- web/media_server.py: FastAPI service owning the permanent library
(library.json + ./media volume), yt-dlp YouTube Music search, queued
download jobs with mp3 transcode (ffmpeg), per-room player desired
state, and an HTTPS proxy for external live-stream URLs.
- agent/media_mcp.py: Hope tools — search_music, play_song,
offer_song_choices, pause/resume/stop/skip/seek, now_playing,
list_library, add_stream.
- agent/agent.py: media toolset wiring + conversation rule (music
playing disables the agent mic; re-engaging pauses music).
- web UI: slide-out Music panel (search, suggestions, library, live
stream add, play/pause, ±10s, seek, volume) with a reconciling poller
and media_state data-channel reports.
- token server returns the minted room name; nginx serves /media/files
as static (native Range) and proxies /media/api to the media server.
- supervisord runs media-server; compose mounts ./media and adds
ffmpeg to the image.
- 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
Compaction:
- GemmaLLM.chat() truncates ChatContext to last 30 items (~15 turns)
before sending to LLM, preventing context window overflow on long
conversations. Preserves system prompt and removes orphaned tool calls.
Skills:
- agent/skills_mcp.py: MCP server with skill_save, skill_recall,
skill_list, skill_update tools backed by .md files in /skills
- skills/ dir bind-mounted into container, git-trackable
- System prompt instructs Hope to save repeatable procedures as skills
and recall them before performing tasks she's done before
- Distinct from memory (facts) — skills are learned *procedures*
- agent/memory_mcp.py: MCP server with memory_recall, memory_save, memory_list
tools backed by .md files in /memory (simple keyword matching for v1)
- memory/ dir bind-mounted into container, persists across rebuilds,
easily backed up via git
- System prompt instructs Hope to recall on past references and save
personal info/preferences naturally without announcing it
- Dockerfile: copy memory_mcp.py; compose: ./memory:/memory volume
snowspeeder
Shane