feat: adding response_id in streaming response

lib/crewai/src/crewai/events/types/llm_events.py

@@ -84,3 +84,4 @@ class LLMStreamChunkEvent(LLMEventBase):
     chunk: str
     tool_call: ToolCall | None = None
     call_type: LLMCallType | None = None
+    response_id: str | None = None

lib/crewai/src/crewai/llm.py

@@ -768,6 +768,10 @@ class LLM(BaseLLM):
 
                 # Extract content from the chunk
                 chunk_content = None
+                response_id = None
+
+                if hasattr(chunk,'id'):
+                    response_id = chunk.id
 
                 # Safely extract content from various chunk formats
                 try:
@@ -823,6 +827,7 @@ class LLM(BaseLLM):
                                         available_functions=available_functions,
                                         from_task=from_task,
                                         from_agent=from_agent,
+                                        response_id=response_id
                                     )
 
                                     if result is not None:
@@ -844,6 +849,7 @@ class LLM(BaseLLM):
                             from_task=from_task,
                             from_agent=from_agent,
                             call_type=LLMCallType.LLM_CALL,
+                            response_id=response_id
                         ),
                     )
             # --- 4) Fallback to non-streaming if no content received
@@ -1021,6 +1027,7 @@ class LLM(BaseLLM):
         available_functions: dict[str, Any] | None = None,
         from_task: Task | None = None,
         from_agent: Agent | None = None,
+        response_id: str | None = None,
     ) -> Any:
         for tool_call in tool_calls:
             current_tool_accumulator = accumulated_tool_args[tool_call.index]
@@ -1041,6 +1048,7 @@ class LLM(BaseLLM):
                     from_task=from_task,
                     from_agent=from_agent,
                     call_type=LLMCallType.TOOL_CALL,
+                    response_id=response_id
                 ),
             )
 
@@ -1402,11 +1410,13 @@ class LLM(BaseLLM):
 
         params["stream"] = True
         params["stream_options"] = {"include_usage": True}
+        response_id = None
 
         try:
             async for chunk in await litellm.acompletion(**params):
                 chunk_count += 1
                 chunk_content = None
+                response_id = chunk.id if hasattr(chunk, "id") else None
 
                 try:
                     choices = None
@@ -1466,6 +1476,7 @@ class LLM(BaseLLM):
                             chunk=chunk_content,
                             from_task=from_task,
                             from_agent=from_agent,
+                            response_id=response_id
                         ),
                     )
 
@@ -1503,6 +1514,7 @@ class LLM(BaseLLM):
                         available_functions=available_functions,
                         from_task=from_task,
                         from_agent=from_agent,
+                        response_id=response_id,
                     )
                     if result is not None:
                         return result

lib/crewai/src/crewai/llms/base_llm.py

@@ -404,6 +404,7 @@ class BaseLLM(ABC):
         from_agent: Agent | None = None,
         tool_call: dict[str, Any] | None = None,
         call_type: LLMCallType | None = None,
+        response_id: str | None = None
     ) -> None:
         """Emit stream chunk event.
 
@@ -413,6 +414,7 @@ class BaseLLM(ABC):
             from_agent: The agent that initiated the call.
             tool_call: Tool call information if this is a tool call chunk.
             call_type: The type of LLM call (LLM_CALL or TOOL_CALL).
+            response_id: Unique ID for a particular LLM response, chunks have same response_id.
         """
         if not hasattr(crewai_event_bus, "emit"):
             raise ValueError("crewai_event_bus does not have an emit method") from None
@@ -425,6 +427,7 @@ class BaseLLM(ABC):
                 from_task=from_task,
                 from_agent=from_agent,
                 call_type=call_type,
+                response_id=response_id
             ),
         )
 

lib/crewai/src/crewai/llms/providers/anthropic/completion.py

@@ -700,7 +700,11 @@ class AnthropicCompletion(BaseLLM):
 
