feat: switch LLM to OpenWebUI with live model selection

- 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

agent/task_worker.py

@@ -1,7 +1,7 @@
 """Background task worker — runs an autonomous LLM loop with tools.
 
 Each dispatched task gets its own TaskWorker instance running in a separate
-asyncio task. The worker calls Gemma iteratively, executing tool calls and
+asyncio task. The worker calls the LLM iteratively, executing tool calls and
 logging each step to the registry so the UI can display live progress.
 """
 from __future__ import annotations
@@ -31,9 +31,21 @@ class TaskWorker:
         except ImportError:
             from task_registry import registry as reg
 
-        base_url = os.environ.get("GEMMA_BASE_URL", "http://192.168.86.2:8023/v1")
-        model = os.environ.get("GEMMA_MODEL", "gemma-4-e4b")
-        api_key = os.environ.get("GEMMA_API_KEY", "not-needed")
+        base_url = (
+            os.environ.get("LLM_BASE_URL")
+            or os.environ.get("GEMMA_BASE_URL")
+            or "http://192.168.86.2:3005/api"
+        )
+        model = (
+            os.environ.get("LLM_MODEL")
+            or os.environ.get("GEMMA_MODEL")
+            or "gemma-4-e4b"
+        )
+        api_key = (
+            os.environ.get("LLM_API_KEY")
+            or os.environ.get("GEMMA_API_KEY")
+            or "not-needed"
+        )
 
         reg.add_step(self.task_id, "thinking", f"Starting: {self.description}")