Superwise

{
  "type": "string"
}

{
  "type": "string"
}

{
  "type": "array",
  "items": {
    "$ref": "#/components/schemas/models.AccountCashflowOverview"
  }
}

{
  "type": "string"
}

{
  "type": "string"
}

{
  "type": "array",
  "items": {
    "$ref": "#/components/schemas/models.UserPersonasResponse"
  }
}

{
  "type": "string"
}

{
  "type": "object",
  "properties": {
    "error": {
      "type": "string"
    }
  }
}

{
  "type": "object",
  "required": [
    "account_type",
    "inflow_amount",
    "net_cashflow_amount",
    "outflow_amount"
  ],
  "properties": {
    "account_type": {
      "type": "string",
      "description": "Account type"
    },
    "inflow_amount": {
      "type": "number",
      "description": "Inflow amount on the given window"
    },
    "outflow_amount": {
      "type": "number",
      "description": "Outflow amount on the given window"
    },
    "net_cashflow_amount": {
      "type": "number",
      "description": "Net cashflow amount on the given window"
    }
  },
  "description": "Cashflow details for a given account of a given user"
}

{
  "type": "object",
  "required": [
    "client_id",
    "client_secret"
  ],
  "properties": {
    "client_id": {
      "type": "string",
      "example": "4681f83e-a4e9-11ee-a506-0242ac120002"
    },
    "client_secret": {
      "type": "string",
      "example": "W5qNTpWIT81r5qE3wHrtwXBujKdmGAvx"
    }
  }
}

{
  "type": "object",
  "properties": {
    "api_key": {
      "type": "string",
      "example": "v2.local.V0bmLbcYzFAs4w0VLqdV-XBssuwRPIflBf94lhrUHu3Lcg18Qiwb4fPgqIc9pLqvhDYPQhTDho5sBCWV_ZwwJ4sKYEc0g5GKEn9BUA8d-KnIbHnLyYKuqMDZflzQSCUdhwnFAcDqAlIqqpENdDVf01IL4wyhyC2F3CLqLVnwWCCFLonLjwpi7eNztZJ4REYPellWBDq3jL-2td4fQmcUvhGXz0T7GBlg9jGtOrs47sbUWS_QHgd1esEjgYm823OdTAk5yjuWD7CKF8P7bqg66A.bnVsbA"
    }
  }
}

{
  "type": "object",
  "required": [
    "path"
  ],
  "properties": {
    "path": {
      "type": "string",
      "description": "Path where parquet file with the batch scores will be written"
    }
  }
}

{
  "type": "object",
  "required": [
    "engagement_type",
    "positive_label_users"
  ],
  "properties": {
    "engagement_type": {
      "type": "string",
      "description": "Intended use case of this product, between MULTI_ENGAGE and SINGLE_ENGAGE"
    },
    "run_description": {
      "type": "string",
      "description": "Custom run description to attach to run"
    },
    "negative_label_users": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.LookalikeLabel"
      },
      "description": "List of negative users in lookalike model. Model will be trained to identify users dissimilar to these users. If None, negative users will be generated from data. List length must be either 0 or greater than 10."
    },
    "positive_label_users": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.LookalikeLabel"
      },
      "description": "List of positive users in lookalike model. Model will be trained to identify users similar to these users. This list must contain at least ten elements."
    }
  }
}

{
  "type": "object",
  "required": [
    "input_label_summary",
    "run_id"
  ],
  "properties": {
    "run_id": {
      "type": "string",
      "description": "RunID is the unique identifier for the AutoML run"
    },
    "run_description": {
      "type": "string",
      "description": "Description of the run"
    },
    "input_label_summary": {
      "$ref": "#/components/schemas/models.InputLabelSummary"
    }
  },
  "x-konfig-properties": {
    "input_label_summary": {
      "description": "Analysis of input labels detailing amounts of labels given, amounts of labels detected, monthly breakdowns of positive rates and counts, and a breakdown of weights by label value."
    }
  }
}

