feat(models): add Eden AI model scanning

Add scanEdenAiModels() function to scan Eden AI's model registry with
support for provider filtering, free model detection, and the
{object, data} response format.

- Add EDENAI_API_KEY env variable support
- Add --source edenai option to `clawdbot models scan`
- Add edenai to provider list in models status
- Add unit tests for Eden AI scanning

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/agents/model-auth.ts

@@ -277,6 +277,7 @@ export function resolveEnvApiKey(provider: string): EnvApiKeyResult | null {
     cerebras: "CEREBRAS_API_KEY",
     xai: "XAI_API_KEY",
     openrouter: "OPENROUTER_API_KEY",
+    edenai: "EDENAI_API_KEY",
     "vercel-ai-gateway": "AI_GATEWAY_API_KEY",
     moonshot: "MOONSHOT_API_KEY",
     "kimi-code": "KIMICODE_API_KEY",

src/agents/model-scan.test.ts

@@ -1,6 +1,6 @@
 import { describe, expect, it } from "vitest";
 
-import { scanOpenRouterModels } from "./model-scan.js";
+import { scanEdenAiModels, scanOpenRouterModels } from "./model-scan.js";
 
 function createFetchFixture(payload: unknown): typeof fetch {
   return async () =>
@@ -86,3 +86,149 @@ describe("scanOpenRouterModels", () => {
     }
   });
 });
+
+describe("scanEdenAiModels", () => {
+  it("lists models from {object, data} response format", async () => {
+    const fetchImpl = createFetchFixture({
+      object: "list",
+      data: [
+        {
+          id: "anthropic/claude-3-haiku",
+          model_name: "Claude 3 Haiku",
+          owned_by: "anthropic",
+          context_length: 200000,
+          created: 1700000000,
+          capabilities: {
+            supports_function_calling: true,
+            supports_vision: false,
+            supports_tool_choice: true,
+            input_modalities: ["text"],
+            output_modalities: ["text"],
+          },
+          pricing: { input_cost_per_token: 0.00025, output_cost_per_token: 0.00125 },
+        },
+      ],
+    });
+
+    const results = await scanEdenAiModels({
+      fetchImpl,
+      apiKey: "test-key",
+      probe: false,
+    });
+
+    expect(results).toHaveLength(1);
+    expect(results[0]?.id).toBe("anthropic/claude-3-haiku");
+    expect(results[0]?.modelRef).toBe("edenai/anthropic/claude-3-haiku");
+    expect(results[0]?.provider).toBe("edenai");
+    expect(results[0]?.name).toBe("Claude 3 Haiku");
+    expect(results[0]?.supportsToolsMeta).toBe(true);
+  });
+
+  it("requires an API key", async () => {
+    const fetchImpl = createFetchFixture({ object: "list", data: [] });
+    const previousKey = process.env.EDENAI_API_KEY;
+    try {
+      delete process.env.EDENAI_API_KEY;
+      await expect(scanEdenAiModels({ fetchImpl, probe: false, apiKey: "" })).rejects.toThrow(
+        /Missing Eden AI API key/,
+      );
+    } finally {
+      if (previousKey === undefined) {
+        delete process.env.EDENAI_API_KEY;
+      } else {