         # Make streaming API call
         with self.client.messages.stream(**stream_params) as stream:
+            response_id = None
             for event in stream:
+                if hasattr(event, "message") and hasattr(event.message, "id"):
+                    response_id = event.message.id
+                
                 if hasattr(event, "delta") and hasattr(event.delta, "text"):
                     text_delta = event.delta.text
                     full_response += text_delta
@@ -708,6 +712,7 @@ class AnthropicCompletion(BaseLLM):
                         chunk=text_delta,
                         from_task=from_task,
                         from_agent=from_agent,
+                        response_id=response_id
                     )
 
                 if event.type == "content_block_start":
@@ -734,6 +739,7 @@ class AnthropicCompletion(BaseLLM):
                                 "index": block_index,
                             },
                             call_type=LLMCallType.TOOL_CALL,
+                            response_id=response_id
                         )
                 elif event.type == "content_block_delta":
                     if event.delta.type == "input_json_delta":
@@ -757,6 +763,7 @@ class AnthropicCompletion(BaseLLM):
                                     "index": block_index,
                                 },
                                 call_type=LLMCallType.TOOL_CALL,
+                                response_id=response_id
                             )
 
             final_message: Message = stream.get_final_message()
@@ -1114,7 +1121,11 @@ class AnthropicCompletion(BaseLLM):
         current_tool_calls: dict[int, dict[str, Any]] = {}
 
         async with self.async_client.messages.stream(**stream_params) as stream:
+            response_id = None
             async for event in stream:
+                if hasattr(event, "message") and hasattr(event.message, "id"):
+                    response_id = event.message.id
+
                 if hasattr(event, "delta") and hasattr(event.delta, "text"):
                     text_delta = event.delta.text
                     full_response += text_delta
@@ -1122,6 +1133,7 @@ class AnthropicCompletion(BaseLLM):
                         chunk=text_delta,
                         from_task=from_task,
                         from_agent=from_agent,
+                        response_id=response_id
                     )
 
                 if event.type == "content_block_start":
@@ -1148,6 +1160,7 @@ class AnthropicCompletion(BaseLLM):
                                 "index": block_index,
                             },
                             call_type=LLMCallType.TOOL_CALL,
+                            response_id=response_id
                         )
                 elif event.type == "content_block_delta":
                     if event.delta.type == "input_json_delta":
@@ -1171,6 +1184,7 @@ class AnthropicCompletion(BaseLLM):
                                     "index": block_index,
                                 },
                                 call_type=LLMCallType.TOOL_CALL,
+                                response_id=response_id
                             )
 
             final_message: Message = await stream.get_final_message()

lib/crewai/src/crewai/llms/providers/azure/completion.py

@@ -726,6 +726,7 @@ class AzureCompletion(BaseLLM):
         """
         if update.choices:
             choice = update.choices[0]
+            response_id = update.id if hasattr(update,"id") else None
             if choice.delta and choice.delta.content:
                 content_delta = choice.delta.content
                 full_response += content_delta
@@ -733,6 +734,7 @@ class AzureCompletion(BaseLLM):
                     chunk=content_delta,
                     from_task=from_task,
                     from_agent=from_agent,
+                    response_id=response_id
                 )
 
             if choice.delta and choice.delta.tool_calls:
@@ -767,6 +769,7 @@ class AzureCompletion(BaseLLM):
                             "index": idx,
                         },
                         call_type=LLMCallType.TOOL_CALL,
+                        response_id=response_id
                     )
 
         return full_response

lib/crewai/src/crewai/llms/providers/bedrock/completion.py

@@ -736,6 +736,7 @@ class BedrockCompletion(BaseLLM):
             )
 
             stream = response.get("stream")
+            response_id = None
             if stream:
                 for event in stream:
                     if "messageStart" in event:
@@ -767,6 +768,7 @@ class BedrockCompletion(BaseLLM):
                                     "index": tool_use_index,
                                 },
                                 call_type=LLMCallType.TOOL_CALL,
+                                response_id=response_id,
                             )
                         logging.debug(
                             f"Tool use started in stream: {json.dumps(current_tool_use)} (ID: {tool_use_id})"
@@ -782,6 +784,7 @@ class BedrockCompletion(BaseLLM):
                                 chunk=text_chunk,
                                 from_task=from_task,
                                 from_agent=from_agent,
+                                response_id=response_id,
                             )
                         elif "toolUse" in delta and current_tool_use:
                             tool_input = delta["toolUse"].get("input", "")
@@ -802,6 +805,7 @@ class BedrockCompletion(BaseLLM):
                                         "index": tool_use_index,
                                     },
                                     call_type=LLMCallType.TOOL_CALL,
+                                    response_id=response_id
                                 )
                     elif "contentBlockStop" in event:
                         logging.debug("Content block stopped in stream")
@@ -1122,6 +1126,7 @@ class BedrockCompletion(BaseLLM):
             )
 
