MemoryBear v0.3.1 Community Release Notes — The Boundless

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MemoryBear v0.3.1 Community Release Notes — The Boundless

Release Date: April 22, 2026 | Codename: WuJing (无境 · The Boundless)

MemoryBear v0.3.1 Community Edition delivers a focused set of application-level improvements, memory API extensibility, and workflow reliability fixes. This release introduces model JSON output control, memory API key provisioning, enhanced workflow validation, and numerous UX refinements — dissolving boundaries between components and integrations to let capability flow freely.

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🚀 I. Core Upgrade Overview

1. Application & Model Enhancements

• Model Auto-Disable on Key Deletion: When all API keys for a model are deleted, the model is now automatically disabled, preventing runtime errors from keyless model references.
• Model JSON Formatted Output Toggle: Model JSON structured output can now be toggled on and off. The official JSON control parameter ensures more stable JSON output — critical for migrating legacy middleware workflows that depend on strict JSON formatting. Custom models also support JSON output configuration.
• Configuration Import with Override: Application configurations now support import-with-override, allowing users to replace the current configuration entirely from an exported file.
• Import Cleanup for Missing Resources: When importing an application, if a referenced tool does not exist, the tool node configuration is automatically cleared. Similarly, missing knowledge bases are cleaned up, preventing broken references in imported workflows.

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2. Memory API & Intelligence 📚

• Memory Read/Write API with End-User Key Provisioning: Memory read and write operations are now accessible via API, with support for creating end_user API keys and retrieving memory configuration API keys — enabling third-party integrations to interact with the memory layer directly.
• Memory Store API & Configuration Update: The memory store now exposes API endpoints for memory retrieval and configuration updates (with sequential interface support), providing programmatic control over memory settings.
• End-User Metadata Storage: A new storage scheme for end_user metadata has been implemented, allowing richer user context to be persisted alongside memory entries.

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3. Workflow & UX Improvements ⚙️

• Conversation History File Metadata: Conversation history file entries now include file size, file name, and specific type labels (experience sharing, working memory), providing richer context in chat history.
• Iteration Node Parallel Input Fix: Fixed an issue where iteration nodes did not correctly handle parallel input, restoring expected concurrent execution behavior.
• API Key Last Four Digits Display: API keys now display their last four characters across the platform (including knowledge base and memory engine keys), improving key identification without exposing full secrets.
• Condition Branch Multi-File Sub-Variables: Condition branch nodes in MemoryBear now support adding sub-variables to multi-file variable types, enabling more granular conditional logic.
• Agent Model Config Reset Endpoint: Added the missing backend API endpoint for the "Reset to Default" action in Agent model configuration, completing the frontend-backend contract.
• Three-Level Variable Keyboard Navigation: Three-level variable selectors in workflows now support keyboard up/down arrow navigation, improving the variable selection experience.
• Dynamic Tab Title for Applications: Opening a new application in MemoryBear's application management now dynamically sets the browser tab title to the application name, replacing the previous static "记忆熊" text.
• Variable Aggregator Three-Level Checkbox Fix: Fixed an issue where three-level variable checkboxes in the variable aggregator node did not behave correctly.
• Workflow Checklist Validation Enhancements: The workflow checklist now includes tool node required-tool validation and LLM node vision-enabled required-variable validation, catching configuration errors before execution.
• Variable Aggregator to Parameter Extractor Output: Fixed a bug where a parameter extractor node following a variable aggregator node could not access the aggregator's output variables.

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4. Knowledge Base & Performance ⚡

• Async Document Parsing & Graph Execution: Document upload parsing and graph processing in document_task now execute asynchronously, with increased thread counts for work-document and work-graph workers, significantly improving document ingestion throughput.

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5. Robustness & Bug Fixes 🔧

• Tool Node Raw Parameter Types: Tool nodes now send request parameters with their original values and types instead of converting everything to strings, fixing type mismatch issues in downstream tool integrations.
• Stale Frontend Resource Import Error: Resolved an issue where, after a frontend deployment, users with cached stale resources would encounter import errors when the system attempted to load outdated data chunks.
• Workflow Tool Node Required Validation: The workflow checklist now enforces that tool nodes have their required tool configured, and LLM nodes with vision enabled must have their vision variable set — preventing incomplete configurations from being published.

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🧭 Looking Ahead

MemoryBear v0.3.1 represents a pivotal moment in the platform's philosophical evolution — the dissolution of boundaries. Where previous releases built walls of capability, this release tears them down: SSO tenant management, subscription plan configuration, and workspace-scoped API key provisioning create a seamless fabric where identity, billing, and resource isolation coexist without friction. Every enhancement was driven by the demands of real-world enterprise adoption, yet guided by the vision that true power lies in openness.

The expanded memory API surface — with end-user key provisioning, metadata storage, and extraction pipeline tuning — signals MemoryBear's trajectory toward becoming an open, programmable memory infrastructure. Third-party systems can now interact with the memory layer as a service, not just as an embedded component. This shift from closed to open memory access is the philosophical core of this release: boundaries are illusions, and capability should flow like water.

Looking forward, we will deepen the SaaS management capabilities with usage analytics, billing integration, and tenant-level quota enforcement. The memory intelligence pipeline will continue to evolve with improved extraction accuracy, cross-memory reasoning, and adaptive forgetting strategies. Beyond boundaries, beyond limits — the boundless awaits.