+        process.env.EDENAI_API_KEY = previousKey;
+      }
+    }
+  });
+
+  it("filters by provider", async () => {
+    const fetchImpl = createFetchFixture({
+      object: "list",
+      data: [
+        {
+          id: "anthropic/claude-3",
+          model_name: "Claude",
+          owned_by: "anthropic",
+          context_length: 200000,
+          created: 1700000000,
+          capabilities: {
+            supports_function_calling: true,
+            supports_vision: false,
+            supports_tool_choice: true,
+            input_modalities: ["text"],
+            output_modalities: ["text"],
+          },
+          pricing: { input_cost_per_token: 0.001, output_cost_per_token: 0.002 },
+        },
+        {
+          id: "openai/gpt-4",
+          model_name: "GPT-4",
+          owned_by: "openai",
+          context_length: 128000,
+          created: 1700000000,
+          capabilities: {
+            supports_function_calling: true,
+            supports_vision: true,
+            supports_tool_choice: true,
+            input_modalities: ["text", "image"],
+            output_modalities: ["text"],
+          },
+          pricing: { input_cost_per_token: 0.003, output_cost_per_token: 0.006 },
+        },
+      ],
+    });
+
+    const results = await scanEdenAiModels({
+      fetchImpl,
+      apiKey: "test-key",
+      probe: false,
+      providerFilter: "anthropic",
+    });
+
+    expect(results).toHaveLength(1);
+    expect(results[0]?.id).toBe("anthropic/claude-3");
+  });
+
+  it("detects free models", async () => {
+    const fetchImpl = createFetchFixture({
+      object: "list",
+      data: [
+        {
+          id: "free/model",
+          model_name: "Free Model",
+          owned_by: "free",
+          context_length: 4096,
+          created: 1700000000,
+          capabilities: {
+            supports_function_calling: false,
+            supports_vision: false,
+            supports_tool_choice: false,
+            input_modalities: ["text"],
+            output_modalities: ["text"],
+          },
+          pricing: { input_cost_per_token: 0, output_cost_per_token: 0 },
+        },
+        {
+          id: "paid/model",
+          model_name: "Paid Model",
+          owned_by: "paid",
+          context_length: 8192,
+          created: 1700000000,
+          capabilities: {
+            supports_function_calling: true,
+            supports_vision: false,
+            supports_tool_choice: true,
+            input_modalities: ["text"],
+            output_modalities: ["text"],
+          },
+          pricing: { input_cost_per_token: 0.001, output_cost_per_token: 0.002 },
+        },
+      ],
+    });
+
+    const results = await scanEdenAiModels({ fetchImpl, apiKey: "test-key", probe: false });
+
+    expect(results.find((r) => r.id === "free/model")?.isFree).toBe(true);
+    expect(results.find((r) => r.id === "paid/model")?.isFree).toBe(false);
+  });
+});

