Cameron CordesandClaude Opus 5.5
aa3536afee
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>
76 lines
3.5 KiB
TOML
76 lines
3.5 KiB
TOML
# ImageApi LLM configuration. Copy to `llm.toml` next to `.env` (or point
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# LLM_CONFIG_PATH at it). Every key is optional; omitted keys use the
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# defaults shown in the comments.
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#
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# Secrets stay in env: OPENROUTER_API_KEY enables the hybrid backend.
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#
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# The local model catalog (which models exist, vision, context size) is NOT
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# listed here. It is discovered from llama-swap's /v1/models, using each
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# model's `metadata:` block in llama-swap/config.yaml (kind/vision/ctx/dim).
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#
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# The old env vars (LLAMA_SWAP_*, OLLAMA_*, OPENROUTER_* except the key,
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# EMBED_*, EMBEDDING_DIM, AGENTIC_*, LLM_BACKEND, UNIFIED_SEARCH_MODEL) still
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# work for now and OVERRIDE this file, with a deprecation warning at startup.
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# Local stack for chat, vision describe and embeddings: "ollama" | "llamacpp".
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# Global on purpose: don't flip it without re-embedding (mixed vector spaces
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# break similarity search).
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backend = "llamacpp"
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# Small model pinned for /photos/search/unified query translation, so it can
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# stay loaded alongside CLIP. Unset = the client's selected model.
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unified_search_model = "gemma4-e4b"
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[llamacpp]
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url = "http://localhost:9292/v1" # unset = llama.cpp client + TTS disabled
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chat = "qwen3.8-27b-abliterated" # default chat model (default "chat")
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vision = "qwen3.8-27b-code-vision" # describe_photo model (default: chat)
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timeout_secs = 180
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# The picker shows every llama-swap model with `kind: chat` metadata (param
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# aliases like `:sub` / `:fast` are always hidden), minus `exclude`.
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# `include`, if set, is a strict allowlist instead.
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[llamacpp.picker]
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exclude = ["nemotron3.5-lightning-30b-A3B"]
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# include = ["qwen3.8-27b-code", "gemma4-31"]
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[embedding]
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# Must all agree with what the stored corpus was embedded with. Changing any
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# of them means `cargo run --bin reembed_embeddings`.
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model = "embed" # llama-swap id (Ollama always uses nomic-embed-text:v1.5)
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dim = 768 # 768 nomic v1.5 | 1024 Qwen3-Embedding-0.6B
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# Prefixes default to empty. Set them only together with a re-embed; a
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# corpus embedded without them won't match queries embedded with them.
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query_prefix = "" # nomic v1.5: "search_query: " | Qwen3: "Instruct: <task>\nQuery: "
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document_prefix = "" # nomic v1.5: "search_document: " | Qwen3: ""
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[tts]
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# Chatterbox behind llama-swap; needs llamacpp.url but not backend = "llamacpp".
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model = "chatterbox"
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voice = "m" # default voice when a request omits one (unset = server default)
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ref_seconds = 30 # max voice-clone reference clip length
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timeout_secs = 600 # long chunked text takes minutes
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[ollama]
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primary_url = "http://localhost:11434"
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primary_model = "nemotron-3-nano:30b"
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# Tried on connection failure. fallback_model unset = reuse primary_model.
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# fallback_url = "http://server:11434"
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# fallback_model = "llama3.2:3b"
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timeout_secs = 120
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[openrouter]
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default_model = "anthropic/claude-sonnet-4"
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allowed = ["openai/gpt-4o-mini", "anthropic/claude-haiku-4-5", "google/gemini-2.5-flash"]
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max_tokens = 16384 # 0 = uncapped (OpenRouter reserves credit against it)
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# base_url = "https://openrouter.ai/api/v1"
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# embedding_model = "openai/text-embedding-3-small"
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# http_referer = "https://your-site.example"
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# app_title = "ImageApi"
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[agentic]
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max_iterations = 12 # tool-loop cap for agentic insight generation
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chat_max_iterations = 6 # per chat turn; per-request values are clamped to it
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chat_default_num_ctx = 32768 # assumed window when neither request nor backend reports one
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chat_turn_timeout_secs = 300 # reconnectable chat turns are dropped after this
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