"use strict";
var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
    var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;
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};
var __metadata = (this && this.__metadata) || function (k, v) {
    if (typeof Reflect === "object" && typeof Reflect.metadata === "function") return Reflect.metadata(k, v);
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.SubmitLlmResponseDto = void 0;
const class_validator_1 = require("class-validator");
const swagger_1 = require("@nestjs/swagger");
class SubmitLlmResponseDto {
}
exports.SubmitLlmResponseDto = SubmitLlmResponseDto;
__decorate([
    (0, swagger_1.ApiProperty)({
        description: 'Raw LLM response text to be parsed and orchestrated',
    }),
    (0, class_validator_1.IsString)(),
    (0, class_validator_1.IsNotEmpty)(),
    __metadata("design:type", String)
], SubmitLlmResponseDto.prototype, "raw_llm_response", void 0);
__decorate([
    (0, swagger_1.ApiProperty)({
        description: 'UUID of existing SessionInput to attach response to',
        format: 'uuid',
    }),
    (0, class_validator_1.IsUUID)(),
    __metadata("design:type", String)
], SubmitLlmResponseDto.prototype, "inputId", void 0);
__decorate([
    (0, swagger_1.ApiPropertyOptional)({
        description: 'Execution strategy',
        enum: ['review_first', 'apply_revert'],
    }),
    (0, class_validator_1.IsOptional)(),
    (0, class_validator_1.IsString)(),
    (0, class_validator_1.IsNotEmpty)(),
    __metadata("design:type", String)
], SubmitLlmResponseDto.prototype, "execution_strategy", void 0);
__decorate([
    (0, swagger_1.ApiPropertyOptional)({
        description: 'Number of input tokens used',
        minimum: 0,
    }),
    (0, class_validator_1.IsOptional)(),
    (0, class_validator_1.IsInt)(),
    __metadata("design:type", Number)
], SubmitLlmResponseDto.prototype, "input_token_count", void 0);
__decorate([
    (0, swagger_1.ApiPropertyOptional)({
        description: 'Number of output tokens generated',
        minimum: 0,
    }),
    (0, class_validator_1.IsOptional)(),
    (0, class_validator_1.IsInt)(),
    __metadata("design:type", Number)
], SubmitLlmResponseDto.prototype, "output_token_count", void 0);
__decorate([
    (0, swagger_1.ApiPropertyOptional)({
        description: 'Number of cached tokens used',
        minimum: 0,
    }),
    (0, class_validator_1.IsOptional)(),
    (0, class_validator_1.IsInt)(),
    __metadata("design:type", Number)
], SubmitLlmResponseDto.prototype, "cached_token_count", void 0);
__decorate([
    (0, swagger_1.ApiPropertyOptional)({
        description: 'Native tool calls from LLM response (array of tool call objects)',
    }),
    (0, class_validator_1.IsOptional)(),
    (0, class_validator_1.IsArray)(),
    (0, class_validator_1.IsObject)({ each: true }),
    __metadata("design:type", Array)
], SubmitLlmResponseDto.prototype, "tool_calls", void 0);
//# sourceMappingURL=submit-llm-response.dto.js.map