Update model configurations and enhance LLM runtime logic

- Revised model URLs and descriptions in `llamacpp-models.example.yaml` and `ollama-models.example.yaml` to reflect new recommendations and vision capabilities.
- Updated the LLM runtime logic to support vision projectors and improved model resolution handling.
- Enhanced the installation script to conditionally include vision projectors when available.
- Added tests to validate the inclusion of vision projectors in model presets and ensure proper URL remapping for deprecated models.
- Improved documentation to clarify model usage and configuration options.

docs/llm.md

@@ -84,11 +84,12 @@ $env:OLLAMA_HOST = "http://127.0.0.1:17811"
 
 | # | ключ | tag / смысл |
 | --- | --- | --- |
-| 1 | **recommended** | `huihui_ai/qwen2.5-abliterate:7b` — RU/EN, ~5 GB |
+| 1 | **recommended** | `huihui_ai/qwen2.5-vl-abliterated:7b` — vision+RU, ~6 GB |
-| 2 | light | `qwen2.5:3b` |
+| 2 | light | VL 3B abliterate (~3 GB) |
-| 3 | stock | `qwen2.5:7b` |
+| 3 | text | text-only `qwen2.5-abliterate:7b` |
-| 4 | alt | другой abliterate 7B |
+| 4 | stock | `qwen2.5:7b` |
-| 5 | empty | только runtime |
+| 5 | alt | другой text abliterate 7B |
+| 6 | empty | только runtime |
 | — | keep | не трогать yaml (если уже спросили повторно) |
 
 `default: true` в yaml — preferred в логе; pull идёт по всему списку.
@@ -123,10 +124,11 @@ Unit `gpu-rent-ollama` читает `/mnt/swarm_data/.gpu-rent-gpu.json`:
 
 | # | ключ | что |
 | --- | --- | --- |
-| 1 | **recommended** | Qwen2.5 7B abliterate Q4_K_M (~4.7 GB) |
+| 1 | **recommended** | Qwen2.5-VL 7B abliterate + mmproj (~4.7+0.8 GB, картинки+RU) |
-| 2 | light | Qwen2.5 3B Instruct Q4_K_M |
+| 2 | light | Qwen2.5 3B Instruct text Q4_K_M |
-| 3 | stock | официальный 7B Instruct Q4_K_M |
+| 3 | text | Qwen2.5 7B abliterate text-only |
-| 4 | empty | только runtime |
+| 4 | stock | официальный 7B Instruct Q4_K_M |
+| 5 | empty | только runtime |
 | — | keep | не трогать yaml |
 
 `-ngl` / `-c` — по GPU probe. Для recommended abliterate GGUF нужен **`HF_TOKEN`** в `.env` (иначе 401). Вручную: положи GGUF в models и `systemctl restart gpu-rent-llamacpp`.

llamacpp-models.example.yaml

@@ -1,15 +1,16 @@
 # Copy to llamacpp-models.yaml (gitignored). Used when LLM_RUNTIME=llamacpp.
-# url = direct HTTPS link to a .gguf (Hugging Face resolve/main/…).
+# url = direct HTTPS link to a .gguf; mmproj = vision projector (Qwen2.5-VL).
-# Empty models: [] → only llama-server, GGUF клади вручную на VM.
+# Empty models: [] → only llama-server, GGUF клади вручную.
-# Purpose: prompt-help beside SwarmUI (RU/EN).
+# Purpose: prompt-help / vision beside SwarmUI (RU/EN, low refusal).
 
 models:
-  # Recommended: Qwen2.5 7B abliterate Q4_K_M (~4.7 GB)
+  # Recommended: Qwen2.5-VL 7B abliterate Q4_K_M + mmproj (~4.7 + 0.8 GB)
-  - url: https://huggingface.co/bartowski/huihui-ai_Qwen2.5-7B-Instruct-abliterated-GGUF/resolve/main/huihui-ai_Qwen2.5-7B-Instruct-abliterated-Q4_K_M.gguf
+  - url: https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q4_K_M.gguf
+    mmproj: https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.mmproj-Q8_0.gguf
     default: true
 