src/agents/model-scan.ts

@@ -10,6 +10,7 @@ import {
 import { Type } from "@sinclair/typebox";
 
 const OPENROUTER_MODELS_URL = "https://openrouter.ai/api/v1/models";
+const EDENAI_MODELS_URL = "https://api.edenai.run/v3/llm/models";
 const DEFAULT_TIMEOUT_MS = 12_000;
 const DEFAULT_CONCURRENCY = 3;
 
@@ -463,5 +464,220 @@ export async function scanOpenRouterModels(
   );
 }
 
-export { OPENROUTER_MODELS_URL };
+// Eden AI model scanning
-export type { OpenRouterModelMeta, OpenRouterModelPricing };
+
+type EdenAiModelMeta = {
+  id: string;
+  model_name: string;
+  owned_by: string;
+  context_length: number | null;
+  created: number;
+  capabilities: {
+    supports_function_calling: boolean;
+    supports_vision: boolean;
+    supports_tool_choice: boolean;
+    input_modalities: string[];
+    output_modalities: string[];
+  };
+  pricing: {
+    input_cost_per_token: number;
+    output_cost_per_token: number;
+  };
+};
+
+export type EdenAiScanOptions = {
+  apiKey?: string;
+  fetchImpl?: typeof fetch;
+  timeoutMs?: number;
+  concurrency?: number;
+  minParamB?: number;
+  maxAgeDays?: number;
+  providerFilter?: string;
+  probe?: boolean;
+  onProgress?: (update: { phase: "catalog" | "probe"; completed: number; total: number }) => void;
+};
+
+function parseEdenAiModality(meta: EdenAiModelMeta): Array<"text" | "image"> {
+  const modalities = meta.capabilities?.input_modalities ?? [];
+  const hasImage = modalities.some((m) => m.toLowerCase() === "image");
+  return hasImage ? ["text", "image"] : ["text"];
+}
+
+async function fetchEdenAiModels(
+  fetchImpl: typeof fetch,
+  apiKey: string,
+): Promise<EdenAiModelMeta[]> {
+  const res = await fetchImpl(EDENAI_MODELS_URL, {
+    headers: {
+      Accept: "application/json",
+      Authorization: `Bearer ${apiKey}`,
+    },
+  });
+  if (!res.ok) {
+    throw new Error(`Eden AI /llm/models failed: HTTP ${res.status}`);
+  }
+  const payload = (await res.json()) as unknown;
+  // Eden AI returns {object: "list", data: [...]} format
+  const entries = Array.isArray(payload)
+    ? payload
+    : payload &&
+        typeof payload === "object" &&
+        "data" in payload &&
+        Array.isArray((payload as { data: unknown }).data)
+      ? (payload as { data: unknown[] }).data
+      : [];
+
+  return entries
+    .map((entry) => {
+      if (!entry || typeof entry !== "object") return null;
+      const obj = entry as Record<string, unknown>;
+      const id = typeof obj.id === "string" ? obj.id.trim() : "";
+      if (!id) return null;
+      const model_name =
+        typeof obj.model_name === "string" && obj.model_name.trim() ? obj.model_name.trim() : id;
+      const owned_by = typeof obj.owned_by === "string" ? obj.owned_by.trim() : "";
+
+      const context_length =
+        typeof obj.context_length === "number" && Number.isFinite(obj.context_length)
+          ? obj.context_length
+          : null;
+
+      const created =
+        typeof obj.created === "number" && Number.isFinite(obj.created) ? obj.created : 0;
+
+      const caps = (obj.capabilities ?? {}) as Record<string, unknown>;
+      const capabilities = {
+        supports_function_calling: caps.supports_function_calling === true,
+        supports_vision: caps.supports_vision === true,
+        supports_tool_choice: caps.supports_tool_choice === true,
+        input_modalities: Array.isArray(caps.input_modalities)
+          ? caps.input_modalities.filter((m): m is string => typeof m === "string")
+          : [],
+        output_modalities: Array.isArray(caps.output_modalities)
+          ? caps.output_modalities.filter((m): m is string => typeof m === "string")
+          : [],
+      };
+
+      const pricingRaw = (obj.pricing ?? {}) as Record<string, unknown>;
+      const pricing = {
+        input_cost_per_token:
+          typeof pricingRaw.input_cost_per_token === "number" ? pricingRaw.input_cost_per_token : 0,
+        output_cost_per_token:
+          typeof pricingRaw.output_cost_per_token === "number"
+            ? pricingRaw.output_cost_per_token
+            : 0,
+      };
+
+      return {
+        id,
+        model_name,
+        owned_by,
+        context_length,
+        created,
+        capabilities,
+        pricing,
+      } satisfies EdenAiModelMeta;
+    })
+    .filter((entry): entry is EdenAiModelMeta => Boolean(entry));
+}
+
+function isFreeEdenAiModel(entry: EdenAiModelMeta): boolean {
+  return entry.pricing.input_cost_per_token === 0 && entry.pricing.output_cost_per_token === 0;
+}
+
+export async function scanEdenAiModels(
+  options: EdenAiScanOptions = {},
+): Promise<ModelScanResult[]> {
+  const fetchImpl = options.fetchImpl ?? fetch;
+  const probe = options.probe ?? true;
+  const apiKey = options.apiKey?.trim() || getEnvApiKey("edenai") || "";
+  if (!apiKey) {
+    throw new Error("Missing Eden AI API key. Set EDENAI_API_KEY to run models scan.");
+  }
+
+  // timeoutMs reserved for future probing support
+  const concurrency = Math.max(1, Math.floor(options.concurrency ?? DEFAULT_CONCURRENCY));
+  const minParamB = Math.max(0, Math.floor(options.minParamB ?? 0));
+  const maxAgeDays = Math.max(0, Math.floor(options.maxAgeDays ?? 0));
+  const providerFilter = options.providerFilter?.trim().toLowerCase() ?? "";
+
+  const catalog = await fetchEdenAiModels(fetchImpl, apiKey);
+  const now = Date.now();
+
+  const filtered = catalog.filter((entry) => {
+    if (providerFilter) {
+      const prefix = entry.id.split("/")[0]?.toLowerCase() ?? "";
+      if (prefix !== providerFilter) return false;
+    }
+    if (minParamB > 0) {
+      const params = inferParamBFromIdOrName(`${entry.id} ${entry.model_name}`);
+      if (!params || params < minParamB) return false;
+    }
+    if (maxAgeDays > 0 && entry.created > 0) {
+      const createdMs = entry.created * 1000;
+      const ageMs = now - createdMs;
+      const ageDays = ageMs / (24 * 60 * 60 * 1000);
+      if (ageDays > maxAgeDays) return false;
+    }
+    return true;
+  });
+
+  options.onProgress?.({
+    phase: "probe",
+    completed: 0,
+    total: filtered.length,
+  });
+
+  return mapWithConcurrency(
+    filtered,
+    concurrency,
+    async (entry) => {
+      const isFree = isFreeEdenAiModel(entry);
+      const inferredParamB = inferParamBFromIdOrName(`${entry.id} ${entry.model_name}`);
+      const modalities = parseEdenAiModality(entry);
+      const modalityString = modalities.includes("image") ? "text+image" : "text";
+
+      const baseResult = {
+        id: entry.id,
+        name: entry.model_name,
+        provider: "edenai",
+        modelRef: `edenai/${entry.id}`,
+        contextLength: entry.context_length,
+        maxCompletionTokens: null,
+        supportedParametersCount: 0,
+        supportsToolsMeta: entry.capabilities.supports_function_calling,
+        modality: modalityString,
+        inferredParamB,
+        createdAtMs: entry.created > 0 ? entry.created * 1000 : null,
+        pricing: {
+          prompt: entry.pricing.input_cost_per_token,
+          completion: entry.pricing.output_cost_per_token,
+          request: 0,
+          image: 0,
+          webSearch: 0,
+          internalReasoning: 0,
+        },
+        isFree,
+      };
+
+      // Eden AI probing is not yet supported - their API structure differs from OpenAI
+      // Use --no-probe for catalog listing, or implement Eden AI-specific probing later
+      return {
+        ...baseResult,
+        tool: { ok: false, latencyMs: null, skipped: !probe },
+        image: { ok: false, latencyMs: null, skipped: !probe },
+      } satisfies ModelScanResult;
+    },
+    {
+      onProgress: (completed, total) =>
+        options.onProgress?.({
+          phase: "probe",
+          completed,
+          total,
+        }),
+    },
+  );
+}
+
+export { OPENROUTER_MODELS_URL, EDENAI_MODELS_URL };
+export type { OpenRouterModelMeta, OpenRouterModelPricing, EdenAiModelMeta };