{
  "type": "object",
  "required": [
    "run_description",
    "run_id",
    "status",
    "timestamp"
  ],
  "properties": {
    "run_id": {
      "type": "string",
      "description": "RunID is the unique identifier for the AutoML run"
    },
    "status": {
      "type": "string",
      "description": "RunStatus is the status of the AutoML training run"
    },
    "timestamp": {
      "type": "string",
      "description": "Timestamp is the time when the training run began"
    },
    "run_metrics": {
      "$ref": "#/components/schemas/models.AutoMLRunMetrics"
    },
    "engagement_type": {
      "type": "string",
      "description": "Engagement type of this product run"
    },
    "run_description": {
      "type": "string",
      "description": "RunDescription is the description of the AutoML training run"
    },
    "input_label_summary": {
      "$ref": "#/components/schemas/models.InputLabelSummary"
    },
    "number_of_train_users": {
      "type": "integer",
      "description": "NumberOfTrainUsers is the number of users in model training"
    },
    "number_of_inference_users": {
      "type": "integer",
      "description": "NumberOfInferenceUsers is the number of users in model inference"
    }
  },
  "x-konfig-properties": {
    "run_metrics": {
      "description": "RunMetrics is the metrics of the AutoML training run"
    },
    "input_label_summary": {
      "description": "Analysis of input labels detailing amounts of labels given, amounts of labels detected, monthly breakdowns of positive rates and counts, and a breakdown of weights by label value."
    }
  }
}

{
  "type": "object",
  "properties": {
    "test_ks": {
      "type": "number",
      "description": "KS of the test set"
    },
    "test_auc": {
      "type": "number",
      "description": "AUC of the test set"
    },
    "train_ks": {
      "type": "number",
      "description": "KS of the training set"
    },
    "train_auc": {
      "type": "number",
      "description": "AUC of the training set"
    },
    "label_positive_rate": {
      "type": "number",
      "description": "The percentage of users with positive label in the test set."
    },
    "positive_rate_by_decile": {
      "type": "object",
      "description": "The percentage of positive examples (examples with a positive label) in each of the ten equally-sized groups (deciles) of the test data when this data is sorted based on the model's predicted scores.",
      "additionalProperties": {
        "type": "number"
      }
    },
    "cumulative_positive_rate": {
      "type": "object",
      "description": "Cumulative positive rates at various thresholds, including ascending (lower to higher thresholds) and descending (higher to lower thresholds). It indicates how the proportion of positive instances within the total instances changes as the classification threshold is adjusted.",
      "additionalProperties": {
        "type": "object",
        "additionalProperties": {
          "type": "number"
        }
      }
    }
  }
}

{
  "type": "object",
  "required": [
    "run_description",
    "run_id",
    "status",
    "timestamp"
  ],
  "properties": {
    "run_id": {
      "type": "string",
      "description": "RunID is the unique identifier for the AutoML run"
    },
    "status": {
      "type": "string",
      "description": "RunStatus is the status of the AutoML training run"
    },
    "timestamp": {
      "type": "string",
      "description": "Timestamp is the time when the training run began"
    },
    "run_metrics": {
      "$ref": "#/components/schemas/models.AutoMLRunMetrics"
    },
    "engagement_type": {
      "type": "string",
      "description": "Engagement type of this product run"
    },
    "run_description": {
      "type": "string",
      "description": "RunDescription is the description of the AutoML training run"
    },
    "input_label_summary": {
      "$ref": "#/components/schemas/models.InputLabelSummary"
    },
    "number_of_train_users": {
      "type": "integer",
      "description": "NumberOfTrainUsers is the number of users in model training"
    },
    "number_of_inference_users": {
      "type": "integer",
      "description": "NumberOfInferenceUsers is the number of users in model inference"
    }
  },
  "x-konfig-properties": {
    "run_metrics": {
      "description": "RunMetrics is the metrics of the AutoML training run"
    },
    "input_label_summary": {
      "description": "Analysis of input labels detailing amounts of labels given, amounts of labels detected, monthly breakdowns of positive rates and counts, and a breakdown of weights by label value."
    }
  }
}

