Selective RabbitMQ dead-letter replay: move only matching messages with a Python script

·6 views

Replaying an entire RabbitMQ dead-letter queue resends messages that should not be retried, such as orders and declined payments. Basic get-and-requeue loops fail because requeued messages return to the head of the queue. The article's approach keeps unwanted messages unacknowledged while reading onward, then returns them all with a single negative acknowledgement. Matching messages are republished with publisher confirms and mandatory routing before the original is acked, and dead-letter headers are stripped. Tests on classic and quorum queues reportedly preserved the order of the messages left behind and kept nothing moved if a failure occurred.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Disney Agrees to Hire Most of Character.AI's Staff in a Bid That Could Be Topped

A court filing indicates Disney has agreed to hire the majority of Character.AI's workforce as part of a stalking horse bid for the company. The vast majority of employees who were offered jobs have accepted them, according to the filing. Because a stalking horse bid is an initial offer that rival buyers can outbid, the Disney arrangement may serve as a baseline rather than the final price. The deal is therefore a talent-focused move rather than a completed acquisition. Analysts note that users and developers relying on Character.AI's products or contracts should plan for both a Disney-led outcome and a competing bid.

0 comments Read more at DEV Community

ProgrammingHacker News ·

Agent-Skills.market launches as a site listing skills for AI agents

A new website called Agent-Skills.market was shared on Hacker News, where it received 7 points and one comment. The site appears to be a marketplace or directory for skills intended for AI agents. The source material provides only the site's URL, its Hacker News discussion link, and basic engagement metrics. Beyond these details, no further information about the platform's features, creators, or launch date is available from the item.

0 comments Read more at Hacker News

ProgrammingDEV Community ·

llama.cpp UI Adds HuggingFace Hub Model Discovery and Synced Sidecar Downloads

A recent pull request brings a Discover Models view into the llama.cpp UI, letting users search and filter GGUF models hosted on HuggingFace Hub without leaving the app. Previously, users had to locate and download quantized models manually, and draft sidecar files such as dflash or mtp had to be tracked separately. The new view shows download buttons that reflect live states like queued, in progress, or paused, and lists draft files as sub-items under their main model. The download subsystem in common/download.cpp was extended so that downloading a main model automatically queues its sidecars, with pause, resume, and cancel applying to all related files together. The change also includes settings toggles to enable or disable the Discover integration and to filter out unsupported models.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

BillBuddhi: Local-First AI Tool Turns Invoices into Reviewable Ledgers

BillBuddhi is an open-source prototype aimed at Indian freelancers and small businesses, built by a developer for a Hacktoberfest AI challenge. The tool accepts invoice images and text-based PDFs, extracting text with Tesseract OCR and pypdf before a local Gemma model running through Ollama suggests structured fields such as supplier, tax components, and totals. Users can correct the extracted values, review basic consistency flags, and export confirmed entries to CSV. The project is built with Python and Streamlit, and its creator stresses that it is not accounting software and does not provide GST compliance or tax advice. Running the model locally is presented as a way to keep sensitive financial data under the user's control.

0 comments Read more at DEV Community