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>

llm.example.toml

@@ -39,8 +39,10 @@ exclude = ["nemotron3.5-lightning-30b-A3B"]
 # of them means `cargo run --bin reembed_embeddings`.
 model = "embed"                        # llama-swap id (Ollama always uses nomic-embed-text:v1.5)
 dim = 768                              # 768 nomic v1.5 | 1024 Qwen3-Embedding-0.6B
-query_prefix = "search_query: "        # Qwen3: "Instruct: <task>\nQuery: "
-document_prefix = "search_document: "  # Qwen3: ""
+# Prefixes default to empty. Set them only together with a re-embed; a
+# corpus embedded without them won't match queries embedded with them.
+query_prefix = ""      # nomic v1.5: "search_query: " | Qwen3: "Instruct: <task>\nQuery: "
+document_prefix = ""   # nomic v1.5: "search_document: " | Qwen3: ""
 
 [tts]
 # Chatterbox behind llama-swap; needs llamacpp.url but not backend = "llamacpp".