{
  "type": "object",
  "properties": {
    "allow_users": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.UserMetadata"
      },
      "description": "List of users to return user scores for"
    },
    "block_users": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.UserMetadata"
      },
      "description": "List of users to omit from returned user scores"
    },
    "tag_filters": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.TagCategoricalAttributeFilter"
      },
      "description": "Categorical Filters on pf_type metadata"
    }
  }
}

{
  "type": "object",
  "required": [
    "user_scores"
  ],
  "properties": {
    "user_scores": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.UserScore"
      },
      "description": "List of user scores"
    },
    "last_scored_date": {
      "type": "string",
      "description": "Date string of last inference in `YYYY-MM-DD hh:mm:ss` format"
    }
  }
}

{
  "type": "object",
  "required": [
    "runs"
  ],
  "properties": {
    "runs": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.AutoMLRunSummary"
      },
      "description": "List of AutoML run summaries"
    }
  }
}

{
  "type": "object",
  "required": [
    "user_list"
  ],
  "properties": {
    "user_list": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.UserMetadata"
      },
      "description": "List of users' metadata"
    }
  }
}

{
  "type": "object",
  "required": [
    "user_ids"
  ],
  "properties": {
    "user_ids": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "All user ids we want to fetch personas for"
    }
  }
}

{
  "type": "object",
  "properties": {
    "window_end": {
      "type": "string",
      "description": "End time of the given window"
    },
    "window_start": {
      "type": "string",
      "description": "Start time of the given window"
    },
    "inflow_amount": {
      "type": "number",
      "description": "Inflow amount on the given window"
    },
    "outflow_amount": {
      "type": "number",
      "description": "Outflow amount on the given window"
    }
  },
  "description": "Inflow and outflow for a given user in a given time window"
}

{
  "type": "object",
  "required": [
    "allowed_values",
    "blocked_values"
  ],
  "properties": {
    "allowed_values": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "example": [
        "['0002']"
      ],
      "description": "Allowed values"
    },
    "blocked_values": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Blocked values"
    }
  }
}

{
  "type": "object",
  "properties": {
    "transactions": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.Transaction"
      },
      "description": "List of transactions to be categorized"
    }
  }
}

{
  "type": "object",
  "properties": {
    "categorized_transactions": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.TransactionCategory"
      },
      "description": "Categorized transactions"
    }
  }
}

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Human-friendly category name"
    },
    "amount": {
      "type": "number",
      "description": "Aggregate amount for the given category"
    },
    "percentage": {
      "type": "number",
      "description": "Absolute amount flow for the category"
    },
    "taxonomy_path": {
      "type": "string",
      "description": "Human-friendly category taxonomy path"
    }
  },
  "description": "Amount percentage for a given category, related to either the total inflow or outflow"
}

{
  "type": "object",
  "properties": {
    "score": {
      "type": "string",
      "description": "A float between 0 and 1 representing a confidence on the predicted category. The higher the number, the greater the confidence."
    },
    "category": {
      "type": "string",
      "description": "The category of the transaction represented by a unique identifier in the Hyperplane's Taxonomy."
    }
  }
}

{
  "type": "object",
  "properties": {
    "is_disabled": {
      "type": "boolean",
      "example": false
    },
    "access_key_id": {
      "type": "string",
      "example": "823e064a-4cb7-11ee-be56-0242ac120002"
    }
  }
}

{
  "type": "object",
  "required": [
    "name",
    "weight"
  ],
  "properties": {
    "name": {
      "type": "string",
      "example": "international_traveler",
      "description": "Name of the facet"
    },
    "weight": {
      "type": "number",
      "example": 0.5,
      "description": "Weight of the facet"
    }
  }
}

