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| """This file contains the function calling implementation for different actions. | |
| This is similar to the functionality of `CodeActResponseParser`. | |
| """ | |
| import json | |
| from litellm import ( | |
| ChatCompletionToolParam, | |
| ModelResponse, | |
| ) | |
| from openhands.agenthub.codeact_agent.function_calling import combine_thought | |
| from openhands.agenthub.codeact_agent.tools import FinishTool | |
| from openhands.agenthub.loc_agent.tools import ( | |
| SearchEntityTool, | |
| SearchRepoTool, | |
| create_explore_tree_structure_tool, | |
| ) | |
| from openhands.core.exceptions import ( | |
| FunctionCallNotExistsError, | |
| ) | |
| from openhands.core.logger import openhands_logger as logger | |
| from openhands.events.action import ( | |
| Action, | |
| AgentFinishAction, | |
| IPythonRunCellAction, | |
| MessageAction, | |
| ) | |
| from openhands.events.tool import ToolCallMetadata | |
| def response_to_actions( | |
| response: ModelResponse, | |
| mcp_tool_names: list[str] | None = None, | |
| ) -> list[Action]: | |
| actions: list[Action] = [] | |
| assert len(response.choices) == 1, 'Only one choice is supported for now' | |
| choice = response.choices[0] | |
| assistant_msg = choice.message | |
| if hasattr(assistant_msg, 'tool_calls') and assistant_msg.tool_calls: | |
| # Check if there's assistant_msg.content. If so, add it to the thought | |
| thought = '' | |
| if isinstance(assistant_msg.content, str): | |
| thought = assistant_msg.content | |
| elif isinstance(assistant_msg.content, list): | |
| for msg in assistant_msg.content: | |
| if msg['type'] == 'text': | |
| thought += msg['text'] | |
| # Process each tool call to OpenHands action | |
| for i, tool_call in enumerate(assistant_msg.tool_calls): | |
| action: Action | |
| logger.debug(f'Tool call in function_calling.py: {tool_call}') | |
| try: | |
| arguments = json.loads(tool_call.function.arguments) | |
| except json.decoder.JSONDecodeError as e: | |
| raise RuntimeError( | |
| f'Failed to parse tool call arguments: {tool_call.function.arguments}' | |
| ) from e | |
| # ================================================ | |
| # LocAgent's Tools | |
| # ================================================ | |
| ALL_FUNCTIONS = [ | |
| 'explore_tree_structure', | |
| 'search_code_snippets', | |
| 'get_entity_contents', | |
| ] | |
| if tool_call.function.name in ALL_FUNCTIONS: | |
| # We implement this in agent_skills, which can be used via Jupyter | |
| func_name = tool_call.function.name | |
| code = f'print({func_name}(**{arguments}))' | |
| logger.debug(f'TOOL CALL: {func_name} with code: {code}') | |
| action = IPythonRunCellAction(code=code) | |
| # ================================================ | |
| # AgentFinishAction | |
| # ================================================ | |
| elif tool_call.function.name == FinishTool['function']['name']: | |
| action = AgentFinishAction( | |
| final_thought=arguments.get('message', ''), | |
| task_completed=arguments.get('task_completed', None), | |
| ) | |
| else: | |
| raise FunctionCallNotExistsError( | |
| f'Tool {tool_call.function.name} is not registered. (arguments: {arguments}). Please check the tool name and retry with an existing tool.' | |
| ) | |
| # We only add thought to the first action | |
| if i == 0: | |
| action = combine_thought(action, thought) | |
| # Add metadata for tool calling | |
| action.tool_call_metadata = ToolCallMetadata( | |
| tool_call_id=tool_call.id, | |
| function_name=tool_call.function.name, | |
| model_response=response, | |
| total_calls_in_response=len(assistant_msg.tool_calls), | |
| ) | |
| actions.append(action) | |
| else: | |
| actions.append( | |
| MessageAction( | |
| content=str(assistant_msg.content) if assistant_msg.content else '', | |
| wait_for_response=True, | |
| ) | |
| ) | |
| # Add response id to actions | |
| # This will ensure we can match both actions without tool calls (e.g. MessageAction) | |
| # and actions with tool calls (e.g. CmdRunAction, IPythonRunCellAction, etc.) | |
| # with the token usage data | |
| for action in actions: | |
| action.response_id = response.id | |
| assert len(actions) >= 1 | |
| return actions | |
| def get_tools() -> list[ChatCompletionToolParam]: | |
| tools = [FinishTool] | |
| tools.append(SearchRepoTool) | |
| tools.append(SearchEntityTool) | |
| tools.append(create_explore_tree_structure_tool(use_simplified_description=True)) | |
| return tools | |