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DeepInfra's chat API is plain OpenAI-compatible (api.deepinfra.com/v1/openai)
and its GET /models returns the OpenAI data envelope, but the declared
engine could not describe it: metadata sits under dotted paths
(metadata.context_length, metadata.pricing.*), capabilities ride a
metadata.tags string array, and the catalog mixes in tts/stt/embed/image
models with no way to keep only chat ones.
Three generic extensions to the declared engine close that, usable by any
future provider entry:
- map field names accept dotted paths (metadata.pricing.input_tokens)
- map.tags + map.capability_tags enable a capability when the model's
tags array contains a value (a vision one also sets the vision flag)
- models.filter { field, contains } keeps only listed models whose
string-array field holds the value (endpoint listings only)
The deepinfra entry filters on the chat tag, maps context/pricing/vision/
reasoning from the live catalog, and wires the flat reasoning_effort knob
(disabled remaps to none) for models tagged reasoning_effort.
214 lines
9.5 KiB
YAML
214 lines
9.5 KiB
YAML
# Declarative OpenAI-compatible LLM providers.
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#
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# Loaded at boot from this file (resolved against the process working
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# directory, like config.yml) — edit and `restart`, no rebuild needed. An
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# invalid entry is logged and skipped; native providers (anthropic, ollama,
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# openai, openrouter — whose behavior is not plain OpenAI-compatible) are
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# unaffected. Entries whose `id` collides with a native provider are skipped.
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#
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# Entry shape (optional unless noted):
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# id: unique type id stored in the DB (required)
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# name: display name (required)
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# kind: openai_compatible — the only kind for now
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# base_url: chat base URL, OpenAI-compatible (required)
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# base_url_overridable: the DB instance's base_url overrides this default
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# api_key: required | optional | none (default: required)
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# prompt_cache: true | false (default: false)
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# dtl: DTL wire format for this provider's models that carry
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# the `tool_search` capability: kimi_system_tools (default: none)
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# ui: { color, icon, description } (color/icon required)
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# fields: UI form fields [{ key, label, required, secret }]
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# models: remote catalog config — omit to disable listing:
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# endpoint: GET path joined to models_url (OpenAI `data` envelope)
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# models_url: defaults to the resolved base_url
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# auth: bearer | none (default: bearer unless api_key: none)
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# static: [model ids] — alternative to endpoint
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# filter: { field, contains } — keep only listed models whose
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# string-array field (dotted path, e.g. metadata.tags)
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# contains the value (endpoint listings only)
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# map: per-model JSON field names, all optional; every
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# field name accepts a dotted path
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# (e.g. metadata.pricing.input_tokens):
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# id / name / context_length / max_completion_tokens / knowledge_cutoff
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# vision: <bool field> (also adds the `vision` capability)
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# price_input_per_million / price_output_per_million: <number field>
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# capability_flags: { <capability>: <bool field> } (e.g. reasoning)
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# tags: <string-array field> (e.g. metadata.tags)
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# capability_tags: { <capability>: <tag> } — on when tags contains tag
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# (a `vision` one also sets the vision flag)
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# base_capabilities: capabilities every listed model gets
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# defaults: { vision: bool } — used when the source omits it
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# enrich: first-matching rule wins, glob on the model id
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# (`*` is the only wildcard, case-insensitive):
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# - match: "k3*" prefix / "*reasoner*" contains / "glm-5" exact
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# mode: fill | override fill keeps endpoint values (default),
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# override lets the rule win
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# context_length / max_completion_tokens / vision / add_capabilities
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# reasoning: reasoning knob — omit when models don't reason:
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# request: how the selected value reaches the request body:
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# { kind: effort, remap: { disabled: none } } {"reasoning_effort": v}
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# { kind: thinking } {"thinking": {...}} (+effort)
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# modes: first-matching rule wins:
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# - when: { models: [globs], capability: name } both present = OR;
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# values: [...] absent = every model
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# default: ...
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providers:
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- id: moonshot
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name: "Moonshot AI pay-as-you-go"
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base_url: "https://api.moonshot.ai/v1"
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dtl: kimi_system_tools
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ui:
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color: "#2563eb"
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icon: "bi-moon-stars"
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description: "Kimi models on the Moonshot AI platform (OpenAI-compatible)"
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fields:
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- { key: api_key, label: "API Key", required: true, secret: true }
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models:
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endpoint: /models
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map:
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context_length: context_length
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vision: supports_image_in
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capability_flags:
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reasoning: supports_reasoning
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base_capabilities: [function_calling]
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- id: moonshot_code
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name: "Moonshot AI Kimi Code"
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base_url: "https://api.kimi.com/coding/v1"
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dtl: kimi_system_tools
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ui:
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color: "#000000"
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icon: "bi-code-slash"
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description: "Kimi Code subscription models — k3 / kimi-for-coding (OpenAI-compatible)"
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fields:
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- { key: api_key, label: "API Key", required: true, secret: true }
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models:
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endpoint: /models
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map:
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context_length: context_length
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vision: supports_image_in
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capability_flags:
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reasoning: supports_reasoning
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base_capabilities: [function_calling]
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# Fills the metadata the endpoint may omit (endpoint values always win):
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# k3 → 1M context + native vision and video input; kimi-for-coding → 256k.
