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

tests/README.md

@@ -9,7 +9,7 @@ tool servers, and agent process.
 - The container is up: `docker compose up -d` (and healthy)
 - Host deps installed: `pip install -r tests/requirements.txt`
   (or `uv pip install -r tests/requirements.txt`)
-- The LLM at `GEMMA_BASE_URL` (default `http://192.168.86.2:8023/v1`) is reachable
+- The LLM at `LLM_BASE_URL` (default `http://192.168.86.2:3005/api`, OpenWebUI) is reachable
 - Internet access for the weather tool tests (wttr.in)
 
 ## Run
@@ -25,10 +25,10 @@ python -m pytest tests/ -v -m "not slow"   # skip LLM/network-heavy tests
 | File | Target | Notes |
 |------|--------|-------|
 | `test_web_ui.py` | nginx HTTPS UI (:9178) + token endpoint (:8091) | static assets, `/token` (direct + via nginx), `/livekit/` proxy |
-| `test_llm_api.py` | Gemma LLM API directly | completion, tool calling, `enable_thinking=false` latency, streaming |
+| `test_llm_api.py` | LLM API directly | completion, tool calling, `enable_thinking=false` latency, streaming |
 | `test_mcp_tools.py` | MCP servers via `docker exec` | weather/time, authenticated remote memory save/recall/delete, and local skills — probes are cleaned up |
 | `test_agent_integration.py` | running container | agent process alive, worker registered with LiveKit, all 4 supervised processes up, container health, LiveKit HTTP API |
-| `test_compaction.py` | `GemmaLLM._compact_context` in-container | compaction triggers >24 items, system prompt preserved, short context untouched |
+| `test_compaction.py` | `HopeLLM._compact_context` in-container | compaction triggers >24 items, system prompt preserved, short context untouched |
 
 ## Notes
 

tests/conftest.py

@@ -3,7 +3,7 @@
 Tests run on the HOST machine against the live "voice" container:
 - HTTPS web UI  -> https://localhost:9178 (self-signed cert, verify=False)
 - Token server  -> http://127.0.0.1:8091 (host network mode)
-- LLM API       -> GEMMA_BASE_URL (default http://192.168.86.2:8023/v1)
+- LLM API       -> LLM_BASE_URL (default http://192.168.86.2:3005/api)
 - In-container  -> docker exec voice ...
 """
 
@@ -18,8 +18,21 @@ import pytest
 CONTAINER = "voice"
 WEB_BASE_URL = os.environ.get("VOICE_WEB_URL", "https://localhost:9178")
 TOKEN_URL = os.environ.get("VOICE_TOKEN_URL", "http://127.0.0.1:8091/token")
-GEMMA_BASE_URL = os.environ.get("GEMMA_BASE_URL", "http://192.168.86.2:8023/v1").rstrip("/")
-GEMMA_MODEL = os.environ.get("GEMMA_MODEL", "gemma-4-e4b")
+LLM_BASE_URL = (
+    os.environ.get("LLM_BASE_URL")
+    or os.environ.get("GEMMA_BASE_URL")
+    or "http://192.168.86.2:3005/api"
+).rstrip("/")
+LLM_MODEL = (
+    os.environ.get("LLM_MODEL")
+    or os.environ.get("GEMMA_MODEL")
+    or "gemma-4-e4b"
+)
+LLM_API_KEY = (
+    os.environ.get("LLM_API_KEY")
+    or os.environ.get("GEMMA_API_KEY")
+    or "not-needed"
+)
 _users = json.loads((Path(__file__).parents[1] / "config" / "users.json").read_text())
 _shane_memory = _users["users"]["shane"]["memory"]
 MEMORY_MCP_URL = os.environ.get("MEMORY_MCP_URL", _shane_memory["url"])
@@ -88,8 +101,11 @@ def token() -> dict:
 
 @pytest.fixture(scope="session")
 def llm_client():
-    """httpx client pointed at the Gemma LLM API (same one Hope uses)."""
-    with httpx.Client(base_url=GEMMA_BASE_URL, timeout=60) as c:
+    """httpx client pointed at the LLM API (same one Hope uses)."""
+    headers = {}
+    if LLM_API_KEY and LLM_API_KEY != "not-needed":
+        headers["Authorization"] = f"Bearer {LLM_API_KEY}"
+    with httpx.Client(base_url=LLM_BASE_URL, headers=headers, timeout=60) as c:
         yield c
 
 

tests/test_compaction.py

@@ -1,26 +1,27 @@
-"""Tests for GemmaLLM context compaction (agent.GemmaLLM._compact_context).
+"""Tests for HopeLLM context compaction (agent.HopeLLM._compact_context).
 
-Compaction runs a real side LLM call to the xNAS, so these are marked slow.
-The agent module is imported inside the container via docker exec.
+Compaction runs a real side LLM call to the configured endpoint, so these
+are marked slow. The agent module is imported inside the container via
+docker exec.
 """
 
 import pytest
 
-from conftest import GEMMA_BASE_URL, GEMMA_MODEL, docker_exec_python
+from conftest import LLM_BASE_URL, LLM_MODEL, docker_exec_python
 
 # {num_messages} and {do_chat} are filled per test; all other braces are literal.
 TEMPLATE = '''
-import logging, sys
+import logging, os, sys
 from livekit.agents import llm as lk_llm
 sys.path.insert(0, "/opt/voice-agent")
-from agent import GemmaLLM
+from agent import HopeLLM
 
 logging.basicConfig(level=logging.INFO, stream=sys.stdout)
 
-llm = GemmaLLM(
+llm = HopeLLM(
     model="{model}",
     base_url="{base_url}",
-    api_key="not-needed",
+    api_key=os.environ.get("LLM_API_KEY", "not-needed"),
     max_completion_tokens=100,
     extra_body={{"chat_template_kwargs": {{"enable_thinking": False}}}},
 )
@@ -44,7 +45,7 @@ async def main():
     print("AFTER items=" + str(len(compacted.items)))
     for it in compacted.items:
         role = getattr(it, "role", None)
-        content = GemmaLLM._msg_content_text(it)
+        content = HopeLLM._msg_content_text(it)
         print("ITEM " + str(role) + ": " + content[:120])
 
     {do_chat}
@@ -57,8 +58,8 @@ CHAT_SNIPPET = '    stream = llm.chat(chat_ctx=compacted)\n    collected = await
 
 def _run(num_messages: int, *, do_chat: bool = False) -> str:
     code = TEMPLATE.format(
-        model=GEMMA_MODEL,
-        base_url=GEMMA_BASE_URL,
+        model=LLM_MODEL,
+        base_url=LLM_BASE_URL,
         num_messages=num_messages,
         do_chat=CHAT_SNIPPET if do_chat else "pass",
     )

tests/test_llm_api.py

@@ -1,10 +1,10 @@
-"""Tests for the Gemma LLM API — the exact endpoint Hope's agent uses."""
+"""Tests for the LLM API — the exact endpoint Hope's agent uses."""
 
 import time
 
 import pytest
 
-from conftest import GEMMA_BASE_URL, GEMMA_MODEL
+from conftest import LLM_BASE_URL, LLM_MODEL
 
 WEATHER_TOOL = {
     "type": "function",
@@ -22,7 +22,7 @@ WEATHER_TOOL = {
 
 def _chat(llm_client, messages, *, tools=None, stream=False, max_tokens=200):
     payload = {
-        "model": GEMMA_MODEL,
+        "model": LLM_MODEL,
         "messages": messages,
         "max_tokens": max_tokens,
         "temperature": 0.3,