migrate apis without implementations

llama_toolchain/batch_inference/api/api.py

@@ -51,11 +51,21 @@ class BatchInference(Protocol):
     @webmethod(route="/batch_inference/completion")
     async def batch_completion(
         self,
-        request: BatchCompletionRequest,
+        model: str,
+        content_batch: List[InterleavedTextMedia],
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        logprobs: Optional[LogProbConfig] = None,
     ) -> BatchCompletionResponse: ...
 
     @webmethod(route="/batch_inference/chat_completion")
     async def batch_chat_completion(
         self,
-        request: BatchChatCompletionRequest,
+        model: str,
+        messages_batch: List[List[Message]],
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        # zero-shot tool definitions as input to the model
+        tools: Optional[List[ToolDefinition]] = list,
+        tool_choice: Optional[ToolChoice] = ToolChoice.auto,
+        tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
+        logprobs: Optional[LogProbConfig] = None,
     ) -> BatchChatCompletionResponse: ...

llama_toolchain/dataset/api/api.py

@@ -46,7 +46,8 @@ class Datasets(Protocol):
     @webmethod(route="/datasets/create")
     def create_dataset(
         self,
-        request: CreateDatasetRequest,
+        uuid: str,
+        dataset: TrainEvalDataset,
     ) -> None: ...
 
     @webmethod(route="/datasets/get")

llama_toolchain/evaluations/api/api.py

@@ -86,19 +86,19 @@ class Evaluations(Protocol):
     @webmethod(route="/evaluate/text_generation/")
     def evaluate_text_generation(
         self,
-        request: EvaluateTextGenerationRequest,
+        metrics: List[TextGenerationMetric],
     ) -> EvaluationJob: ...
 
     @webmethod(route="/evaluate/question_answering/")
     def evaluate_question_answering(
         self,
-        request: EvaluateQuestionAnsweringRequest,
+        metrics: List[QuestionAnsweringMetric],
     ) -> EvaluationJob: ...
 
     @webmethod(route="/evaluate/summarization/")
     def evaluate_summarization(
         self,
-        request: EvaluateSummarizationRequest,
+        metrics: List[SummarizationMetric],
     ) -> EvaluationJob: ...
 
     @webmethod(route="/evaluate/jobs")

llama_toolchain/post_training/api/api.py

@@ -179,13 +179,33 @@ class PostTraining(Protocol):
     @webmethod(route="/post_training/supervised_fine_tune")
     def supervised_fine_tune(
         self,
-        request: PostTrainingSFTRequest,
+        job_uuid: str,
+        model: str,
+        dataset: TrainEvalDataset,
+        validation_dataset: TrainEvalDataset,
+        algorithm: FinetuningAlgorithm,
+        algorithm_config: Union[
+            LoraFinetuningConfig, QLoraFinetuningConfig, DoraFinetuningConfig
+        ],
+        optimizer_config: OptimizerConfig,
+        training_config: TrainingConfig,
+        hyperparam_search_config: Dict[str, Any],
+        logger_config: Dict[str, Any],
     ) -> PostTrainingJob: ...
 
     @webmethod(route="/post_training/preference_optimize")
     def preference_optimize(
         self,
-        request: PostTrainingRLHFRequest,
+        job_uuid: str,
+        finetuned_model: URL,
+        dataset: TrainEvalDataset,
+        validation_dataset: TrainEvalDataset,
+        algorithm: RLHFAlgorithm,
+        algorithm_config: Union[DPOAlignmentConfig],
+        optimizer_config: OptimizerConfig,
+        training_config: TrainingConfig,
+        hyperparam_search_config: Dict[str, Any],
+        logger_config: Dict[str, Any],
     ) -> PostTrainingJob: ...
 
     @webmethod(route="/post_training/jobs")

llama_toolchain/reward_scoring/api/api.py

@@ -50,5 +50,6 @@ class RewardScoring(Protocol):
     @webmethod(route="/reward_scoring/score")
     def reward_score(
         self,
-        request: RewardScoringRequest,
+        dialog_generations: List[DialogGenerations],
+        model: str,
     ) -> Union[RewardScoringResponse]: ...

llama_toolchain/synthetic_data_generation/api/api.py

@@ -48,5 +48,7 @@ class SyntheticDataGeneration(Protocol):
     @webmethod(route="/synthetic_data_generation/generate")
     def synthetic_data_generate(
         self,
-        request: SyntheticDataGenerationRequest,
+        dialogs: List[Message],
+        filtering_function: FilteringFunction = FilteringFunction.none,
+        model: Optional[str] = None,
     ) -> Union[SyntheticDataGenerationResponse]: ...

llama_toolchain/telemetry/api/api.py

@@ -136,7 +136,11 @@ class LogSearchRequest(BaseModel):
 
 class Telemetry(Protocol):
     @webmethod(route="/experiments/create")
-    def create_experiment(self, request: CreateExperimentRequest) -> Experiment: ...
+    def create_experiment(
+        self,
+        name: str,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Experiment: ...
 
     @webmethod(route="/experiments/list")
     def list_experiments(self) -> List[Experiment]: ...
@@ -145,28 +149,62 @@ class Telemetry(Protocol):
     def get_experiment(self, experiment_id: str) -> Experiment: ...
 
     @webmethod(route="/experiments/update")
-    def update_experiment(self, request: UpdateExperimentRequest) -> Experiment: ...
+    def update_experiment(
+        self,
+        experiment_id: str,
+        status: Optional[ExperimentStatus] = None,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Experiment: ...
 
     @webmethod(route="/experiments/create_run")
-    def create_run(self, request: CreateRunRequest) -> Run: ...
+    def create_run(
+        self,
+        experiment_id: str,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Run: ...
 
     @webmethod(route="/runs/update")
-    def update_run(self, request: UpdateRunRequest) -> Run: ...
+    def update_run(
+        self,
+        run_id: str,
+        status: Optional[str] = None,
+        ended_at: Optional[datetime] = None,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Run: ...
 
     @webmethod(route="/runs/log_metrics")
-    def log_metrics(self, request: LogMetricsRequest) -> None: ...
+    def log_metrics(
+        self,
+        run_id: str,
+        metrics: List[Metric],
+    ) -> None: ...
 
     @webmethod(route="/runs/metrics", method="GET")
     def get_metrics(self, run_id: str) -> List[Metric]: ...
 
     @webmethod(route="/logging/log_messages")
-    def log_messages(self, request: LogMessagesRequest) -> None: ...
+    def log_messages(
+        self,
+        logs: List[Log],
+        run_id: Optional[str] = None,
+    ) -> None: ...
 
     @webmethod(route="/logging/get_logs")
-    def get_logs(self, request: LogSearchRequest) -> List[Log]: ...
+    def get_logs(
+        self,
+        query: str,
+        filters: Optional[Dict[str, Any]] = None,
+    ) -> List[Log]: ...
 
     @webmethod(route="/experiments/artifacts/upload")
-    def upload_artifact(self, request: UploadArtifactRequest) -> Artifact: ...
+    def upload_artifact(
+        self,
+        experiment_id: str,
+        name: str,
+        artifact_type: str,
+        content: bytes,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> Artifact: ...
 
     @webmethod(route="/experiments/artifacts/get")
     def list_artifacts(self, experiment_id: str) -> List[Artifact]: ...