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3.35 kB
| # Copyright 2023-2024 SGLang Team | |
| # Copyright 2025 ModelBest Inc. and/or its affiliates | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import json | |
| from typing import Any, Optional | |
| from uuid import uuid4 | |
| from verl.utils.rollout_trace import rollout_trace_op | |
| from .schemas import OpenAIFunctionToolSchema, ToolResponse | |
| class BaseTool: | |
| """Base class for tools. | |
| A tool should support the following methods: | |
| - `get_openai_tool_schema`: return the tool schema in OpenAI format. | |
| - `create`: create a tool instance for a trajectory. | |
| - `execute`: execute the tool. | |
| - `calc_reward`: calculate the reward respect to tool state. | |
| - `release`: release the tool instance. | |
| """ | |
| def __init__(self, config: dict, tool_schema: OpenAIFunctionToolSchema): | |
| self.config = config | |
| self.tool_schema = tool_schema or self.get_openai_tool_schema() | |
| assert self.tool_schema is not None, "Tool schema is not set!" | |
| self.name = self.tool_schema.function.name | |
| print(json.dumps(self.tool_schema.model_dump(exclude_unset=True, exclude_none=True), indent=2)) | |
| def get_openai_tool_schema(self) -> OpenAIFunctionToolSchema: | |
| return self.tool_schema | |
| async def create(self, instance_id: Optional[str] = None, **kwargs) -> tuple[str, ToolResponse]: | |
| """Create a tool instance. | |
| Args: | |
| instance_id: The instance id of the tool. | |
| Returns: | |
| The instance id of the tool. | |
| tool_creation_response: The response of the tool when creating the instance. | |
| """ | |
| if instance_id is None: | |
| return str(uuid4()), ToolResponse() | |
| else: | |
| return instance_id, ToolResponse() | |
| async def execute(self, instance_id: str, parameters: dict[str, Any], **kwargs) -> tuple[ToolResponse, float, dict]: | |
| """Execute the tool. | |
| Args: | |
| instance_id: The instance id of the tool. | |
| parameters: The json string of the parameters of the tool. | |
| Returns: tool_response, tool_reward_score, tool_metrics | |
| tool_response: The ToolResponse object containing text, image, and/or video content. | |
| tool_reward_score: The step reward score of the tool. | |
| tool_metrics: The metrics of the tool. | |
| """ | |
| return ToolResponse(text="Updated the tool state."), 0.0, {} | |
| async def calc_reward(self, instance_id: str, **kwargs) -> float: | |
| """Calculate the reward of the tool. | |
| Args: | |
| instance_id: The instance id of the tool. | |
| Returns: | |
| The reward of the tool. | |
| """ | |
| return 0.0 | |
| async def release(self, instance_id: str, **kwargs) -> None: | |
| """Release the tool instance. | |
| Args: | |
| instance_id: The instance id of the tool. | |
| """ | |
| pass | |