> ## Documentation Index > Fetch the complete documentation index at: https://docs.getlimina.ai/llms.txt > Use this file to discover all available pages before exploring further. # Process Files Uri > Detect entities such as PII, PHI or PCI in the file located at the provided URI using Private AI's entity detection engine. After entity detection, a copy of the file with all entities removed is created and placed in the folder specified by `PAI_OUTPUT_FILE_DIR` on the local host. This route is similar to `/v3/process/files/base64`, but relies on URIs instead of base64-encoded strings. As this route avoids the overhead of base64 encoding, it is more suitable for processing large files and large volumes of data. This route supports the following content types: application/json, application/msword, application/pdf, application/vnd.ms-excel, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/xml, message/rfc822, text/csv, text/plain, jpeg, jpeg, tiff, tiff, png, bmp, bmp, mp4, m4a, m4a, mp3, mp3, wav, wav ## OpenAPI ````yaml /openapi/privateai_3.3.3.json post /v3/process/files/uri openapi: 3.0.2 info: title: API Reference description: Private AI API Reference termsOfService: https://www.private-ai.com/terms-of-use/ contact: url: https://www.private-ai.com/contact/ email: info@private-ai.com version: 3.3.3 servers: - url: https://api.private-ai.com/deid description: Private AI Demo Server - url: http://localhost:8080 description: Local Server security: [] paths: /v3/process/files/uri: post: summary: Process Files Uri description: >- Detect entities such as PII, PHI or PCI in the file located at the provided URI using Private AI's entity detection engine. After entity detection, a copy of the file with all entities removed is created and placed in the folder specified by `PAI_OUTPUT_FILE_DIR` on the local host. This route is similar to `/v3/process/files/base64`, but relies on URIs instead of base64-encoded strings. As this route avoids the overhead of base64 encoding, it is more suitable for processing large files and large volumes of data. This route supports the following content types: application/json, application/msword, application/pdf, application/vnd.ms-excel, application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/xml, message/rfc822, text/csv, text/plain, jpeg, jpeg, tiff, tiff, png, bmp, bmp, mp4, m4a, m4a, mp3, mp3, wav, wav operationId: process_files_uri_v3_process_files_uri_post parameters: - required: false schema: title: X-Api-Key type: string default: '' name: x-api-key in: header requestBody: content: application/json: schema: $ref: '#/components/schemas/ProcessFileRequest' examples: process_files: summary: Process File with uri payload value: uri: /home/azureuser/example-image.jpeg entity_detection: accuracy: high return_entity: true required: true responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/ProcessFileResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' components: schemas: ProcessFileRequest: title: ProcessFileRequest required: - uri type: object properties: uri: title: Uri type: string description: >- URI of the file to be processed. It must be an accessible file path on the host machine (e.g. /Users/sam/files/file.pdf). entity_detection: title: Entity Detection allOf: - $ref: '#/components/schemas/PIIDetectionParams' description: >- This section contains a set of parameters to control the PII detection process. All fields have sensible default that can be changed for specific needs. pdf_options: title: Pdf Options allOf: - $ref: '#/components/schemas/PDFOptions' description: >- Options to process PDF files, such as the rendering quality when each page is turned into an image. audio_options: title: Audio Options allOf: - $ref: '#/components/schemas/AudioOptions' description: >- Options to process audio files, such as the padding to add while redacting audio segments. project_id: title: Project Id maxLength: 32 pattern: ^[a-zA-Z0-9\-_\:]*$ type: string description: >- Used to categorize requests for reporting purposes. Limited to alphanumeric characters or the following special characters :_- additionalProperties: false ProcessFileResponse: title: ProcessFileResponse required: - result_uri - processed_text - entities - entities_present type: object properties: result_uri: title: Result Uri type: string description: >- URI of the processed file in the output directory (e.g. /Users/sam/files/file.redacted.pdf). processed_text: title: Processed Text type: string description: >- This field contains the redacted version of any text that was extracted from the input file. It corresponds to a redacted ASR transcript for audio files and any text found inside a document such as a PDF or image file. entities: title: Entities type: array items: $ref: '#/components/schemas/FileEntityItem' description: A list of all entities found in the provided file. entities_present: title: Entities Present type: boolean description: Returns `True` if the list of detected entities is not empty. HTTPValidationError: title: HTTPValidationError type: object properties: detail: title: Detail type: array items: $ref: '#/components/schemas/ValidationError' PIIDetectionParams: title: PIIDetectionParams type: object properties: accuracy: allOf: - $ref: '#/components/schemas/AccuracyMode' description: >- Selects the model used to identify PII in the input text. By default, the `high` accuracy model is used. While the models used by the Private AI solution are highly optimized (~25X faster than a reference transformer implementation), in high-throughput cases it is possible to trade accuracy for speed by selecting either the `standard` or `standard_high` accuracy modes. Multilingual support can be enabled by using one of the multilingual models, namely `standard_high_multilingual` (GPU