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Brandon/eng 266 conversation crew v1 (#1843)
* worked on foundation for new conversational crews. Now going to work on chatting. * core loop should be working and ready for testing. * high level chat working * its alive!! * Added in Joaos feedback to steer crew chats back towards the purpose of the crew * properly return tool call result * accessing crew directly instead of through uv commands * everything is working for conversation now * Fix linting * fix llm_utils.py and other type errors * fix more type errors * fixing type error * More fixing of types * fix failing tests * Fix more failing tests * adding tests. cleaing up pr. * improve * drop old functions * improve type hintings
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Devin AI
parent
ed5bdfcf9f
commit
ad28360436
@@ -37,6 +37,7 @@ from crewai.tasks.task_output import TaskOutput
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from crewai.telemetry import Telemetry
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from crewai.tools.agent_tools.agent_tools import AgentTools
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from crewai.tools.base_tool import Tool
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from crewai.types.crew_chat import ChatInputs
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from crewai.types.usage_metrics import UsageMetrics
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from crewai.utilities import I18N, FileHandler, Logger, RPMController
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from crewai.utilities.constants import TRAINING_DATA_FILE
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@@ -204,6 +205,10 @@ class Crew(BaseModel):
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default=None,
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description="Knowledge sources for the crew. Add knowledge sources to the knowledge object.",
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)
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chat_llm: Optional[Any] = Field(
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default=None,
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description="LLM used to handle chatting with the crew.",
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)
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_knowledge: Optional[Knowledge] = PrivateAttr(
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default=None,
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)
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@@ -992,6 +997,31 @@ class Crew(BaseModel):
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return self._knowledge.query(query)
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return None
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def fetch_inputs(self) -> Set[str]:
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"""
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Gathers placeholders (e.g., {something}) referenced in tasks or agents.
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Scans each task's 'description' + 'expected_output', and each agent's
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'role', 'goal', and 'backstory'.
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Returns a set of all discovered placeholder names.
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"""
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placeholder_pattern = re.compile(r"\{(.+?)\}")
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required_inputs: Set[str] = set()
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# Scan tasks for inputs
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for task in self.tasks:
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# description and expected_output might contain e.g. {topic}, {user_name}, etc.
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text = f"{task.description or ''} {task.expected_output or ''}"
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required_inputs.update(placeholder_pattern.findall(text))
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# Scan agents for inputs
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for agent in self.agents:
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# role, goal, backstory might have placeholders like {role_detail}, etc.
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text = f"{agent.role or ''} {agent.goal or ''} {agent.backstory or ''}"
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required_inputs.update(placeholder_pattern.findall(text))
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return required_inputs
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def copy(self):
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"""Create a deep copy of the Crew."""
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@@ -1047,7 +1077,7 @@ class Crew(BaseModel):
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def _interpolate_inputs(self, inputs: Dict[str, Any]) -> None:
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"""Interpolates the inputs in the tasks and agents."""
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[
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task.interpolate_inputs(
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task.interpolate_inputs_and_add_conversation_history(
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# type: ignore # "interpolate_inputs" of "Task" does not return a value (it only ever returns None)
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inputs
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)
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