feat(provider): add v4 effort ladder and wire mapping

src/provider/deepseek-v4-effort.test.ts

@@ -0,0 +1,53 @@
+import { describe, test, expect } from "bun:test";
+import {
+  DEEPSEEK_V4_EFFORTS,
+  isDeepSeekV4Model,
+  mapV4Effort,
+} from "./deepseek-v4-effort.js";
+
+describe("isDeepSeekV4Model", () => {
+  test.each([
+    "deepseek-v4",
+    "deepseek-v4-pro",
+    "deepseek-v4-flash",
+    "deepseek-v4-flash-vision-exp",
+  ])("true for V4 id %s", (model) => {
+    expect(isDeepSeekV4Model(model)).toBe(true);
+  });
+  test.each([
+    "deepseek-v3",
+    "deepseek-r1",
+    "gpt-5",
+    "kimi-k2",
+    "claude-sonnet-4.5",
+    "glm-5.3",
+    "grok-4.6",
+    "some-proxy-deepseek-v4-pro",
+  ])("false for non-V4 id %s", (model) => {
+    expect(isDeepSeekV4Model(model)).toBe(false);
+  });
+});
+
+describe("DEEPSEEK_V4_EFFORTS", () => {
+  test("ladder is none/xhigh/max", () => {
+    expect(DEEPSEEK_V4_EFFORTS).toEqual(["none", "xhigh", "max"]);
+  });
+});
+
+describe("mapV4Effort", () => {
+  test.each([
+    ["xhigh", "xhigh"],
+    ["max", "max"],
+  ] as const)("maps %s raw to %s", (effort, wire) => {
+    expect(mapV4Effort(effort)).toBe(wire);
+  });
+  test("maps none to null (drop the wire effort)", () => {
+    expect(mapV4Effort("none")).toBeNull();
+  });
+  test.each(["low", "medium", "high"] as const)(
+    "maps off-ladder %s to undefined",
+    (effort) => {
+      expect(mapV4Effort(effort)).toBeUndefined();
+    },
+  );
+});

src/provider/deepseek-v4-effort.ts

@@ -0,0 +1,30 @@
+import type { ReasoningEffort } from "../agent/profile-types.js";
+
+// DeepSeek V4 effort translator shared by the adapter and the effort picker.
+// V4 ships under several ids across two catalogs — deepseek-v4-pro/-flash/
+// -flash-vision-exp — so the family is matched by prefix rather than an exact
+// id list, mirroring the grok/kimi/muse-spark prefix predicates elsewhere.
+export function isDeepSeekV4Model(model: string): boolean {
+  return /^deepseek-v4/i.test(model.trim());
+}
+
+// The native V4 rungs. `none` is a toggle, never a wire effort; `xhigh`/`max`
+// are the wire rungs sent raw (the API docs' low/high/max is the gateway
+// normalization layer, not what the model/encoder honors).
+export const DEEPSEEK_V4_EFFORTS: readonly ReasoningEffort[] = [
+  "none",
+  "xhigh",
+  "max",
+];
+
+// Translate a V4 effort to its raw wire value: `none` maps to null (the caller
+// drops `reasoning_effort`, since `reasoning_effort:"none"` is illegal on the
+// wire), `xhigh`/`max` pass through verbatim, and any off-ladder value returns
+// undefined so the caller leaves effort untouched.
+export function mapV4Effort(
+  effort: ReasoningEffort,
+): "xhigh" | "max" | null | undefined {
+  if (effort === "none") return null;
+  if (effort === "xhigh" || effort === "max") return effort;
+  return undefined;
+}

