Files
buzz/scripts/model-capabilities.json
T
npub1mn7jgtj4w2pd0g0zeuhxsa6jy6p0rewxz4kujt98my82ahfmp72sxjexk7andWill Pfleger 60fc24b0c6 fix(models): round-3 corrective pass — boundary strip, gpt-version-segment, 6-axis corpus, validation symmetry, prototype-leak
- stripCatalogPrefix boundary-aligned: customgpt/sgpt/mygpt no longer false-strip
  to gpt-* forms; boundary check requires position 0 or non-alphanumeric precursor
- New match_kind gpt-version-segment: gpt-neox-20b routes mlflow-chat (was residual
  collision); gpt segment match requires next segment to start with digit or be
  dashless gpt5 form
- PROVIDER_FALLBACKS Record→Map: constructor/__proto__ prototype-key leak closed;
  resolveModelCapabilities/getProviderEffortConfig return complete records for all
  provider strings
- Corpus 69→77 vectors, all 6-axis mandatory; JS and Rust runners hard-fail on missing
  axes; prototype-key vectors added; boundary-negative vectors added (sgpt-5-5,
  mygpt-5, customgpt-5-5-endpoint all route mlflow-chat); gpt-neox-20b pinned as
  mlflow-chat (corrected behavior, not residual collision)
- Manifest validator 33→42 tests: family match_priority integer guard, lowercase
  duplicate-key detection, post-inheritance materialized default∈supported check,
  assertEfforts shared helper covering family/fallback/exact
- Clippy: map_or(false)→is_some_and in emitter template; fmt clean
- Desktop regression tests: constructor/__proto__ prototype-key stability

Co-authored-by: Will Pfleger <pfleger.will@gmail.com>
Signed-off-by: Will Pfleger <pfleger.will@gmail.com>
2026-08-04 15:30:06 -04:00

899 lines
26 KiB
JSON

{
"_comment": "Hand-curated model capability manifest. Edit here; run scripts/generate-model-capabilities.mjs to regenerate artifacts.",
"_generated_by": "scripts/generate-model-capabilities.mjs",
"_sources": {
"models_dev": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0)",
"anthropic_thinking": "https://platform.claude.com/docs/en/build-with-claude/extended-thinking (July 2025)",
"anthropic_effort": "https://platform.claude.com/docs/en/build-with-claude/effort (July 2025)",
"openai_reasoning": "https://platform.openai.com/docs/guides/reasoning (July 2025)",
"goose_known_models": "goose revision 6789d4af (crates/goose-providers/src/databricks_v2.rs:41-42) \u2014 two IDs: databricks-gpt-5-5, databricks-claude-opus-4-7"
},
"family_tokens": [
"claude-",
"gpt-"
],
"family_rules": [
{
"id": "anthropic-manual-budget-claude3",
"match_kind": "prefix",
"match_value": "claude-3",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "manual-budget",
"supported_efforts": [
"low",
"medium",
"high"
],
"default_effort": null,
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none"
},
{
"id": "anthropic-manual-budget-opus-4-5",
"match_kind": "exact",
"match_value": "claude-opus-4-5",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "manual-budget",
"supported_efforts": [
"low",
"medium",
"high"
],
"default_effort": null,
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Opus 4.5"
},
{
"id": "anthropic-adaptive-xhigh-opus-4-7",
"match_kind": "prefix",
"match_value": "claude-opus-4-7",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Opus 4.7"
},
{
"id": "anthropic-adaptive-xhigh-opus-4-8",
"match_kind": "prefix",
"match_value": "claude-opus-4-8",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Opus 4.8"
},
{
"id": "anthropic-adaptive-xhigh-opus-5",
"match_kind": "prefix",
"match_value": "claude-opus-5",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Opus 5"
},
{
"id": "anthropic-adaptive-xhigh-sonnet-5",
"match_kind": "prefix",
"match_value": "claude-sonnet-5",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Sonnet 5"
},
{
"id": "anthropic-adaptive-xhigh-fable-5",
"match_kind": "prefix",
"match_value": "claude-fable-5",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Fable 5"
},
{
"id": "anthropic-adaptive-xhigh-mythos-5",
"match_kind": "prefix",
"match_value": "claude-mythos-5",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Mythos 5"
},
{
"id": "anthropic-adaptive-no-xhigh-opus-4-6",
"match_kind": "prefix",
"match_value": "claude-opus-4-6",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Opus 4.6"
},
{
"id": "anthropic-adaptive-no-xhigh-sonnet-4-6",
"match_kind": "prefix",
"match_value": "claude-sonnet-4-6",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Sonnet 4.6"