container only) and `high_multilingual`. The multilingual models process all supported languages including English, without the need to specify language. It is advisable to use the English-only models where possible, as they perform slightly better on English. default: high entity_types: title: Entity Types type: array items: anyOf: - $ref: '#/components/schemas/EnableEntityTypeSelector' - $ref: '#/components/schemas/DisableEntityTypeSelector' description: >- Controls which entity types and legislation sets are detected. See [Supported Entity Types](https://docs.private-ai.com/entities/#supported-entities) for the list of possible entities and legislation sets. By default, all entities are detected and removed. You can specify one of many selectors, which can be either an individual entity type such as `LOCATION_CITY` or a legislation like `GDPR`. `EnableEntityTypeSelector` selectors will add entity types to detect. On the contrary, `DisableEntityTypeSelector` selectors will ignore entities of the specified types. If only `DisableEntityTypeSelector` selectors are specified, they are assumed to be ignoring entity types from the entire supported list of entity types. filter: title: Filter type: array items: anyOf: - $ref: '#/components/schemas/AllowFilter' - $ref: '#/components/schemas/BlockFilter' description: >- Allows the user to customize PII detection via allow and block lists. See [Supported Entity Types](https://docs.private-ai.com/entities/#supported-entities) for the list of possible entities. return_entity: title: Return Entity type: boolean description: >- Controls whether the PII list in the response contains the `text` field. Turning this off means that no sensitive PII is returned in the response. default: true override: title: Override type: boolean description: >- Determines whether the disabled entity is used to override any other entities that the PII might belong to. Using this will force the system to keep a detected PII in the text. default: false additionalProperties: false PDFOptions: title: PDFOptions type: object properties: density: title: Density type: integer description: >- PDFs are converted into images using this DPI value. Smaller values result in images with smaller resolutions, which will take up less storage space and process faster, at the cost of output quality & redaction accuracy. default: 200 max_resolution: title: Max Resolution type: integer description: >- PDFs are converted into images using the `density` DPI value. Any resulting images with maximum size length larger than this will be resized to this value, while preserving aspect ratio. default: 3000 additionalProperties: false AudioOptions: title: AudioOptions type: object properties: bleep_start_padding: title: Bleep Start Padding minimum: 0 type: number description: Additional padding at the start of bleep, in seconds. default: 0 bleep_end_padding: title: Bleep End Padding minimum: 0 type: number description: Additional padding at the end of bleep, in seconds. default: 0 additionalProperties: false FileEntityItem: title: FileEntityItem required: - processed_text - text - location - best_label - labels type: object properties: processed_text: title: Processed Text type: string description: >- The corresponding marker in the de-identified text (result field), where the entity exists. Note that this field is only populated for text-based formats such as `.txt` text: title: Text type: string description: >- The text corresponding to the entity. For images the text is obtained using OCR, while for audio the text is obtained using ASR. location: title: Location anyOf: - $ref: '#/components/schemas/TextLocation' - $ref: '#/components/schemas/ImageLocation' - $ref: '#/components/schemas/AudioLocation' best_label: title: Best Label type: string description: The entity label with the highest likelihood. labels: title: Labels type: object additionalProperties: type: number description: >- A dictionary of all possible labels, together with associated likelihoods. Note that these are not strictly probabilities and do not sum to 1, as a word can belong to multiple classes. The scores have also been thresholded, so no additional thresholding is necessary. description: Empty ValidationError: title: ValidationError required: - loc - msg - type type: object properties: loc: title: Location type: array items: anyOf: - type: string - type: integer msg: title: Message type: string type: title: Error Type type: string AccuracyMode: title: AccuracyMode enum: - standard - standard_high - standard_high_multilingual - high - high_multilingual type: string description: >- Selects the model used to identify PII in the input text. By default, the "high" accuracy model is used. While the models used by the Private AI solution are highly optimized (~25X faster than a reference transformer implementation), in high-throughput cases it is possible to trade accuracy for speed by selecting either the "standard" or "standard_high" accuracy modes. Multilingual support can be enabled by using one of the multilingual models, namely "standard_high_multilingual" (GPU container only) and "high_multilingual". The multilingual models process all supported languages including English, without the need to specify language. It is advisable to use the English-only models where possible, as they perform slightly better on English. EnableEntityTypeSelector: title: EnableEntityTypeSelector type: object properties: type: title: Type enum: - ENABLE type: string default: ENABLE value: title: Value type: array items: type: string description: >- A list of entity types to detect and remove. See [Supported Entity Types](https://docs.private-ai.com/entities/#supported-entities) for a complete list of entity types. This can also be one or many legislations. We