{ "family": "glm", "model": "/Users/gb/Library/Application Support/de.rfc1437.ds4server/models/glm-5.3-flash/GLM-5.3-Flash-Q2.gguf", "cases": [ { "prompt": "Give a summary of the following text:\n\n# DS4Server\n\nDS4Server is a native macOS application for running DwarfStar models as a local\ncoding agent and as a localhost inference server. The inference engine, model\nlifecycle, agent loop, and application UI are implemented in Rust with Iced;\nthe Metal kernels and small native integration layers are adapted from\n[DwarfStar (`ds4`)](https://github.com/antirez/ds4).\n\n## Capabilities\n\n- **Project-based coding chat.** Add local project folders, keep multiple\n persistent sessions per project, and rename, retitle, pin, archive, compact,\n rebuild, or delete sessions. Chats stream Markdown, reasoning, tool activity,\n context use, and generation speed.\n- **Local coding tools.** The agent can read, search, list, write, and edit\n project files; run and monitor asynchronous shell commands; search Google;\n and visit rendered web pages. File access is confined to the project, output\n is bounded, risky shell or visible-browser actions require approval, and\n tool calls are validated against the same typed schemas shown to the model.\n- **Fresh-agent Ralph loops.** For a bounded coding objective, the agent can\n run foreground rounds in fresh model contexts while preserving workspace\n changes between rounds. A validated structured report is the only\n conversational handoff to the next worker; the loop stops on reported\n completion, a blocker, failure, cancellation, or its configurable round\n limit.\n- **Workspace instructions and reusable skills.** A global `AGENTS.md` plus\n project and nested `AGENTS.md`/`AGENTS.local.md` files provide hierarchical\n guidance that is reconciled as the agent enters or changes a workspace area.\n Standard `~/.agents/skills//SKILL.md` packages are advertised by\n metadata and loaded in full only when a task matches.\n- **Project-backed Dev Brain.** An optional managed Obsidian vault provides\n source-verified wiki pages, ranked search, and on-demand skills. Each session\n receives the verified skill names, descriptions, and paths, then loads full\n instructions only when a task matches.\n- **Long-running sessions.** Transcripts and summaries are stored in SQLite.\n Automatic and manual context compaction preserve the complete visible chat,\n while durable KV checkpoints make follow-up turns and relaunches resumable.\n- **Native Metal inference.** DeepSeek V4 Flash, DeepSeek V4 Pro, and GLM 5.2\n run through model-specific Rust/Metal executors with long-context prefill,\n sampling, cancellation, idle unload, and a bounded resident session pool.\n Supported acceleration includes SSD expert streaming, DeepSeek legacy MTP,\n DSpark, GLM MTP, directional steering, and model-specific memory admission.\n- **Local HTTP APIs.** A configurable listener on `127.0.0.1:4000` exposes\n Models, Chat Completions, Completions, Anthropic Messages, and Responses APIs\n with streaming, tool calls, usage accounting, cancellation, and prefix-aware\n KV reuse. Endpoint conversations remain client-owned and are not added to\n project history.\n- **Model and runtime management.** Model Manager downloads, resumes, verifies,\n and deletes supported GGUF artifacts with byte progress, speed, and ETA.\n Preferences cover generation, runtime, SSD, speculative decoding, steering,\n KV storage, the local endpoint, and idle unload. The Stats view reports model,\n cache, SSD, speculative, session, and HTTP activity.\n\nProjects, sessions, and transcripts use SQLite. Settings use a compact YAML file\nthat contains only values changed from their defaults and can also be edited by\nhand.\n\n## A2UI widgets\n\nDS4Server renders A2UI v1.0 surfaces with these widgets:\n\n- **Content:** Markdown text, images (including avatars), icons, video and audio\n players, and dividers.\n- **Layout:** rows, columns, lists, cards, modals, and tabs.\n- **Controls:** buttons, text fields, checkboxes, sliders, date/time inputs, and\n choice pickers.\n- **Research:** bar, line, area, stacked-bar, pie, donut, and heatmap charts; tables,\n metrics, timelines, maps, mind maps, and forms.\n\nVideo posters render in the surface; video and audio playback uses native\nmacOS AVKit player windows with standard transport, volume, and fullscreen\ncontrols.