},
{
"id": "anthropic-adaptive-no-xhigh-mythos-preview",
"match_kind": "prefix",
"match_value": "claude-mythos-preview",
"providers": [
"anthropic",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none",
"registry_label": "Claude Mythos Preview"
},
{
"id": "openai-gpt5-pro",
"match_kind": "gpt5-token",
"match_value": "gpt-5-pro",
"match_aliases": [
"gpt5-pro"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 20,
"thinking_mode": "none",
"supported_efforts": [
"high"
],
"default_effort": "high",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5 Pro"
},
{
"id": "openai-gpt5-6",
"match_kind": "gpt5-token",
"match_value": "gpt-5.6",
"match_aliases": [
"gpt5.6",
"gpt-5-6",
"gpt5-6"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 15,
"thinking_mode": "none",
"supported_efforts": [
"none",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5.6"
},
{
"id": "openai-gpt5-5",
"match_kind": "gpt5-token",
"match_value": "gpt-5.5",
"match_aliases": [
"gpt5.5",
"gpt-5-5",
"gpt5-5"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 15,
"thinking_mode": "none",
"supported_efforts": [
"none",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5.5"
},
{
"id": "openai-gpt5-4",
"match_kind": "gpt5-token",
"match_value": "gpt-5.4",
"match_aliases": [
"gpt5.4",
"gpt-5-4",
"gpt5-4"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 15,
"thinking_mode": "none",
"supported_efforts": [
"none",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5.4"
},
{
"id": "openai-gpt5-1",
"match_kind": "gpt5-token",
"match_value": "gpt-5.1",
"match_aliases": [
"gpt5.1",
"gpt-5-1",
"gpt5-1"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 15,
"thinking_mode": "none",
"supported_efforts": [
"none",
"low",
"medium",
"high"
],
"default_effort": "none",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5.1"
},
{
"id": "openai-gpt5-base",
"match_kind": "gpt5-base",
"match_value": "gpt-5",
"match_aliases": [
"gpt5"
],
"providers": [
"openai",
"databricks",
"databricks_v2"
],
"match_priority": 10,
"thinking_mode": "none",
"supported_efforts": [
"minimal",
"low",
"medium",
"high"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-standard",
"registry_label": "GPT-5"
},
{
"id": "dbv2-claude-code-names-segment",
"_comment": "DBv2-only rule: endpoint names containing a Claude code-name segment (opus, sonnet, haiku, mythos, fable, claude) route via Anthropic Messages. This matches goose-opus-5 (segments: goose,opus,5) etc. Effort classification uses conservative defaults because prefix-stripped alias ('opus-5') is not a recognized Claude family.",
"match_kind": "segment",
"match_value": "claude",
"match_aliases": [
"opus",
"sonnet",
"haiku",
"mythos",
"fable"
],
"providers": [
"databricks_v2"
],
"match_priority": 5,
"thinking_mode": "omit-fields",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"databricks_v2_wire_route": "anthropic-messages",
"normalization_policy": "none"
},
{
"id": "dbv2-gpt-code-names-segment",
"_comment": "DBv2-only rule: models whose normalized alias has 'gpt' as a segment followed by a numeric segment (e.g. databricks-gpt-5.5 \u2192 'gpt' seg + '5' seg) route via OpenAI Responses. 'gpt5' dashless alias catches gpt5-custom forms. match_kind=gpt-version-segment: token must be an exact segment AND the next segment must start with a digit \u2014 prevents gptoss/gptj (no 'gpt' segment) AND gpt-neox-20b ('gpt' segment but next segment 'neox' is not numeric). Priority 6 > dbv2-claude's 5.",
"match_kind": "gpt-version-segment",
"match_value": "gpt",
"providers": [
"databricks_v2"
],
"match_priority": 6,
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-clamp-max-to-xhigh",
"match_aliases": [
"gpt5"
]
},
{
"id": "dbv2-sol-luna-terra-segment",
"_comment": "DBv2-only rule: sol/luna/terra are OpenAI code names. Route via OpenAI Responses. Must use segment match to avoid matching substrings (consolidated-llama has 'sol' but not as a segment).",
"match_kind": "segment",
"match_value": "sol",
"match_aliases": [
"luna",
"terra"
],
"providers": [
"databricks_v2"
],
"match_priority": 5,
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"databricks_v2_wire_route": "openai-responses",
"normalization_policy": "openai-clamp-max-to-xhigh"
}
],
"_comment_registry_labels": "All 30 Databricks v2 endpoint-ID to display-name pairs. Represented as [{id,label}] array so duplicate-ID detection is structurally possible. Generated into DATABRICKS_MODEL_NAMES in both Rust and TS.",
