deepkeep

Deepkeep API Quickstart - Python

Welcome to the official repository for quick start applications utilizing the Deepkeep's SDK. Our SDK is designed to streamline interactions with ML models like LLMs and Object detection, providing an intuitive Python interface for managing models, datasets, users, and processing pipelines to provied ML security security and trust assessments or provied a firewall for ML Models incrissing trust and security rubustness. This repository is your starting point to dive into leveraging our advanced AI and machine learning trust and security capabilities across various endpoints, including model management, user authentication, conversational AI, and customized content moderation pipelines.

Basic request

To send your first API request with the Deepkeep Python SDK, make sure you have the right dependencies installed and then run the following code:

host_id = "DEEPKEEP_HOST_ID"
access_key = "DEEPKEEP_ACCESS_KEY"
secret_key = "DEEPKEEP_SECRET_KEY"
base_url = "DEEPKEEP_BASE_URL"

user_id = access_key
dk_client = Deepkeep(access_key=access_key, secret_key=secret_key, base_url=base_url)

# Create a new conversaion
conversation_id = dk_client.conversation.create(user_id=user_id, host_id=host_id)["id"]

# Convers with the assistant
content = "<MESSAGE>"
assistant_response = dk_client.message.create(host_id=host_id, conversation_id=conversation_id, content=content)
print(assistant_response["content"])

# Converse Debug Mode
content = "<MESSAGE>"
assistant_response = dk_client.message.create(monitor=host_id, conversation_id=conversation_id, content=content, verbose=True)
print(assistant_response["content"])
print(assistant_response["statistics"])

# Note: another optional way to create Deepkeep client is using a token instead of access_key and secret_key
# client = Deepkeep(token="<Access Token>", base_url=base_url)

Setup

If you don't have Python installed, install it from Python.org.
Clone this repository.
Navigate into the project directory:
```
$ cd deepkeep-quickstart-python
```

Create a new virtual environment:

macOS:

$ python -m venv venv
$ . venv/bin/activate

Windows:

> python -m venv venv
> .\venv\Scripts\activate

Install the requirements:
```
$ pip install -r requirements.txt
```
Run the notebooks:

Install JupyterLab with pip:

pip install jupyterlab

Once installed, launch JupyterLab with:

jupyter lab

You should now be able to access the notebooks from your browser at the following URL: http://localhost:8888/lab!

Release files for deepkeep 1.2.13

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for deepkeep 1.2.13
File	Size	Uploaded
deepkeep-1.2.13.tar.gz	15.1 kB	Mar 6, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for deepkeep 1.2.13
File	Interpreter	ABI	Platform	Reset
deepkeep-1.2.13-py3-none-any.whl 28.2 kB Mar 6, 2025	Python 3	none	any	Details

Total release size: 43.2 kB

Release files / deepkeep-1.2.13.tar.gz

Download URL	deepkeep-1.2.13.tar.gz
Size	15.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`9c15d2c6f3f2b16ada9e2ffdd88dfbe5f913472daf14f240a9dbf7e47ef05c92`
BLAKE2b-256 checksum How to use checksums	`0983ff2d72545a3991000fd826f11ac754d83c331ce423a2282c367223cf29f8`
Upload date	Mar 6, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.6.1 CPython/3.11.9 Darwin/24.0.0`

Release files / deepkeep-1.2.13-py3-none-any.whl

Download URL	deepkeep-1.2.13-py3-none-any.whl
Size	28.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`1fd1c9e627634df873acf44ea962c18b07f5c1d829534f0ccd88d079ac450818`
BLAKE2b-256 checksum How to use checksums	`4343133635eb3a377ed5ed9d0074b01ea8755f53e2e4a9b829e2fa135076043c`
Upload date	Mar 6, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.6.1 CPython/3.11.9 Darwin/24.0.0`