From cab621ac14f29cba5c67b9cbd7d7432bec2c74cc Mon Sep 17 00:00:00 2001 From: cthomas Date: Thu, 7 Aug 2025 13:17:36 -0700 Subject: [PATCH] feat: continue stream processing on client cancel (#3796) --- .../anthropic_streaming_interface.py | 556 ++--- .../interfaces/openai_streaming_interface.py | 516 ++--- poetry.lock | 1897 +++++++++-------- 3 files changed, 1536 insertions(+), 1433 deletions(-) diff --git a/letta/interfaces/anthropic_streaming_interface.py b/letta/interfaces/anthropic_streaming_interface.py index 82d9287f..2b167e23 100644 --- a/letta/interfaces/anthropic_streaming_interface.py +++ b/letta/interfaces/anthropic_streaming_interface.py @@ -126,271 +126,6 @@ class AnthropicStreamingInterface: logger.error("Error checking inner thoughts: %s", e) raise - async def process( - self, - stream: AsyncStream[BetaRawMessageStreamEvent], - ttft_span: Optional["Span"] = None, - ) -> AsyncGenerator[LettaMessage | LettaStopReason, None]: - prev_message_type = None - message_index = 0 - try: - async with stream: - async for event in stream: - # TODO: Support BetaThinkingBlock, BetaRedactedThinkingBlock - if isinstance(event, BetaRawContentBlockStartEvent): - content = event.content_block - - if isinstance(content, BetaTextBlock): - self.anthropic_mode = EventMode.TEXT - # TODO: Can capture citations, etc. - elif isinstance(content, BetaToolUseBlock): - self.anthropic_mode = EventMode.TOOL_USE - self.tool_call_id = content.id - self.tool_call_name = content.name - self.inner_thoughts_complete = False - - if not self.use_assistant_message: - # Buffer the initial tool call message instead of yielding immediately - tool_call_msg = ToolCallMessage( - id=self.letta_message_id, - tool_call=ToolCallDelta(name=self.tool_call_name, tool_call_id=self.tool_call_id), - date=datetime.now(timezone.utc).isoformat(), - ) - self.tool_call_buffer.append(tool_call_msg) - elif isinstance(content, BetaThinkingBlock): - self.anthropic_mode = EventMode.THINKING - # TODO: Can capture signature, etc. - elif isinstance(content, BetaRedactedThinkingBlock): - self.anthropic_mode = EventMode.REDACTED_THINKING - if prev_message_type and prev_message_type != "hidden_reasoning_message": - message_index += 1 - hidden_reasoning_message = HiddenReasoningMessage( - id=self.letta_message_id, - state="redacted", - hidden_reasoning=content.data, - date=datetime.now(timezone.utc).isoformat(), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - self.reasoning_messages.append(hidden_reasoning_message) - prev_message_type = hidden_reasoning_message.message_type - yield hidden_reasoning_message - - elif isinstance(event, BetaRawContentBlockDeltaEvent): - delta = event.delta - - if isinstance(delta, BetaTextDelta): - # Safety check - if not self.anthropic_mode == EventMode.TEXT: - raise RuntimeError( - f"Streaming integrity failed - received BetaTextDelta object while not in TEXT EventMode: {delta}" - ) - - # Combine buffer with current text to handle tags split across chunks - combined_text = self.partial_tag_buffer + delta.text - - # Remove all occurrences of tag - cleaned_text = combined_text.replace("", "") - - # Extract just the new content (without the buffer part) - if len(self.partial_tag_buffer) <= len(cleaned_text): - delta.text = cleaned_text[len(self.partial_tag_buffer) :] - else: - # Edge case: the tag was removed and now the text is shorter than the buffer - delta.text = "" - - # Store the last 10 characters (or all if less than 10) for the next chunk - # This is enough to catch " 10 else combined_text - self.accumulated_inner_thoughts.append(delta.text) - - if prev_message_type and prev_message_type != "reasoning_message": - message_index += 1 - reasoning_message = ReasoningMessage( - id=self.letta_message_id, - reasoning=self.accumulated_inner_thoughts[-1], - date=datetime.now(timezone.utc).isoformat(), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - self.reasoning_messages.append(reasoning_message) - prev_message_type = reasoning_message.message_type - yield reasoning_message - - elif isinstance(delta, BetaInputJSONDelta): - if not self.anthropic_mode == EventMode.TOOL_USE: - raise RuntimeError( - f"Streaming integrity failed - received BetaInputJSONDelta object while not in TOOL_USE EventMode: {delta}" - ) - - self.accumulated_tool_call_args += delta.partial_json - current_parsed = self.json_parser.parse(self.accumulated_tool_call_args) - - # Start detecting a difference in inner thoughts - previous_inner_thoughts = self.previous_parse.get(INNER_THOUGHTS_KWARG, "") - current_inner_thoughts = current_parsed.get(INNER_THOUGHTS_KWARG, "") - inner_thoughts_diff = current_inner_thoughts[len(previous_inner_thoughts) :] - - if inner_thoughts_diff: - if prev_message_type and prev_message_type != "reasoning_message": - message_index += 1 - reasoning_message = ReasoningMessage( - id=self.letta_message_id, - reasoning=inner_thoughts_diff, - date=datetime.now(timezone.utc).isoformat(), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - self.reasoning_messages.append(reasoning_message) - prev_message_type = reasoning_message.message_type - yield reasoning_message - - # Check if inner thoughts are complete - if so, flush the buffer - if not self.inner_thoughts_complete and