add reward scoring and synthetic data gen

source/api_definitions.py

@@ -203,7 +203,66 @@ class AgenticSystem(Protocol):
     ) -> None: ...
 
 
-class LlamaStackEndpoints(Inference, AgenticSystem): ...
+@json_schema_type
+@dataclass
+class RewardScoringRequest:
+    """Request to score a reward function. A list of prompts and a list of responses per prompt."""
+
+    prompt_responses: List[Tuple(prompt:str, List[response:str])]
+
+@json_schema_type
+@dataclass
+class RewardScoringResponse:
+    """Response from the reward scoring. Batch of (prompt, response, score) tuples that pass the threshold."""
+
+    prompt_responses: List[Tuple(prompt:str, List[Tuple(response:str, score:float)])]
+
+class RewardScoring(Protocol):
+    @webmethod(route="/reward_scoring/score")
+    def post_score(
+        self,
+        request: RewardScoringRequest,
+    ) -> Union[RewardScoringResponse]: ...
+
+class FilteringFunction(Enum):
+    """The type of filtering function."""
+
+    none = "none"
+    random = "random"
+    top_k = "top_k"
+    top_p = "top_p"
+    top_k_top_p = "top_k_top_p"
+    sigmoid = "sigmoid"
+
+@json_schema_type
+@dataclass
+class SyntheticDataGenerationRequest:
+    """Request to generate synthetic data. A small batch of prompts and a filtering function"""
+
+    prompts: List[str]
+    filtering_function: FilteringFunction = FilteringFunction.none
+    reward_scoring: RewardScoring
+
+@json_schema_type
+@dataclass
+class SyntheticDataGenerationResponse:
+    """Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold."""
+
+    synthetic_data: List[Tuple(prompt:str, response:str, score:float)]
+    """The actual synthetic data"""
+    statistics: Dict[str, float]
+    """Statistics on how many prompts were generated and how many were filtered out"""
+
+class SyntheticDataGeneration(Protocol):
+    @webmethod(route="/synthetic_data_generation/generate")
+    def post_generate(
+        self,
+        request: SyntheticDataGenerationRequest,
+    ) -> Union[SyntheticDataGenerationResponse]: ...
+
+
+
+class LlamaStackEndpoints(Inference, AgenticSystem, RewardScoring, SyntheticDataGeneration): ...
 
 
 if __name__ == "__main__":