01 / Process
So entstehen diese Notizen
Nach dem Einchecken des Codes rekonstruieren wir die Geschichte aus Commit, Diff, Tests und Laufzeitbelegen. Das Ergebnis bleibt als technische Dokumentation für Nutzer und Beitragende erhalten.
OpenMake Engineering-Log
Kein nacherzähltes Changelog. Jeder Eintrag erklärt Problem, Designentscheidungen, Implementierungsgrenze, Belege und Abwägungen hinter einer veröffentlichten OpenMake-Änderung.
01 / Process
Nach dem Einchecken des Codes rekonstruieren wir die Geschichte aus Commit, Diff, Tests und Laufzeitbelegen. Das Ergebnis bleibt als technische Dokumentation für Nutzer und Beitragende erhalten.
02 / Team
OpenMake Team ist die Community-Identität; openmake_llm ist das Softwareprojekt; OpenMake ist der Produktname. Der nicht entwickelnde Maker riskpw leitet openmake_llm per Vibe Coding, und der professionelle Entwickler rocky unterstützt die Entwicklung.
Technischer Deep Dive

A Mac mini runs the app, a DGX Spark runs the models, and one 127.5 GB pool holds everything on the far side. Here is where that went wrong over six months — a model swap that stayed invisible because an alias was doing its job, a fan-out that met real rate limits, and a bottleneck that turned out not to be memory at all.
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1.23.0 is not a release that added features. It is the release that decided what a user and an operator can each do when the answer is wrong, the task is dead, or the records have vanished entirely.
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The four deep dives written so far have something in common. Something we believed was in place was not, and what told us was never the test suite — it was production.
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The roadmap names the Execution Graph as the next step. Rather than building it in one pass, we split it into three increments that measure first and fix second. The first measurement came back at 45%, and the cause was not the code.
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How OpenMake changed large agent-task attachments from one oversized request into an authenticated, resumable-by-chunk protocol while preserving the existing task file contract.
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We shipped OS-level isolation for external MCP servers in a day, then deleted it the next morning. The tool we had chosen turned out to quietly do nothing on the host we actually run on.
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The code was tied to one server's dialect. A compatible signature let us move 100-plus call sites in a single day and delete 4,500 lines, but clearing what that compatibility layer left behind took another thirteen.
Entwicklungsnotiz lesen2026 / W04–W37
W18 (27. April – 3. Mai) fehlt, weil es in dieser Woche keine Commits gab. Eine leere Woche bleibt leer, statt nachträglich beschrieben zu werden.

W37 moved from guarding individual model settings to making model choice and multimodal execution visible. Compare mode put two answers side by side; Agent Tasks exposed parallel progress; and the model layer became a Planner-led capability path for text, image, vision, audio, video, and web work. From September 7 through 13, main added 86 commits and produced 35 tagged releases from 1.48.0 through 1.62.3.
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From August 31 through September 6, GitHub main added 95 commits. On Thursday, in a separate repository, OpenMake Bench was built and put up at bench.openmake.cc: a measurement tool that runs the same prompts across models and routes under identical conditions, and benchmarks your own models through chat account SSO. The previous week's leftovers, 1.35.0 and 1.35.1, were cut in the small hours of Monday, and nineteen releases followed, 1.36.0 through 1.47.0. Three threads overlapped. HWP, HWPX, and HML documents, which the app accepted but could not read, are now extracted, and that work exposed a context-overflow error presented as a transient failure and a token underestimation, both fixed alongside. The local default model changed to qwen3.8-27b, local models are now discovered from the gateway instead of a static catalog, and the sampling defaults, reasoning preservation, and image-count issues found while checking the new model were handled in sequence. On the external side, hasa and B.AI arrived as BYOK providers, Discussion and Deep Research gained per-provider concurrency and 429 backoff so a free key's per-minute limit no longer collapses them, and the three-step reasoning-effort control is actually forwarded to external models. In between, three high, one medium, and many low findings from an apps/api security review were closed over two days, the routing golden set grew to 150 cases and routing accuracy went from 77.5% to 100%, and a nightly real-model evaluation was put on the operations Mac. From Thursday evening to Saturday midnight, work of a different character followed. Six Deep Research consistency defects were closed at once, the language drift that answered Korean questions in English was caught on two fronts, and the same Instrument design tokens were laid down across web, iOS, and Bench. The socket problem that lost the in-flight response when a tab was switched was fixed with stream detach/resume, and in the prompt-trimming work the first post-deployment measurement reversed the design twice in a row. On the site, a Simplified Chinese locale went up, making four languages. Sunday, the last day, had a character of its own. It began by closing memory defects an external review had flagged, cut four releases in a single day (1.45.0 through 1.45.3), and closed with agent-task coding work grounded in 30 days of production measurement plus a code-navigation tool that runs without an approval prompt (1.46.0 and 1.47.0).