self._check_inner_thoughts_complete(self.accumulated_tool_call_args): - self.inner_thoughts_complete = True - # Flush all buffered tool call messages - if len(self.tool_call_buffer) > 0: - if prev_message_type and prev_message_type != "tool_call_message": - message_index += 1 - - # Strip out the inner thoughts from the buffered tool call arguments before streaming - tool_call_args = "" - for buffered_msg in self.tool_call_buffer: - tool_call_args += buffered_msg.tool_call.arguments if buffered_msg.tool_call.arguments else "" - tool_call_args = tool_call_args.replace(f'"{INNER_THOUGHTS_KWARG}": "{current_inner_thoughts}"', "") - - tool_call_msg = ToolCallMessage( - id=self.tool_call_buffer[0].id, - otid=Message.generate_otid_from_id(self.tool_call_buffer[0].id, message_index), - date=self.tool_call_buffer[0].date, - name=self.tool_call_buffer[0].name, - sender_id=self.tool_call_buffer[0].sender_id, - step_id=self.tool_call_buffer[0].step_id, - tool_call=ToolCallDelta( - name=self.tool_call_name, - tool_call_id=self.tool_call_id, - arguments=tool_call_args, - ), - ) - prev_message_type = tool_call_msg.message_type - yield tool_call_msg - self.tool_call_buffer = [] - - # Start detecting special case of "send_message" - if self.tool_call_name == DEFAULT_MESSAGE_TOOL and self.use_assistant_message: - previous_send_message = self.previous_parse.get(DEFAULT_MESSAGE_TOOL_KWARG, "") - current_send_message = current_parsed.get(DEFAULT_MESSAGE_TOOL_KWARG, "") - send_message_diff = current_send_message[len(previous_send_message) :] - - # Only stream out if it's not an empty string - if send_message_diff: - if prev_message_type and prev_message_type != "assistant_message": - message_index += 1 - assistant_msg = AssistantMessage( - id=self.letta_message_id, - content=[TextContent(text=send_message_diff)], - date=datetime.now(timezone.utc).isoformat(), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = assistant_msg.message_type - yield assistant_msg - else: - # Otherwise, it is a normal tool call - buffer or yield based on inner thoughts status - tool_call_msg = ToolCallMessage( - id=self.letta_message_id, - tool_call=ToolCallDelta( - name=self.tool_call_name, tool_call_id=self.tool_call_id, arguments=delta.partial_json - ), - date=datetime.now(timezone.utc).isoformat(), - ) - if self.inner_thoughts_complete: - if prev_message_type and prev_message_type != "tool_call_message": - message_index += 1 - tool_call_msg.otid = Message.generate_otid_from_id(self.letta_message_id, message_index) - prev_message_type = tool_call_msg.message_type - yield tool_call_msg - else: - self.tool_call_buffer.append(tool_call_msg) - - # Set previous parse - self.previous_parse = current_parsed - elif isinstance(delta, BetaThinkingDelta): - # Safety check - if not self.anthropic_mode == EventMode.THINKING: - raise RuntimeError( - f"Streaming integrity failed - received BetaThinkingBlock object while not in THINKING EventMode: {delta}" - ) - - if prev_message_type and prev_message_type != "reasoning_message": - message_index += 1 - reasoning_message = ReasoningMessage( - id=self.letta_message_id, - source="reasoner_model", - reasoning=delta.thinking, - date=datetime.now(timezone.utc).isoformat(), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - self.reasoning_messages.append(reasoning_message) - prev_message_type = reasoning_message.message_type - yield reasoning_message - elif isinstance(delta, BetaSignatureDelta): - # Safety check - if not self.anthropic_mode == EventMode.THINKING: - raise RuntimeError( - f"Streaming integrity failed - received BetaSignatureDelta object while not in THINKING EventMode: {delta}" - ) - - if prev_message_type and prev_message_type != "reasoning_message": - message_index += 1 - reasoning_message = ReasoningMessage( - id=self.letta_message_id, - source="reasoner_model", - reasoning="", - date=datetime.now(timezone.utc).isoformat(), - signature=delta.signature, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - self.reasoning_messages.append(reasoning_message) - prev_message_type = reasoning_message.message_type - yield reasoning_message - elif isinstance(event, BetaRawMessageStartEvent): - self.message_id = event.message.id - self.input_tokens += event.message.usage.input_tokens - self.output_tokens += event.message.usage.output_tokens - self.model = event.message.model - elif isinstance(event, BetaRawMessageDeltaEvent): - self.output_tokens += event.usage.output_tokens - elif isinstance(event, BetaRawMessageStopEvent): - # Don't do anything here! We don't want to stop the stream. - pass - elif isinstance(event, BetaRawContentBlockStopEvent): - # If we're exiting a tool use block and there are still buffered messages, - # we should flush them now - if self.anthropic_mode == EventMode.TOOL_USE and self.tool_call_buffer: - for buffered_msg in self.tool_call_buffer: - yield buffered_msg - self.tool_call_buffer = [] - - self.anthropic_mode = None - except asyncio.CancelledError as e: - import traceback - - logger.error("Cancelled stream %s: %s", e, traceback.format_exc()) - ttft_span.add_event( - name="stop_reason", - attributes={"stop_reason": StopReasonType.cancelled.value, "error": str(e), "stacktrace": traceback.format_exc()}, - ) - raise e - except Exception as e: - import traceback - - logger.error("Error