Database system for AI-powered apps
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EvaDB enables software developers to build AI apps in a few lines of code. Its powerful SQL API simplifies AI app development for both structured and unstructured data. EvaDB's benefits include:
Structured Data Sources | Unstructured Data Sources | Application Data Sources |
---|---|---|
- PostgreSQL - SQLite - MySQL - MariaDB - Clickhouse - Snowflake | - Local filesystem - AWS S3 bucket | - Github |
Hugging Face | OpenAI | YOLO |
---|---|---|
- Audio Classification - Automatic Speech Recognition - Text Classification - Summarization - Text2Text Generation - Text Generation - Image Classification - Image Segmentation - Image-to-Text - Object Detection - Depth Estimation | - gpt-4 - gpt-4-0314 - gpt-4-32k - gpt-4-32k-0314 - gpt-3.5-turbo - gpt-3.5-turbo-0301 | - yolov8n.pt - yolov8s.pt - yolov8m.pt - yolov8l.pt - yolov8x.pt |
Regression | Classification | Time Series Forecasting |
---|---|---|
- Ludwig - Sklearn - Xgboost | - Ludwig - Xboost | - Statsforecast - Neuralforecast |
๐ Hey! If you're excited about our vision of bringing AI inside database systems, show some โค๏ธ by:
We would love to learn about your AI app. Please complete this 1-minute form: https://v0fbgcue0cm.typeform.com/to/BZHZWeZm
You can find the complete documentation of EvaDB at evadb.ai/docs ๐โจ๐
In the world of AI, we've reached a stage where many AI tasks that were traditionally handled by AI or ML engineers can now be automated. EvaDB enables software developers with the ability to perform advanced AI tasks without needing to delve into the intricate details.
EvaDB covers many AI applications, including regression, classification, image recognition, question answering, and many other generative AI applications. EvaDB targets 99% of AI problems that are often repetitive and can be automated with a simple function call in an SQL query. Until now, there is no comprehensive open-source framework for bringing AI into an existing SQL database system with a principled AI optimization framework, and that's where EvaDB comes in.
Our target audience is software developers who may not necessarily have a background in AI but require AI capabilities to solve specific problems. We target programmers who write simple SQL queries inside their CRUD apps. With EvaDB, it is possible to easily add AI features to these apps by calling built-in AI functions in the queries.
SELECT name, country, email, programming_languages, social_media, GPT4(prompt,topics_of_interest)
FROM gpt4all_StargazerInsights;
--- Prompt to GPT-4
You are given 10 rows of input, each row is separated by two new line characters.
Categorize the topics listed in each row into one or more of the following 3 technical areas - Machine Learning, Databases, and Web development. If the topics listed are not related to any of these 3 areas, output a single N/A. Do not miss any input row. Do not add any additional text or numbers to your output.
The output rows must be separated by two new line characters. Each input row must generate exactly one output row. For example, the input row [Recommendation systems, Deep neural networks, Postgres] must generate only the output row [Machine Learning, Databases].
The input row [enterpreneurship, startups, venture capital] must generate the output row N/A.
CREATE INDEX reddit_sift_image_index
ON reddit_dataset (SiftFeatureExtractor(data))
USING FAISS
SELECT name FROM reddit_dataset ORDER BY
Similarity(
SiftFeatureExtractor(Open('reddit-images/g1074_d4mxztt.jpg')),
SiftFeatureExtractor(data)
)
LIMIT 5
Here are some illustrative AI apps built using EvaDB (each notebook can be opened on Google Colab):
We would love to learn about your AI app. Please complete this 1-minute form: https://v0fbgcue0cm.typeform.com/to/BZHZWeZm
If you run into any bugs or have any comments, you can reach us on our Slack Community ๐ or create a Github Issue :bug:.
Here is EvaDB's public roadmap ๐ค๏ธ. We prioritize features based on user feedback, so we'd love to hear from you!
We are a lean team on a mission to bring AI inside database systems! All kinds of contributions to EvaDB are appreciated ๐ If you'd like to get involved, here's information on where we could use your help: contribution guide ๐ค
Copyright (c) Georgia Tech Database Group. Licensed under an Apache License.