src/provider/openai-compatible-adapter.test.ts

@@ -164,3 +164,84 @@ describe("openai-compatible adapter reasoning_content handling", () => {
     expect(assistant?.["reasoning_content"]).toBe("ponder");
   });
 });
+
+describe("openai-compatible adapter V4 effort wiring", () => {
+  function bodyForModel(
+    model: string,
+    options: InferenceOptions,
+  ): Record<string, unknown> {
+    const adapter = createOpenAICompatibleAdapter({
+      ...source,
+      model,
+    } as typeof source);
+    const built = adapter.buildRequest(messages, model, options);
+    return JSON.parse(built.body) as Record<string, unknown>;
+  }
+
+  test("none drops reasoning_effort and sets thinking off", () => {
+    const body = bodyForModel("deepseek-v4-pro", {
+      providerOptions: { reasoning_effort: "none" },
+    } as InferenceOptions);
+    expect("reasoning_effort" in body).toBe(false);
+    expect(body["chat_template_kwargs"]).toEqual({ thinking: false });
+  });
+
+  test.each(["xhigh", "max"] as const)(
+    "maps ladder %s through verbatim",
+    (effort) => {
+      const body = bodyForModel("deepseek-v4-pro", {
+        providerOptions: { reasoning_effort: effort },
+      } as InferenceOptions);
+      expect(body["reasoning_effort"]).toBe(effort);
+    },
+  );
+
+  test.each(["low", "medium", "high"] as const)(
+    "leaves off-ladder %s untouched",
+    (effort) => {
+      const body = bodyForModel("deepseek-v4-pro", {
+        providerOptions: { reasoning_effort: effort },
+      } as InferenceOptions);
+      expect(body["reasoning_effort"]).toBe(effort);
+    },
+  );
+
+  describe("v4-effort is no-op for non-V4", () => {
+    const models = [
+      "gpt-5",
+      "gpt-5.1",
+      "kimi-k2",
+      "grok-4.6",
+      "claude-sonnet-4.5",
+      "glm-5.3",
+      "some-openai-compatible-model",
+      "deepseek-r1",
+      "deepseek-v3",
+    ];
+
+    test.each(models)(
+      "merged body for %s is byte-identical to a manual base+merge (V4 step no-op)",
+      (model) => {
+        const base = bodyForModel(model, {} as InferenceOptions);
+        const withEffort = bodyForModel(model, {
+          providerOptions: { reasoning_effort: "high" },
+        } as InferenceOptions);
+        const expected = {
+          ...base,
+          ...({ reasoning_effort: "high" } as const),
+        };
+        expect(withEffort).toEqual(expected);
+      },
+    );
+
+    test.each(models)(
+      "merged body for %s carries reasoning_effort verbatim",
+      (model) => {
+        const body = bodyForModel(model, {
+          providerOptions: { reasoning_effort: "high" },
+        } as InferenceOptions);
+        expect(body["reasoning_effort"]).toBe("high");
+      },
+    );
+  });
+});

src/provider/openai-compatible-adapter.ts

@@ -1,5 +1,7 @@
 import { type BuiltRequest, type ProviderAdapter } from "@intx/inference";
 import { createOpenAIAdapter } from "@intx/inference/providers";
+import type { ReasoningEffort } from "../agent/profile-types.js";
+import { isDeepSeekV4Model, mapV4Effort } from "./deepseek-v4-effort.js";
 import { normalizeNullDeltaFields } from "./null-delta-fields.js";
 
 // The stock OpenAI adapter builds the request body from a fixed set of fields
@@ -45,14 +47,41 @@ export function createOpenAICompatibleAdapter(
     const providerOptions = options.providerOptions;
     const hasProviderOptions =
       providerOptions !== undefined && Object.keys(providerOptions).length > 0;
+    // Normalize the model once so every predicate below reads from the same
+    // lower-cased, trimmed string rather than re-normalizing per call.
+    const m = model.toLowerCase().trim();
     // DeepSeek returns HTTP 400 if `reasoning_content` appears in input messages,
     // whereas the base adapter emits it for any model with thinking enabled.
-    const stripReasoning = model.toLowerCase().includes("deepseek");
+    const stripReasoning = m.includes("deepseek");
     needsDeepSeekPatch = stripReasoning;
+    const isV4 = isDeepSeekV4Model(m);
     if (!hasProviderOptions && !stripReasoning) return ensureAccept(built);
 
