github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-06-30 10:23:30 +00:00
Code Issues Packages Projects Releases Wiki Activity

docs[patch]: microsoft platform page update (#14476)

Browse Source 
Added `presidio` and `OneNote` references to `microsoft.mdx`; added link
and description to the `presidio` notebook

---------

Co-authored-by: Erick Friis <erickfriis@gmail.com>
This commit is contained in:
Leonid Ganeline 2023-12-08 17:40:30 -08:00 committed by GitHub
parent 84a57f5350
commit 2fa81739b6
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 38 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
docs/docs/guides/privacy/presidio_data_anonymization/index.ipynb
View File

@ -8,6 +8,8 @@
"\n",
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain/blob/master/docs/docs/guides/privacy/presidio_data_anonymization/index.ipynb)\n",
"\n",
">[Presidio](https://microsoft.github.io/presidio/) (Origin from Latin praesidium ‘protection, garrison’) helps to ensure sensitive data is properly managed and governed. It provides fast identification and anonymization modules for private entities in text and images such as credit card numbers, names, locations, social security numbers, bitcoin wallets, US phone numbers, financial data and more.\n",
"\n",
"## Use case\n",
"\n",
"Data anonymization is crucial before passing information to a language model like GPT-4 because it helps protect privacy and maintain confidentiality. If data is not anonymized, sensitive information such as names, addresses, contact numbers, or other identifiers linked to specific individuals could potentially be learned and misused. Hence, by obscuring or removing this personally identifiable information (PII), data can be used freely without compromising individuals' privacy rights or breaching data protection laws and regulations.\n",
@ -530,7 +532,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.12"
}
},
"nbformat": 4,

35
docs/docs/integrations/platforms/microsoft.mdx
View File

@ -151,6 +151,20 @@ See a [usage example](/docs/integrations/document_loaders/microsoft_powerpoint).
from langchain.document_loaders import UnstructuredPowerPointLoader
```
### Microsoft OneNote
First, let's install dependencies:
```bash
pip install bs4 msal
```
See a [usage example](/docs/integrations/document_loaders/onenote).
```python
from langchain.document_loaders.onenote import OneNoteLoader
```
## Vector stores
@ -259,4 +273,25 @@ from langchain.agents.agent_toolkits import PowerBIToolkit
from langchain.utilities.powerbi import PowerBIDataset
```
## More
### Microsoft Presidio
>[Presidio](https://microsoft.github.io/presidio/) (Origin from Latin praesidium ‘protection, garrison’)
> helps to ensure sensitive data is properly managed and governed. It provides fast identification and
> anonymization modules for private entities in text and images such as credit card numbers, names,
> locations, social security numbers, bitcoin wallets, US phone numbers, financial data and more.
First, you need to install several python packages and download a `SpaCy` model.
```bash
pip install langchain-experimental openai presidio-analyzer presidio-anonymizer spacy Faker
python -m spacy download en_core_web_lg
```
See [usage examples](/docs/guides/privacy/presidio_data_anonymization/).
```python
from langchain_experimental.data_anonymizer import PresidioAnonymizer, PresidioReversibleAnonymizer
```