apt: remove incompatible syntax,etc.

Author: zhansheng.lzs

dashscope/finetune/agentic_rl.py

@@ -3,8 +3,6 @@
 
 # Copyright (c) Alibaba, Inc. and its affiliates.
 
-import yaml
-from pathlib import Path
 from typing import Union, List, Optional, ClassVar, Dict, Any
 from typing_extensions import Self
 
@@ -29,8 +27,6 @@
 from dashscope.finetune.reinforcement import (
     FunctionType,
     DatasetsType,
-    TrainingType,
-    DataSourceType,
 )
 from dashscope.finetune.reinforcement import (
     RewardInput,
@@ -47,7 +43,6 @@
 from dashscope.finetune.reinforcement.common.errors import (
     RegistrationError,
     ValidationError,
-    IOErrorWithCode,
     RuntimeErrorWithCode,
     ValueErrorWithCode,
     DatasetsError,
@@ -65,7 +60,8 @@ def __init__(self, api_key: str = None):
         except Exception as e:
             logger.error("API key initialization failed", exc_info=True)
             raise ValueErrorWithCode(
-                "Invalid API key configuration", error_code=3000
+                "Invalid API key configuration",
+                error_code=3000,
             ) from e
 
     def init(self, config_path: Optional[str] = None, **kwargs) -> Self:
@@ -86,7 +82,14 @@ async def register_functions(
             ]
         ] = None,
         lazy_load: Optional[bool] = True,
-    ) -> tuple[List[str], List[str], List[str], List[str], List[str], List[str]]:
+    ) -> tuple[
+        List[str],
+        List[str],
+        List[str],
+        List[str],
+        List[str],
+        List[str],
+    ]:
         """Register function components and return entity/instance IDs."""
         if functions:
             self.tuning.functions = functions
@@ -105,10 +108,12 @@ async def register_functions(
             logger.info("Function components registered")
         except Exception as e:
             logger.error(
-                "Function component registration failed", exc_info=True
+                "Function component registration failed",
+                exc_info=True,
             )
             raise RegistrationError(
-                "Function registration error", error_code=3200
+                "Function registration error",
+                error_code=3200,
             ) from e
 
         return (
@@ -130,17 +135,19 @@ async def upload_datasets(
             self.tuning.datasets = datasets
 
         try:
-            uploaded_training_ids, uploaded_validation_ids = (
-                await self.tuning.upload_datasets(
-                    training_files=training_files,
-                    validation_files=validation_files,
-                )
+            (
+                uploaded_training_ids,
+                uploaded_validation_ids,
+            ) = await self.tuning.upload_datasets(
+                training_files=training_files,
+                validation_files=validation_files,
             )
             logger.info("Datasets uploaded")
         except Exception as e:
             logger.error("Datasets upload failed", exc_info=True)
             raise DatasetsError(
-                "Datasets upload error", error_code=3300
+                "Datasets upload error",
+                error_code=3300,
             ) from e
 
         return uploaded_training_ids, uploaded_validation_ids
@@ -187,16 +194,16 @@ def submit_job(
             self.tuning.functions = functions
         try:
             rollouts = self.tuning.combine_ids_runtimes(
-                functype=FunctionType.ROLLOUT
+                functype=FunctionType.ROLLOUT,
             )
             rewards = self.tuning.combine_ids_runtimes(
-                functype=FunctionType.REWARD
+                functype=FunctionType.REWARD,
             )
             rewards.extend(
                 self.tuning.combine_ids_runtimes(
                     functype=FunctionType.GROUP_REWARD,
                     id_str=get_func_type_id(FunctionType.REWARD),
-                )
+                ),
             )
         except Exception as e:
             logger.error(
@@ -207,7 +214,8 @@ def submit_job(
         # names of functions
         if not self.tuning.check_function_names():
             raise ValueErrorWithCode(
-                "Duplicate function names detected. All function names must be unique.",
+                "Duplicate function names detected. All function names must "
+                "be unique.",
                 error_code=3401,
             )
 
@@ -259,7 +267,8 @@ def submit_job(
         except Exception as e:
             logger.error("Job submission failed", exc_info=True)
             raise RuntimeErrorWithCode(
-                "Job submission error", error_code=3400
+                "Job submission error",
+                error_code=3400,
             ) from e
 
         return FineTune(**resp)
@@ -296,15 +305,16 @@ async def run(
         """
         try:
             logger.info(
-                "🟦 Path-Driven mode: Registering functions & uploading datasets..."
+                "🟦 Path-Driven mode: Registering functions & uploading "
+                "datasets...",
             )
             await self.register_functions(
                 functions=functions,
                 lazy_load=True,
             )
 
             datasets = list(training_datasets or []) + list(
-                validation_datasets or []
+                validation_datasets or [],
             )
             await self.upload_datasets(
                 datasets=datasets,
@@ -321,7 +331,8 @@ async def run(
         except Exception as e:
             logger.error("RL tuning workflow failed", exc_info=True)
             raise RuntimeErrorWithCode(
-                f"RL tuning workflow failed: {str(e)}", error_code=3500
+                f"RL tuning workflow failed: {str(e)}",
+                error_code=3500,
             ) from e
 
