..., description="The type of evaluation to perform")
 
-    # Graph structure flags — sourced from params, not from the response/answer graph payload
+    # Graph structure flags — now sourced from the answer object, not from params
     directed: bool = Field(False, description="Whether the graph is directed")
     weighted: bool = Field(False, description="Whether the graph is weighted")
     multigraph: bool = Field(False, description="Whether the graph allows multiple edges")

evaluation_function/schemas/request.py

@@ -2,10 +2,11 @@
 Request/Response Schemas
 """
 
-from typing import Optional
+from typing import Optional, Literal
 from pydantic import BaseModel, Field
 
 from .graph import Graph
+from .evaluation_types import EvaluationType
 
 
 class Response(BaseModel):
@@ -34,6 +35,24 @@ class Config:
 
 
 class Answer(BaseModel):
+    # Evaluation configuration (moved from params)
+    evaluation_type: Optional[EvaluationType] = Field(None, description="The type of evaluation to perform")
+    directed: Optional[bool] = Field(None, description="Whether the graph is directed")
+    weighted: Optional[bool] = Field(None, description="Whether the graph is weighted")
+    multigraph: Optional[bool] = Field(None, description="Whether the graph allows multiple edges")
+    
+    # Optional evaluation sub-params
+    connectivity: Optional[dict] = Field(None, description="Connectivity evaluation parameters")
+    bipartite: Optional[dict] = Field(None, description="Bipartite evaluation parameters")
+    graph_coloring: Optional[dict] = Field(None, description="Graph coloring evaluation parameters")
+    cycle_detection: Optional[dict] = Field(None, description="Cycle detection parameters")
+    isomorphism: Optional[dict] = Field(None, description="Isomorphism evaluation parameters")
+    
+    # Global evaluation params
+    feedback_level: Optional[Literal["minimal", "standard", "detailed"]] = Field(None, description="Level of detail in feedback")
+    tolerance: Optional[float] = Field(None, description="Numerical tolerance for comparisons")
+    
+    # Expected graph and answers
     graph: Optional[Graph] = Field(None, description="The expected/correct graph")
     is_connected: Optional[bool] = None
     is_bipartite: Optional[bool] = None