feat: switch LLM to OpenWebUI with live model selection
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- Point the agent at OpenWebUI's OpenAI-compatible API (LLM_BASE_URL,
LLM_API_KEY, LLM_MODEL) with GEMMA_* env fallbacks
- Add list_available_models() fetching {base_url}/models, filtering
non-chat ids (embedding/reranker)
- Rename GemmaLLM -> HopeLLM with update_options(model=...) for runtime
model switching (mutates _opts.model) and instance-based compaction
- Data channel: agent publishes {type: models} after connect and on
get_models; set_model switches live and acks model_changed
- Web UI: Brain section in the settings sheet with a model picker that
persists the choice in localStorage
- Update tests, CI workflow env, and docs for the new endpoint
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@@ -9,7 +9,7 @@ tool servers, and agent process.
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- The container is up: `docker compose up -d` (and healthy)
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- Host deps installed: `pip install -r tests/requirements.txt`
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(or `uv pip install -r tests/requirements.txt`)
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- The LLM at `GEMMA_BASE_URL` (default `http://192.168.86.2:8023/v1`) is reachable
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- The LLM at `LLM_BASE_URL` (default `http://192.168.86.2:3005/api`, OpenWebUI) is reachable
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- Internet access for the weather tool tests (wttr.in)
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## Run
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@@ -25,10 +25,10 @@ python -m pytest tests/ -v -m "not slow" # skip LLM/network-heavy tests
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| File | Target | Notes |
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|------|--------|-------|
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| `test_web_ui.py` | nginx HTTPS UI (:9178) + token endpoint (:8091) | static assets, `/token` (direct + via nginx), `/livekit/` proxy |
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| `test_llm_api.py` | Gemma LLM API directly | completion, tool calling, `enable_thinking=false` latency, streaming |
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| `test_llm_api.py` | LLM API directly | completion, tool calling, `enable_thinking=false` latency, streaming |
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| `test_mcp_tools.py` | MCP servers via `docker exec` | weather/time, authenticated remote memory save/recall/delete, and local skills — probes are cleaned up |
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| `test_agent_integration.py` | running container | agent process alive, worker registered with LiveKit, all 4 supervised processes up, container health, LiveKit HTTP API |
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| `test_compaction.py` | `GemmaLLM._compact_context` in-container | compaction triggers >24 items, system prompt preserved, short context untouched |
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| `test_compaction.py` | `HopeLLM._compact_context` in-container | compaction triggers >24 items, system prompt preserved, short context untouched |
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## Notes
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