feat: support to filter LLM Events from Lite Agent

src/crewai/agent.py

@@ -775,6 +775,7 @@ class Agent(BaseAgent):
             LiteAgentOutput: The result of the agent execution.
         """
         lite_agent = LiteAgent(
+            id=self.id,
             role=self.role,
             goal=self.goal,
             backstory=self.backstory,

src/crewai/lite_agent.py

@@ -15,12 +15,14 @@ from typing import (
     get_origin,
 )
 
+
 try:
     from typing import Self
 except ImportError:
     from typing_extensions import Self
 
 from pydantic import (
+    UUID4,
     BaseModel,
     Field,
     InstanceOf,
@@ -129,6 +131,7 @@ class LiteAgent(FlowTrackable, BaseModel):
     model_config = {"arbitrary_types_allowed": True}
 
     # Core Agent Properties
+    id: UUID4 = Field(default_factory=uuid.uuid4, frozen=True)
     role: str = Field(description="Role of the agent")
     goal: str = Field(description="Goal of the agent")
     backstory: str = Field(description="Backstory of the agent")
@@ -517,6 +520,7 @@ class LiteAgent(FlowTrackable, BaseModel):
                         messages=self._messages,
                         tools=None,
                         callbacks=self._callbacks,
+                        from_agent=self,
                     ),
                 )
 
@@ -526,6 +530,7 @@ class LiteAgent(FlowTrackable, BaseModel):
                         messages=self._messages,
                         callbacks=self._callbacks,
                         printer=self._printer,
+                        from_agent=self,
                     )
 
                     # Emit LLM call completed event
@@ -534,13 +539,14 @@ class LiteAgent(FlowTrackable, BaseModel):
                         event=LLMCallCompletedEvent(
                             response=answer,
                             call_type=LLMCallType.LLM_CALL,
+                            from_agent=self,
                         ),
                     )
                 except Exception as e:
                     # Emit LLM call failed event
                     crewai_event_bus.emit(
                         self,
-                        event=LLMCallFailedEvent(error=str(e)),
+                        event=LLMCallFailedEvent(error=str(e), from_agent=self),
                     )
                     raise e
 

src/crewai/llm.py

@@ -420,6 +420,7 @@ class LLM(BaseLLM):
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
         from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> str:
         """Handle a streaming response from the LLM.
 
@@ -427,6 +428,8 @@ class LLM(BaseLLM):
             params: Parameters for the completion call
             callbacks: Optional list of callback functions
             available_functions: Dict of available functions
+            from_task: Optional task object
+            from_agent: Optional agent object
 
         Returns:
             str: The complete response text
@@ -512,6 +515,7 @@ class LLM(BaseLLM):
                                         accumulated_tool_args=accumulated_tool_args,
                                         available_functions=available_functions,
                                         from_task=from_task,
+                                        from_agent=from_agent,
                                     )
                                     if result is not None:
                                         chunk_content = result
@@ -529,7 +533,7 @@ class LLM(BaseLLM):
                     assert hasattr(crewai_event_bus, "emit")
                     crewai_event_bus.emit(
                         self,
-                        event=LLMStreamChunkEvent(chunk=chunk_content, from_task=from_task),
+                        event=LLMStreamChunkEvent(chunk=chunk_content, from_task=from_task, from_agent=from_agent),
                     )
             # --- 4) Fallback to non-streaming if no content received
             if not full_response.strip() and chunk_count == 0:
@@ -542,7 +546,7 @@ class LLM(BaseLLM):
                     "stream_options", None
                 )  # Remove stream_options for non-streaming call
                 return self._handle_non_streaming_response(
-                    non_streaming_params, callbacks, available_functions, from_task
+                    non_streaming_params, callbacks, available_functions, from_task, from_agent
                 )
 
             # --- 5) Handle empty response with chunks
@@ -627,7 +631,7 @@ class LLM(BaseLLM):
                 # Log token usage if available in streaming mode
                 self._handle_streaming_callbacks(callbacks, usage_info, last_chunk)
                 # Emit completion event and return response
-                self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task)
+                self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task, from_agent)
                 return full_response
 
             # --- 9) Handle tool calls if present
@@ -639,7 +643,7 @@ class LLM(BaseLLM):
             self._handle_streaming_callbacks(callbacks, usage_info, last_chunk)
 
             # --- 11) Emit completion event and return response
-            self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task)
+            self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task, from_agent)
             return full_response
 
         except ContextWindowExceededError as e:
@@ -651,14 +655,14 @@ class LLM(BaseLLM):
             logging.error(f"Error in streaming response: {str(e)}")
             if full_response.strip():
                 logging.warning(f"Returning partial response despite error: {str(e)}")
-                self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task)
+                self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL, from_task, from_agent)
                 return full_response
 
             # Emit failed event and re-raise the exception
             assert hasattr(crewai_event_bus, "emit")
             crewai_event_bus.emit(
                 self,
-                event=LLMCallFailedEvent(error=str(e), from_task=from_task),
+                event=LLMCallFailedEvent(error=str(e), from_task=from_task, from_agent=from_agent),
             )
             raise Exception(f"Failed to get streaming response: {str(e)}")
 