-  # Lighter (~2 GB):
+  # Text-only abliterate 7B (~4.7 GB):
-  # - url: https://huggingface.co/bartowski/Qwen2.5-3B-Instruct-GGUF/resolve/main/Qwen2.5-3B-Instruct-Q4_K_M.gguf
+  # - url: https://huggingface.co/RichardErkhov/huihui-ai_-_Qwen2.5-7B-Instruct-abliterated-gguf/resolve/main/Qwen2.5-7B-Instruct-abliterated.Q4_K_M.gguf
 
-  # Official stock 7B (more refusals):
+  # Lighter text (~2 GB):
-  # - url: https://huggingface.co/bartowski/Qwen2.5-7B-Instruct-GGUF/resolve/main/Qwen2.5-7B-Instruct-Q4_K_M.gguf
+  # - url: https://huggingface.co/bartowski/Qwen2.5-3B-Instruct-GGUF/resolve/main/Qwen2.5-3B-Instruct-Q4_K_M.gguf

ollama-models.example.yaml

@@ -1,17 +1,17 @@
 # Copy to ollama-models.yaml (gitignored). Used when LLM_RUNTIME=ollama.
 # name = exact tag for `ollama pull`. Empty models: [] → runtime only, no pull.
-# Purpose: help craft SwarmUI prompts (RU/EN, low refusal).
+# Purpose: SwarmUI prompt help + vision (RU/EN, low refusal).
 
 models:
-  # Recommended: Russian+English, ~5GB, low refusal (community abliterate).
+  # Recommended: vision + Russian/English, ~6GB, abliterated
-  - name: huihui_ai/qwen2.5-abliterate:7b
+  - name: huihui_ai/qwen2.5-vl-abliterated:7b
     default: true
 
-  # Lighter / faster (weaker prompts):
+  # Lighter vision:
-  # - name: qwen2.5:3b
+  # - name: huihui_ai/qwen2.5-vl-abliterated:3b
+
+  # Text-only abliterate (~5GB):
+  # - name: huihui_ai/qwen2.5-abliterate:7b
 
   # Official stock (more refusals):
   # - name: qwen2.5:7b
-
-  # Alternate abliterate pack:
-  # - name: richardyoung/qwen2.5-7b-instruct-abliterated

src/gpu_rent/llm_runtime.py

@@ -19,18 +19,21 @@ from gpu_rent.paths import (
 VALID_RUNTIMES = frozenset({"none", "ollama", "llamacpp"})
 
 OLLAMA_PRESETS: dict[str, list[str]] = {
-    "recommended": ["huihui_ai/qwen2.5-abliterate:7b"],
+    # Vision + RU/EN + low refusal — best default for swarm-assistent / prompt help with images
-    "light": ["qwen2.5:3b"],
+    "recommended": ["huihui_ai/qwen2.5-vl-abliterated:7b"],
+    "light": ["huihui_ai/qwen2.5-vl-abliterated:3b"],
+    "text": ["huihui_ai/qwen2.5-abliterate:7b"],
     "stock": ["qwen2.5:7b"],
     "alt": ["richardyoung/qwen2.5-7b-instruct-abliterated"],
     "empty": [],
 }
 
 OLLAMA_PRESET_LABELS: dict[str, str] = {
-    "recommended": "Qwen2.5 7B abliterate (RU/EN, мало отказов, ~5GB)",
+    "recommended": "Qwen2.5-VL 7B abliterate (картинки+RU, ~6GB)",
-    "light": "qwen2.5:3b (быстрее, слабее)",
+    "light": "Qwen2.5-VL 3B abliterate (vision, быстрее, ~3GB)",
+    "text": "Qwen2.5 7B abliterate text-only (~5GB)",
     "stock": "официальный qwen2.5:7b (больше цензуры)",
-    "alt": "другой abliterate-пак 7B",
+    "alt": "другой text abliterate-пак 7B",
     "empty": "только runtime, без pull",
     "keep": "не менять ollama-models.yaml",
 }
@@ -40,22 +43,51 @@ PRESET_HELP = "\n".join(
     f"{k} — {v}" for k, v in OLLAMA_PRESET_LABELS.items() if k != "keep"
 )
 
