lastchat-catalog

name lastchat-catalog description Use this skill whenever you need to add, edit, or review entries in the LastChat model catalog (catalog/lastchat_catalog.json). Covers the resolution pipeline, family/version/override hierarchy, modality rules, provider UUIDs, and step-by-step checklists for adding new models, families, and providers correctly. LastChat Catalog — Authoring Guide The catalog ( catalog/lastchat_catalog.json ) is the source-of-truth for model metadata, provider presets, and service provider registries. It is a layered inheritance system . Always express metadata through the highest applicable layer — avoid repeating fields that a parent layer already provides. 1. Top-Level Sections JSON key Kotlin type Purpose providers List<CatalogProvider> Preset AI provider configs (base URL, auth type, icon, setup defaults) model_families List<CatalogModelFamily> Pattern-based metadata inherited by all matching model IDs global_rules List<CatalogModelRule> Cross-family rules evaluated before family matching model_overrides List<CatalogModelOverride> Exact-ID entries; primarily bind model IDs to provider UUIDs search_providers List<CatalogServiceProvider> Web search service registry tts_providers List<CatalogTTSProvider> Text-to-speech provider registry stt_providers List<CatalogServiceProvider> Speech-to-text provider registry Kotlin data models live in: app/src/main/java/me/rerere/rikkahub/data/ai/models/ModelCatalog.kt 2. Resolution Pipeline For every model ID the app encounters, metadata is built up in this exact order. Each layer overrides the previous : 1. global_rules — pattern rules across all families (e.g. "embed" → EMBEDDING type) 2. model_families — family defaults: type, icon, modalities, abilities, provider_slug 3. └─ versions — sub-patterns within a family that override specific fields 4. model_overrides — exact ID + provider_id match; sets provider_ids and narrow corrections The builder starts empty and each matched layer is applied with applyRule → applyFamily → applyVersion → applyOverride . A model is only resolved if at least one rule matched ( hasMatchedRule = true ). Critical: Icon Resolution CatalogModelOverride has no icon field . Icons are always inherited from the matched model_families entry (set via builder.iconUrl = matchedFamily.icon?.toCatalogIconUrl() ). Never put an icon in a model_overrides entry — it will be silently ignored. 3. ModelType Values Value Meaning Auto input modality Auto output modality CHAT Conversational LLM ["TEXT"] ["TEXT"] EMBEDDING Vector embedding model ["TEXT"] ["TEXT"] IMAGE Image generation ["TEXT"] ["IMAGE"] STT Speech-to-text transcription ["AUDIO"] ["TEXT"] toModelTypeOrNull() in ModelMetadataResolver.kt maps these strings: String → ModelType "chat" CHAT "embedding" EMBEDDING "image" , "image_generation" IMAGE "stt" STT 4. Modality Rules "AUDIO" must only appear in input_modalities of ModelType.STT entries. Chat models must never have "AUDIO" in their input_modalities — there is no audio-to-chat pipeline in the app. The UI modality selector only exposes TEXT and IMAGE for user-editable chat models. "AUDIO" in output_modalities is not used by any current feature. 5. Layer-by-Layer Authoring Guide 5.1 model_families — Define a family when models share a brand/architecture name Required fields: id , match_patterns , icon , type Optional: input_modalities , output_modalities , abilities , provider_slug , versions { "id" : "whisper" , "aliases" : [ "whisper" ] , "match_patterns" : [ "whisper" , "distil-whisper" ] , "icon" : "icons/openai.svg" , "type" : "STT" , "input_modalities" : [ "AUDIO" ] , "output_modalities" : [ "TEXT" ] , "abilities" : [ ] , "provider_slug" : "openai" , "versions" : [ ] } match_patterns are regex patterns tested against the model ID and its canonical form. Use anchors like (^|[/._-]) and (?=$|[:/._-]) to avoid false positives. Available icons: All SVG files in catalog/icons/ . Common ones: openai.svg , gemini.svg , claude.svg , groq.svg , deepseek.svg , mistral.svg , meta.svg , qwen.svg , siliconflow.svg , dashscope.svg , deepinfra.svg , fireworks.svg , together.svg , volcengine.svg , minimax.svg , zhipu.svg , aihubmix.svg , novita.svg , gemma.svg , internlm.svg , baidu.svg , spark.svg 5.2 versions (inside a family) — Override specific fields for model sub-variants Use a version when a subset of models within a family differs in type , input_modalities , output_modalities , abilities , or reasoning_behavior . Fields are nullable — only set what differs from the family default: { "id" : "gpt-transcribe" , "match_patterns" : [ "gpt-.