             stream = response.get("stream")
+            response_id = None
             if stream:
                 async for event in stream:
                     if "messageStart" in event:
@@ -1153,6 +1158,7 @@ class BedrockCompletion(BaseLLM):
                                     "index": tool_use_index,
                                 },
                                 call_type=LLMCallType.TOOL_CALL,
+                                response_id=response_id,
                             )
                             logging.debug(
                                 f"Tool use started in stream: {current_tool_use.get('name')} (ID: {tool_use_id})"
@@ -1168,6 +1174,7 @@ class BedrockCompletion(BaseLLM):
                                 chunk=text_chunk,
                                 from_task=from_task,
                                 from_agent=from_agent,
+                                response_id=response_id
                             )
                         elif "toolUse" in delta and current_tool_use:
                             tool_input = delta["toolUse"].get("input", "")
@@ -1188,6 +1195,7 @@ class BedrockCompletion(BaseLLM):
                                         "index": tool_use_index,
                                     },
                                     call_type=LLMCallType.TOOL_CALL,
+                                    response_id=response_id,
                                 )
 
                     elif "contentBlockStop" in event:

lib/crewai/src/crewai/llms/providers/gemini/completion.py

@@ -790,6 +790,7 @@ class GeminiCompletion(BaseLLM):
         Returns:
             Tuple of (updated full_response, updated function_calls, updated usage_data)
         """
+        response_id=chunk.response_id if hasattr(chunk,"response_id") else None
         if chunk.usage_metadata:
             usage_data = self._extract_token_usage(chunk)
 
@@ -799,6 +800,7 @@ class GeminiCompletion(BaseLLM):
                 chunk=chunk.text,
                 from_task=from_task,
                 from_agent=from_agent,
+                response_id=response_id
             )
 
         if chunk.candidates:
@@ -835,6 +837,7 @@ class GeminiCompletion(BaseLLM):
                                 "index": call_index,
                             },
                             call_type=LLMCallType.TOOL_CALL,
+                            response_id=response_id
                         )
 
         return full_response, function_calls, usage_data

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -1047,8 +1047,12 @@ class OpenAICompletion(BaseLLM):
         final_response: Response | None = None
 
         stream = self.client.responses.create(**params)
+        response_id_stream = None
 
         for event in stream:
+            if event.type == "response.created":
+                response_id_stream = event.response.id
+
             if event.type == "response.output_text.delta":
                 delta_text = event.delta or ""
                 full_response += delta_text
@@ -1056,6 +1060,7 @@ class OpenAICompletion(BaseLLM):
                     chunk=delta_text,
                     from_task=from_task,
                     from_agent=from_agent,
+                    response_id=response_id_stream
                 )
 
             elif event.type == "response.function_call_arguments.delta":
@@ -1170,8 +1175,12 @@ class OpenAICompletion(BaseLLM):
         final_response: Response | None = None
 
         stream = await self.async_client.responses.create(**params)
+        response_id_stream = None
 
         async for event in stream:
+            if event.type == "response.created":
+                response_id_stream = event.response.id
+
             if event.type == "response.output_text.delta":
                 delta_text = event.delta or ""
                 full_response += delta_text
@@ -1179,6 +1188,7 @@ class OpenAICompletion(BaseLLM):
                     chunk=delta_text,
                     from_task=from_task,
                     from_agent=from_agent,
+                    response_id=response_id_stream,
                 )
 
             elif event.type == "response.function_call_arguments.delta":
@@ -1699,6 +1709,8 @@ class OpenAICompletion(BaseLLM):
                 **parse_params, response_format=response_model
             ) as stream:
                 for chunk in stream:
+                    response_id_stream=chunk.id if hasattr(chunk,"id") else None
+
                     if chunk.type == "content.delta":
                         delta_content = chunk.delta
                         if delta_content:
@@ -1706,6 +1718,7 @@ class OpenAICompletion(BaseLLM):
                                 chunk=delta_content,
                                 from_task=from_task,
                                 from_agent=from_agent,
+                                response_id=response_id_stream
                             )
 