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enrich:
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- { match: "k3*", context_length: 1048576, vision: true, add_capabilities: [video, tool_search] }
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- { match: "kimi-for-coding*", context_length: 262144 }
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reasoning:
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# k3 exposes a graded reasoning_effort ("disabled" routes to K2.6);
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# kimi-for-coding always thinks and has no knob.
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request: { kind: effort, remap: { disabled: none } }
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modes:
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- when: { models: ["k3*"] }
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values: [disabled, low, high, max]
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default: max
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- id: deepseek
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name: "DeepSeek"
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base_url: "https://api.deepseek.com/v1"
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ui:
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color: "#0ea5e9"
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icon: "bi-search"
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fields:
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- { key: api_key, label: "API Key", required: true, secret: true }
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models:
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endpoint: /models
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models_url: "https://api.deepseek.com"
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map:
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context_length: context_length
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base_capabilities: [function_calling]
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# Known metadata wins over whatever the endpoint returns.
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enrich:
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- { match: "*coder*", context_length: 16384, mode: override }
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- { match: "*reasoner*", context_length: 65536, mode: override, add_capabilities: [reasoning] }
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- { match: "deepseek-v4*", context_length: 1048576, mode: override, max_completion_tokens: 393216 }
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- { match: "deepseek-chat*", context_length: 65536, mode: override }
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- { match: "deepseek-v3*", context_length: 65536, mode: override }
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reasoning:
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# Thinking toggle + graded reasoning_effort; low/medium map to high
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# server-side, xhigh to max.
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request: { kind: thinking }
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modes:
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- when: { capability: reasoning, models: ["*reasoner*", "deepseek-v4*"] }
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values: [disabled, low, medium, high, xhigh, max]
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default: high
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- id: zai
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name: "Z.AI"
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base_url: "https://api.z.ai/api/paas/v4"
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ui:
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color: "#4f46e5"
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icon: "bi-stars"
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description: "Zhipu AI GLM models (OpenAI-compatible)"
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fields:
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- { key: api_key, label: "API Key", required: true, secret: true }
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models:
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# Z.AI exposes no GET /models endpoint; this mirrors the console menu.
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static: [glm-5.2, glm-5.1, glm-5, glm-5-turbo, glm-4.7, glm-4.6, glm-4.5, glm-4-32b-0414-128k]
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defaults: { vision: false }
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base_capabilities: [function_calling]
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enrich:
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- { match: "*128k*", context_length: 131072 }
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- { match: "glm-5*", context_length: 1048576 }
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- { match: "glm-4.7*", context_length: 200000 }
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- { match: "glm-4.6*", context_length: 200000 }
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- { match: "glm-4.5*", context_length: 131072 }
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reasoning:
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request: { kind: thinking }
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modes:
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# GLM-5.2+ adds a graded effort on top of the thinking toggle.
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- when: { models: ["glm-5.2*"] }
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values: [disabled, minimal, low, medium, high, xhigh, max]
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default: max
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- when: { models: ["glm-5*", "glm-4.7*", "glm-4.6*", "glm-4.5*"] }
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values: [disabled, enabled]
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default: enabled
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- id: deepinfra
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name: "DeepInfra"
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base_url: "https://api.deepinfra.com/v1/openai"
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ui:
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color: "#4C59D3"
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icon: "bi-lightning-charge"
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description: "Hosted open-source model inference (OpenAI-compatible)"
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fields:
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- { key: api_key, label: "API Key", required: true, secret: true }
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models:
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endpoint: /models
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# The catalog also serves tts/stt/embed/image/video models; keep LLMs.
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filter: { field: metadata.tags, contains: chat }
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map:
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context_length: metadata.context_length
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price_input_per_million: metadata.pricing.input_tokens
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price_output_per_million: metadata.pricing.output_tokens
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tags: metadata.tags
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capability_tags:
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vision: vision
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reasoning: reasoning
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reasoning_effort: reasoning_effort
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base_capabilities: [function_calling]
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reasoning:
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# Flat reasoning_effort (none/minimal/low/medium/high/xhigh/max);
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# "none" disables reasoning where the model supports it. Models tagged
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# `reasoning` but not `reasoning_effort` always think — no knob.
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request: { kind: effort, remap: { disabled: none } }
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modes:
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- when: { capability: reasoning_effort }
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values: [disabled, minimal, low, medium, high, xhigh, max]
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default: high
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- id: lm_studio
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name: "LM Studio"
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base_url: "http://localhost:1234/v1"
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base_url_overridable: true
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api_key: none
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ui:
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color: "#6b7280"
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icon: "bi-window-stack"
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description: "Local models via LM Studio"
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fields:
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- { key: base_url, label: "Base URL", required: false, secret: false }
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models:
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endpoint: /models
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