dsh: offer the local .27 Ollama models in the chat model dropdown
The dropdown is built from the hardcoded MODEL_CHOICES list in app.py, not from OmniRoute, so 'ollama/qwen2.5*' existed upstream but could never appear in DSH. - add ollama/qwen2.5:14b and ollama/qwen2.5-coder:14b to MODEL_CHOICES + MODEL_LABELS - labels note that Ollama must be started first, since it now boots off on .27 - docs/dsh-architecture.md: new section on model selection, incl. the rebuild requirement (app.py is baked into the image via COPY . .) and the ordering trap that a model can be live in OmniRoute yet invisible in DSH Verified: /api/models lists both ids on 3081-3084, and real streamed replies come back from both local models through DSH.
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@@ -77,7 +77,40 @@ DSH routes user requests across specialized AI services and local house infrastr
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---
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## 5. API Endpoints & Request Flow
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## 5. Model Selection (the chat dropdown)
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**The model list is hardcoded in `dsh/app.py`** (`MODEL_CHOICES`, ~line 660). DSH does
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**not** discover models from OmniRoute. `GET /api/models` simply returns that list
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plus `MODEL_LABELS` for the friendly names.
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Consequence: a model can exist in OmniRoute and still be invisible in DSH until it
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is added to `MODEL_CHOICES` **and** `MODEL_LABELS`.
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A chosen model is validated server-side (`if active_model not in MODEL_CHOICES:
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active_model = LLM_MODEL`), so an unlisted id silently falls back to the default.
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### Adding a model
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1. Confirm it works through OmniRoute first — `curl http://127.0.0.1:20129/v1/models`
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and then a real `chat/completions` call with a short timeout.
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2. Add the id to `MODEL_CHOICES` and a friendly string to `MODEL_LABELS` in
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`dsh/app.py`.
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3. Deploy: copy `app.py` to `.13:/home/sam/Docker/Containers/dsh/`, then
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`docker compose build && docker compose up -d` in that directory (the image
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bakes `app.py` via `COPY . .`, so a rebuild is required — restarting is not enough).
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4. Verify: `curl -s http://127.0.0.1:3081/api/models` should list the new id.
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### Local Ollama models
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The `.27` models are exposed by OmniRoute as `ollama/qwen2.5:14b` and
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`ollama/qwen2.5-coder:14b` (`ollama-local/…` also exists but is duplicated).
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Because Ollama now starts **off** at boot, these fail until it is started from the
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family console; hence the `needs Ollama on` label. Inference is CPU-only on `.27`,
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so expect it to be slower than the cloud routes.
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---
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## 6. API Endpoints & Request Flow
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### Primary API Routes (`dsh/app.py`)
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@@ -96,7 +129,7 @@ DSH routes user requests across specialized AI services and local house infrastr
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---
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## 6. Embedding & Security Headers
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## 8. Embedding & Security Headers
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To support seamless inline framing inside the Family Home Lab Console (`/tool/dsh`):
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- **Content Security Policy (CSP)**: `frame-ancestors https://console.lab.audasmedia.com.au`
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@@ -104,7 +137,7 @@ To support seamless inline framing inside the Family Home Lab Console (`/tool/ds
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---
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## 7. Environment Variables Reference
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## 9. Environment Variables Reference
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| Variable | Default Value | Purpose |
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| :--- | :--- | :--- |
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@@ -665,6 +665,11 @@ MODEL_CHOICES = ["auto/best-chat",
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"auto/best-reasoning",
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"auto/best-coding",
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"auto/best-vision",
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# Local models on .27, reached through OmniRoute. Free to run, but
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# Ollama must be started first (family console -> AI Tools ->
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# Ollama Local LLM). CPU inference, so slower than the cloud ones.
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"ollama/qwen2.5:14b",
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"ollama/qwen2.5-coder:14b",
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"openrouter/deepseek/deepseek-v4-flash",
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"openrouter/deepseek/deepseek-v4-pro"]
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MODEL_LABELS = {
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@@ -676,6 +681,8 @@ MODEL_LABELS = {
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"auto/best-reasoning": "Reasoning · OmniRoute best",
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"auto/best-coding": "Coding · OmniRoute best",
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"auto/best-vision": "Multimodal · OmniRoute vision",
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"ollama/qwen2.5:14b": "Local · Qwen2.5 14B (.27, needs Ollama on)",
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"ollama/qwen2.5-coder:14b": "Local · Qwen2.5 Coder 14B (.27, needs Ollama on)",
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"openrouter/deepseek/deepseek-v4-flash": "DeepSeek v4 flash (OpenRouter)",
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"openrouter/deepseek/deepseek-v4-pro": "DeepSeek v4 pro (OpenRouter)",
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}
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