"registry_labels": [
{
"id": "databricks-claude-haiku-4-5",
"label": "Claude Haiku 4.5 (latest)"
},
{
"id": "databricks-claude-opus-4-1",
"label": "Claude Opus 4.1 (latest)"
},
{
"id": "databricks-claude-opus-4-5",
"label": "Claude Opus 4.5 (latest)"
},
{
"id": "databricks-claude-opus-4-6",
"label": "Claude Opus 4.6"
},
{
"id": "databricks-claude-opus-4-7",
"label": "Claude Opus 4.7"
},
{
"id": "databricks-claude-sonnet-4",
"label": "Claude Sonnet 4.5"
},
{
"id": "databricks-claude-sonnet-4-5",
"label": "Claude Sonnet 4.5 (latest)"
},
{
"id": "databricks-claude-sonnet-4-6",
"label": "Claude Sonnet 4.6"
},
{
"id": "databricks-gemini-2-5-flash",
"label": "Gemini 2.5 Flash"
},
{
"id": "databricks-gemini-2-5-pro",
"label": "Gemini 2.5 Pro"
},
{
"id": "databricks-gemini-3-1-flash-lite",
"label": "Gemini 3.1 Flash Lite Preview"
},
{
"id": "databricks-gemini-3-1-pro",
"label": "Gemini 3.1 Pro Preview Custom Tools"
},
{
"id": "databricks-gemini-3-flash",
"label": "Gemini 3 Flash Preview"
},
{
"id": "databricks-gemini-3-pro",
"label": "Gemini 3 Pro Preview"
},
{
"id": "databricks-glm-5-2",
"label": "GLM-5.2"
},
{
"id": "databricks-gpt-5",
"label": "GPT-5"
},
{
"id": "databricks-gpt-5-1",
"label": "GPT-5.1"
},
{
"id": "databricks-gpt-5-2",
"label": "GPT-5.2"
},
{
"id": "databricks-gpt-5-4",
"label": "GPT-5.4"
},
{
"id": "databricks-gpt-5-4-mini",
"label": "GPT-5.4 mini"
},
{
"id": "databricks-gpt-5-4-nano",
"label": "GPT-5.4 nano"
},
{
"id": "databricks-gpt-5-5",
"label": "GPT-5.5"
},
{
"id": "databricks-gpt-5-6-luna",
"label": "GPT-5.6 Luna"
},
{
"id": "databricks-gpt-5-6-sol",
"label": "GPT-5.6 Sol"
},
{
"id": "databricks-gpt-5-6-terra",
"label": "GPT-5.6 Terra"
},
{
"id": "databricks-gpt-5-mini",
"label": "GPT-5 Mini"
},
{
"id": "databricks-gpt-5-nano",
"label": "GPT-5 Nano"
},
{
"id": "databricks-gpt-oss-120b",
"label": "GPT OSS 120B"
},
{
"id": "databricks-gpt-oss-20b",
"label": "GPT OSS 20B"
},
{
"id": "databricks-kimi-k2-7-code",
"label": "Kimi K2.7 Code"
}
],
"_comment_databricks_v2_known_models": "Authoritative list of Databricks v2 known model IDs. Mirrors goose DATABRICKS_V2_KNOWN_MODELS at revision 6789d4af (crates/goose-providers/src/databricks_v2.rs:41-42). Generated into DATABRICKS_V2_KNOWN_MODELS in both Rust and TS. Uniqueness enforced by the generator. Opt-in drift check: node scripts/generate-model-capabilities.mjs --check-goose",
"databricks_v2_known_models": [
"databricks-gpt-5-5",
"databricks-claude-opus-4-7"
],
"exact_records": [
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-4-mini",
"registry_label": "GPT-5.4 Mini",
"supported_efforts_override": [
"low",
"medium",
"high"
],
"source": "models.dev reasoning_options: low|medium|high (family rule adds none+xhigh \u2014 adopt provider-advertised)",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev advertises low|medium|high. Family rule (gpt5-4) adds none+xhigh. Provider-advertised wins per plan F1 policy.",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0): providers.databricks.models[\"databricks-gpt-5-4-mini\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\"]}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-4-nano",
"registry_label": "GPT-5.4 Nano",
"supported_efforts_override": [
"low",
"medium",
"high"
],
"source": "models.dev reasoning_options: low|medium|high",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev advertises low|medium|high. Same as gpt-5-4-mini. Adopt.",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0): providers.databricks.models[\"databricks-gpt-5-4-nano\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\"]}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-6-sol",
"registry_label": "GPT-5.6 Sol",
"supported_efforts_override": [
"low",
"medium",
"high",
"max"
],
"source": "models.dev reasoning_options: low|medium|high|max (family rule adds none+xhigh \u2014 provider-advertised wins per plan F1)",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev advertises [low, medium, high, max]. Family rule (gpt5-6) has none+xhigh+max; sol endpoint does not expose none or xhigh. Provider-advertised wins.",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0): providers.databricks.models[\"databricks-gpt-5-6-sol\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\",\"max\"]}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-5",
