The fake audio upstream bound the test host's loopback, which the Unraid
media server cannot reach (and its LAN route is firewalled). Local runs
keep the controlled upstream; remote runs use a public reference mp3 and
assert Range semantics without byte equality. docker-exec MCP probes
skip on remote targets (they necessarily exercise the local container).
The Unraid deployment's /media/api requests were answered by an
Apache/YOURLS stack squatting on 8092, surfacing as UI 503s; the CI
healthcheck (curl without -f) counted that 503 as healthy, so run #15
deployed green against a broken media server.
- media server port 8092 -> 8093 everywhere (server, MCP, agent, nginx,
compose, CI, .env.example, docs, tests).
- healthchecks use curl -f in compose and rebuild.yml so HTTP error
statuses fail deployment.
- tests default to the Unraid deployment (VOICE_WEB_URL=
https://192.168.86.2:9178); token goes through nginx (loopback :8091
is unreachable off-host); bind-mount-coupled tests skip on remote
targets. AGENTS.md documents the convention and both failure modes.
Small local models (qwen2.5-vl-3b, gemma-4-e4b) narrate actions ('Sure,
I'll pause the music') without emitting the tool call once the full
system prompt and 26-tool set are in context. Measured: qwen emitted
tools in 2/8 realistic intents, gemma 5/8; single-tool tests pass 100%,
so this is context-induced drift, not plumbing.
- agent/intent_router.py: deterministic forced-call router for
high-frequency intents — media controls, now_playing/list_library,
'remember that ...' memory saves, explicit YouTube Music searches,
and personal-fact recall (memory_recall/search_notes/skill_recall,
excluded for weather/time questions). Fires only when the tool is
available; guards against how-do-I questions.
- agent.py: generalize _ForcedToolCallStream to any tool; route through
intent_router after the dispatch check. System prompt adds a hard
'call, don't narrate' rule and reconditions 'answer directly'.
- tests/test_intent_router.py: 30 unit tests pinning router behavior.
Verified against the live LLM with the full fidelity harness: combined
forced-or-emitted coverage 8/8 on qwen2.5-vl-3b (was 2/8) and 8/8 on
gemma-4-e4b (was 5/8). Full suite: 79 passed.
Document the media server process, /media/ port map, library layout on
the ./media bind mount, Hope's media MCP toolset, the music/mic
mutual-exclusion rule, and yt-dlp download/proxy conventions.
- Default LLM_MODEL to qwen2.5-vl-3b across agent, task worker, tests,
compose, workflow, and docs
- Cap min/max length-style constraints in tool schemas to 1000 before
LLM requests; llama.cpp rejects grammar repetitions >= 2000 and the
memory MCP's update_note body maxLength (200000) broke qwen2.5-vl-3b
with 'Failed to initialize samplers: failed to parse grammar'
- 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
- Remove memory_mcp.py (stdio markdown-file memory)
- Add Cognee MCP as remote Streamable HTTP toolset at 192.168.86.2:8003/mcp
- Filter to only remember/recall/forget tools via allowed_tools
- Update system prompt: Memory section moved to top priority with
explicit 'call recall FIRST' instructions and examples
- Add COGNEE_MCP_URL env var to docker-compose
- Remove /memory volume mount (no longer needed)
- Rewrite memory tests to use Cognee HTTP client fixture
- 28/28 tests passing