{
  "type": "object",
  "required": [
    "num_input_labels",
    "num_input_users",
    "num_matched_labels",
    "num_training_users"
  ],
  "properties": {
    "monthly_counts": {
      "type": "object",
      "description": "For each month (shown in YYYY-MM format), the number of labels given.",
      "additionalProperties": {
        "type": "integer"
      }
    },
    "num_input_users": {
      "type": "integer",
      "description": "Number of distinct users that were provided by the user"
    },
    "num_input_labels": {
      "type": "integer",
      "description": "Number of labels that were provided by the user."
    },
    "num_matched_labels": {
      "type": "integer",
      "description": "Number of data rows that will be used in training"
    },
    "num_training_users": {
      "type": "integer",
      "description": "Number of distinct users that will be used in training"
    },
    "label_weight_counts": {
      "type": "object",
      "description": "Counts of given labels, broken down by label and weight. The keys are stringified pairs of (label_value, weight_value).",
      "additionalProperties": {
        "type": "integer"
      }
    },
    "monthly_positive_rates": {
      "type": "object",
      "description": "For each month (shown in YYYY-MM format), what is the rate of positive labels given.",
      "additionalProperties": {
        "type": "number"
      }
    }
  }
}

{
  "type": "object",
  "required": [
    "personas"
  ],
  "properties": {
    "personas": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.PersonaCreateResponse"
      }
    }
  },
  "description": "Response of users linked to a given persona"
}

{
  "type": "object",
  "properties": {
    "city": {
      "type": "string",
      "description": "City name"
    },
    "type": {
      "type": "string",
      "description": "Type of location (e.g., personal, home, business, ...)"
    },
    "state": {
      "type": "string",
      "description": "State name"
    },
    "country": {
      "type": "string",
      "description": "Country name"
    },
    "latitude": {
      "type": "number",
      "description": "Location latitude"
    },
    "city_code": {
      "type": "string",
      "description": "IBGE city code"
    },
    "longitude": {
      "type": "number",
      "description": "Location longitude"
    },
    "postal_code": {
      "type": "string",
      "description": "Postal code (i.e., CEP, e.g., '22620-171')"
    },
    "full_address": {
      "type": "string",
      "description": "Full address (e.g., Av. Lúcio Costa 1234, Copacabana, Rio de Janeiro, Brasil)"
    },
    "primary_address": {
      "type": "string",
      "description": "Primary address (e.g., Av. Lúcio Costa, 1234)"
    }
  },
  "description": "Location where the transaction happened"
}

{
  "type": "object",
  "required": [
    "user_id"
  ],
  "properties": {
    "user_id": {
      "type": "string",
      "description": "UserID is the unique identifier for the user"
    },
    "timestamp": {
      "type": "string",
      "description": "Timestamp to filter the features available to the model. Should reflect when the model is called: email sent date, loan initialized date, etc. If None, all user features will be used"
    }
  }
}

{
  "type": "object",
  "properties": {
    "cnae": {
      "type": "string",
      "description": "Merchant CNAE"
    },
    "cnpj": {
      "type": "string",
      "description": "Merchant CNPJ"
    },
    "name": {
      "type": "string",
      "description": "Merchant name"
    },
    "category": {
      "type": "string",
      "description": "Merchant category"
    },
    "business_name": {
      "type": "string",
      "description": "Merchant business name"
    }
  },
  "description": "Inferred merchant info after transaction enrichment"
}

{
  "type": "object",
  "required": [
    "max_value",
    "min_value"
  ],
  "properties": {
    "max_value": {
      "type": "number",
      "example": 100000,
      "description": "Max attribute value"
    },
    "min_value": {
      "type": "number",
      "example": 0,
      "description": "Min attribute value"
    }
  },
  "description": "Definition of a filter on an attribute of numerical type."
}

{
  "type": "object",
  "required": [
    "next_page",
    "page_size"
  ],
  "properties": {
    "next_page": {
      "type": "integer",
      "example": 2,
      "description": "Next page number"
    },
    "page_size": {
      "type": "integer",
      "example": 100,
      "description": "Number of elements per page"
    }
  }
}