\n\nThe newest A2UI surface is pinned above the transcript in a default 50/50\nworkspace split. Dismissing it requires confirmation and records a durable\nboundary in the chat database, so reopening the session restores only the\nnewest surface created after the last dismissal. Left and right arrow buttons\nreconstruct earlier and later read-only surface epochs from the recorded A2UI\nprotocol calls; model updates remain routed only to the current surface.\n\n### Live A2UI validation\n\nWith DS4Server running and its local endpoint enabled, run the opt-in model\nvalidation suite with:\n\n```sh\ncargo run --release -- validate-a2ui\n```\n\nIt sends natural-language chart, form, choice, and full-composition prompts\nthrough the current A2UI tool description, then replays every returned protocol\nmessage through the real catalog and component-graph validators. Use `--case\npie-natural`, `--case composed-basics`, `--attempts 3`, `--model MODEL_ID`, or\n`--endpoint URL` to narrow or repeat runs. This slow, model-dependent suite is\nintentionally separate from `cargo test`.\n\n### Headless model evaluation\n\nRun a bounded, instrumented generation through the production runtime without\nopening the UI:\n\n```sh\ncargo run --release -- model-eval \\\n --model qwen3.8-flash-next \\\n --reasoning low \\\n --acceleration off \\\n --power-percent 100\n```\n\nThe evaluator first performs a short unmeasured warmup through the same system-prompt\nbuilder and production runtime as the UI, then resets its GPU counters and starts\nthe measured request. `warmup_result.elapsed_ms` includes initial model loading;\nits `timing` object separates `model_load_ms` and `non_loading_elapsed_ms` (the\nlatter still includes setup, inference, and checkpoint work). Do not add the\nreported load time to the warmup total. A `model_loaded` event reports the same\nload duration as the shared runtime metrics. Canary samples retain their start\n`phase` and record `completion_phase`, actual completion `elapsed_ms`, and host\nobservation `observed_elapsed_ms`; per-phase summaries group by probe start.\n`result.timing.decode_ms` measures the shared engine decode loop, including\nsampling and streamed output callbacks but excluding subsequent pending-token\nfinalization and checkpoint work. Stats shows the same measurement as \"Decode\nloop (without checkpoint)\". The older host-observed interval through request\ncompletion is retained as `decode_to_request_end_ms`; it is not pure decode time.\n`decode_loop_tokens_per_second` uses completion tokens divided by the loop duration;\n`decode_tokens_per_second` remains the UI's last progress rate. `checkpoint_io`\nreports request operation counts and the last read/write duration, not summed I/O\ntime. A missing decode duration is `null`, not zero.\nThe default test\nprompt identifies a prose-generation test and asks the model to choose\nits own genre, setting, and characters, then output only a complete short story\nwithout questions, choices, limitations, or coding discussion. JSON Lines report\nruntime phases, prefill and decode speed, Metal busy time,\ncommand-buffer duration, CPU, physical memory, disk I/O, and the complete reasoning\nand answer. `--input-file PATH` appends a UTF-8 file to the supplied prompt for\nrealistic long-prefill tests. Repeat `--prompt` to run multiple turns in one\nongoing chat: every later turn includes all preceding user prompts and complete\nassistant responses and continues from the same session checkpoint. An independent\nMetal canary runs inside the same\nprocess as the production runtime through\nloading, prefill, decode, and finishing, reporting per-phase scheduling and\ncompletion latency plus stalls that could make a UI unresponsive. Use\n`--acceleration on|off` to compare DSpark on DeepSeek or integrated MTP on\nGLM/Qwen. The canary itself submits GPU work, so use `--canary off` for clean\nthroughput measurements and `--canary on` for responsiveness diagnostics. The UI\ncanary is off by default and can be enabled in Stats. A supervisor terminates\nthe worker only when startup or token progress stalls, or when the memory limit\nis exceeded; there is no whole-run timeout. See `model-eval --help` for all\noverrides. The evaluator only opens already installed model artifacts and never\ndownloads missing models.