import {z} from 'zod'

export type GetApiAgentsJobIdConfigHistoryVersionArgs = {job_id: string, version: number};

export type GetApiAgentsJobIdConfigHistoryVersionOptions = {baseUrl?: string | undefined, FronteggHTTPAuthentication?: string | undefined, fetch?: typeof fetch | undefined};

export const agentTypeEnum = z.enum(["workflow", "react"]);

export const agentSerializationEnum = z.enum(["JsonConfluent", "AvroConfluent"]);

export const agentInputConfig = z.object({topicPattern: z.string().min(1).max(1024), inputSerialization: agentSerializationEnum.optional(), fields: z.array(z.string()).nullable().optional(), createTableSQL: z.string().max(4000).nullable().optional(), filterSQL: z.string().max(4000).nullable().optional()});

export const agentOutputSchemaTypeEnum = z.enum(["STRING", "DOUBLE", "INT32", "INT64", "BOOLEAN"]);

export const agentOutputConfig = z.object({topic: z.string().min(1).max(249), deadLetterTopic: z.string().max(249).nullable().optional(), outputSerialization: agentSerializationEnum.optional(), schema: z.record(z.string(), agentOutputSchemaTypeEnum).optional()});

export const agentLlmProviderEnum = z.enum(["anthropic", "openai", "openai-responses", "ollama", "azure", "azure-openai", "bedrock", "qwen", "openai-compatible"]);

export const agentLlmConfig = z.object({provider: agentLlmProviderEnum, model: z.string().min(1), apiKey: z.string().max(512).optional(), llmConnectionId: z.string().max(100).nullable().optional(), baseUrl: z.string().nullable().optional(), temperature: z.number().gte(0).lte(2).nullable().optional(), maxTokens: z.number().int().gte(1).lte(100000).nullable().optional(), timeout: z.number().int().gte(1).lte(600).nullable().optional(), reasoningEffort: z.enum(["none", "minimal", "low", "medium", "high", "xhigh"]).nullable().optional(), thinkingBudgetTokens: z.number().int().gte(0).lte(64000).nullable().optional(), ollamaThink: z.boolean().nullable().optional(), maxRetries: z.number().int().gte(0).lte(20).nullable().optional(), region: z.string().max(64).nullable().optional(), strict: z.boolean().nullable().optional(), store: z.boolean().nullable().optional(), instructions: z.string().max(8192).nullable().optional(), additionalKwargs: z.record(z.string(), z.unknown()).nullable().optional(), apiVersion: z.string().max(32).nullable().optional(), azureEndpoint: z.string().max(512).nullable().optional(), azureUrlPathMode: z.enum(["AUTO", "LEGACY", "UNIFIED"]).nullable().optional()});

export const agentPromptConfig = z.object({system: z.string().max(8000).optional(), customInstructions: z.string().max(8000).optional(), user: z.string().max(2000).optional()});

export const agentMcpServerConfig = z.object({projectKeyId: z.string().max(128).nullable().optional(), serverUrl: z.string().min(1).max(2048).nullable().optional(), headers: z.record(z.string(), z.string()).optional()});

export const agentToolTypeEnum = z.enum(["http", "transform", "mcp"]);

export const agentToolParameterConfig = z.object({name: z.string().min(1).max(100), type: z.string().max(50).optional(), description: z.string().max(2000).optional()});

export const agentToolConfig = z.object({name: z.string().min(1).max(100), type: agentToolTypeEnum, description: z.string().max(2000).optional(), config: z.record(z.string(), z.unknown()).optional(), parameters: z.array(agentToolParameterConfig).optional()});

export const agentShortTermMemoryConfig = z.object({enabled: z.boolean().optional(), ttlMs: z.number().int().gte(0).optional(), maxEntries: z.number().int().gte(1).lte(100).optional()});

export const agentLongTermMemoryConfig = z.object({enabled: z.boolean().optional(), vectorStoreConnectionId: z.string().max(64).nullable().optional(), namespace: z.string().max(200).nullable().optional(), destinationId: z.string().max(64).nullable().optional()});

export const agentMemoryConfig = z.object({keyField: z.string().nullable().optional(), shortTerm: agentShortTermMemoryConfig.optional(), longTerm: agentLongTermMemoryConfig.optional()});

export const agentKnowledgeBaseRef = z.object({id: z.string().min(1).max(64), name: z.string().max(200).optional()});

export const agentProcessingConfig = z.object({parallelism: z.number().int().gte(1).lte(128).optional(), checkpointIntervalMin: z.number().int().gte(1).lte(60).optional(), maxIterations: z.number().int().gte(1).lte(25).optional(), maxTokensPerHour: z.number().int().gte(0).optional()});

export const createAgentConfigRequest = z.object({name: z.string().min(1).max(200), description: z.string().max(500).nullable().optional(), enabled: z.boolean().optional(), agentType: agentTypeEnum.optional(), input: agentInputConfig, output: agentOutputConfig, llm: agentLlmConfig, prompts: agentPromptConfig, mcpServer: agentMcpServerConfig.nullable().optional(), tools: z.array(agentToolConfig).optional(), memory: agentMemoryConfig.nullable().optional(), knowledgeBases: z.array(agentKnowledgeBaseRef).optional(), processing: agentProcessingConfig.optional()});

export const agentConfigHistoryDetailResponse = z.object({version: z.number().int().gte(0), changedByEmail: z.string().nullable().optional(), changedTimestamp: z.string(), changeKind: z.enum(["create", "update", "rollback"]), rollbackSourceVersion: z.number().int().nullable().optional(), changeNote: z.string().nullable().optional(), agentConfig: createAgentConfigRequest}).and(z.record(z.string(), z.unknown()));

export const validateResponse = async <Output>(
  schema: {
    readonly '~standard': {
      readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }>
    }
  },
  value: unknown
): Promise<Output> => {
  const result = await schema['~standard'].validate(value)

  if (result.issues !== undefined) {
    const detail = result.issues
      .map(({ message, path }) =>
        path?.length
          ? `${path.map((segment) => String(typeof segment === 'object' ? segment.key : segment)).join('.')}: ${message}`
          : message
      )
      .join('; ')

    throw new Error(`Response does not match the schema: ${detail}`, { cause: { issues: result.issues } })
  }

  return result.value
};

/**
 * Get Agent Config History Entry
 * 
 * GET /agents/{job_id}/config/history/{version}
 */
export const getApiAgentsJobIdConfigHistoryVersion = async (args: GetApiAgentsJobIdConfigHistoryVersionArgs, options?: GetApiAgentsJobIdConfigHistoryVersionOptions) => {
const {baseUrl = "https://api.streamkap.com", fetch: fetchFn = fetch, FronteggHTTPAuthentication} = options ?? {}

const query = new URLSearchParams()
const headers = new Headers()
headers.set('accept', "application/json")

if (FronteggHTTPAuthentication !== undefined) headers.set('authorization', `Bearer ${FronteggHTTPAuthentication}`)

const url = `${baseUrl.replace(/\/+$/, '')}/agents/${encodeURIComponent(String(args.job_id))}/config/history/${encodeURIComponent(String(args.version))}${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "GET", headers})

if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}})

return validateResponse(agentConfigHistoryDetailResponse, await res.json())
};