{
  "type": "object",
  "properties": {
    "score": {
      "type": "number",
      "example": 0.5,
      "description": "Score calculated for the given percentile"
    },
    "percentile": {
      "type": "number",
      "example": 0.1,
      "description": "Percentile for which the score is being fetched"
    }
  },
  "description": "Percentile and associated score."
}

{
  "type": "object",
  "required": [
    "persona_name"
  ],
  "properties": {
    "locations": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Optional list of zip codes or city ids to filter users by. If left empty, no location-based filtering is done."
    },
    "persona_name": {
      "type": "string",
      "example": "Young Professional",
      "description": "A name for describing this persona. Used for easy human-friendly identification."
    },
    "company_facets": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.FacetWeightObject"
      },
      "description": "Optional list of behavioral facet component objects. Each object outlines how a user's likelihood\nto consume from a particular company's products and how much it contributes to the persona definition. If left\nempty, no company-based scoring is done. Company facets can be found by listing personas of facet type\n'company'. Facet name must be a valid company facet in the persona taxonomy."
    },
    "interest_facets": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.FacetWeightObject"
      },
      "description": "Optional list of interest facet component objects. Each object represents how much an interest\nweighs in the persona. If left empty, no interest-based scoring is done. Interests can be found\nby listing personas of facet type 'interest'. Facet name must be a valid interest in the persona taxonomy."
    },
    "demographic_facets": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.FacetWeightObject"
      },
      "description": "Optional list of interest facet component objects. Defines how much each demographic attribute\n(location, affluence, household composition, etc.)  weighs in the persona. If left empty, no demographic-based\nscoring is done. Demographic facets can be found by listing personas of facet type 'demographic'. Facet name\nmust be a valid demographic facet in the persona taxonomy."
    },
    "pre_defined_personas": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.FacetWeightObject"
      },
      "description": "Optional list of pre-defined persona facet component objects. Each object outlines how a pre-defined\npersona ('Car Owners' or 'International Travelers') contributes to the persona definition. If left\nempty, no predefined personas are incorporated into the persona definition. Pre-defined personas have\nbeen optimized for financial use cases and have been validated at scale. They can be found by listing\npersonas of facet type 'pre_defined_persona'. Facet name must be a valid pre-defined persona facet in\nthe persona taxonomy."
    }
  },
  "description": "Defines a persona. Stores various weighted facets including their interests, demographics, location, company affinity, as well as predefined personas."
}

{
  "type": "object",
  "required": [
    "creation_datetime",
    "persona_id",
    "persona_name"
  ],
  "properties": {
    "persona_id": {
      "type": "string",
      "example": "1",
      "description": "Unique identifier for the persona"
    },
    "persona_name": {
      "type": "string",
      "example": "Young Professional",
      "description": "Name of the persona"
    },
    "creation_datetime": {
      "type": "string",
      "example": "2020-01-01T00:00:00",
      "description": "Creation datetime of persona"
    }
  }
}

{
  "type": "object",
  "required": [
    "creation_datetime",
    "definition",
    "persona_id",
    "persona_score_statistics"
  ],
  "properties": {
    "definition": {
      "$ref": "#/components/schemas/models.PersonaCreateRequest"
    },
    "persona_id": {
      "type": "string",
      "example": "1",
      "description": "Unique identifier for the persona"
    },
    "creation_datetime": {
      "type": "string",
      "example": "2020-01-01T00:00:00",
      "description": "Creation datetime of persona"
    },
    "persona_score_statistics": {
      "$ref": "#/components/schemas/models.PersonaScoreStatistics"
    }
  },
  "x-konfig-properties": {
    "definition": {
      "description": "The persona definition used to create this persona"
    },
    "persona_score_statistics": {
      "description": "Statistical attributes about the persona score distribution"
    }
  }
}