"registry_label": "GPT-5.5",
"source": "models.dev reasoning_options: low|medium|high (family rule adds none+xhigh \u2014 provider-advertised wins per plan F1)",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev (pinned payload) advertises [low, medium, high]. Family rule (gpt5-5) has none+xhigh; this Databricks endpoint does not expose none or xhigh. Provider-advertised wins.",
"supported_efforts_override": [
"low",
"medium",
"high"
],
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0): providers.databricks.models[\"databricks-gpt-5-5\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\"]}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-claude-opus-4-7",
"registry_label": "Claude Opus 4.7",
"source": "DATABRICKS_V2_KNOWN_MODELS; family rule anthropic-adaptive-xhigh-opus-4-7 applies",
"_reconciliation": "no-effort-divergence",
"_reconciliation_note": "models.dev advertises reasoning_options=[{\"type\":\"budget_tokens\",\"min\":1024}]. This is a different capability axis (extended thinking token budget), not an effort-level selector. No effort divergence to reconcile \u2014 efforts for this model come from the anthropic family rule (anthropic-adaptive-xhigh-opus-4-7).",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-07-31, SHA-256 d5a4974cd69f19b0f67713acaa6bb3b16e920defdc07ecbdf6b0a936181bb0e0): providers.databricks.models[\"databricks-claude-opus-4-7\"].reasoning_options=[{\"type\":\"budget_tokens\",\"min\":1024}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-6-luna",
"registry_label": "GPT-5.6 Luna",
"supported_efforts_override": [
"low",
"medium",
"high"
],
"source": "models.dev reasoning_options: low|medium|high",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev advertises [low, medium, high]. Family rule (gpt5-6) has none+xhigh+max; luna endpoint does not expose none, xhigh, or max. Provider-advertised wins.",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-08-04): providers.databricks.models[\"databricks-gpt-5-6-luna\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\"]}]"
},
{
"provider": "databricks_v2",
"raw_model_id": "databricks-gpt-5-6-terra",
"registry_label": "GPT-5.6 Terra",
"supported_efforts_override": [
"low",
"medium",
"high"
],
"source": "models.dev reasoning_options: low|medium|high",
"_reconciliation": "adopt",
"_reconciliation_note": "models.dev advertises [low, medium, high]. Family rule (gpt5-6) has none+xhigh+max; terra endpoint does not expose none, xhigh, or max. Provider-advertised wins.",
"_reconciliation_doc": "https://models.dev/api.json (retrieved 2026-08-04): providers.databricks.models[\"databricks-gpt-5-6-terra\"].reasoning_options=[{\"type\":\"effort\",\"values\":[\"low\",\"medium\",\"high\"]}]"
}
],
"provider_fallbacks": {
"anthropic": {
"blank": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "adaptive",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"normalization_policy": "none"
},
"concrete_unknown": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "omit-fields",
"supported_efforts": [
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "high",
"normalization_policy": "none"
}
},
"openai": {
"blank": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
},
"concrete_unknown": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
}
},
"databricks_v2": {
"blank": {
"databricks_v2_wire_route": "route-unknown",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
},
"concrete_unknown": {
"databricks_v2_wire_route": "mlflow-chat",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
}
},
"databricks": {
"blank": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
},
"concrete_unknown": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh"
],
"default_effort": "medium",
"normalization_policy": "openai-clamp-max-to-xhigh"
}
},
"openrouter": {
"blank": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"normalization_policy": "none"
},
"concrete_unknown": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"normalization_policy": "none"
}
},
"_default": {
"blank": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"normalization_policy": "none"
},
"concrete_unknown": {
"databricks_v2_wire_route": "not-applicable",
"thinking_mode": "none",
"supported_efforts": [
"none",
"minimal",
"low",
"medium",
"high",
"xhigh",
"max"
],
"default_effort": "medium",
"normalization_policy": "none"
}
}
}
}