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From August 24 to 30, GitHub main added 81 commits and three releases: 1.33.0, 1.33.1, and 1.34.0. After the previous week's feature run, the work moved toward making agent work recoverable and legible: local tasks can be resumed, inspected, and shared as read-only work; a shared artifact viewer keeps published output on an isolated origin; and read-only tools can run in parallel within one turn. Later in the week tool failure gained a denominator, and a circuit that cuts off repeatedly failing external tools was put in place with the gate off by default. The same pass tightened the extension and MCP boundaries, removed mock-only administrator surfaces, stopped expired sessions from polling forever, and moved task workspaces and logs out of ephemeral /tmp onto a persistent path.
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One hundred and fifteen commits shipped nine releases this week, 1.26.0 through 1.32.1. Answer rendering was rebuilt for phone screens and the phone gained maps, location, and a camera, while OpenMake Code opened a path for running tools on the user's own machine and closed it out with an audit trail and a single bridge core. The desktop moved its centre of gravity: the Electron shell was frozen and a SwiftUI native companion took over. On the last day the direction turned once more, from trusting written configuration to trusting the model itself - capability and context length are measured at boot, reasoning effort became a user choice, answer verification arrived, and every LLM call was routed through a single LiteLLM path. In parallel, quietly leaking boundaries - skill injection, SSRF, API key scopes - were tightened and unused code and the GitHub integration were removed.
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This week (44 commits) surfaced extension bundles, the marketplace, and workspace sharing into the product, consolidated OpenAPI contracts as the single source of truth, and opened the first work on iOS authentication and a SwiftUI MVP. At the same time we strengthened large-repo skill installation and hardened boundaries around citations, OAuth, and session recovery to raise scalability and reliability.
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This week we tightened orchestration reliability and frontend/backend feature consistency, implemented chunked upload for large attachments that exceed Cloudflare request limits, and completed an analysis path that handles scanned PDFs with no text layer. Small documents fall back to multi-page native OCR; large documents are split so a sandbox targets only the necessary pages for OCR. We then retroactively analyzed 20 failed Agent Tasks and added exponential-backoff retries for transient LLM errors and a demotion that removes approval-required tools when approval responses time out repeatedly, allowing completion with the available information. These changes, along with integrating Agent Tasks into history, were released as 1.21.0.
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In the last week of July we focused on structure rather than feature additions. We reviewed provider contracts, the Desktop boundary, MCP, operations, and LiteLLM·vLLM topologies to ensure orchestration control remains with OpenMake.
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At the end of July we connected autonomous tasks to real projects and authentication boundaries. We worked in parallel on Agent Task’s Git capabilities, OAuth, a comprehensive source audit, Cloudflare migration, release documentation, and desktop recovery.
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We added a new gateway and stronger chat behavior while explicitly changing model assignments. Work progressed on Discord, provider roles, execution plans, routing measurement, and self-learning evaluation, balancing the associated trade-offs.
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In the second week of July we advanced implementation and deep review in parallel. We worked on the MCP catalog, Agent task design, self-learning measurement, a frontend audit, and an interactive log tool, documenting both achievements and remaining failures.
