refactor(ai): read LLM settings from LlmConfig instead of env

Every LLM env reader now goes through ai::config::llm_config():
build_ollama / build_llamacpp / build_openrouter take config sections
(OPENROUTER_API_KEY is still read from env), and the backend switch,
embedding dim + prefixes, Ollama / llama.cpp / TTS timeouts, TTS voice and
ref length, agentic caps, chat turn timeout and the unified-search model
read their sections. LocalLlm::from_env -> from_config; the
test_daily_summary and populate_knowledge bins take Ollama defaults from
the config. env_max_iterations / env_default_num_ctx are renamed to
max_chat_iterations / default_num_ctx.

The picker still uses picker.include (= LLAMA_SWAP_ALLOWED_MODELS) until
discovery lands. Legacy env vars keep working through the config's
override layer; checked against the deployed .env, which resolves to the
same values. The LLM_BACKEND parsing tests move to ai::config.

llm.example.toml now leaves the embed prefixes empty: copying the
nomic prefixes onto a corpus embedded without them breaks search.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

src/bin/reembed_embeddings.rs

@@ -284,7 +284,7 @@ async fn main() -> Result<()> {
     let mut conn = SqliteConnection::establish(&database_url)
         .with_context(|| format!("connecting to {}", database_url))?;
 
-    let llm = LocalLlm::from_env();
+    let llm = LocalLlm::from_config();
     let model_version = llm.embedding_model_version();
     println!("Embedding via '{}'", model_version);
     if args.dry_run {