leetcrypt 69bce5ead8 feat(ai): stream agent replies token-by-token to the room ... Closes the cross-language half of token streaming (perf-plan A3). On the CPU-only box perceived latency is time-to-first-token, so showing the reply as it generates makes a slow model feel live. - Agent: OllamaProvider.stream() runs on a worker thread; bridge relays cumulative previews as throttled (~5/sec) `_ai:"stream"` control frames, then a `done` frame clears the preview as the final persisted chat message is posted. Providers without stream() fall back to blocking complete(). - Rust client: new Net::AiStream variant + parse_ai branch; App.ai_stream map holds the in-progress text per agent; draw_chat renders it as a dim, italic preview bubble below history. Cleared on done and on agent leave. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>		2026-06-02 22:42:08 -07:00
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__init__.py	feat(agent): model-agnostic AI agent bridge (PoC) + pin lets-hack demo to main	2026-06-01 02:05:48 -07:00
__main__.py	perf(ai): CPU-tuned local inference + qwen2.5-coder sandbox path	2026-06-02 22:37:59 -07:00
bridge.py	feat(ai): stream agent replies token-by-token to the room	2026-06-02 22:42:08 -07:00
memory.py	feat(ai): in-RAM semantic recall (RAG) for conversation context	2026-06-02 17:59:01 -07:00
profiles.py	feat(ai): model profiles, capability discovery, and agentless /ai list|models	2026-06-01 15:25:07 -07:00
providers.py	perf(ai): CPU-tuned local inference + qwen2.5-coder sandbox path	2026-06-02 22:37:59 -07:00