currently support these legislations ['GDPR', 'GDPR_SENSITIVE', 'HIPAA', 'CPRA', 'QUEBEC_PRIVACY_ACT', 'PCI', 'APPI', 'APPI_SENSITIVE', 'LIDI']. additionalProperties: false DisableEntityTypeSelector: title: DisableEntityTypeSelector type: object properties: type: title: Type enum: - DISABLE type: string default: DISABLE value: title: Value type: array items: type: string description: >- A list of entity types to ignore. See [Supported Entity Types](https://docs.private-ai.com/entities/#supported-entities) for a complete list of entity types. additionalProperties: false AllowFilter: title: AllowFilter required: - pattern type: object properties: type: title: Type enum: - ALLOW type: string description: >- Any entities in this list that match the regex pattern provided will be discarded. It is also possible to set this option via environment variable. See [Environment Variables](https://docs.private-ai.com/environment-variables) default: ALLOW pattern: title: Pattern type: string description: >- Any string matching this regex pattern will not be caught by the PII detection algorithm. additionalProperties: false BlockFilter: title: BlockFilter required: - entity_type - pattern type: object properties: type: title: Type enum: - BLOCK type: string description: >- The block feature allows you to extend the functionality of the Private AI models by using regular expressions. This way, you can define a Python regex pattern that will be used to identify additional tokens with the given PII label. Several block list filters can be specified with their own regex pattern. Lastly,for supported labels, if you would like the model to pick up only the tokens from the block list, you can use the enabled entity type feature together with the block list feature. This can be done by defining a list of enabled entity types and not including the supported label you are adding to the block list. For example, if you would like the label `ORGANIZATION` to only pick up Microsoft, you can define the enabled entity types as `[{"type":"ENABLE", "value": "NAME"}, {"type": "ENABLE", "value": "LOCATION"}, {"type": "ENABLE", "value": "AGE"}, ...]` (and omitting `ORGANIZATION`) and the block list as `[{"type": "BLOCK", "entitiy_type": "ORGANIZATION", "pattern": "Microsoft"}]`. default: BLOCK entity_type: title: Entity Type type: string description: >- Name of the custom entity type. It can either be a completely new entity type such as `CUSTOM_ID` or an existing entity, such as `NAME`. pattern: title: Pattern type: string description: >- This is a pattern to match in the text. This feature uses regex patterns, you can either pass a word (e.g. the, word, custom, etc.) or you can pass a valid Python regex pattern. It is important to note that regex patterns may require escaping when used in JSON objects. To give an example, if you would like to send the regex pattern `r"\b\w{4}\b"` which will catch every 4-character word, you need to send it as `"\\b\\w{4}\\b"`. A complete JSON grammar is found here: https://www.json.org/json-en.html. More information on how to write a python regex is found here: https://docs.python.org/3/library/re.html It is important to note also that only non-overlapping matches are returned. threshold: title: Threshold type: number description: >- This is defining a likelihood threshold for custom entity. This likelihood is compared against the predicted model likelihood and if it is greater then the custom entity is outputted instead of the model predicted entity. By default this threshold is set to 1.0 which will ensure that the blocked entities will always be preferred over a matching model predicted entity. This can be any value between 0 and 1. default: 1 additionalProperties: false TextLocation: title: TextLocation required: - stt_idx - end_idx - stt_idx_processed - end_idx_processed type: object properties: stt_idx: title: Stt Idx type: integer description: Start character index of the entity in the original text. end_idx: title: End Idx type: integer description: >- Index of the character immediately following the entity, such that end_idx - stt_idx = number of characters in the entity. stt_idx_processed: title: Stt Idx Processed type: integer description: Start character index of the entity in the processed text. end_idx_processed: title: End Idx Processed type: integer description: >- Index of the character immediately following the entity in the processed text. description: >- Start and end indices of the entity in a text-based file format such as `.txt`. ImageLocation: title: ImageLocation required: - page - x0 - x1 - y0 - y1 type: object properties: page: title: Page type: integer description: >- The page or layer that the entity occurs on. This corresponds to page in a PDF document or layer in a TIFF image. x0: title: X0 type: number description: X coordinate of the upper left point of the entity bounding box. x1: title: X1 type: number description: X coordinate of the lower right point of the entity bounding box. y0: title: Y0 type: number description: Y coordinate of the upper left point of the entity bounding box. y1: title: Y1 type: number description: Y coordinate of the lower right point of the entity bounding box. description: >- Bounding box of the entity in an image or PDF file (PDF files are converted to images). The origin is the upper left pixel of the image. Coordinates are given as a fraction of the X and Y image dimensions. AudioLocation: title: AudioLocation required: - stt_time - end_time type: object properties: stt_time: title: Stt Time type: number description: The start timestamp of the entity, in seconds end_time: title: End Time type: number description: The end timestamp of the entity, in seconds description: Timestamp of the entity in an audio file such as `.wav`. ````