# SoloEngine v0.3.0 Release — Checkpoint Mechanism & Message Queue > Source: > Published: 2026-06-29 15:35:44+00:00 `ReActCore` introduces three checkpoints during streaming: `content_ended` (after text content), `before_tool_calls` (before tool calls), and `after_tool_calls` (after tool calls), enabling precise interception and state synchronization of the execution flow.`MessageQueue` class in `run.py` , supporting async enqueue, drain, and remove operations. Users can now queue messages while the LLM is running; queued messages are sent automatically after the current task completes. The frontend introduces a `QueueBar` component to display queued messages, with CSS spinning animation, single-line ellipsis, and hover-to-delete functionality.`MessageQueue.drain_all()` now merges consecutive messages with the same `name` into a single message, preventing fragmented user input when multiple queue entries share the same sender.`message_queued` , `queue_drained` , and `queue_returned` (`useRunWebSocket.ts` ). The frontend processes queue state updates in real time.`queue_returned` . Checkpoint stops cleanly clear the queue and automatically start the next message.`SystemMessage` type (with `notification` role) to separate error messages from assistant content. Errors are now rendered as independent notification bubbles, no longer embedded within assistant message cards.`ReActCore` initializes a `tiktoken` encoder on startup for real-time token counting during streaming. Unknown models fall back to `o200k_base` .`ModelManager` has been upgraded from `Select` to `AutoComplete` , allowing users to type custom model names not in the predefined list.`ToolCallsBlock` type (`message_block.py` ), unifying the internal tool-call format to an OpenAI-style `tool_calls` list, replacing the legacy `ToolUseBlock` .`_get_valid_token_value` to uniformly handle `None` /0/empty values from the API, preventing placeholder values from overwriting accumulated values.`react_core.py` refactored: each `ChatResponse` now contains only a single block type (`SoloTextBlock` or `SoloThinkingBlock` ), replacing the previous pattern of accumulating multiple blocks before yielding. This enables the frontend to precisely handle each type of incremental content.`LLMMessage[]` to `Message[]` (`LLMMessage | SystemMessage` ). `convertToLLMMessages` now splits system messages such as `error` into independent `SystemMessage` entries rather than reusing `LLMMessage` . Updated `MessageList` and `RunPanel` to render `SystemMessage` entries.`save_assistant_message` now follow the same code path. `error` is saved as an independent field and no longer written into the data block.`on_execution_done` now detects empty-collector scenarios (where `stream_callback` was never triggered) and automatically sets the status to `error` with detailed LLM failure output. This prevents false "completed" status during silent failures.`createNewSession` in `runPanelStore` now immediately inserts the new session into the `sessions` array, ensuring the UI reflects the new session without requiring a refresh.`isRunning` or `isWaitingReply` is true. The ENTER key now triggers send (queue) as long as the input has content, no longer blocked by `isRunning` state.`execution_start` now generates a new `msg_asst_${Date.now()}` ID, preventing React key conflicts when the queue drain triggers a new assistant message that would otherwise duplicate the previous message ID.`websocket_handler.py` has been significantly simplified, removing complex grace period and takeover logic. `RunContext` now owns its own event loop, and the WebSocket only acts as a transport layer with injected callbacks.`aclose()` closing the stream in `ReActCore` no longer raises `CancelledError` ; it is treated as a normal end (breaking out of the loop), avoiding misinterpreting expected stream closure as a cancellation error.`ToolCallEventManager` now uniformly sends tool-call events to the frontend through `tool_calls` blocks, removing the legacy `tool_use` block handling logic.`TruncatedFormatterBase` removed `token_counter` and `max_tokens` parameters along with dead code such as `_truncate` and `_count` ; the constructor is simplified to a no-arg empty implementation. `OpenAIChatFormatter` removed the `OpenAIMultiAgentFormatter` subclass.`anthropic_model.py` captures `input_tokens` in the `message_start` event and accumulated `output_tokens` in the `message_delta` event, resolving inaccurate token counts in Anthropic streaming responses.`_convert_openai_to_anthropic_messages` static method that converts OpenAI-format messages (`tool_calls` , `reasoning_content` ) to Anthropic format (`tool_use` , `thinking` ).`anthropic_model.py` and `qwen_model.py` now yield a separate `ChatResponse` for each `tool_call` , enabling precise handling on the frontend.`backend/SoloAgent/token_counter/` directory, including `__init__.py` , `openai_token_counter.py` , and `token_base.py` . The original functionality has been merged into `ReActCore` inline accumulation.`backend/SoloAgent/formatter/truncated_formatter_base.py` — removed from the exports in `__init__.py` ; the file is preserved but is no longer public API.`OpenAIMultiAgentFormatter` from `openai_formatter.py` .`ToolUseBlock` — the message block type was unified from `tool_use` to `tool_calls` ; the legacy `tool_use` type is no longer used.`_convert_anthropic_message_to_solo_format` function — removed a 99-line Anthropic→Solo format conversion function in `anthropic_model.py` , replaced by the new OpenAI→Anthropic conversion method.`reasoning_content` from content in `OpenAIChatFormatter` , and removed the compatibility code (with DEBUG logs) that forcibly added an empty `reasoning_content` to messages carrying `tool_calls` .`TruncatedFormatterBase._group_messages` now only checks `tool_calls` and `tool_result` types, removing `tool_use` compatibility code.`agent.reply` caught an exception and returned an error string, but `_execute_agent` treated the run as `completed` because the collector was empty. `on_execution_done` now checks `collector.get_chunk_count() > 0` and forces `status="error"` with the actual LLM error output.`content` blocks; they are rendered as independent `notification` -role messages with proper styling and status indicators.`tool_use` blocks in streaming responses, unifying to the `tool_calls` format.`OpenAIChatFormatter` adds filtering logic: when an assistant message has empty `content` and no `tool_calls` , it is skipped. This fixes the LLM API error "Input is a zero-length, empty document".`ChunkCollector._extract_raw_type` in `run.py` removed recognition of the `'tool_use'` type string, unifying the mapping to `'tool_calls'` .`aclose()` closing the stream in `react_core.py` no longer raises `CancelledError` ; it breaks out of the loop and is treated as a normal end, avoiding misinterpreting expected stream closure as a cancellation error.`aclose` in `react_core.py` , it is no longer converted to `asyncio.CancelledError` ; it breaks out of the loop and is treated as a normal end, avoiding misinterpreting expected stream closure as a cancellation error.`flow_compiler.py` adds new logic: immediately after creating the flow, check whether `cancel_event` is already set, and if so, cancel the flow right away, avoiding wasted HTTP connections.`flow_compiler.py` fixed a bug where an interrupted Agent incorrectly returned `"completed"` ; it now returns `"stop"` status. The `output` field is no longer filled with `error` , preventing error pollution of the output.`MessageList.tsx` unifies on the W3C Clipboard API, ensuring that Windows clipboard history (Win+V) is correctly captured; fixed the issue where clipboard history could not be triggered on Windows.We're looking for like-minded contributors who share our passion for SoloEngine and Agentic AI. Every contribution — from a typo fix to a full feature — makes SoloEngine better. 📝 [Contributing Guide](https://github.com/Sh4r1ock/SoloEngine/blob/main/CONTRIBUTING.md) · 💬 [Discussions](https://github.com/Sh4r1ock/SoloEngine/discussions) · 📧 [Contact Us](mailto:sh4r1ock@qq.com)