{
  "type": "object",
  "properties": {
    "percentile_10": {
      "type": "number",
      "example": 0.1
    },
    "percentile_20": {
      "type": "number",
      "example": 0.2
    },
    "percentile_30": {
      "type": "number",
      "example": 0.3
    },
    "percentile_40": {
      "type": "number",
      "example": 0.4
    },
    "percentile_50": {
      "type": "number",
      "example": 0.5
    },
    "percentile_60": {
      "type": "number",
      "example": 0.6
    },
    "percentile_70": {
      "type": "number",
      "example": 0.7
    },
    "percentile_80": {
      "type": "number",
      "example": 0.8
    },
    "percentile_90": {
      "type": "number",
      "example": 0.9
    }
  },
  "description": "Percentile scores for users scored for a particular persona."
}

{
  "type": "object",
  "required": [
    "maximum_user_score",
    "minimum_user_score",
    "persona_score_threshold",
    "score_average",
    "score_percentiles",
    "score_standard_deviation",
    "total_users_above_threshold",
    "total_users_with_non_zero_score"
  ],
  "properties": {
    "score_average": {
      "type": "number",
      "example": 0.5,
      "description": "Average score over all scored users in this persona"
    },
    "score_percentiles": {
      "$ref": "#/components/schemas/models.PersonaScorePercentiles"
    },
    "maximum_user_score": {
      "type": "number",
      "example": 0.5,
      "description": "Highest persona score assigned to a user for this persona"
    },
    "minimum_user_score": {
      "type": "number",
      "example": 0.5,
      "description": "Lowest persona score assigned to a user for this persona"
    },
    "persona_score_threshold": {
      "type": "number",
      "example": 0.5,
      "description": "Score threshold used to determine whether a user belongs to this persona"
    },
    "score_standard_deviation": {
      "type": "number",
      "example": 0.5,
      "description": "Standard deviation over all scored users in this persona"
    },
    "total_users_above_threshold": {
      "type": "integer",
      "example": 1000,
      "description": "Total number of users who meet or exceed the score threshold to be considered part of this persona."
    },
    "total_users_with_non_zero_score": {
      "type": "integer",
      "example": 1000,
      "description": "Total number of users who have received a score for this persona."
    }
  },
  "description": "Statistical attributes about the score distribution for a particular persona.",
  "x-konfig-properties": {
    "score_percentiles": {
      "description": "Percentile distribution of scores for users who have been assigned a score for this persona"
    }
  }
}

{
  "type": "object",
  "required": [
    "id"
  ],
  "properties": {
    "id": {
      "type": "string",
      "example": "1",
      "description": "Unique identifier for the user"
    },
    "score": {
      "type": "number",
      "example": 0.5,
      "description": "Relevance score of user in this persona. In range `[0,1]`"
    }
  },
  "description": "User associated with a given persona"
}

{
  "type": "object",
  "required": [
    "users"
  ],
  "properties": {
    "users": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.PersonaUser"
      },
      "description": "Top users belonging to this persona"
    }
  },
  "description": "Response of users linked to a given persona"
}

{
  "type": "object",
  "required": [
    "blocklist",
    "branch"
  ],
  "properties": {
    "branch": {
      "$ref": "#/components/schemas/models.CategoricalAttributeFilter"
    },
    "cbo_code": {
      "$ref": "#/components/schemas/models.CategoricalAttributeFilter"
    },
    "blocklist": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "example": [
        "['1234']"
      ],
      "description": "List of user ids to not be included in the response"
    },
    "job_title": {
      "$ref": "#/components/schemas/models.CategoricalAttributeFilter"
    },
    "birth_date": {
      "$ref": "#/components/schemas/models.TimestampAttributeFilter"
    },
    "declared_monthly_income": {
      "$ref": "#/components/schemas/models.NumericalAttributeFilter"
    }
  },
  "description": "Extra information for filtering users",
  "x-konfig-properties": {
    "branch": {
      "description": "Filter branch based on a list of allowed values"
    },
    "cbo_code": {
      "description": "Filter cbo code based on a list of allowed values"
    },
    "job_title": {
      "description": "Filter job title based on a list of allowed values"
    },
    "birth_date": {
      "description": "Filter birth date based on a date range"
    },
    "declared_monthly_income": {
      "description": "Filter declared monthly income based on a numeric range"
    }
  }
}

