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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 | |