-LLAMACPP_PRESETS: dict[str, list[str]] = {
+# Each preset entry: {"url": "...gguf", "mmproj": optional vision projector url}
+LLAMACPP_PRESETS: dict[str, list[dict[str, str]]] = {
     "recommended": [
-        "https://huggingface.co/bartowski/huihui-ai_Qwen2.5-7B-Instruct-abliterated-GGUF/resolve/main/huihui-ai_Qwen2.5-7B-Instruct-abliterated-Q4_K_M.gguf",
+        {
+            "url": (
+                "https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/"
+                "resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.Q4_K_M.gguf"
+            ),
+            "mmproj": (
+                "https://huggingface.co/mradermacher/Qwen2.5-VL-7B-Instruct-abliterated-GGUF/"
+                "resolve/main/Qwen2.5-VL-7B-Instruct-abliterated.mmproj-Q8_0.gguf"
+            ),
+        },
     ],
     "light": [
-        "https://huggingface.co/bartowski/Qwen2.5-3B-Instruct-GGUF/resolve/main/Qwen2.5-3B-Instruct-Q4_K_M.gguf",
+        {
+            "url": (
+                "https://huggingface.co/bartowski/Qwen2.5-3B-Instruct-GGUF/"
+                "resolve/main/Qwen2.5-3B-Instruct-Q4_K_M.gguf"
+            ),
+        },
+    ],
+    "text": [
+        {
+            "url": (
+                "https://huggingface.co/RichardErkhov/huihui-ai_-_Qwen2.5-7B-Instruct-abliterated-gguf/"
+                "resolve/main/Qwen2.5-7B-Instruct-abliterated.Q4_K_M.gguf"
+            ),
+        },
     ],
     "stock": [
-        "https://huggingface.co/bartowski/Qwen2.5-7B-Instruct-GGUF/resolve/main/Qwen2.5-7B-Instruct-Q4_K_M.gguf",
+        {
+            "url": (
+                "https://huggingface.co/bartowski/Qwen2.5-7B-Instruct-GGUF/"
+                "resolve/main/Qwen2.5-7B-Instruct-Q4_K_M.gguf"
+            ),
+        },
     ],
     "empty": [],
 }
 
 LLAMACPP_PRESET_LABELS: dict[str, str] = {
-    "recommended": "Qwen2.5 7B abliterate GGUF Q4_K_M (~4.7GB, мало отказов)",
+    "recommended": "Qwen2.5-VL 7B abliterate + mmproj (~4.7+0.8GB, картинки+RU)",
-    "light": "Qwen2.5 3B Instruct Q4_K_M (~2GB)",
+    "light": "Qwen2.5 3B Instruct Q4_K_M text (~2GB)",
+    "text": "Qwen2.5 7B abliterate text-only Q4_K_M (~4.7GB)",
     "stock": "официальный Qwen2.5 7B Instruct Q4_K_M",
     "empty": "только llama-server, GGUF вручную",
     "keep": "не менять llamacpp-models.yaml",
@@ -118,6 +150,7 @@ class OllamaModelEntry:
 class LlamaCppModelEntry:
     url: str
     filename: str | None = None
+    mmproj_url: str | None = None
     default: bool = False
 
 
@@ -185,6 +218,20 @@ def gguf_filename_from_url(url: str) -> str:
     return "model.gguf"
 
