3 Commits

Include renames

Author	SHA1	Message	Date
kamilkrzywda	cdd52a3ddb	Send #rss get summaries as 3-5 separate mesh messages (v0.21.0) ... The single-message summary was too small (owner request). The summarizer prompt now asks for exactly 3-5 lines, one item per line, in the format '<short header>: <one or two short sentences>' with a <=20-char header, no intro/outro/numbering. maxTokens stays 2500 (reasoning-token headroom). The reply is parsed into items: drop empty lines and lines without a ':' header separator, cap at 5; fewer than 3 valid lines sends what we got (no failure/retry), zero valid lines sends nothing. Each item goes out as its own mesh message via respond(id, line) - all threaded to the trigger packet id on its channel. Per-item backstop fitOneLine() hard-cuts any line >185 chars at a word boundary near 180 so every item fits one packet; the old whole-reply fitOnePacket() cut is gone. CommandService sends array replies line by line through the same routing as single replies (respond per line, or legacy sendText fallback per line when there is no packet id). LLM failure path unchanged: single 'summary failed' reply.	2026-09-25 20:09:16 +00:00
kamilkrzywda	e2d712a26c	Cap #rss get summaries to one mesh packet (v0.20.1) ... Replies >~190 chars fragment into fire-and-forget packets recipients often never receive; old prompt produced ~326-334 char replies. Prompt now asks for at most 3 short bullet lines, each under 45 chars, bullets only (verified live: exactly 3 compliant bullets, ~110 chars). fitOnePacket() backstop cuts any over-length reply at complete-bullet boundaries so delivery is one packet even if the model ignores the prompt. maxTokens 200 -> 2500 on the summary chat(): empirically verified that this server's reasoning tokens count against max_tokens (cap 150 -> completion 150 of which 105 were reasoning; cap 500 fully consumed by reasoning, zero visible content) and thinking is uncontrollable server-side (/no_think, chat_template_kwargs.enable_thinking, thinking_budget all ignored), observed 32..1776 tokens for this task. 2500 covers every observed run + ~80 content tokens, worst case ~42 s under the 60 s LLM timeout.	2026-09-25 19:22:13 +00:00
kamilkrzywda	eda1cbd125	Add #rss command family with LLM tags and summaries (v0.20.0) ... #rss subcommands on the command channel: help / add <url> <name> / remove <name> / tags / sources / get <name|#tag>. Sources are stored in a new rss_sources table in the existing MESH_DB_PATH file (second node:sqlite connection, case-insensitive names); feeds parsed with fast-xml-parser (RSS 2.0 + Atom); AI tags and headline summaries via injected LlmService.chat() with bounded maxTokens (50/200). CommandService gains prefix registration so one handler owns the whole #rss family while #ping stays an exact match; wired in CommandModule's factory — still no constructor-level cycle, no forwardRef. One dead feed does not sink a tag summary.	2026-09-25 18:44:06 +00:00