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

src/crewai/crew.py

@@ -1,10 +1,11 @@
 import asyncio
 import json
+import re
 import uuid
 import warnings
 from concurrent.futures import Future
 from hashlib import md5
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
 
 from pydantic import (
     UUID4,
@@ -36,6 +37,7 @@ from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import Tool
+from crewai.types.crew_chat import ChatInputs
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.constants import TRAINING_DATA_FILE
@@ -203,6 +205,10 @@ class Crew(BaseModel):
         default=None,
         description="Knowledge sources for the crew. Add knowledge sources to the knowledge object.",
     )
+    chat_llm: Optional[Any] = Field(
+        default=None,
+        description="LLM used to handle chatting with the crew.",
+    )
     _knowledge: Optional[Knowledge] = PrivateAttr(
         default=None,
     )
@@ -991,6 +997,31 @@ class Crew(BaseModel):
             return self._knowledge.query(query)
         return None
 
+    def fetch_inputs(self) -> Set[str]:
+        """
+        Gathers placeholders (e.g., {something}) referenced in tasks or agents.
+        Scans each task's 'description' + 'expected_output', and each agent's
+        'role', 'goal', and 'backstory'.
+
+        Returns a set of all discovered placeholder names.
+        """
+        placeholder_pattern = re.compile(r"\{(.+?)\}")
+        required_inputs: Set[str] = set()
+
+        # Scan tasks for inputs
+        for task in self.tasks:
+            # description and expected_output might contain e.g. {topic}, {user_name}, etc.
+            text = f"{task.description or ''} {task.expected_output or ''}"
+            required_inputs.update(placeholder_pattern.findall(text))
+
+        # Scan agents for inputs
+        for agent in self.agents:
+            # role, goal, backstory might have placeholders like {role_detail}, etc.
+            text = f"{agent.role or ''} {agent.goal or ''} {agent.backstory or ''}"
+            required_inputs.update(placeholder_pattern.findall(text))
+
+        return required_inputs
+
     def copy(self):
         """Create a deep copy of the Crew."""
 
@@ -1046,7 +1077,7 @@ class Crew(BaseModel):
     def _interpolate_inputs(self, inputs: Dict[str, Any]) -> None:
         """Interpolates the inputs in the tasks and agents."""
         [
-            task.interpolate_inputs(
+            task.interpolate_inputs_and_add_conversation_history(
                 # type: ignore # "interpolate_inputs" of "Task" does not return a value (it only ever returns None)
                 inputs
             )