processing stream: %s", e, traceback.format_exc()) - ttft_span.add_event( - name="stop_reason", - attributes={"stop_reason": StopReasonType.error.value, "error": str(e), "stacktrace": traceback.format_exc()}, - ) - yield LettaStopReason(stop_reason=StopReasonType.error) - raise e - finally: - logger.info("AnthropicStreamingInterface: Stream processing complete.") - def get_reasoning_content(self) -> list[TextContent | ReasoningContent | RedactedReasoningContent]: def _process_group( group: list[ReasoningMessage | HiddenReasoningMessage], group_type: str @@ -445,3 +180,294 @@ class AnthropicStreamingInterface: content.text = content.text[:cutoff] return merged + + async def process( + self, + stream: AsyncStream[BetaRawMessageStreamEvent], + ttft_span: Optional["Span"] = None, + ) -> AsyncGenerator[LettaMessage | LettaStopReason, None]: + prev_message_type = None + message_index = 0 + event = None + try: + async with stream: + async for event in stream: + try: + async for message in self._process_event(event, ttft_span, prev_message_type, message_index): + new_message_type = message.message_type + if new_message_type != prev_message_type: + if prev_message_type != None: + message_index += 1 + prev_message_type = new_message_type + yield message + except asyncio.CancelledError as e: + import traceback + + logger.info("Cancelled stream attempt but overriding %s: %s", e, traceback.format_exc()) + async for message in self._process_event(event, ttft_span, prev_message_type, message_index): + new_message_type = message.message_type + if new_message_type != prev_message_type: + if prev_message_type != None: + message_index += 1 + prev_message_type = new_message_type + yield message + + # Don't raise the exception here + continue + + except Exception as e: + import traceback + + logger.error("Error processing stream: %s", e, traceback.format_exc()) + ttft_span.add_event( + name="stop_reason", + attributes={"stop_reason": StopReasonType.error.value, "error": str(e), "stacktrace": traceback.format_exc()}, + ) + yield LettaStopReason(stop_reason=StopReasonType.error) + raise e + finally: + logger.info("AnthropicStreamingInterface: Stream processing complete.") + + async def _process_event( + self, + event: BetaRawMessageStreamEvent, + ttft_span: Optional["Span"] = None, + prev_message_type: Optional[str] = None, + message_index: int = 0, + ) -> AsyncGenerator[LettaMessage | LettaStopReason, None]: + """Process a single event from the Anthropic stream and yield any resulting messages. + + Args: + event: The event to process + + Yields: + Messages generated from processing this event + """ + if isinstance(event, BetaRawContentBlockStartEvent): + content = event.content_block + + if isinstance(content, BetaTextBlock): + self.anthropic_mode = EventMode.TEXT + # TODO: Can capture citations, etc. + elif isinstance(content, BetaToolUseBlock): + self.anthropic_mode = EventMode.TOOL_USE + self.tool_call_id = content.id + self.tool_call_name = content.name + self.inner_thoughts_complete = False + + if not self.use_assistant_message: + # Buffer the initial tool call message instead of yielding immediately + tool_call_msg = ToolCallMessage( + id=self.letta_message_id, + tool_call=ToolCallDelta(name=self.tool_call_name, tool_call_id=self.tool_call_id), + date=datetime.now(timezone.utc).isoformat(), + ) + self.tool_call_buffer.append(tool_call_msg) + elif isinstance(content, BetaThinkingBlock): + self.anthropic_mode = EventMode.THINKING + # TODO: Can capture signature, etc. + elif isinstance(content, BetaRedactedThinkingBlock): + self.anthropic_mode = EventMode.REDACTED_THINKING + if prev_message_type and prev_message_type != "hidden_reasoning_message": + message_index += 1 + hidden_reasoning_message = HiddenReasoningMessage( + id=self.letta_message_id, + state="redacted", + hidden_reasoning=content.data, + date=datetime.now(timezone.utc).isoformat(), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + self.reasoning_messages.append(hidden_reasoning_message) + prev_message_type = hidden_reasoning_message.message_type + yield hidden_reasoning_message + + elif isinstance(event, BetaRawContentBlockDeltaEvent): + delta = event.delta + + if isinstance(delta, BetaTextDelta): + # Safety check + if not self.anthropic_mode == EventMode.TEXT: + raise RuntimeError(f"Streaming integrity failed - received BetaTextDelta object while not in TEXT EventMode: {delta}") + + # Combine buffer with current text to handle tags split across chunks + combined_text = self.partial_tag_buffer + delta.text + + # Remove all occurrences of tag + cleaned_text = combined_text.replace("", "") + + # Extract just the new content (without the buffer part) + if len(self.partial_tag_buffer) <= len(cleaned_text): + delta.text = cleaned_text[len(self.partial_tag_buffer) :] + else: + # Edge case: the tag was removed and now the text is shorter than the buffer + delta.text = "" + + # Store the last 10 characters (or all if less than 10) for the next chunk + # This is enough to catch " 10 else combined_text + self.accumulated_inner_thoughts.append(delta.text) + + if prev_message_type and prev_message_type != "reasoning_message": + message_index += 1 + reasoning_message = ReasoningMessage( + id=self.letta_message_id, + reasoning=self.accumulated_inner_thoughts[-1], + date=datetime.now(timezone.utc).isoformat(), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + self.reasoning_messages.append(reasoning_message) + prev_message_type = reasoning_message.message_type + yield reasoning_message + + elif isinstance(delta, BetaInputJSONDelta): + if not self.anthropic_mode == EventMode.TOOL_USE: + raise RuntimeError( + f"Streaming integrity failed - received BetaInputJSONDelta object while not in TOOL_USE EventMode: {delta}" + ) + + self.accumulated_tool_call_args += delta.partial_json + current_parsed = self.json_parser.parse(self.accumulated_tool_call_args) + + # Start detecting a difference in inner thoughts + previous_inner_thoughts = self.previous_parse.get(INNER_THOUGHTS_KWARG, "") + current_inner_thoughts = current_parsed.get(INNER_THOUGHTS_KWARG, "") + inner_thoughts_diff = current_inner_thoughts[len(previous_inner_thoughts) :] + + if inner_thoughts_diff: + if prev_message_type and prev_message_type != "reasoning_message": + message_index += 1 + reasoning_message = ReasoningMessage( + id=self.letta_message_id, + reasoning=inner_thoughts_diff, + date=datetime.now(timezone.utc).isoformat(), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + self.reasoning_messages.append(reasoning_message) + prev_message_type = reasoning_message.message_type + yield reasoning_message + + # Check if inner thoughts are complete - if so, flush the buffer + if not self.inner_thoughts_complete and self._check_inner_thoughts_complete(self.accumulated_tool_call_args): + self.inner_thoughts_complete = True + # Flush all buffered tool call messages + if len(self.tool_call_buffer) > 0: + if prev_message_type and prev_message_type != "tool_call_message": + message_index += 1 + + # Strip out the inner thoughts from the buffered tool call arguments before streaming + tool_call_args = "" + for buffered_msg in self.tool_call_buffer: + tool_call_args += buffered_msg.tool_call.arguments if buffered_msg.tool_call.arguments else "" + tool_call_args = tool_call_args.replace(f'"{INNER_THOUGHTS_KWARG}": "{current_inner_thoughts}"', "") + + tool_call_msg = ToolCallMessage( + id=self.tool_call_buffer[0].id, + otid=Message.generate_otid_from_id(self.tool_call_buffer[0].id, message_index), + date=self.tool_call_buffer[0].date, + name=self.tool_call_buffer[0].name, + sender_id=self.tool_call_buffer[0].sender_id, + step_id=self.tool_call_buffer[0].step_id, + tool_call=ToolCallDelta( + name=self.tool_call_name, + tool_call_id=self.tool_call_id, + arguments=tool_call_args, + ), + ) + prev_message_type = tool_call_msg.message_type + yield tool_call_msg + self.tool_call_buffer = [] + + # Start detecting special case of "send_message" + if self.tool_call_name == DEFAULT_MESSAGE_TOOL and self.use_assistant_message: + previous_send_message = self.previous_parse.get(DEFAULT_MESSAGE_TOOL_KWARG, "") + current_send_message = current_parsed.get(DEFAULT_MESSAGE_TOOL_KWARG, "") + send_message_diff = current_send_message[len(previous_send_message) :] + + # Only stream out if it's not an empty string + if send_message_diff: + if prev_message_type and prev_message_type != "assistant_message": + message_index += 1 + assistant_msg = AssistantMessage( + id=self.letta_message_id, + content=[TextContent(text=send_message_diff)], + date=datetime.now(timezone.utc).isoformat(), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = assistant_msg.message_type + yield assistant_msg + else: + # Otherwise, it is a normal tool call - buffer or yield based on inner thoughts status + tool_call_msg = ToolCallMessage( + id=self.letta_message_id, + tool_call=ToolCallDelta(name=self.tool_call_name, tool_call_id=self.tool_call_id, arguments=delta.partial_json), + date=datetime.now(timezone.utc).isoformat(), + ) + if self.inner_thoughts_complete: + if prev_message_type and prev_message_type != "tool_call_message": + message_index += 1 + tool_call_msg.otid = Message.generate_otid_from_id(self.letta_message_id, message_index) + prev_message_type = tool_call_msg.message_type + yield tool_call_msg + else: + self.tool_call_buffer.append(tool_call_msg) + + # Set previous parse + self.previous_parse = current_parsed + elif isinstance(delta, BetaThinkingDelta): + # Safety check + if not self.anthropic_mode == EventMode.THINKING: + raise RuntimeError( + f"Streaming integrity failed - received BetaThinkingBlock object while not in THINKING EventMode: {delta}" + ) + + if prev_message_type and prev_message_type != "reasoning_message": + message_index += 1 + reasoning_message = ReasoningMessage( + id=self.letta_message_id, + source="reasoner_model", + reasoning=delta.thinking, + date=datetime.now(timezone.utc).isoformat(), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + self.reasoning_messages.append(reasoning_message) + prev_message_type = reasoning_message.message_type + yield reasoning_message + elif isinstance(delta, BetaSignatureDelta): + # Safety check + if not self.anthropic_mode == EventMode.THINKING: + raise RuntimeError( + f"Streaming integrity failed - received BetaSignatureDelta object while not in THINKING EventMode: {delta}" + ) + + if prev_message_type and prev_message_type != "reasoning_message": + message_index += 1 + reasoning_message = ReasoningMessage( + id=self.letta_message_id, + source="reasoner_model", + reasoning="", + date=datetime.now(timezone.utc).isoformat(), + signature=delta.signature, + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + self.reasoning_messages.append(reasoning_message) + prev_message_type = reasoning_message.message_type + yield reasoning_message + elif isinstance(event, BetaRawMessageStartEvent): + self.message_id = event.message.id + self.input_tokens += event.message.usage.input_tokens + self.output_tokens += event.message.usage.output_tokens + self.model = event.message.model + elif isinstance(event, BetaRawMessageDeltaEvent): + self.output_tokens += event.usage.output_tokens + elif isinstance(event, BetaRawMessageStopEvent): + # Don't do anything here! We don't want to stop the stream. + pass + elif isinstance(event, BetaRawContentBlockStopEvent): + # If we're exiting a tool use block and there are still buffered messages, + # we should flush them now + if self.anthropic_mode == EventMode.TOOL_USE and self.tool_call_buffer: + for buffered_msg in self.tool_call_buffer: + yield buffered_msg + self.tool_call_buffer = [] + + self.anthropic_mode = None diff --git a/letta/interfaces/openai_streaming_interface.py b/letta/interfaces/openai_streaming_interface.py index 656402f2..e00f4b96 100644 --- a/letta/interfaces/openai_streaming_interface.py +++ b/letta/interfaces/openai_streaming_interface.py @@ -120,260 +120,34 @@ class OpenAIStreamingInterface: tool_dicts = [tool["function"] if isinstance(tool, dict) and "function" in tool else tool for tool in self.tools] self.fallback_input_tokens += num_tokens_from_functions(tool_dicts) + prev_message_type = None + message_index = 0 try: async with stream: - prev_message_type = None - message_index = 0 async for chunk in stream: - if not self.model or not self.message_id: - self.model = chunk.model - self.message_id = chunk.id + try: + async for message in self._process_chunk(chunk, ttft_span, prev_message_type, message_index): + new_message_type = message.message_type + if new_message_type != prev_message_type: + if prev_message_type != None: + message_index += 1 + prev_message_type = new_message_type + yield message + except asyncio.CancelledError as e: + import traceback - # track usage - if chunk.usage: - self.input_tokens += chunk.usage.prompt_tokens - self.output_tokens += chunk.usage.completion_tokens + logger.info("Cancelled stream attempt but overriding %s: %s", e, traceback.format_exc()) + async for message in self._process_chunk(chunk, ttft_span, prev_message_type, message_index): + new_message_type = message.message_type + if new_message_type != prev_message_type: + if prev_message_type != None: + message_index += 1 + prev_message_type = new_message_type + yield message - if chunk.choices: - choice = chunk.choices[0] - message_delta = choice.delta + # Don't raise the exception here + continue - if message_delta.tool_calls is not None and len(message_delta.tool_calls) > 0: - tool_call = message_delta.tool_calls[0] - - if tool_call.function.name: - # If we're waiting for the first key, then we should hold back the name - # ie add it to a buffer instead of returning it as a chunk - if self.function_name_buffer is None: - self.function_name_buffer = tool_call.function.name - else: - self.function_name_buffer += tool_call.function.name - - if tool_call.id: - # Buffer until next time - if self.function_id_buffer is None: - self.function_id_buffer = tool_call.id - else: - self.function_id_buffer += tool_call.id - - if tool_call.function.arguments: - # updates_main_json, updates_inner_thoughts = self.function_args_reader.process_fragment(tool_call.function.arguments) - self.current_function_arguments += tool_call.function.arguments - updates_main_json, updates_inner_thoughts = self.function_args_reader.process_fragment( - tool_call.function.arguments - ) - - if self.is_openai_proxy: - self.fallback_output_tokens += count_tokens(tool_call.function.arguments) - - # If we have inner thoughts, we should output them as a chunk - if updates_inner_thoughts: - if prev_message_type and prev_message_type != "reasoning_message": - message_index += 1 - self.reasoning_messages.append(updates_inner_thoughts) - reasoning_message = ReasoningMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - reasoning=updates_inner_thoughts, - # name=name, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = reasoning_message.message_type - yield reasoning_message - - # Additionally inner thoughts may stream back with a chunk of main JSON - # In that case, since we can only return a chunk at a time, we should buffer it - if updates_main_json: - if self.function_args_buffer is None: - self.function_args_buffer = updates_main_json - else: - self.function_args_buffer += updates_main_json - - # If we have main_json, we should output a ToolCallMessage - elif updates_main_json: - - # If there's something in the function_name buffer, we should release it first - # NOTE: we could output it as part of a chunk that has both name and args, - # however the frontend may expect name first, then args, so to be - # safe we'll output name first in a separate chunk - if self.function_name_buffer: - - # use_assisitant_message means that we should also not release main_json raw, and instead should only release the