                 final_completion = stream.get_final_completion()
@@ -1735,6 +1748,8 @@ class OpenAICompletion(BaseLLM):
         usage_data = {"total_tokens": 0}
 
         for completion_chunk in completion_stream:
+            response_id_stream=completion_chunk.id if hasattr(completion_chunk,"id") else None
+
             if hasattr(completion_chunk, "usage") and completion_chunk.usage:
                 usage_data = self._extract_openai_token_usage(completion_chunk)
                 continue
@@ -1751,6 +1766,7 @@ class OpenAICompletion(BaseLLM):
                     chunk=chunk_delta.content,
                     from_task=from_task,
                     from_agent=from_agent,
+                    response_id=response_id_stream
                 )
 
             if chunk_delta.tool_calls:
@@ -1789,6 +1805,7 @@ class OpenAICompletion(BaseLLM):
                             "index": tool_calls[tool_index]["index"],
                         },
                         call_type=LLMCallType.TOOL_CALL,
+                        response_id=response_id_stream
                     )
 
         self._track_token_usage_internal(usage_data)
@@ -2000,6 +2017,8 @@ class OpenAICompletion(BaseLLM):
             accumulated_content = ""
             usage_data = {"total_tokens": 0}
             async for chunk in completion_stream:
+                response_id_stream=chunk.id if hasattr(chunk,"id") else None
+
                 if hasattr(chunk, "usage") and chunk.usage:
                     usage_data = self._extract_openai_token_usage(chunk)
                     continue
@@ -2016,6 +2035,7 @@ class OpenAICompletion(BaseLLM):
                         chunk=delta.content,
                         from_task=from_task,
                         from_agent=from_agent,
+                        response_id=response_id_stream
                     )
 
             self._track_token_usage_internal(usage_data)
@@ -2051,6 +2071,8 @@ class OpenAICompletion(BaseLLM):
         usage_data = {"total_tokens": 0}
 
         async for chunk in stream:
+            response_id_stream=chunk.id if hasattr(chunk,"id") else None
+
             if hasattr(chunk, "usage") and chunk.usage:
                 usage_data = self._extract_openai_token_usage(chunk)
                 continue
@@ -2067,6 +2089,7 @@ class OpenAICompletion(BaseLLM):
                     chunk=chunk_delta.content,
                     from_task=from_task,
                     from_agent=from_agent,
+                    response_id=response_id_stream
                 )
 
             if chunk_delta.tool_calls:
@@ -2105,6 +2128,7 @@ class OpenAICompletion(BaseLLM):
                             "index": tool_calls[tool_index]["index"],
                         },
                         call_type=LLMCallType.TOOL_CALL,
+                        response_id=response_id_stream
                     )
 
         self._track_token_usage_internal(usage_data)

lib/crewai/tests/llms/openai/test_openai.py

@@ -511,10 +511,13 @@ def test_openai_streaming_with_response_model():
         mock_chunk1 = MagicMock()
         mock_chunk1.type = "content.delta"
         mock_chunk1.delta = '{"answer": "test", '
+        mock_chunk1.id = "response-1"
 
+        # Second chunk
         mock_chunk2 = MagicMock()
         mock_chunk2.type = "content.delta"
         mock_chunk2.delta = '"confidence": 0.95}'
+        mock_chunk2.id = "response-2"
 
         # Create mock final completion with parsed result
         mock_parsed = TestResponse(answer="test", confidence=0.95)

lib/crewai/tests/utilities/test_events.py

@@ -984,8 +984,8 @@ def test_streaming_fallback_to_non_streaming():
     def mock_call(messages, tools=None, callbacks=None, available_functions=None):
         nonlocal fallback_called
         # Emit a couple of chunks to simulate partial streaming
-        crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 1"))
+        crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 1", response_id = "Id"))
-        crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 2"))
+        crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 2", response_id = "Id"))
 
         # Mark that fallback would be called
         fallback_called = True
@@ -1041,7 +1041,7 @@ def test_streaming_empty_response_handling():
     def mock_call(messages, tools=None, callbacks=None, available_functions=None):
         # Emit a few empty chunks
         for _ in range(3):
-            crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk=""))
+            crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="",response_id="id"))
 
         # Return the default message for empty responses
         return "I apologize, but I couldn't generate a proper response. Please try again or rephrase your request."