 
+# Dead / moved HF mirrors → current resolve URL (same Q4_K_M abliterate weights).
+_LLAMACPP_URL_ALIASES: dict[str, str] = {
+    "https://huggingface.co/bartowski/huihui-ai_Qwen2.5-7B-Instruct-abliterated-GGUF/resolve/main/huihui-ai_Qwen2.5-7B-Instruct-abliterated-Q4_K_M.gguf": (
+        "https://huggingface.co/RichardErkhov/huihui-ai_-_Qwen2.5-7B-Instruct-abliterated-gguf/resolve/main/Qwen2.5-7B-Instruct-abliterated.Q4_K_M.gguf"
+    ),
+}
+
+
+def remap_llamacpp_url(url: str) -> str:
+    """Rewrite known-dead GGUF mirrors so old llamacpp-models.yaml still works."""
+    key = (url or "").strip()
+    return _LLAMACPP_URL_ALIASES.get(key, key)
+
+
 def parse_llamacpp_models(path: Path) -> list[LlamaCppModelEntry]:
     if not path.is_file():
         return []
@@ -199,21 +246,23 @@ def parse_llamacpp_models(path: Path) -> list[LlamaCppModelEntry]:
     out: list[LlamaCppModelEntry] = []
     for item in items:
         if isinstance(item, str):
-            url = item.strip()
+            url = remap_llamacpp_url(item.strip())
             if url:
                 out.append(LlamaCppModelEntry(url=url))
             continue
         if not isinstance(item, dict):
             continue
-        url = str(item.get("url") or "").strip()
+        url = remap_llamacpp_url(str(item.get("url") or "").strip())
         if not url:
             continue
         fname = item.get("filename")
         filename = str(fname).strip() if fname else None
+        mmproj = remap_llamacpp_url(str(item.get("mmproj") or item.get("mmproj_url") or "").strip())
         out.append(
             LlamaCppModelEntry(
                 url=url,
                 filename=filename or None,
+                mmproj_url=mmproj or None,
                 default=bool(item.get("default")),
             )
         )
@@ -244,17 +293,23 @@ def write_llamacpp_models_preset(path: Path, preset: str) -> None:
     key = (preset or "recommended").strip().lower()
     if key not in LLAMACPP_PRESETS:
         raise ValueError(f"пресет {preset!r}; варианты: {', '.join(LLAMACPP_PRESETS)}")
-    urls = LLAMACPP_PRESETS[key]
+    specs = LLAMACPP_PRESETS[key]
     lines = [
         "# Локальный манифест llama.cpp GGUF (не коммить). Пример: llamacpp-models.example.yaml",
-        "# url = прямой HTTPS на .gguf. Пустой models: [] — без скачивания.",
+        "# url = прямой HTTPS на .gguf; mmproj = projector для vision (Qwen2.5-VL и т.п.).",
         "models:",
     ]
-    if not urls:
+    if not specs:
         lines.append("  []")
     else:
-        for i, url in enumerate(urls):
+        for i, spec in enumerate(specs):
+            url = str(spec.get("url") or "").strip()
+            if not url:
+                continue
             lines.append(f"  - url: {url}")
+            mmproj = str(spec.get("mmproj") or "").strip()
+            if mmproj:
+                lines.append(f"    mmproj: {mmproj}")
             if i == 0:
                 lines.append("    default: true")
     path.write_text("\n".join(lines) + "\n", encoding="utf-8")

src/gpu_rent/provision.py

@@ -478,13 +478,21 @@ def provision_llm(cfg: Config, host: str, log: Log) -> None:
                 f"{defaults[0].filename or gguf_filename_from_url(defaults[0].url)}"
             )
         if entries:
-            jobs = [
+            jobs = []
+            for e in entries:
+                jobs.append(
                     {
                         "url": e.url,
                         "filename": e.filename or gguf_filename_from_url(e.url),
                     }
-                for e in entries
+                )
-            ]
+                if e.mmproj_url:
+                    jobs.append(
+                        {
+                            "url": e.mmproj_url,
+                            "filename": gguf_filename_from_url(e.mmproj_url),
+                        }
+                    )
             put_text(
                 cfg, host, "/tmp/gpu-rent-llamacpp-models.json", json.dumps(jobs, indent=2)
             )