     const body = JSON.parse(built.body) as Record<string, unknown>;
     if (hasProviderOptions) Object.assign(body, providerOptions);
+    // V4's ladder (none/xhigh/max) is translated here: `none` drops
+    // reasoning_effort and toggles the encoder's thinking off (it is illegal
+    // on the wire), while `xhigh`/`max` go out raw. Effort absent under V4 is
+    // left absent. Off-ladder efforts (low/medium/high) are left untouched.
+    if (isV4) {
+      if ("reasoning_effort" in body) {
+        const raw = body["reasoning_effort"] as ReasoningEffort;
+        const wireEffort = mapV4Effort(raw);
+        if (wireEffort === null) {
+          delete body["reasoning_effort"];
+          // Merge into any existing kwargs so provider-supplied keys survive.
+          const kwargs =
+            body["chat_template_kwargs"] !== null &&
+            typeof body["chat_template_kwargs"] === "object"
+              ? (body["chat_template_kwargs"] as Record<string, unknown>)
+              : {};
+          kwargs.thinking = false;
+          Object.assign(body, { chat_template_kwargs: kwargs });
+        } else if (wireEffort !== undefined) {
+          body["reasoning_effort"] = wireEffort;
+        }
+      }
+    }
     if (stripReasoning && Array.isArray(body["messages"])) {
       for (const msg of body["messages"]) {
         if (msg !== null && typeof msg === "object")

src/provider/reasoning-effort.test.ts

@@ -116,6 +116,17 @@ describe("supportedEfforts", () => {
     expect(supportedEfforts("glm-5.3")).toEqual(["low", "high", "max"]);
   });
 
+  test("V4 model gets the native none/xhigh/max ladder", () => {
+    expect(supportedEfforts("deepseek-v4-pro")).toEqual([
+      "none",
+      "xhigh",
+      "max",
+    ]);
+  });
+  test("pre-V4 deepseek-v3 stays on the unknown-model subset", () => {
+    expect(supportedEfforts("deepseek-v3")).toEqual(["low", "medium", "high"]);
+  });
+
   // Every catalog Muse Spark id reaches supportedEfforts unnormalized, so
   // they must all land on the same ladder — two ids pin the family rule.
   test.each(["muse-spark-1.3-contributor", "muse-spark-1.3-contributor-free"])(
@@ -175,6 +186,15 @@ describe("validateEffort", () => {
     expect(validateEffort("glm-5.3", "medium").ok).toBe(false);
     expect(validateEffort("glm-5.3", "max")).toEqual({ ok: true });
   });
+
+  test("V4 accepts none/xhigh/max and rejects medium (and low/high)", () => {
+    for (const effort of ["none", "xhigh", "max"] as const) {
+      expect(validateEffort("deepseek-v4-pro", effort)).toEqual({ ok: true });
+    }
+    for (const effort of ["medium", "low", "high"] as const) {
+      expect(validateEffort("deepseek-v4-pro", effort).ok).toBe(false);
+    }
+  });
 });
 
 describe("cycleReasoningEffort", () => {
@@ -448,6 +468,10 @@ describe("defaultEffortForModel", () => {
     expect(defaultEffortForModel("glm-5.3")).toBe("max");
   });
 
+  test("V4 model defaults to max", () => {
+    expect(defaultEffortForModel("deepseek-v4-pro")).toBe("max");
+  });
+
   test("gpt-5 and o-series default to medium", () => {
     expect(defaultEffortForModel("gpt-5")).toBe("medium");
     expect(defaultEffortForModel("o4-mini")).toBe("medium");

src/provider/reasoning-effort.ts

@@ -7,6 +7,10 @@
 // profile schema and the runtime cannot drift. Re-exported here for callers
 // that already import from this module.
 import { REASONING_EFFORTS as CANONICAL_EFFORTS } from "../agent/profile-types.js";
+import {
+  DEEPSEEK_V4_EFFORTS,
+  isDeepSeekV4Model,
+} from "./deepseek-v4-effort.js";
 
 export const REASONING_EFFORTS = CANONICAL_EFFORTS;
 export type ReasoningEffort = (typeof REASONING_EFFORTS)[number];
@@ -186,6 +190,9 @@ export function supportedEfforts(
   if (GLM_53_MODELS.includes(model)) {
     return [...GLM_53_EFFORTS];
   }
+  if (isDeepSeekV4Model(model)) {
+    return [...DEEPSEEK_V4_EFFORTS];
+  }
   if (isMuseSparkModel(model)) {
     return [...MUSE_SPARK_EFFORTS];
   }
@@ -287,6 +294,7 @@ export function defaultEffortForModel(
   }
   if (model.startsWith("grok")) return pick("high");
   if (GLM_53_MODELS.includes(model)) return pick("max");
+  if (isDeepSeekV4Model(model)) return pick("max");
   if (isMuseSparkModel(model)) return pick("low");
   if (!isCodex && supported.includes("none")) return "none";
   if (isCodex || isKnownOpenAIReasoningModel(model)) return pick("medium");