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As we moved into July, we wrapped up work on web execution, artifacts, and Agent Task items, then returned to real chat and authentication behavior. From this period, Claude session records with precise project paths began to reappear.
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In the busiest week of June we expanded execution scope beyond simple conversation. We tied task sandboxes, browser and web paths, artifacts, attachments, MCP, and chat orchestration together into a single runtime.
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As features increased, we strengthened guardrails. We improved security fixes, API key controls, in-depth research, caching, design consistency, and usage visibility.
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Search and answer quality were the focus. We connected deep research, evaluation hooks, prompts, chat behaviors, artifacts, and agent tasks into a grounded answers pipeline.
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In the first week of June we elevated Agent Tasks from a simple chat mode to an independent feature. We added task execution, management, and routing, and redesigned the UI to provide a dedicated surface for long-running autonomous work.
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At the end of May we focused on artifacts, chat routing, sockets, and structural cleanup. We clarified the lifecycle of generated outputs and narrowed the gap between model decisions and the user-facing screens.
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This was the week with the most commits during the audit period. We connected individual features into a manageable platform through MCP collection, skill creation, agent collection, the model catalog, navigation, and GDPR-related work.
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In the week following large provider and UI work, we focused on review and cleanup. We reduced the risks introduced by the prior volume of changes through reviews of security and configuration assumptions and by refactoring LLM integration code.
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Development velocity increased significantly in early May. We revamped provider integrations, model selection, brand presentation, and the main chat screen to connect the matured backend to a product users can understand.
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In the final active week of April, we closed storage fixes and addressed small feature gaps. All changes were recorded based on Git to avoid inventing an unverifiable AI collaboration narrative when no matching Claude session existed.
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Security requirements were translated into concrete implementations. We strengthened the Content Security Policy (CSP), WebSocket settings, CSRF defenses, storage rules, and response headers across public-facing and authentication screens.
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Even during a period when no matching local Claude Code session could be found, development in Git continued. The repository contains changes to infrastructure, configuration, and operations documents, so this weekly entry is compiled solely from the Git record.
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We intentionally operated at a smaller scale during the transition from March to April. We整理ed prior stabilization efforts through documentation, configuration, and maintenance work, preparing for the next infrastructure phase.
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Advanced agent and routing behavior while removing outdated abstractions. By eliminating the legacy A2A route, we made the remaining execution model easier to understand and operate.
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One of the busiest weeks in March, with broad fixes and refactoring across the codebase. Defects related to API keys, memory, agents, RAG, MCP, and user-facing screens were handled as a single reliability-improvement effort.
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Focused on relatively small-scale bug fixes, provider behavior, and integrating parallel branches. It was a week spent maintaining platform consistency in a fast-changing environment rather than delivering notable new features.
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In early March we focused on operating rich answers reliably. We reviewed and stabilized Firecrawl, cache, MCP and AI feature toggles, ES module cleanup, Mermaid, and KaTeX.
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OpenMake has begun moving beyond basic chat. We added skills, memory, schemas, upload security, MCP controls, and deeper tests to build components of a scalable AI workspace.
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Focused on the boundaries users encounter first — login, anonymous sessions, route behavior, and server reliability. Through refactoring and bug fixes, we began turning initial features into a platform that can withstand everyday use.
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In the second week of February, we expanded the initial platform and overhauled project documentation to prepare for faster iterative development. The focus was on foundational work that makes the system understandable before broadening functionality.
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On February 3, the first commit for OpenMake LLM 1.5.0 was recorded. The design explorations from January have become a milestone in the codebase that anyone can revisit.
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In the final week of January we moved beyond structural analysis into concrete implementation sessions to resolve router collisions. Provider flows and responsibility boundaries were clarified, but the public repository history had not yet begun.
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January's entry starts not with repository milestones but with preliminary research. We reviewed existing OpenMake screens, deployment assumptions, and routing conflicts to define the system boundaries that must be understood before actual implementation.
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