> ## 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.

# Processing TXT Files

> This guide will get you started with TXT deidentification.

Limina supports scanning TXT files for PII and creating de-identified or redacted copies. Limina’s supported entity types function across each file type, with localized variants of different **PII** (Personally Identifiable Information) entities, **PHI** (Protected Health Information) entities, and **PCI** (Payment Card Industry) entities being detected. Our [Supported Languages](/languages) and [Supported Entity Types](/entities) page provides a more detailed look.

<Info>
  If you'd like to try it yourself, please [sign up for an account](https://portal.getlimina.ai/) to get a free API key.
</Info>

## How TXT Files Are Processed

TXT files are processed by simply reading in the contents of the TXT files verbatim and passing it through Limina's text module. The resulting file will contain the labelled and redacted version of contents of the original.

## Constraints

* Limina currently only supports `utf-8` encoding for text files.

## Support Matrix

|           | CPU Container | GPU Container | Community API | Professional API |
| --------- | ------------- | ------------- | ------------- | ---------------- |
| Supported | Yes           | Yes           | Up to 250 KiB | No               |

## Sample Request

<Info>
  [Connect with one of our privacy experts](https://getlimina.ai/en/contact-us/?utm_source=docs\&utm_medium=website) to run this code.
</Info>

<CodeGroup>
  ```json Request Body wrap lines theme={"theme":"poimandres"}
  {
    "file": {
      "data": "<file_content_base64>",
      "content_type": "text/plain"
    },
    "entity_detection": {
      "return_entity": true
    }
  }
  ```

  ```shell curl wrap lines theme={"theme":"poimandres"}
  echo '{
            "file": {"data": "'$(base64 -w 0 sample.txt)'", 
            "content_type": "text/plain"}, 
            "entity_detection": {"return_entity": "True"}
        }' \
  | curl --request POST --url 'https://api.private-ai.com/community/v4/process/files/base64' \
         -H 'Content-Type: application/json' \
         -H 'x-api-key: <YOUR KEY HERE>' \
         -d @- \
         | jq -r .processed_file \
         | base64 -d > 'sample.redacted.txt'
  ```

  ```python python wrap lines theme={"theme":"poimandres"}
  import requests
  import base64

  file_url = "https://paidocumentation.blob.core.windows.net/$web/sample.txt"
  filename_out = "/path/to/output/sample.redacted.txt"
  file_content = requests.get(file_url).content
  file_content_base64 = base64.b64encode(file_content).decode()

  url = "https://api.private-ai.com/community/v4/process/files/base64"

  headers = {"Content-Type": "application/json", "x-api-key": "<INSERT API KEY>"}

  payload = {
    "file":{
      "data": file_content_base64,
      "content_type": "text/plain",
    },
    "entity_detection": {
      "return_entity": True
    }
  }

  response = requests.post(url, json=payload, headers=headers)
  with open(filename_out, "wb") as f:
      f.write(base64.b64decode(response.json()["processed_file"]))
  ```

  ```python Python Client wrap lines theme={"theme":"poimandres"}
  from privateai_client import PAIClient
  from privateai_client.objects import request_objects
  import base64

  filename_in = "sample.txt"
  filename_out = "sample.redacted.txt"

  file_type= "text/plain"
  client = PAIClient(url="https://api.private-ai.com/community/v4/", api_key="<YOUR API KEY>")

  with open(filename_in, "rb") as b64_file:
      file_data = base64.b64encode(b64_file.read())
      file_data = file_data.decode("ascii")

  file_obj = request_objects.file_obj(data=file_data, content_type=file_type)
  request_obj = request_objects.file_base64_obj(file=file_obj)
  resp = client.process_files_base64(request_object=request_obj)

  with open(filename_out, 'wb') as redacted_file:
      processed_file = resp.processed_file.encode("ascii")
      processed_file = base64.b64decode(processed_file, validate=True)
      redacted_file.write(processed_file)
  ```
</CodeGroup>

## Sample Response

```json Response wrap lines theme={"theme":"poimandres"}
{
  "processed_file": "Base64 Encoded File Content of the Redacted File",
  "processed_text": "string",
  "entities": "List[Entity]",
  "entities_present": true,
  "languages_detected": {"lang_1": 0.67, "lang_2": 0.74}
}
```