@@ -668,6 +672,7 @@ class LLM(BaseLLM):
         accumulated_tool_args: DefaultDict[int, AccumulatedToolArgs],
         available_functions: Optional[Dict[str, Any]] = None,
         from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> None | str:
         for tool_call in tool_calls:
             current_tool_accumulator = accumulated_tool_args[tool_call.index]
@@ -686,6 +691,7 @@ class LLM(BaseLLM):
                     tool_call=tool_call.to_dict(),
                     chunk=tool_call.function.arguments,
                     from_task=from_task,
+                    from_agent=from_agent,
                 ),
             )
 
@@ -753,6 +759,7 @@ class LLM(BaseLLM):
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
         from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> str:
         """Handle a non-streaming response from the LLM.
 
@@ -761,6 +768,7 @@ class LLM(BaseLLM):
             callbacks: Optional list of callback functions
             available_functions: Dict of available functions
             from_task: Optional Task that invoked the LLM
+            from_agent: Optional Agent that invoked the LLM
 
         Returns:
             str: The response text
@@ -801,7 +809,7 @@ class LLM(BaseLLM):
 
         # --- 5) If no tool calls or no available functions, return the text response directly
         if not tool_calls or not available_functions:
-            self._handle_emit_call_events(text_response, LLMCallType.LLM_CALL, from_task)
+            self._handle_emit_call_events(text_response, LLMCallType.LLM_CALL, from_task, from_agent)
             return text_response
 
         # --- 6) Handle tool calls if present
@@ -810,7 +818,7 @@ class LLM(BaseLLM):
             return tool_result
 
         # --- 7) If tool call handling didn't return a result, emit completion event and return text response
-        self._handle_emit_call_events(text_response, LLMCallType.LLM_CALL, from_task)
+        self._handle_emit_call_events(text_response, LLMCallType.LLM_CALL, from_task, from_agent)
         return text_response
 
     def _handle_tool_call(
@@ -896,6 +904,7 @@ class LLM(BaseLLM):
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
         from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> Union[str, Any]:
         """High-level LLM call method.
 
@@ -911,6 +920,7 @@ class LLM(BaseLLM):
             available_functions: Optional dict mapping function names to callables
                                that can be invoked by the LLM.
             from_task: Optional Task that invoked the LLM
+            from_agent: Optional Agent that invoked the LLM
 
         Returns:
             Union[str, Any]: Either a text response from the LLM (str) or
@@ -931,6 +941,7 @@ class LLM(BaseLLM):
                 callbacks=callbacks,
                 available_functions=available_functions,
                 from_task=from_task,
+                from_agent=from_agent,
             ),
         )
 
@@ -959,11 +970,11 @@ class LLM(BaseLLM):
                 # --- 7) Make the completion call and handle response
                 if self.stream:
                     return self._handle_streaming_response(
-                        params, callbacks, available_functions, from_task
+                        params, callbacks, available_functions, from_task, from_agent
                     )
                 else:
                     return self._handle_non_streaming_response(
-                        params, callbacks, available_functions, from_task
+                        params, callbacks, available_functions, from_task, from_agent
                     )
 
             except LLMContextLengthExceededException:
@@ -975,12 +986,12 @@ class LLM(BaseLLM):
                 assert hasattr(crewai_event_bus, "emit")
                 crewai_event_bus.emit(
                     self,
-                    event=LLMCallFailedEvent(error=str(e), from_task=from_task),
+                    event=LLMCallFailedEvent(error=str(e), from_task=from_task, from_agent=from_agent),
                 )
                 logging.error(f"LiteLLM call failed: {str(e)}")
                 raise
 
-    def _handle_emit_call_events(self, response: Any, call_type: LLMCallType, from_task: Optional[Any] = None):
+    def _handle_emit_call_events(self, response: Any, call_type: LLMCallType, from_task: Optional[Any] = None, from_agent: Optional[Any] = None):
         """Handle the events for the LLM call.
 
         Args:
@@ -990,7 +1001,7 @@ class LLM(BaseLLM):
         assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
-            event=LLMCallCompletedEvent(response=response, call_type=call_type, from_task=from_task),
+            event=LLMCallCompletedEvent(response=response, call_type=call_type, from_task=from_task, from_agent=from_agent),
         )
 
     def _format_messages_for_provider(

src/crewai/llms/base_llm.py

@@ -48,6 +48,7 @@ class BaseLLM(ABC):
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
         from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> Union[str, Any]:
         """Call the LLM with the given messages.
 