contents of "message": "..." - if self.use_assistant_message and self.function_name_buffer == self.assistant_message_tool_name: - - # Store the ID of the tool call so allow skipping the corresponding response - if self.function_id_buffer: - self.prev_assistant_message_id = self.function_id_buffer - - else: - if prev_message_type and prev_message_type != "tool_call_message": - message_index += 1 - self.tool_call_name = str(self.function_name_buffer) - tool_call_msg = ToolCallMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - tool_call=ToolCallDelta( - name=self.function_name_buffer, - arguments=None, - tool_call_id=self.function_id_buffer, - ), - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = tool_call_msg.message_type - yield tool_call_msg - - # Record what the last function name we flushed was - self.last_flushed_function_name = self.function_name_buffer - if self.last_flushed_function_id is None: - self.last_flushed_function_id = self.function_id_buffer - # Clear the buffer - self.function_name_buffer = None - self.function_id_buffer = None - # Since we're clearing the name buffer, we should store - # any updates to the arguments inside a separate buffer - - # Add any main_json updates to the arguments buffer - if self.function_args_buffer is None: - self.function_args_buffer = updates_main_json - else: - self.function_args_buffer += updates_main_json - - # If there was nothing in the name buffer, we can proceed to - # output the arguments chunk as a ToolCallMessage - else: - # use_assistant_message means that we should also not release main_json raw, and instead should only release the contents of "message": "..." - if self.use_assistant_message and ( - self.last_flushed_function_name is not None - and self.last_flushed_function_name == self.assistant_message_tool_name - ): - # do an additional parse on the updates_main_json - if self.function_args_buffer: - updates_main_json = self.function_args_buffer + updates_main_json - self.function_args_buffer = None - - # Pretty gross hardcoding that assumes that if we're toggling into the keywords, we have the full prefix - match_str = '{"' + self.assistant_message_tool_kwarg + '":"' - if updates_main_json == match_str: - updates_main_json = None - - else: - # Some hardcoding to strip off the trailing "}" - if updates_main_json in ["}", '"}']: - updates_main_json = None - if updates_main_json and len(updates_main_json) > 0 and updates_main_json[-1:] == '"': - updates_main_json = updates_main_json[:-1] - - if not updates_main_json: - # early exit to turn into content mode - continue - - # There may be a buffer from a previous chunk, for example - # if the previous chunk had arguments but we needed to flush name - if self.function_args_buffer: - # In this case, we should release the buffer + new data at once - combined_chunk = self.function_args_buffer + updates_main_json - - if prev_message_type and prev_message_type != "assistant_message": - message_index += 1 - assistant_message = AssistantMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - content=combined_chunk, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = assistant_message.message_type - yield assistant_message - # Store the ID of the tool call so allow skipping the corresponding response - if self.function_id_buffer: - self.prev_assistant_message_id = self.function_id_buffer - # clear buffer - self.function_args_buffer = None - self.function_id_buffer = None - - else: - # If there's no buffer to clear, just output a new chunk with new data - # TODO: THIS IS HORRIBLE - # TODO: WE USE THE OLD JSON PARSER EARLIER (WHICH DOES NOTHING) AND NOW THE NEW JSON PARSER - # TODO: THIS IS TOTALLY WRONG AND BAD, BUT SAVING FOR A LARGER REWRITE IN THE NEAR FUTURE - parsed_args = self.optimistic_json_parser.parse(self.current_function_arguments) - - if parsed_args.get(self.assistant_message_tool_kwarg) and parsed_args.get( - self.assistant_message_tool_kwarg - ) != self.current_json_parse_result.get(self.assistant_message_tool_kwarg): - new_content = parsed_args.get(self.assistant_message_tool_kwarg) - prev_content = self.current_json_parse_result.get(self.assistant_message_tool_kwarg, "") - # TODO: Assumes consistent state and that prev_content is subset of new_content - diff = new_content.replace(prev_content, "", 1) - self.current_json_parse_result = parsed_args - if prev_message_type and prev_message_type != "assistant_message": - message_index += 1 - assistant_message = AssistantMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - content=diff, - # name=name, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = assistant_message.message_type - yield assistant_message - - # Store the ID of the tool call so allow skipping the corresponding response - if self.function_id_buffer: - self.prev_assistant_message_id = self.function_id_buffer - # clear buffers - self.function_id_buffer = None - else: - - # There may be a buffer from a previous chunk, for example - # if the previous chunk had arguments but we needed to flush name - if self.function_args_buffer: - # In this case, we should release the buffer + new data at once - combined_chunk = self.function_args_buffer + updates_main_json - if prev_message_type and prev_message_type != "tool_call_message": - message_index += 1 - tool_call_msg = ToolCallMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - tool_call=ToolCallDelta( - name=self.function_name_buffer, - arguments=combined_chunk, - tool_call_id=self.function_id_buffer, - ), - # name=name, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = tool_call_msg.message_type - yield tool_call_msg - # clear buffer - self.function_args_buffer = None - self.function_id_buffer = None - else: - # If there's no buffer to clear, just output a new chunk with new data - if prev_message_type and prev_message_type != "tool_call_message": - message_index += 1 - tool_call_msg = ToolCallMessage( - id=self.letta_message_id, - date=datetime.now(timezone.utc), - tool_call=ToolCallDelta( - name=None, - arguments=updates_main_json, - tool_call_id=self.function_id_buffer, - ), - # name=name, - otid=Message.generate_otid_from_id(self.letta_message_id, message_index), - ) - prev_message_type = tool_call_msg.message_type - yield tool_call_msg - self.function_id_buffer = None - except asyncio.CancelledError as e: - import traceback - - logger.error("Cancelled stream %s: %s", e, traceback.format_exc()) - ttft_span.add_event( - name="stop_reason", - attributes={"stop_reason": StopReasonType.cancelled.value, "error": str(e), "stacktrace": traceback.format_exc()}, - ) - raise e except Exception as e: import traceback @@ -386,3 +160,249 @@ class OpenAIStreamingInterface: raise e finally: logger.info("OpenAIStreamingInterface: Stream processing complete.") + + async def _process_chunk( + self, + chunk: ChatCompletionChunk, + ttft_span: Optional["Span"] = None, + prev_message_type: Optional[str] = None, + message_index: int = 0, + ) -> AsyncGenerator[LettaMessage | LettaStopReason, None]: + if not self.model or not self.message_id: + self.model = chunk.model + self.message_id = chunk.id + + # track usage + if chunk.usage: + self.input_tokens += chunk.usage.prompt_tokens + self.output_tokens += chunk.usage.completion_tokens + + if chunk.choices: + choice = chunk.choices[0] + message_delta = choice.delta + + if message_delta.tool_calls is not None and len(message_delta.tool_calls) > 0: + tool_call = message_delta.tool_calls[0] + + if tool_call.function.name: + # If we're waiting for the first key, then we should hold back the name + # ie add it to a buffer instead of returning it as a chunk + if self.function_name_buffer is None: + self.function_name_buffer = tool_call.function.name + else: + self.function_name_buffer += tool_call.function.name + + if tool_call.id: + # Buffer until next time + if self.function_id_buffer is None: + self.function_id_buffer = tool_call.id + else: + self.function_id_buffer += tool_call.id + + if tool_call.function.arguments: + # updates_main_json, updates_inner_thoughts = self.function_args_reader.process_fragment(tool_call.function.arguments) + self.current_function_arguments += tool_call.function.arguments + updates_main_json, updates_inner_thoughts = self.function_args_reader.process_fragment(tool_call.function.arguments) + + if self.is_openai_proxy: + self.fallback_output_tokens += count_tokens(tool_call.function.arguments) + + # If we have inner thoughts, we should output them as a chunk + if updates_inner_thoughts: + if prev_message_type and prev_message_type != "reasoning_message": + message_index += 1 + self.reasoning_messages.append(updates_inner_thoughts) + reasoning_message = ReasoningMessage( + id=self.letta_message_id, + date=datetime.now(timezone.utc), + reasoning=updates_inner_thoughts, + # name=name, + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = reasoning_message.message_type + yield reasoning_message + + # Additionally inner thoughts may stream back with a chunk of main JSON + # In that case, since we can only return a chunk at a time, we should buffer it + if updates_main_json: + if self.function_args_buffer is None: + self.function_args_buffer = updates_main_json + else: + self.function_args_buffer += updates_main_json + + # If we have main_json, we should output a ToolCallMessage + elif updates_main_json: + + # If there's something in the function_name buffer, we should release it first + # NOTE: we could output it as part of a chunk that has both name and args, + # however the frontend may expect name first, then args, so to be + # safe we'll output name first in a separate chunk + if self.function_name_buffer: + + # use_assisitant_message means that we should also not release main_json raw, and instead should only release the contents of "message": "..." + if self.use_assistant_message and self.function_name_buffer == self.assistant_message_tool_name: + + # Store the ID of the tool call so allow skipping the corresponding response + if self.function_id_buffer: + self.prev_assistant_message_id = self.function_id_buffer + + else: + if prev_message_type and prev_message_type != "tool_call_message": + message_index += 1 + self.tool_call_name = str(self.function_name_buffer) + tool_call_msg = ToolCallMessage( + id=self.letta_message_id, + date=datetime.now(timezone.utc), + tool_call=ToolCallDelta( + name=self.function_name_buffer, + arguments=None, + tool_call_id=self.function_id_buffer, + ), + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = tool_call_msg.message_type + yield tool_call_msg + + # Record