{
  "type": "object",
  "required": [
    "allowed_values",
    "blocked_values",
    "tag_name"
  ],
  "properties": {
    "tag_name": {
      "type": "string",
      "description": "Tag name"
    },
    "allowed_values": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "example": [
        "['0002']"
      ],
      "description": "Allowed values"
    },
    "blocked_values": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Blocked values"
    }
  }
}

{
  "type": "object",
  "required": [
    "max_value",
    "min_value"
  ],
  "properties": {
    "max_value": {
      "type": "string",
      "example": "2020-01-01T00:00:00",
      "description": "Max attribute value"
    },
    "min_value": {
      "type": "string",
      "example": "2000-01-01T00:00:00",
      "description": "Min attribute value"
    }
  },
  "description": "Definition of a filter on an attribute of timestamp type."
}

{
  "type": "object",
  "properties": {
    "name": {
      "type": "string",
      "description": "Human-friendly category name"
    },
    "amount": {
      "type": "number",
      "description": "Aggregate amount for the given category"
    },
    "categories": {
      "type": "array",
      "items": {
        "$ref": "#/components/schemas/models.CategoryCashflow"
      },
      "description": "Detailed predicted categories under the top-level"
    },
    "percentage": {
      "type": "number",
      "description": "Absolute amount flow for the category"
    }
  },
  "description": "Amount percentage for a given top level category. As well as subcategories division"
}

{
  "type": "object",
  "properties": {
    "amount": {
      "type": "number",
      "description": "The monetary value of a transaction. This is always a positive value."
    },
    "bank_id": {
      "type": "string",
      "description": "The name of the bank that is originating the transaction. For credit cards, this is the issuing bank."
    },
    "user_id": {
      "type": "string",
      "description": "A unique identifier for the user within the bank or institution."
    },
    "currency": {
      "type": "string",
      "description": "Currency enum based on ISO 4217. Eg: BRL, USD, MXN."
    },
    "account_id": {
      "type": "string",
      "description": "A unique identifier for the account within the bank or institution."
    },
    "description": {
      "type": "string",
      "description": "The raw text description of the transaction (do not clean or transform this).\nIt usually includes some information about the payment method, processor,\nmerchant, and in cases of transfer might include CNPJ or other reference numbers.\nSome examples:\n   - Pag*Mariaivaneidede\n   - Ifd*Puro Acai Beira Ma\n   - TED BCO 1 AGE 4598  CTA 291412  - RETIRADA EM C/C"
    },
    "account_type": {
      "type": "string",
      "description": "One of the following: checking, saving, credit card or investment."
    },
    "location_city": {
      "type": "string",
      "description": "The city in which the transaction happened. e.g. São Paulo, Mexico City, San Francisco."
    },
    "location_state": {
      "type": "string",
      "description": "The state in which the transaction happened. Eg: SP, CA."
    },
    "transaction_id": {
      "type": "string",
      "description": "A unique identifier for each transaction to identify the transaction within your bank or institution."
    },
    "location_country": {
      "type": "string",
      "description": "The country in which the transaction happened in ISO 3166-1 alpha-3 format. e.g. BRA (for transaction in Brazil), ESP (for transaction in Spain)."
    },
    "transaction_flow": {
      "type": "string",
      "description": "One of the following options: outflow (for spending) or inflow (for earning)."
    },
    "transaction_datetime": {
      "type": "string",
      "description": "Time when the transaction was performed."
    },
    "transaction_metadata": {
      "$ref": "#/components/schemas/models.TransactionMetadata"
    }
  },
  "x-konfig-properties": {
    "transaction_metadata": {
      "description": "A map used to store additional context about a transaction that might be useful for cleaning and understanding."
    }
  }
}