# MemoryBear v0.2.10 Community Release Notes — Forging the Blade

[keeees]

Release Date: April 8, 2026 | Codename: LianJian (炼剑 · Forging the Blade)

MemoryBear v0.2.10 Community Edition delivers a comprehensive set of workflow enhancements, deeper memory capabilities, and critical stability fixes. This release introduces deep thinking mode for Agents, form-based workflow interactions, and multimodal memory reading — sharpening the platform for real-world production use.

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🚀 I. Core Upgrade Overview

1. Workflow Engine Enhancements

• Session Variable File Support: Workflow session variables now support file-type values with configurable defaults, supporting both local and remote file sources. This enables richer data passing between workflow nodes.
• List Operation Node: A new dedicated node for list manipulation operations, allowing workflows to process, filter, and transform array data natively without custom code.
• Template Conversion HTML Support: The template conversion node now supports HTML output, expanding rendering capabilities for rich-content workflows.
• Form Return & Submission: Workflows can now return interactive form definitions to the conversation UI, and the frontend supports form submission back into the workflow — enabling structured data collection mid-conversation.
• HTTP Node XML Response: The workflow HTTP request node now supports XML format responses, broadening integration compatibility with legacy and enterprise APIs.
• Opening Remarks & File References: Workflow conversations now support configurable opening remarks and the ability to reference attached files, improving the guided conversation experience.
• Template Conversion Three-Level Variables: Template conversion nodes now support three-level nested variable access, enabling more complex data extraction from deeply structured objects.
• Node Connection Add Button: Workflow canvas node connections now include an inline add button, making it easier to insert new nodes between existing connections.

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2. Agent Intelligence 🧠

• Agent Deep Thinking Mode: Agents now support a deep thinking mode that enables more thorough reasoning before responding. This produces higher-quality answers for complex queries at the cost of additional processing time.
• Model Deep Thinking Feature Toggle: A new model-level feature flag indicates whether a model supports deep thinking, along with a toggle to enable or disable it per application. This gives fine-grained control over reasoning behavior.

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3. Memory System Upgrades 📚

• User Memory Pagination: The user memory library now supports pagination, improving performance and usability when browsing large memory collections.
• RAG User Memory Data Structure Refresh: The RAG user memory backend API data structures have been redesigned to align with the latest UI requirements, providing cleaner and more consistent data contracts.
• Multimodal Memory Reading: The memory system now supports reading multimodal memory entries, enabling retrieval of image, audio, and other non-text memory content.
• Semantic Pruning Threshold Hints: The memory extraction smart semantic pruning threshold now displays descriptive range labels, making it easier to understand and configure the sensitivity of pruning behavior.

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4. Frontend & Usability 🎨

• Skill Tool Deletion Status Display: The frontend skill library tool list now displays deletion status indicators, providing clear visibility into which tools have been removed.
• Dashboard Day-over-Day Comparison: Total memory capacity, application count, knowledge base count, and API call metrics now include "compared to yesterday" data, enabling quick trend analysis on the home dashboard.

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5. Robustness & Bug Fixes 🔧

• Parameter Extraction Null Handling: Fixed an issue where the parameter extraction node would throw exceptions when processing empty or null values. The node now handles missing data gracefully.
• Token Consumption Display Optimization: Improved the token consumption extraction and display for certain models, ensuring accurate usage reporting across different LLM providers.
• Model Parameter Negative Value Fix: Fixed unclear parameter range definitions in single-Agent model settings where negative values were ambiguously allowed or disallowed.
• App Share Deletion Sync: When a user deletes a previously shared application, the is_active field in the app_shares table now correctly updates for all share records, not just the source application entry.
• Memory Write Task Ordering: Fixed write_message task execution for the same user to respect chronological order. Single end_user tasks now execute sequentially by timestamp while multiple end_user tasks process concurrently.
• Multimodal Model Missing Graceful Handling: When no matching multimodal model is configured in memory settings, perceptual memory writes from workflow experience sharing no longer break mid-process. The system now handles the missing model gracefully.
• Custom Tool Number Variable Pass-through: Custom tools with number type parameters now correctly accept and pass through preceding variable values, resolving type coercion issues.
• Cluster Sub-Agent Display After Save: Fixed a bug where sub-agents in cluster configurations were not reflected in the UI after saving.
• Memory-Enabled Streaming Output Fix: Resolved a streaming output failure that occurred when memory was enabled, caused by a string serialization issue in the output pipeline.

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🧭 Looking Ahead

MemoryBear v0.2.10 represents a significant step toward production maturity. The combination of deep thinking capabilities, interactive form workflows, and multimodal memory reading demonstrates the platform's evolution from a memory storage system into a comprehensive cognitive infrastructure. Each fix in this release was driven by real-world production usage, hardening the system against edge cases that only surface at scale.

The introduction of Agent deep thinking mode and the expanded workflow engine capabilities signal a clear trajectory: MemoryBear is becoming not just a memory layer, but an intelligent orchestration platform where memory, reasoning, and interaction converge. The SaaS management backend additions further position the platform for multi-tenant enterprise deployments.

We are excited for the upcoming v0.3.0 release on April 17, which will mark a major milestone for the platform. Expect deeper agent reasoning capabilities, expanded multi-agent collaboration features, and further refinements to the memory intelligence pipeline. The blade has been forged — now it's time to wield it.