*-transcribe" ] , "type" : "STT" , "input_modalities" : [ "AUDIO" ] , "output_modalities" : [ "TEXT" ] , "abilities" : [ ] } { "id" : "gemini-image" , "match_patterns" : [ "gemini.*image" ] , "type" : "IMAGE" , "image_generation_method" : "multimodal" , "input_modalities" : [ "TEXT" , "IMAGE" ] , "output_modalities" : [ "IMAGE" ] , "abilities" : [ ] } Versions are matched in order — first match wins within a family. 5.3 model_overrides — Bind model IDs to provider UUIDs (and nothing else if possible) The minimal correct form is only three fields : { "id" : "whisper-large-v3" , "canonical_model_id" : "whisper-large-v3" , "provider_ids" : [ "f9fe0a18-2b30-46e1-9c57-5562654e8d64" ] } Only add extra fields when the model genuinely needs to differ from its matched family: { "id" : "dall-e-3" , "canonical_model_id" : "dall-e-3" , "provider_ids" : [ "8f9d0c75-8f29-4a27-9c2b-f8d4fd5f3e91" ] , "type" : "IMAGE" , "image_generation_method" : "diffusion" , "input_modalities" : [ "TEXT" ] , "output_modalities" : [ "IMAGE" ] } 5.4 reasoning_config — Declare model reasoning mode & UI behavior Can be set on model_families , versions , or model_overrides : { "reasoning_config" : { "type" : "effort" , "supported_levels" : [ "off" , "auto" , "low" , "medium" , "high" , "max" ] } } "binary" : Models with a simple on/off thinking toggle (e.g. DeepSeek-R1, Grok, Doubao, InternLM). UI renders a clean 2-item toggle (Disabled vs Enabled). "effort" : Models with qualitative depth scales (e.g. OpenAI o1/o3/o4/gpt-5.6, Gemini 3). UI displays qualitative options without misleading token numbers. "budget" : Models taking token budgets (e.g. Claude 3.7+, Gemini 2.5, DashScope Qwen). Supports min_tokens , max_tokens , and preset_tokens . 5.5 context_window and max_images_in_context Both fields are optional, but strongly recommended for completeness. They can be set at any layer — family, version, or override. { "context_window" : 1000000 , "max_images_in_context" : 100 } context_window (integer, in tokens): The maximum input context the model supports. Common correct values by family (as of 2026): Family context_window GPT-5.6 Sol/Terra 1 050 000 GPT-5.6 Luna 512 000 GPT-4o, GPT-4o-mini 128 000 o1, o3, o4-mini 200 000 Claude 5 (all) 1 000 000 Claude 3.7/3.5 Sonnet 1 000 000 (beta) Claude 3.5 Haiku 200 000 Gemini 1.5 Pro 2 000 000 Gemini 2.0/2.5/3.0 1 000 000 Gemma 4 (31B, 26B A4B) 256 000 Gemma 4 (E4B, E2B) 128 000 Gemma 3 (27B, 12B, 4B) 128 000 Gemma 2 (27B, 9B, 2B) 8 192 Llama 4 Scout 10 000 000 Llama 4 Maverick 1 000 000 DeepSeek-V4 Pro/Flash 1 000 000 (Max output 384k) DeepSeek-V4 Vision Exp 1 000 000 (Vision: TEXT+IMAGE) DeepSeek-VL2 128 000 (Vision: TEXT+IMAGE) DeepSeek-V3, R1 128 000 Mistral Large 2 128 000 Mistral Small 4 256 000 Pixtral 12B / Large 128 000 Qwen 3 (3.8-Max, 3.5, 3-VL) 1 000 000 (Vision: TEXT+IMAGE) Qwen-Plus, Qwen-Turbo, Qwen-Long 1 000 000 Qwen-Max 262 144 Qwen 2.5-VL, QvQ-72B 131 072 (Vision: TEXT+IMAGE) QwQ-32B, Qwen 2.5 131 072 Grok 3/3-mini 131 072 Grok 4 256 000 MiniMax-M3 1 000 000 MiniMax-M2.x 204 800 Kimi K3 1 000 000 Kimi K2.5 256 000 Moonshot V1 128 000 Hunyuan-T1, TurboS 256 000 StepFun 3.5/3.7 Flash 256 000 GLM-5, 5.2 1 000 000 GLM-5V-Turbo, 5.3 Flash 200 000 max_images_in_context (integer): Maximum images the model can accept in a single request. Only set when the model actually accepts image input. Omit for text-only and embedding models. Family max_images_in_context Gemini (all vision) 3 600 Claude (all) 100 GPT-5.6 Sol/Terra, o3, o4-mini 50 GPT-4o 50 Gemma 4 / Gemma 3 (vision) 10 Llama 4 (multimodal) 10 Pixtral Large 30 Pixtral 12B 30 MiniMax-M3, M2 Vision 10 Kimi K3, K2.5 10 GLM-5V, 5.3 Flash 10 Qwen VL / 3.8 (vision) 50 Tip : When in doubt about the exact limit, use a conservative lower bound rather than an inflated number. max_images_in_context is a UX hint, not enforced at the API call layer. api_aliases can list alternate API IDs that map to the same canonical model: { "id" : "gemini-2.5-flash-image" , "canonical_model_id" : "gemini-2.5-flash-image" , "api_aliases" : [ "models/gemini-2.5-flash-image" , "nano-banana" ] , "provider_ids" : [ "4e28ef61-8b96-4a1e-9f91-15b32ce6d886" ] } 5.4 global_rules — Cross-family rules applied to every model ID Useful for patterns that span families, e.g. auto-classifying any model ID containing embed as an embedding model: { "id" : "global-embedding" , "match_patterns" : [ "embed" ] , "type" : "EMBEDDING" , "input_modalities" : [ "TEXT" ] , "output_modalities" : [ "TEXT" ] , "abilities" : [ ] } 5.5 providers — Preset AI provider configs { "id" : "f9fe0a18-2b30-46e1-9c57-5562654e8d64" ,