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.
This commit is contained in:
@@ -104,6 +104,10 @@ struct ModelsSpec {
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/// Static model-id catalog (provider exposes no listing endpoint).
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#[serde(rename = "static")]
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static_models: Option<Vec<String>>,
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/// Keep only listed models whose string-array field (dotted path, e.g.
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/// `metadata.tags`) contains a value — a catalog that also serves
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/// non-chat kinds (tts, embed, image…) would flood the picker.
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filter: Option<FilterSpec>,
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#[serde(default)]
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map: MapSpec,
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#[serde(default)]
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@@ -122,8 +126,17 @@ enum AuthSpec {
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None,
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}
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#[derive(Debug, serde::Deserialize)]
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struct FilterSpec {
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/// Dotted path of a string-array field (e.g. `metadata.tags`).
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field: String,
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/// Required array member (e.g. `chat`).
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contains: String,
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}
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/// Per-model JSON field names → `RemoteLlmModelInfo` fields. Absent mappings
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/// leave the corresponding field `None` (id defaults to `"id"`, name to id).
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/// Field names accept dotted paths (`metadata.pricing.input_tokens`).
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#[derive(Debug, Default, serde::Deserialize)]
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struct MapSpec {
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id: Option<String>,
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@@ -138,6 +151,13 @@ struct MapSpec {
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/// capability name → boolean JSON field that enables it.
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#[serde(default)]
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capability_flags: HashMap<String, String>,
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/// Dotted path of a string-array field carrying the model's feature tags
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/// (e.g. `metadata.tags`); read by `capability_tags`.
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tags: Option<String>,
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/// capability name → tag value: the capability is enabled when the tags
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/// array (at `tags`) contains the tag.
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#[serde(default)]
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capability_tags: HashMap<String, String>,
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}
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#[derive(Debug, Default, serde::Deserialize)]
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@@ -335,7 +355,7 @@ impl DeclaredProvider {
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fn map_model(&self, m: &serde_json::Value, models: &ModelsSpec) -> Option<RemoteLlmModelInfo> {
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let map = &models.map;
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let get = |f: &Option<String>| f.as_deref().map(|k| &m[k]);
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let get = |f: &Option<String>| f.as_deref().and_then(|k| get_path(m, k));
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let id = get(&map.id)
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.or_else(|| Some(&m["id"]))
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.and_then(|v| v.as_str())?
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@@ -358,10 +378,28 @@ impl DeclaredProvider {
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add_cap("vision");
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}
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for (cap, field) in &map.capability_flags {
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if m[field].as_bool().unwrap_or(false) {
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if get_path(m, field).and_then(|v| v.as_bool()).unwrap_or(false) {
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add_cap(cap);
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}
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}
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if let Some(tags) = map
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.tags
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.as_deref()
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.and_then(|p| get_path(m, p))
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.and_then(|v| v.as_array())
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{
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let has = |tag: &str| tags.iter().any(|t| t.as_str() == Some(tag));
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for (cap, tag) in &map.capability_tags {
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if has(tag) {
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add_cap(cap);
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}
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}
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// A tag-derived vision capability also sets the vision flag — the
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// same sync apply_enrich keeps between the two.
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if vision.is_none() && map.capability_tags.get("vision").is_some_and(|t| has(t)) {
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vision = Some(true);
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}
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}
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Some(RemoteLlmModelInfo {
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id,
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name,
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@@ -405,7 +443,10 @@ impl DeclaredProvider {
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.as_array()
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.cloned()
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.ok_or_else(|| anyhow!("unexpected {who} response shape"))?;
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raw.iter().filter_map(|m| self.map_model(m, models)).collect()
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raw.iter()
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.filter(|m| passes_filter(m, models.filter.as_ref()))
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.filter_map(|m| self.map_model(m, models))
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.collect()
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};
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for info in &mut list {
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apply_enrich(&models.enrich, info);
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@@ -414,6 +455,28 @@ impl DeclaredProvider {
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}
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}
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/// Resolves a possibly-dotted field path (`metadata.pricing.input_tokens`)
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/// against a model JSON object. A bare key behaves like a flat lookup; any
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/// missing segment yields `None`.
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fn get_path<'a>(v: &'a serde_json::Value, path: &str) -> Option<&'a serde_json::Value> {
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let mut cur = v;
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for part in path.split('.') {
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cur = cur.get(part)?;
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}
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Some(cur)
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}
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/// Whether a raw catalog entry passes the optional listing filter: no filter
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/// keeps everything, otherwise the entry's string-array field must contain
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/// the required value.
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fn passes_filter(m: &serde_json::Value, filter: Option<&FilterSpec>) -> bool {
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filter.is_none_or(|f| {
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get_path(m, &f.field)
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.and_then(|v| v.as_array())
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.is_some_and(|a| a.iter().any(|t| t.as_str() == Some(f.contains.as_str())))
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})
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}
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/// Applies the first matching enrich rule (later rules are not consulted).
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fn apply_enrich(rules: &[EnrichRule], info: &mut RemoteLlmModelInfo) {
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let Some(rule) = rules.iter().find(|r| glob_match(&r.glob, &info.id)) else {
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@@ -828,6 +891,54 @@ mod tests {
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assert!(info.capabilities.iter().any(|c| c == "video"));
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}
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#[test]
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fn dotted_paths_filter_and_capability_tags() {
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let p = provider(
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r#"
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id: t
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name: T
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base_url: http://x
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ui: { color: c, icon: i }
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models:
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endpoint: /models
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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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tags: metadata.tags
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capability_tags: { vision: vision, reasoning_effort: reasoning_effort }
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"#,
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);
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let models = p.spec.models.as_ref().unwrap();
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let m = serde_json::json!({
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"id": "acme/x",
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"metadata": {
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"context_length": 131072,
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"pricing": { "input_tokens": 0.5 },
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"tags": ["chat", "vision", "reasoning_effort"]
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}
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});
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let info = p.map_model(&m, models).unwrap();
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assert_eq!(info.context_length, Some(131072));
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assert_eq!(info.price_input_per_million, Some(0.5));
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assert_eq!(info.vision, Some(true));
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assert!(info.capabilities.iter().any(|c| c == "vision"));
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assert!(info.capabilities.iter().any(|c| c == "reasoning_effort"));
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// The filter keeps only entries whose tags array holds the value.
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assert!(passes_filter(&m, models.filter.as_ref()));
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let tts = serde_json::json!({ "id": "acme/tts", "metadata": { "tags": ["tts"] } });
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assert!(!passes_filter(&tts, models.filter.as_ref()));
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assert!(passes_filter(&tts, None));
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// Dotted lookups miss cleanly on absent segments.
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let bare = serde_json::json!({ "id": "acme/plain" });
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let info = p.map_model(&bare, models).unwrap();
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assert_eq!(info.context_length, None);
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assert_eq!(info.vision, None);
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assert!(!info.capabilities.iter().any(|c| c == "vision"));
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}
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/// The catalog shipped at the repository root must always parse: the file
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/// is runtime data, but this test keeps a typo from reaching users.
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#[test]
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+42
-1
@@ -23,11 +23,19 @@
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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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# map: per-model JSON field names, all optional:
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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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@@ -157,6 +165,39 @@ providers:
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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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