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MemoryBear v0.2.10 社区版 发布说明 —— 百炼成锋

发布日期： 2026年4月8日 ｜ 版本代号： 炼剑（LianJian · Forging the Blade）

MemoryBear v0.2.10 社区版带来了全面的工作流增强、更深层的记忆能力以及关键的稳定性修复。本版本引入了 Agent 深度思考模式、表单交互式工作流与多模态记忆读取——磨砺平台锋芒，为真实生产环境做好准备。

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🚀 一、核心升级概览

1. 工作流引擎增强

• 会话变量文件格式支持：工作流会话变量现已支持文件类型值，可配置默认值，支持本地和远程文件源，实现节点间更丰富的数据传递。
• 列表操作节点：新增专用列表操作节点，支持工作流中原生处理、过滤和转换数组数据，无需自定义代码。
• 模板转换支持 HTML：模板转换节点现已支持 HTML 输出，扩展了富内容工作流的渲染能力。
• 表单返回与提交：工作流现可向对话界面返回交互式表单定义，前端支持将表单数据提交回工作流——实现对话中的结构化数据采集。
• HTTP 节点 XML 响应：工作流 HTTP 请求节点现已支持 XML 格式响应，拓宽了与传统及企业级 API 的集成兼容性。
• 开场白与文件引用：工作流对话现支持可配置的开场白及附件文件引用功能，提升引导式对话体验。
• 模板转换三级变量：模板转换节点现支持三级嵌套变量访问，可从深层结构化对象中提取复杂数据。
• 节点连线添加按钮：工作流画布节点连线处新增内联添加按钮，便于在已有连接之间插入新节点。

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2. Agent 智能 🧠

• Agent 深度思考模式：Agent 现支持深度思考模式，在回复前进行更充分的推理。对于复杂查询可产出更高质量的回答，代价是额外的处理时间。
• 模型深度思考特性开关：新增模型级特性标识，标明模型是否支持深度思考，并提供应用级开关控制。实现对推理行为的精细化管理。

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3. 记忆系统升级 📚

• 用户记忆库分页：用户记忆库现已支持分页浏览，提升大规模记忆集合的性能和可用性。
• RAG 用户记忆数据结构刷新：RAG 用户记忆后端 API 数据结构已重新设计，与最新 UI 需求对齐，提供更清晰一致的数据契约。
• 多模态记忆读取：记忆系统现支持读取多模态记忆条目，可检索图像、音频等非文本记忆内容。
• 语义剪枝阈值提示文案：记忆萃取智能语义剪枝阈值现显示描述性区间标签，便于理解和配置剪枝灵敏度。

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4. 前端与体验 🎨

• 技能工具删除状态展示：前端技能库工具列表现显示删除状态标识，清晰展示哪些工具已被移除。
• 仪表盘日环比数据：总记忆容量、应用数量、知识库数量及 API 调用次数指标现包含"与昨日相比"数据，支持首页仪表盘的快速趋势分析。

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5. 稳健性与缺陷修复 🔧

• 参数提取空值处理：修复参数提取节点在处理空值或 null 值时抛出异常的问题，现已优雅处理缺失数据。
• Token 消耗展示优化：优化部分模型的 token 消耗提取与展示，确保不同 LLM 提供商的用量报告准确。
• 模型参数负值修复：修复单 Agent 模型参数设置中参数范围定义不明确、负值允许与否模糊的问题。
• 应用共享删除同步：用户删除已共享应用后，app_shares 表中的 is_active 字段现可正确更新所有共享记录，而非仅更新源应用条目。
• 记忆写入任务排序：修复同一用户的 write_message 任务执行顺序问题。单 end_user 任务现按时间戳顺序执行，多 end_user 任务并发处理。
• 多模态模型缺失优雅处理：当记忆配置中未配置对应的多模态模型时，工作流体验分享的感知记忆写入不再中断，系统现已优雅处理模型缺失情况。
• 自定义工具 Number 变量传递：number 类型参数的自定义工具现可正确接受和传递前置变量值，解决类型转换问题。
• 集群子代理保存后显示：修复集群配置中子代理保存后未在界面反显的问题。
• 记忆开启后流式输出修复：解决开启记忆后流式输出失败的问题，原因为输出管道中的字符串序列化问题。

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🧭 未来展望

MemoryBear v0.2.10 标志着平台向生产成熟度迈出的重要一步。深度思考能力、交互式表单工作流与多模态记忆读取的结合，展现了平台从记忆存储系统向综合认知基础设施的演进。本版本的每一项修复都源于真实生产环境的使用反馈，使系统在规模化运行中更加坚韧。

Agent 深度思考模式的引入与工作流引擎能力的扩展，指明了清晰的发展方向：MemoryBear 正在成为不仅仅是记忆层，而是记忆、推理与交互融合的智能编排平台。SaaS 管理后台的新增功能进一步为多租户企业级部署奠定基础。

我们期待 4 月 17 日即将到来的 v0.3.0 发布会，这将是平台的一个重要里程碑。届时将带来更深层的 Agent 推理能力、扩展的多智能体协作功能，以及记忆智能管线的进一步优化。剑已炼成，只待出鞘。

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