PixelyAI Serve Engine
Project description
PixelyAI Core🧬
Introduction
PixelyAI Core is the core component of PixelyAI, an AI assistant that helps businesses manage their customers and their team more effectively. It provides a suite of tools for hosting and interacting with large language models (LLMs), making it easy to integrate these powerful AI capabilities into your applications.
Key Features
-
Support for Multiple Backends: with Using AgentX PixelyAI Core supports popular backends for hosting LLMs Like
GGUF
,Torch
,EasyDeL
andOLlama
. This flexibility allows you to choose the backend that best suits needs and infrastructure. -
Simplified API: PixelyAI Core provides an easy-to-use API for interacting with LLMs. This API makes it simple to send queries to LLMs, receive responses, and handle errors.
-
Gradio Integration: PixelyAI Core integrates seamlessly with
Gradio
, a web framework for building interactive AI applications. This integration allows you to create intuitive interfaces for interacting withLLMs
, making it easier for users to access their capabilities.
Benefits
-
Improved Customer Support: Empower your customer support team with conversational AI capabilities, enabling them to provide more personalized and efficient support.
-
Enhanced Team Collaboration: Facilitate knowledge sharing and collaboration among team members through natural language interactions.
-
Automated Task Delegation: Automate routine tasks, such as report generation and data analysis, freeing up team members to focus on more strategic initiatives.
Getting Started
To install PixelyAI Core, simply use the following command:
pip install pixelyai-core
Once installed, you can start using the PixelyAI Core API to interact with LLMs. For more information, please refer to the official documentation.
Client UseCase Example
Here's a simple use case of PixelyAI Chat and RAG Agents
from pixelyai_core import PixelClient
client = PixelClient(
"http://127.0.0.1:7860/"
)
# in case that contexts is None the RAG agent won't be used
contexts = None
# Using RAG Agent with contexts be Like
contexts = [
(
"The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris,"
" France. It is named after the engineer Gustave Eiffel, whose company designed"
" and built the tower. Constructed from 1887 to 1889 as the entrance to the 1889 World's "
"Fair, it was initially criticized by some of France's leading artists and intellectuals for "
"its design, but it has become a global cultural icon of France and one of the most recognizable"
" structures in the world. The Eiffel Tower is the most-visited paid monument in the world; 6.91 "
"million people ascended it in 2015. The tower is 324 meters (1,063 ft) tall, about the same height "
"as an 81-story building, and the tallest structure in Paris. Its base is square, measuring 125 meters"
" (410 ft) on each side. During its construction, the Eiffel Tower surpassed the Washington Monument to become "
"the tallest man-made structure in the world, a title it held for 41 years until the Chrysler Building in New "
"York City was finished in 1930. It was the first structure to reach a height of 300 meters. Due"
" to the addition of a broadcasting aerial at the top of the tower in 1957, it is now taller than the Chrysler"
" Building by 5.2 meters (17 ft). Excluding transmitters, the Eiffel Tower is the second tallest free-standing "
"structure in France after the Millau Viaduct."
),
(
"The tower has three levels for visitors, with restaurants on the first and second levels."
" The top level's upper platform is 276 m (906 ft) above the ground – the highest observation"
" deck accessible to the public in the European Union. Tickets can be purchased to ascend by "
"stairs or lift to the first and second levels. The climb from ground level to the first level "
"is over 300 steps, as is the climb from the first level to the second. Although there is a staircase"
" to the top level, it is usually accessible only by lift."
)
]
response = client(
prompt="who can i travel to canada?",
contexts=contexts,
conversation_history=[
{"user": "hello"},
{"assistant": "Hello! How can i help you today?"}
]
)
Conclusion
PixelyAI Core is a powerful tool for businesses seeking to leverage the capabilities of LLMs to improve their customer service, collaboration, and productivity. With its support for multiple backends, simplified API, PixelyAI Core provides a versatile and user-friendly platform for integrating LLMs into your applications.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file pixelyai_core-0.0.37.tar.gz
.
File metadata
- Download URL: pixelyai_core-0.0.37.tar.gz
- Upload date:
- Size: 11.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3de40ed4426a2d742c95a298ba623ed696841f55983613498de8110fbdf967af |
|
MD5 | ea9dc6f26bc89d9fd4a5cb22e8d14482 |
|
BLAKE2b-256 | 412e7e305e8615988b48775b6785739cc72f5d23b1f6189c4b1125cf5d677d04 |
File details
Details for the file pixelyai_core-0.0.37-py3-none-any.whl
.
File metadata
- Download URL: pixelyai_core-0.0.37-py3-none-any.whl
- Upload date:
- Size: 11.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4f905835860f0644e0cd3c17590eb934d62e4a0886900a49c480cc7f4ec66cc2 |
|
MD5 | 756ad2c06c29cce7391e4a1ea83421be |
|
BLAKE2b-256 | f8c6b136269ceb5aa4d3b99efdc21370a3cac22db81f6ddd217684aa40a27f27 |