src/gpu_rent/remote/install_llamacpp.sh

@@ -100,15 +100,27 @@ print(prefer[0] if prefer else "")
   rm -rf "$TMP"
 fi
 
-# Pick first GGUF if present; otherwise unit starts but API may idle without model.
+# Prefer a weights GGUF (skip mmproj), then attach --mmproj if present.
 MODEL_ARG=""
-FIRST_GGUF="$(find "$MODELS_DIR" -type f \( -name '*.gguf' -o -name '*.GGUF' \) | head -n1 || true)"
+MMPROJ_ARG=""
+FIRST_GGUF="$(
+  find "$MODELS_DIR" -type f \( -name '*.gguf' -o -name '*.GGUF' \) \
+    ! -iname '*mmproj*' 2>/dev/null | head -n1 || true
+)"
+MMPROJ_GGUF="$(
+  find "$MODELS_DIR" -type f \( -iname '*mmproj*.gguf' -o -iname '*mmproj*.GGUF' \) \
+    2>/dev/null | head -n1 || true
+)"
 if [[ -n "$FIRST_GGUF" ]]; then
   MODEL_ARG="-m ${FIRST_GGUF}"
   log "модель ${FIRST_GGUF}"
 else
   log "нет GGUF в ${MODELS_DIR} — положи файл вручную и systemctl restart ${UNIT}"
 fi
+if [[ -n "$MMPROJ_GGUF" ]]; then
+  MMPROJ_ARG="--mmproj ${MMPROJ_GGUF}"
+  log "mmproj ${MMPROJ_GGUF}"
+fi
 
 # GPU layers: share card with Swarm — full offload on mid+, leave headroom on low.
 NGL=99
@@ -144,7 +156,7 @@ Type=simple
 User=${SWARM_USER}
 Group=${SWARM_USER}
 WorkingDirectory=${LLAMA_ROOT}
-ExecStart=${SERVER_BIN} ${MODEL_ARG} --host 127.0.0.1 --port 8080 -ngl ${NGL} -c ${CTX}
+ExecStart=${SERVER_BIN} ${MODEL_ARG} ${MMPROJ_ARG} --host 127.0.0.1 --port 8080 -ngl ${NGL} -c ${CTX}
 Restart=on-failure
 RestartSec=8
 

tests/test_llm_runtime.py

@@ -5,7 +5,9 @@ import pytest
 from gpu_rent.llm_runtime import (
     decide_runtime,
     normalize_runtime,
+    parse_llamacpp_models,
     parse_ollama_models,
+    remap_llamacpp_url,
     write_ollama_models_preset,
 )
 
@@ -56,4 +58,31 @@ def test_write_preset(tmp_path: Path):
     path = tmp_path / "out.yaml"
     write_ollama_models_preset(path, "recommended")
     entries = parse_ollama_models(path)
-    assert entries[0].name == "huihui_ai/qwen2.5-abliterate:7b"
+    assert entries[0].name == "huihui_ai/qwen2.5-vl-abliterated:7b"
+
+
+def test_write_llamacpp_preset_includes_mmproj(tmp_path: Path):
+    from gpu_rent.llm_runtime import write_llamacpp_models_preset
+
+    path = tmp_path / "lc.yaml"
+    write_llamacpp_models_preset(path, "recommended")
+    entries = parse_llamacpp_models(path)
+    assert len(entries) == 1
+    assert "VL" in entries[0].url or "vl" in entries[0].url.lower()
+    assert entries[0].mmproj_url
+    assert "mmproj" in entries[0].mmproj_url
+
+
+def test_remap_dead_bartowski_abliterate_url(tmp_path: Path):
+    dead = (
+        "https://huggingface.co/bartowski/huihui-ai_Qwen2.5-7B-Instruct-abliterated-GGUF/"
+        "resolve/main/huihui-ai_Qwen2.5-7B-Instruct-abliterated-Q4_K_M.gguf"
+    )
+    fixed = remap_llamacpp_url(dead)
+    assert "RichardErkhov" in fixed
+    assert "Q4_K_M.gguf" in fixed
+    path = tmp_path / "lc.yaml"
+    path.write_text(f"models:\n  - url: {dead}\n    default: true\n", encoding="utf-8")
+    entries = parse_llamacpp_models(path)
+    assert len(entries) == 1
+    assert entries[0].url == fixed