\n\nEvaluation defaults to `--plain-chat on`: the shared UI prompt builder omits\nagent/tool schemas, skill instructions and the built-in coding-agent system\nprompt; an explicitly customized system prompt is preserved. The corresponding\nUI configuration is `plain_chat: true` in its YAML configuration. In that mode\nthe UI also skips workspace/date injections, extension hooks, A2UI handling,\ntool execution, automatic response retries and automatic first-turn titles.\nUse a **new chat** in both frontends: existing history is never silently removed.\nThe normal UI default remains agent mode (`plain_chat: false`). `--plain-chat off`\nrestores agent prompt construction for diagnostics, but does not make the harness\nan agent/tool executor. The effective mode and complete system prompt are reported\nin the start receipt; do not compare runs with different modes.\n\nFor a summary, story, and Python one-shot in a single chat, pass three prompts:\n\n```sh\ntarget/release/ds4-server model-eval \\\n --model qwen3.8-flash-next --reasoning low \\\n --power-percent 100 --acceleration off --canary on \\\n --input-file README.md \\\n --prompt 'Give a concise summary of the following project README. Return the summary directly without asking questions.' \\\n --prompt 'This is a prose-generation test. Respond only with a complete short fictional story in ordinary prose. Choose the genre, setting, and characters yourself and begin the story immediately. Do not ask questions, offer choices, explain limitations, or discuss coding.' \\\n --prompt 'This is an offline code-generation benchmark. Do not invoke tools or emit tool-call markup. Return exactly one Python code block defining has_close_elements(numbers: list[float], threshold: float) -> bool. It must return True if any two distinct numbers are closer than threshold. Include no explanation outside the code block.'\n```\n\nThe input file is appended only to the first prompt. Each turn starts after the\nprevious response finishes; `measurement_start` records the turn number and the\nnumber of history messages (1, 3, 5), and each `result` reports its own timings,\ncached tokens, reasoning, and answer. The warmup uses a separate session and is\nnot included in this history.\n\n## Build and run\n\nDS4Server targets Apple silicon with macOS 15 or newer and requires Rust 1.97 plus\n`cargo-packager` 0.11.8.\n\n```sh\ncargo install cargo-packager --locked --version 0.11.8\nmake bundle\nopen target/release/DS4Server.app\n```\n\nTagged versions are also published as Apple Silicon DMG files on the\n[repository releases page](https://git.rfc1437.de/hugo/DS4Server/releases).\n\n## Application data\n\n```text\n~/Library/Application Support/de.rfc1437.ds4server/data.sqlite3\n~/Library/Application Support/de.rfc1437.ds4server/config.yaml\n~/Library/Application Support/de.rfc1437.ds4server/AGENTS.md\n~/Library/Application Support/de.rfc1437.ds4server/models/\n~/Library/Application Support/de.rfc1437.ds4server/kv-cache/\n```\n\nDeleting a project or session removes DS4Server metadata and its associated\ncheckpoint; it never deletes the referenced project directory. Standard agent\nskills live separately under `~/.agents/skills/`. See the\n[issue tracker](https://git.rfc1437.de/hugo/DS4Server/issues) for remaining\nimplementation work.\n\nThe adapted Metal and browser sources retain their upstream notices in\n[`native/metal/LICENSE`](native/metal/LICENSE) and\n[`native/web/LICENSE`](native/web/LICENSE).\n", "tokens": [ 154822, 154824, 154826, 25062, 287, 29905, 371, 25, 12035, 154827, 34953, 264, 12120, 315, 279, 2701, 1467, 1447, 2, 20535, 19, 5475, 271, 5936, 19, 5475, 374, 264, 9862, 66689, 3766, 369, 4303, 79089, 12693, 4119, 438, 264, 2205, 198, 48064, 8314, 323, 438, 264, 47130, 44120, 3538, 13, 576, 44120, 4712, 11, 1614, 198, 75, 19480, 11, 8314, 6337, 11, 323, 3766, 3689, 525, 11532, 304, 33627, 448, 358, 1998, 280, 1782, 19170, 63062, 323, 2613, 9862, 17565, 13608, 525, 29255, 504, 198, 64446, 32485, 12693, 28552, 5356, 19, 63, 7252, 7, 2428, 1110, 5204, 905, 14, 517, 59322, 3446, 82, 19, 3593, 565, 8011, 8455, 271, 12, 3070, 7849, 5980, 10817, 6236, 13, 334, 2691, 2205, 2390, 29135, 11, 2506, 5248, 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