This latest Home Assistant Core patch brings important fixes to the HTTP configuration system, ensuring a smoother experience during upgrades. The migration of YAML-based HTTP settings now correctly avoids using the new default port 80 unless explicitly configured, preventing accidental exposure. Additionally, a safety check has been introduced to block changes to the HTTP configuration […]
What’s New Portainer CE 2.43.0 introduces a basic workflow details screen, giving you better visibility into your automation pipelines. The Environment Details view now shows GPU information, making it easier to track hardware resources. We’ve also made the setup token more prominent in installation logs to simplify initial configuration. Additionally, source, workflow, and artifact statuses
Fedora thrives on evolution, change, and innovation—not just in our open source technology, but also in how we nurture the community that builds it. As Fedora adapts to a shifting world, the roles that sustain it must evolve too. That includes the Fedora Community Architect position. Today, Justin and Shaun are excited to announce a
The latest n8n update, version 2.33.2, brings a targeted bug fix for self-hosted users relying on the AI Assistant node. Previously, the node could lose its sandbox provider selection, potentially causing workflows to run in unintended environments. This patch ensures that the chosen sandbox configuration stays preserved, maintaining consistent and secure execution for your automations.
n8n 2.33.2 Patch Fixes AI Assistant Sandbox Provider Setting Read More »
The latest build of llama.cpp brings a notable refinement to its computation graph. A custom CPU operation that was previously hard-coded for the M3 graph has been eliminated, and its functionality is now expressed using standard, stock operations. This change simplifies the codebase, making it more maintainable and potentially improving compatibility across different hardware backends.
llama.cpp Release Cleans Up M3 Graph by Replacing Custom CPU Op with Standard Operations Read More »
The latest patch release for Home Assistant brings a host of quality-of-life fixes and stability improvements that self-hosted users will appreciate. A particularly notable change addresses a long-standing inconsistency where YAML-defined helper entities—such as history_stats, derivative, integration, statistics, threshold, trend, mold_indicator, generic_hygrostat, generic_thermostat, and utility_meter—were incorrectly being assigned a device. This caused unnecessary clutter and
Home Assistant Patch Release: YAML Entity Fixes and Integration Updates Read More »
A series of security flaws have been identified in Adobe products, with the most critical carrying the risk of arbitrary code execution. The affected software includes Adobe Bridge, a robust asset management solution that enables creative professionals to preview, organize, edit, and publish creative assets seamlessly across the Creative Cloud ecosystem, and Adobe Format Plugins,
Multiple Adobe Vulnerabilities Expose Users to Arbitrary Code Execution Read More »
n8n 2.33.1 Brings Enhanced Context for Lifecycle Hooks For users running self-hosted n8n instances, version 2.33.1 introduces a useful improvement: external lifecycle hooks can now access the full workflow hook context. This means that when you set up custom scripts or integrations that trigger at key workflow events (like start, success, or error), they will
n8n 2.33.1: Workflow Hook Context Now Available in External Lifecycle Hooks Read More »
LangChain Core version 1.5.2 is now available, bringing a targeted bug fix and several routine dependency updates. The most notable change resolves an issue where empty string values in gateway environment variables were not handled correctly, which could lead to unexpected behavior in certain configurations. This fix ensures more robust handling of environment settings for
LangChain Core v1.5.2 Released with Bug Fix and Dependency Updates Read More »
The latest llama.cpp build, b10176, introduces a valuable new feature for distributed and remote inference scenarios: the tensor_memset remote procedure call. This addition allows for efficient initialization of tensors across RPC connections, which is particularly beneficial for self-hosted setups that distribute model layers across multiple machines. By streamlining how memory is set up remotely, it
llama.cpp Build b10176 Brings Tensor Memset RPC and Expanded Platform Support Read More »