src/cli/models-cli.ts

@@ -246,7 +246,8 @@ export function registerModelsCli(program: Command) {
 
   models
     .command("scan")
-    .description("Scan OpenRouter free models for tools + images")
+    .description("Scan model registries for tools + images")
+    .option("--source <registry>", "Model registry (openrouter, edenai)", "openrouter")
     .option("--min-params <b>", "Minimum parameter size (billions)")
     .option("--max-age-days <days>", "Skip models older than N days")
     .option("--provider <name>", "Filter by provider prefix")

src/commands/models/list.status-command.ts

@@ -131,6 +131,7 @@ export async function modelsStatusCommand(
     "cerebras",
     "xai",
     "openrouter",
+    "edenai",
     "zai",
     "mistral",
     "synthetic",

src/commands/models/scan.ts

@@ -1,6 +1,10 @@
 import { cancel, multiselect as clackMultiselect, isCancel } from "@clack/prompts";
 import { resolveApiKeyForProvider } from "../../agents/model-auth.js";
-import { type ModelScanResult, scanOpenRouterModels } from "../../agents/model-scan.js";
+import {
+  type ModelScanResult,
+  scanEdenAiModels,
+  scanOpenRouterModels,
+} from "../../agents/model-scan.js";
 import { withProgressTotals } from "../../cli/progress.js";
 import { loadConfig } from "../../config/config.js";
 import { logConfigUpdated } from "../../config/logging.js";
@@ -120,6 +124,8 @@ function printScanTable(results: ModelScanResult[], runtime: RuntimeEnv) {
   }
 }
 
+export type ModelScanSource = "openrouter" | "edenai";
+
 export async function modelsScanCommand(
   opts: {
     minParams?: string;
@@ -134,6 +140,7 @@ export async function modelsScanCommand(
     setImage?: boolean;
     json?: boolean;
     probe?: boolean;
+    source?: ModelScanSource;
   },
   runtime: RuntimeEnv,
 ) {
@@ -160,11 +167,15 @@ export async function modelsScanCommand(
 
   const cfg = loadConfig();
   const probe = opts.probe ?? true;
+  const source: ModelScanSource = opts.source ?? "openrouter";
+  const providerForKey = source === "edenai" ? "edenai" : "openrouter";
+  const sourceLabel = source === "edenai" ? "Eden AI" : "OpenRouter";
+
   let storedKey: string | undefined;
-  if (probe) {
+  if (probe || source === "edenai") {
     try {
       const resolved = await resolveApiKeyForProvider({
-        provider: "openrouter",
+        provider: providerForKey,
         cfg,
       });
       storedKey = resolved.apiKey;
@@ -172,14 +183,15 @@ export async function modelsScanCommand(
       storedKey = undefined;
     }
   }
+
   const results = await withProgressTotals(
     {
-      label: "Scanning OpenRouter models...",
+      label: `Scanning ${sourceLabel} models...`,
       indeterminate: false,
       enabled: opts.json !== true,
     },
-    async (update) =>
+    async (progressUpdate) => {
-      await scanOpenRouterModels({
+      const scanOpts = {
         apiKey: storedKey ?? undefined,
         minParamB: minParams,
         maxAgeDays,
@@ -187,22 +199,35 @@ export async function modelsScanCommand(
         timeoutMs: timeout,
         concurrency,
         probe,
-        onProgress: ({ phase, completed, total }) => {
+        onProgress: ({
+          phase,
+          completed,
+          total,
+        }: {
+          phase: string;
+          completed: number;
+          total: number;
+        }) => {
           if (phase !== "probe") return;
           const labelBase = probe ? "Probing models" : "Scanning models";
-          update({
+          progressUpdate({
             completed,
             total,
             label: `${labelBase} (${completed}/${total})`,
           });
         },
-      }),
+      };
+      if (source === "edenai") {
+        return await scanEdenAiModels(scanOpts);
+      }
+      return await scanOpenRouterModels(scanOpts);
+    },
   );
 
   if (!probe) {
     if (!opts.json) {
       runtime.log(
-        `Found ${results.length} OpenRouter free models (metadata only; pass --probe to test tools/images).`,
+        `Found ${results.length} ${sourceLabel} models (metadata only; pass --probe to test tools/images).`,
       );
       printScanTable(sortScanResults(results), runtime);
     } else {
@@ -213,7 +238,7 @@ export async function modelsScanCommand(
 
   const toolOk = results.filter((entry) => entry.tool.ok);
   if (toolOk.length === 0) {
-    throw new Error("No tool-capable OpenRouter free models found.");
+    throw new Error(`No tool-capable ${sourceLabel} models found.`);
   }
 
   const sorted = sortScanResults(results);