Skip to main content

Python SDK for Momento AI — image vectorization, face search, and CLIP embeddings with user-supplied Supabase credentials.

Project description

🧠 MomentoAI — Python SDK

MomentoAI is a lightweight Python SDK that connects to the hosted MomentoAI FastAPI backend and uses your own Supabase project to store images and embeddings.

Official PyPi published library: https://pypi.org/project/momentoai/


📦 Installation

Install MomentoAI via PyPI:

pip install momentoai

⚙️ Initialize the Client

from MomentoAI import MomentoAIClient

client = MomentoAIClient(
    api_key="public-access",   # default key for open access
    api_url="https://momento-ai-1-42230574747.asia-south1.run.app",

    # — your own Supabase credentials —
    supabase_url="https://yourproject.supabase.co",
    supabase_service_key="YOUR_SUPABASE_SERVICE_KEY",
    supabase_bucket="YOUR_BUCKET_NAME"
)

🩺 Check Backend Status

Use .health() to verify the backend is live:

print(client.health())

Expected output:

{
  "models_loaded": true
}

📸 Core SDK Functions

Below are the main operations supported by the MomentoAI SDK.


1️⃣ vectorize_image()

Uploads an image → extracts embeddings → stores them in your Supabase project.

response = client.vectorize_image(
    "me.jpg",
    event_id="event1",
    business_id="business1"
)

print(response)

2️⃣ find_face()

Finds similar faces in your stored Supabase embeddings.

matches = client.find_face(
    "person.jpg",
    event_id="event1",
    business_id="business1"
)

print(matches)

3️⃣ search_images()

Text → Image retrieval using CLIP embeddings.

results = client.search_images(
    "a man smiling outdoors",
    event_id="event1",
    business_id="business1"
)

print(results)

4️⃣ list_embeddings()

Retrieve all embeddings for a specific event + business.

records = client.list_embeddings(
    event_id="event1",
    business_id="business1"
)

print(records)

5️⃣ delete_embedding()

Delete a specific embedding record from Supabase.

client.delete_embedding("some-embedding-id")

🪪 License

MIT License
© 2025 — Manil Modi

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

momentoai-0.1.2.tar.gz (5.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

momentoai-0.1.2-py3-none-any.whl (7.6 kB view details)

Uploaded Python 3

File details

Details for the file momentoai-0.1.2.tar.gz.

File metadata

  • Download URL: momentoai-0.1.2.tar.gz
  • Upload date:
  • Size: 5.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.9

File hashes

Hashes for momentoai-0.1.2.tar.gz
Algorithm Hash digest
SHA256 849f80a1064d51064b921dcdf42849027c0e0f918733fdea271da9c04fff74dc
MD5 6eb554ed7e170724a41862e5b06bfc52
BLAKE2b-256 72e9a566a6bf96e3c8a575a859a8f0adb6af84864d395209b446179c354d9004

See more details on using hashes here.

File details

Details for the file momentoai-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: momentoai-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 7.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.9

File hashes

Hashes for momentoai-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 2aa664a687e9657f2aed72f0ee5802a1715d249526f2565227bd2a4693987eb5
MD5 0b921cf44bb2c75cd7638164c5176b84
BLAKE2b-256 4248ff87f8e9bdcd3d63ffcec9dd5fdbf200fa84b803b2ed41f3a65ff604220d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page