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MemoryBear v0.3.1 社区版 发布说明 —— 无境

发布日期： 2026年4月22日 ｜ 版本代号： 无境（WuJing · The Boundless）

MemoryBear v0.3.1 社区版带来了一系列应用层改进、记忆 API 可扩展性提升和工作流可靠性修复。本版本引入了模型 JSON 输出控制、记忆 API Key 供给、增强的工作流校验以及众多体验优化——打破组件与集成之间的边界，使能力自由流动。

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🚀 一、核心升级概览

1. 应用与模型增强

• 模型 Key 全删后自动关闭：当模型的所有 API Key 被删除后，该模型将自动关闭，避免无 Key 模型引用导致的运行时错误。
• 模型 JSON 格式化输出开关：模型 JSON 结构化输出现可开关控制。官方 JSON 控制参数可确保更稳定的 JSON 输出——这对迁移依赖严格 JSON 格式的旧中台工作流至关重要，强制迁移会导致 JSON 格式报错。自定义模型同样支持 JSON 输出配置。
• 配置导入覆盖：应用配置现支持导入覆盖，用户可从导出文件完整替换当前配置。
• 导入时缺失资源清理：导入应用时，若引用的工具不存在，工具节点配置将自动清空；知识库不存在时同样清空，防止导入后出现断裂引用。

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2. 记忆 API 与智能 📚

• 记忆读写 API 与 End-User Key 供给：记忆读写操作现可通过 API 调用，支持创建 end_user API Key 和获取记忆配置 API Key——使第三方集成可直接与记忆层交互。
• 记忆库 API 与配置更新：记忆库现开放 API 端点，支持记忆检索和配置更新（提供顺序接口），提供对记忆设置的程序化控制。
• End-User 元数据存储：实现了 end_user 元数据的存储方案，允许更丰富的用户上下文与记忆条目一同持久化。

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3. 工作流与体验优化 ⚙️

• 会话历史文件元数据：会话历史文件条目现包含文件大小、文件名称和具体类型标签（体验分享、工作记忆），提供更丰富的聊天历史上下文。
• 迭代节点并行输入修复：修复迭代节点未正确处理并行输入的问题，恢复预期的并发执行行为。
• API Key 后四位展示：API Key 现在全平台展示后四位字符（包括知识库和记忆引擎 Key），在不暴露完整密钥的前提下便于识别。
• 条件分支多文件子变量：记忆熊中条件分支节点现支持为多文件变量类型添加子变量，实现更精细的条件逻辑。
• Agent 模型配置重置接口：补充了 Agent 模型配置"重置默认"操作缺失的后端 API 接口，完善前后端契约。
• 三级变量键盘导航：工作流中三级变量选择器现支持键盘上下箭头导航，提升变量选择体验。
• 应用标签页动态标题：在记忆熊应用管理中打开新应用时，浏览器标签页标题现动态显示应用名称，替代之前固定的"记忆熊"文本。
• 变量聚合三级勾选修复：修复变量聚合器节点中三级变量勾选行为不正确的问题。
• 工作流检查清单校验增强：工作流检查清单现包含工具节点必填工具校验和 LLM 节点视觉开启时视觉变量必填校验，在执行前捕获配置错误。
• 变量聚合器到参数提取器输出：修复参数提取器节点跟在变量聚合器节点后无法获取聚合器输出变量的问题。

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4. 知识库与性能 ⚡

• 文档解析与 Graph 异步执行：document_task 中的文档上传解析与 Graph 处理现异步执行，同时增加 work-document 和 work-graph 的线程数，显著提升文档摄入吞吐量。

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5. 稳健性与缺陷修复 🔧

• 工具节点原始参数类型：工具节点现以原始值及类型发送请求参数，而非全部转换为字符串，修复下游工具集成中的类型不匹配问题。
• 前端部署后资源过期导入错误：解决前端应用部署后，用户设备上缓存的过期资源在系统尝试导入旧数据块时导致导入错误的问题。
• 工作流工具节点必填校验：工作流检查清单现强制要求工具节点配置必填工具，LLM 节点开启视觉时必须设置视觉变量——防止不完整配置被发布。

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🧭 未来展望

MemoryBear v0.3.1 是平台哲学演进中的关键时刻——边界的打破。此前的版本构筑能力之墙，而本版本将其拆解：SSO 租户管理、套餐计划配置和空间级 API Key 供给编织出一张无缝的网络，身份认证、计费与资源隔离在其中和谐共存。每一项增强都源于真实企业落地的需求，却始终以"真正的力量在于开放"为指引。

记忆 API 能力的扩展——End-User Key 供给、元数据存储和萃取流水线调优——标志着 MemoryBear 正朝着开放、可编程的记忆基础设施方向演进。第三方系统现可将记忆层作为服务调用，而非仅作为嵌入式组件。从封闭到开放的记忆访问转变，正是本版本的哲学内核：边界皆为幻象，能力当如水般自由流动。

展望未来，我们将深化 SaaS 管理能力，引入用量分析、计费集成和租户级配额管控。记忆智能管线将持续演进，提升萃取精度、跨记忆推理和自适应遗忘策略。破界而行，臻于无境。

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