what the last function name we flushed was + self.last_flushed_function_name = self.function_name_buffer + if self.last_flushed_function_id is None: + self.last_flushed_function_id = self.function_id_buffer + # Clear the buffer + self.function_name_buffer = None + self.function_id_buffer = None + # Since we're clearing the name buffer, we should store + # any updates to the arguments inside a separate buffer + + # Add any main_json updates to the arguments buffer + if self.function_args_buffer is None: + self.function_args_buffer = updates_main_json + else: + self.function_args_buffer += updates_main_json + + # If there was nothing in the name buffer, we can proceed to + # output the arguments chunk as a ToolCallMessage + else: + # use_assistant_message means that we should also not release main_json raw, and instead should only release the contents of "message": "..." + if self.use_assistant_message and ( + self.last_flushed_function_name is not None + and self.last_flushed_function_name == self.assistant_message_tool_name + ): + # do an additional parse on the updates_main_json + if self.function_args_buffer: + updates_main_json = self.function_args_buffer + updates_main_json + self.function_args_buffer = None + + # Pretty gross hardcoding that assumes that if we're toggling into the keywords, we have the full prefix + match_str = '{"' + self.assistant_message_tool_kwarg + '":"' + if updates_main_json == match_str: + updates_main_json = None + + else: + # Some hardcoding to strip off the trailing "}" + if updates_main_json in ["}", '"}']: + updates_main_json = None + if updates_main_json and len(updates_main_json) > 0 and updates_main_json[-1:] == '"': + updates_main_json = updates_main_json[:-1] + + if not updates_main_json: + # early exit to turn into content mode + pass + + # There may be a buffer from a previous chunk, for example + # if the previous chunk had arguments but we needed to flush name + if self.function_args_buffer: + # In this case, we should release the buffer + new data at once + combined_chunk = self.function_args_buffer + updates_main_json + + if prev_message_type and prev_message_type != "assistant_message": + message_index += 1 + assistant_message = AssistantMessage( + id=self.letta_message_id, + date=datetime.now(timezone.utc), + content=combined_chunk, + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = assistant_message.message_type + yield assistant_message + # Store the ID of the tool call so allow skipping the corresponding response + if self.function_id_buffer: + self.prev_assistant_message_id = self.function_id_buffer + # clear buffer + self.function_args_buffer = None + self.function_id_buffer = None + + else: + # If there's no buffer to clear, just output a new chunk with new data + # TODO: THIS IS HORRIBLE + # TODO: WE USE THE OLD JSON PARSER EARLIER (WHICH DOES NOTHING) AND NOW THE NEW JSON PARSER + # TODO: THIS IS TOTALLY WRONG AND BAD, BUT SAVING FOR A LARGER REWRITE IN THE NEAR FUTURE + parsed_args = self.optimistic_json_parser.parse(self.current_function_arguments) + + if parsed_args.get(self.assistant_message_tool_kwarg) and parsed_args.get( + self.assistant_message_tool_kwarg + ) != self.current_json_parse_result.get(self.assistant_message_tool_kwarg): + new_content = parsed_args.get(self.assistant_message_tool_kwarg) + prev_content = self.current_json_parse_result.get(self.assistant_message_tool_kwarg, "") + # TODO: Assumes consistent state and that prev_content is subset of new_content + diff = new_content.replace(prev_content, "", 1) + self.current_json_parse_result = parsed_args + if prev_message_type and prev_message_type != "assistant_message": + message_index += 1 + assistant_message = AssistantMessage( + id=self.letta_message_id, + date=datetime.now(timezone.utc), + content=diff, + # name=name, + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = assistant_message.message_type + yield assistant_message + + # Store the ID of the tool call so allow skipping the corresponding response + if self.function_id_buffer: + self.prev_assistant_message_id = self.function_id_buffer + # clear buffers + self.function_id_buffer = None + else: + + # There may be a buffer from a previous chunk, for example + # if the previous chunk had arguments but we needed to flush name + if self.function_args_buffer: + # In this case, we should release the buffer + new data at once + combined_chunk = self.function_args_buffer + updates_main_json + if prev_message_type and prev_message_type != "tool_call_message": + message_index += 1 + tool_call_msg = ToolCallMessage( + id=self.letta_message_id, + date=datetime.now(timezone.utc), + tool_call=ToolCallDelta( + name=self.function_name_buffer, + arguments=combined_chunk, + tool_call_id=self.function_id_buffer, + ), + # name=name, + otid=Message.generate_otid_from_id(self.letta_message_id, message_index), + ) + prev_message_type = tool_call_msg.message_type + yield tool_call_msg + # clear buffer + self.function_args_buffer = None + self.function_id_buffer = None + else: + # If there's no buffer to clear, just output a new chunk with new data + if prev_message_type and prev_message_type != "tool_call_message": + message_index += 1 + tool_call_msg = 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