src/crewai/llms/third_party/ai_suite.py

@@ -16,7 +16,8 @@ class AISuiteLLM(BaseLLM):
         tools: Optional[List[dict]] = None,
         callbacks: Optional[List[Any]] = None,
         available_functions: Optional[Dict[str, Any]] = None,
-        from_task: Optional[Task] = None,
+        from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> Union[str, Any]:
         completion_params = self._prepare_completion_params(messages, tools)
         response = self.client.chat.completions.create(**completion_params)

src/crewai/utilities/agent_utils.py

@@ -146,6 +146,7 @@ def get_llm_response(
     callbacks: List[Any],
     printer: Printer,
     from_task: Optional[Any] = None,
+    from_agent: Optional[Any] = None,
 ) -> str:
     """Call the LLM and return the response, handling any invalid responses."""
     try:
@@ -153,6 +154,7 @@ def get_llm_response(
             messages,
             callbacks=callbacks,
             from_task=from_task,
+            from_agent=from_agent,
         )
     except Exception as e:
         printer.print(

src/crewai/utilities/events/llm_events.py

@@ -18,9 +18,14 @@ class LLMEventBase(BaseEvent):
         self._set_task_params(data)
 
     def _set_agent_params(self, data: Dict[str, Any]):
-        if "from_task" in data and (agent := getattr(data["from_task"], "agent", None)):
-            self.agent_id = agent.id
-            self.agent_role = agent.role
+        task = data.get("from_task", None)
+        agent = task.agent if task else data.get("from_agent", None)
+
+        if not agent:
+            return
+
+        self.agent_id = agent.id
+        self.agent_role = agent.role
 
     def _set_task_params(self, data: Dict[str, Any]):
         if "from_task" in data and (task := data["from_task"]):

tests/custom_llm_test.py

@@ -31,6 +31,7 @@ class CustomLLM(BaseLLM):
         callbacks=None,
         available_functions=None,
         from_task=None,
+        from_agent=None,
     ):
         """
         Mock LLM call that returns a predefined response.

tests/utilities/cassettes/test_llm_emits_event_with_lite_agent.yaml

@@ -0,0 +1,171 @@
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+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Speaker. You are a
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+      give my best complete final answer to the task respond using the exact following
+      format:\n\nThought: I now can give a great answer\nFinal Answer: Your final
+      answer must be the great and the most complete as possible, it must be outcome
+      described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user",
+      "content": "say hi!"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"],
+      "stream": true, "stream_options": {"include_usage": true}}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
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+      content-length:
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+      content-type:
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+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.78.0
+      x-stainless-arch:
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+      x-stainless-async:
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+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.78.0
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-read-timeout:
+      - '600.0'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.11.12
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: 'data: {"id":"chatcmpl-BoGFzpBc0nuAKcVrYlEEztNwzrUG6","object":"chat.completion.chunk","created":1751318591,"model":"gpt-4o-mini-2024-07-18","service_tier":"default","system_fingerprint":"fp_34a54ae93c","choices":[{"index":0,"delta":{"role":"assistant","content":"","refusal":null},"logprobs":null,"finish_reason":null}],"usage":null}
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+
+
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+
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+
+
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+
+
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tests/utilities/test_events.py

@@ -903,3 +903,56 @@ def test_llm_emits_event_with_task_and_agent_info(base_agent, base_task):
     assert set(all_agent_id) == {base_agent.id}
     assert set(all_task_id) == {base_task.id}
     assert set(all_task_name) == {base_task.name}
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_llm_emits_event_with_lite_agent():
+    completed_event = []
+    failed_event = []
+    started_event = []
+    stream_event = []
+
+    with crewai_event_bus.scoped_handlers():
+        @crewai_event_bus.on(LLMCallFailedEvent)
+        def handle_llm_failed(source, event):
+            failed_event.append(event)
+
+        @crewai_event_bus.on(LLMCallStartedEvent)
+        def handle_llm_started(source, event):
+            started_event.append(event)
+
+        @crewai_event_bus.on(LLMCallCompletedEvent)
+        def handle_llm_completed(source, event):
+            completed_event.append(event)
+
+        @crewai_event_bus.on(LLMStreamChunkEvent)
+        def handle_llm_stream_chunk(source, event):
+            stream_event.append(event)
+
+        agent = Agent(
+            role="Speaker",
+            llm=LLM(model="gpt-4o-mini", stream=True),
+            goal="Just say hi",
+            backstory="You are a helpful assistant that just says hi",
+        )
+        agent.kickoff(messages=[{"role": "user", "content": "say hi!"}])
+
+
+    assert len(completed_event) == 2
+    assert len(failed_event) == 0
+    assert len(started_event) == 2
+    assert len(stream_event) == 15
+
+    all_events = completed_event + failed_event + started_event + stream_event
+    all_agent_roles = [event.agent_role for event in all_events]
+    all_agent_id = [event.agent_id for event in all_events]
+    all_task_id = [event.task_id for event in all_events if event.task_id]
+    all_task_name = [event.task_name for event in all_events if event.task_name]
+
+    # ensure all events have the agent + task props set
+    assert len(all_agent_roles) == 19
+    assert len(all_agent_id) == 19
+    assert len(all_task_id) == 0
+    assert len(all_task_name) == 0
+
+    assert set(all_agent_roles) == {agent.role}
+    assert set(all_agent_id) == {agent.id}