     @classmethod
@@ -439,7 +450,8 @@ async def test_functions(
                 value = GroupRewardInput.model_validate(input_data)
             else:
                 raise ValueErrorWithCode(
-                    f"Unsupported function type: {functype}", error_code=3600
+                    f"Unsupported function type: {functype}",
+                    error_code=3600,
                 )
 
             logger.info(
@@ -451,13 +463,16 @@ async def test_functions(
             )
 
             return await AgenticRLFunctionComponent.verify_function(
-                value, instance_id
+                value,
+                instance_id,
             )
 
         except Exception as e:
             logger.error(
-                f"Failure during {str(functype)} test: {str(e)}", exc_info=True
+                f"Failure during {str(functype)} test: {str(e)}",
+                exc_info=True,
             )
             raise ValidationError(
-                f"Function test failed: {str(e)}", error_code=3601
+                f"Function test failed: {str(e)}",
+                error_code=3601,
             ) from e

dashscope/finetune/reinforcement/__init__.py

@@ -122,9 +122,6 @@
 from dashscope.finetune.reinforcement.component.processor.abstract_group_reward_processor import (
     AbstractGroupRewardProcessor,
 )
-from dashscope.finetune.reinforcement.component.observability import (
-    observe_processor,
-)
 
 
 def __getattr__(name):
@@ -229,7 +226,6 @@ def __getattr__(name):
     "AbstractRolloutProcessor",
     "AbstractRewardProcessor",
     "AbstractGroupRewardProcessor",
-    "observe_processor",
     # Core Models
     "FunctionComponentModel",
     "TuningModel",
@@ -247,6 +243,4 @@ def __getattr__(name):
     "Observability",
     "AgenticRLTuning",
     "Models",
-    # CLI
-    "app",
 ]

dashscope/finetune/reinforcement/common/model.py

@@ -5,7 +5,6 @@
 import os
 import shutil
 import tempfile
-import time
 import asyncio
 
 # Third-party Libraries
@@ -91,12 +90,9 @@ class Dataset(BaseModel):
     type: DatasetsType = DatasetsType.TRAINING
 
     data_source_type: Optional[DataSourceType] = DataSourceType.FILE_ID
-    # type: file_id
     file_name: Optional[str] = None
     file_id: Optional[str] = None
-    # type: download_url
     download_url: Optional[str] = None
-    # type: oss_mount
     mount_storage: Optional[MountStorage] = None
 
     async def upload_dataset(self) -> str:

dashscope/finetune/reinforcement/component/data/group_reward_input.py

@@ -6,7 +6,7 @@
 """
 
 from pydantic import Field
-from typing import Any, Dict, List, Optional
+from typing import Any, List, Optional
 
 from dashscope.finetune.reinforcement.common.model_types import (
     FunctionType as FuncType,

dashscope/finetune/reinforcement/component/data/group_reward_output.py

@@ -5,7 +5,7 @@
 """
 
 from pydantic import BaseModel, Field
-from typing import Any, Dict, List, Optional
+from typing import List, Optional
 
 from dashscope.finetune.reinforcement.component.data.base_data_model import (
     TaskStatus,

dashscope/finetune/reinforcement/component/data/reward_input.py

@@ -6,7 +6,7 @@
 """
 
 from pydantic import Field
-from typing import Any, Dict, Optional
+from typing import Any, Optional
 
 from dashscope.finetune.reinforcement.common.model_types import (
     FunctionType as FuncType,

dashscope/finetune/reinforcement/component/data/reward_output.py

@@ -5,7 +5,7 @@
 """
 
 from pydantic import BaseModel, Field
-from typing import Any, Dict, Optional
+from typing import Dict, Optional
 
 from dashscope.finetune.reinforcement.component.data.base_data_model import (
     TaskStatus,

dashscope/finetune/reinforcement/component/observability/genai/_core.py

@@ -56,7 +56,8 @@
 except ImportError:  # pragma: no cover
     get_extended_telemetry_handler = None  # type: ignore[assignment]
     ExecuteToolInvocation = None  # type: ignore[assignment]
-    InputMessage = OutputMessage = Text = ToolCall = None  # type: ignore[assignment]
+    # type: ignore[assignment]
+    InputMessage = OutputMessage = Text = ToolCall = None
     GENAI_AVAILABLE = False
 
 _logger = logging.getLogger(__name__)

dashscope/finetune/reinforcement/component/observability/genai/tools.py

@@ -881,7 +881,8 @@ async def _run_tool_with_span_async(
         _emit_trace_tool_debug_line("wrap_ainvoke", tool_name, config)
 
     if not is_tracing_enabled() or not GENAI_AVAILABLE:
-        return await orig_fn(input, config=config, **kwargs)  # type: ignore[misc]
+        # type: ignore[misc]
+        return await orig_fn(input, config=config, **kwargs)
 
     trace_key = _trace_hex_or_none()
     ctx_token: Optional[contextvars.Token[int]] = None
@@ -907,7 +908,8 @@ async def _run_tool_with_span_async(
                     "trace_tool_async:after_use_span", invocation
                 )
                 log_trace_id(f"execute_tool:{tool_name}")
-                result = await orig_fn(input, config=config, **kwargs)  # type: ignore[misc]
+                # type: ignore[misc]
+                result = await orig_fn(input, config=config, **kwargs)
                 invocation.tool_call_result = _json_serializable(result)
                 if hasattr(invocation, "span") and invocation.span is not None:
                     invocation.span.set_status(Status(StatusCode.OK))

dashscope/finetune/reinforcement/component/observability/processor_span.py

@@ -272,7 +272,8 @@ async def auto_wrapper(
         else:
 
             @wraps(fn)
-            def auto_wrapper(self: Any, input_data: Any, *args: Any, **kwargs: Any) -> Any:  # type: ignore[misc]
+            # type: ignore[misc]
+            def auto_wrapper(self: Any, input_data: Any, *args: Any, **kwargs: Any) -> Any:
                 has_func_type = (
                     getattr(input_data, "func_type", None) is not None
                 )