chore: import upstream snapshot with attribution

apps/sim/lib/api/contracts/knowledge/search.ts

@@ -0,0 +1,68 @@
+import { z } from 'zod'
+import { DEFAULT_RERANKER_MODEL, rerankerModelSchema } from '@/lib/knowledge/reranker-models'
+
+export const knowledgeSearchTagFilterSchema = z.object({
+  tagName: z.string(),
+  tagSlot: z.string().optional(),
+  fieldType: z.enum(['text', 'number', 'date', 'boolean']).optional(),
+  operator: z.string().default('eq'),
+  value: z.union([z.string(), z.number(), z.boolean()]),
+  valueTo: z.union([z.string(), z.number()]).optional(),
+})
+
+export const knowledgeSearchBodySchema = z
+  .object({
+    knowledgeBaseIds: z.union([
+      z.string().min(1, 'Knowledge base ID is required'),
+      z.array(z.string().min(1)).min(1, 'At least one knowledge base ID is required'),
+    ]),
+    query: z
+      .string()
+      .optional()
+      .nullable()
+      .transform((val) => val || undefined),
+    topK: z
+      .number()
+      .min(1)
+      .max(100)
+      .optional()
+      .nullable()
+      .default(10)
+      .transform((val) => val ?? 10),
+    tagFilters: z
+      .array(knowledgeSearchTagFilterSchema)
+      .optional()
+      .nullable()
+      .transform((val) => val || undefined),
+    rerankerEnabled: z.boolean().optional().default(false),
+    rerankerModel: rerankerModelSchema.optional().default(DEFAULT_RERANKER_MODEL),
+    /**
+     * Number of vector results sent to Cohere as the documents array for reranking. Capped at 100
+     * so each rerank call stays within a single Cohere search unit (1 query × ≤100 docs); see
+     * `RERANK_MODEL_PRICING` in `providers/models.ts`.
+     */
+    rerankerInputCount: z
+      .number()
+      .int('rerankerInputCount must be an integer')
+      .min(1, 'rerankerInputCount must be at least 1')
+      .max(100, 'rerankerInputCount cannot exceed 100')
+      .optional()
+      .nullable()
+      .transform((val) => val ?? undefined),
+    rerankerApiKey: z
+      .string()
+      .optional()
+      .nullable()
+      .transform((val) => val || undefined),
+  })
+  .refine(
+    (data) => {
+      const hasQuery = data.query && data.query.trim().length > 0
+      const hasTagFilters = data.tagFilters && data.tagFilters.length > 0
+      return hasQuery || hasTagFilters
+    },
+    {
+      message: 'Please provide either a search query or tag filters to search your knowledge base',
+    }
+  )
+export type KnowledgeSearchBody = z.output<typeof knowledgeSearchBodySchema>