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kumoai

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library2.22.0pypypi✓ verified 85d ago

The Kumo Python SDK (`kumoai`) provides a composable, modular interface for interacting with the Kumo machine learning platform. This platform leverages Graph Neural Networks (GNNs) to generate predictive analytics and insights directly from relational data. The SDK is currently at version 0.79.0 and receives frequent updates, often including new features and stability enhancements.

pip install kumoai
INSTALL
IMPORT
SIG · KUMOAI
K
kumoai
ai-mlpythonv2.22.0
Install
19.3s avg
Import
3994ms
Disk
441MB
Pass rate
9/ 10
Env Coverage9 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v2.22.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
glibc
py 3.10
✓ —
✓ 20.66s
py 3.11
✓ —
✓ 18.18s
py 3.12
✓ —
✓ 16.84s
py 3.13
✓ —
✓ 17.38s
py 3.9
✕ build_error
✓ 23.38s
441MB installed
● package 441MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

rfm
import kumoai.experimental.rfm as rfm
Primary import for KumoRFM client and graph operations.
kumoai
import kumoai as kumo
General import for broader SDK functionalities.
LocalGraph
from kumoai.experimental.rfm import LocalGraph
from kumoai.graph import LocalGraph
LocalGraph is part of the `experimental.rfm` submodule for the KumoRFM API, not directly under `kumoai.graph` for this use case.

This quickstart demonstrates how to install the Kumo SDK, initialize a client with an API key, load an example dataset using pandas, create a local graph, and make a predictive query using KumoRFM.

import os import pandas as pd import kumoai.experimental.rfm as rfm # Retrieve API key from environment variable for security KUMO_API_KEY = os.environ.get('KUMO_API_KEY', '') # Initialize the KumoRFM client # You can generate an API key at https://kumorfm.ai/api-keys rfm.init(api_key=KUMO_API_KEY) # Example: Load E-Commerce dataset using pandas dataset_url = "s3://kumo-sdk-public/rfm-datasets/online-shopping" users_df = pd.read_parquet(f"{dataset_url}/users.parquet") items_df = pd.read_parquet(f"{dataset_url}/items.parquet") orders_df = pd.read_parquet(f"{dataset_url}/orders.parquet") # Create a local graph from dataframes graph = rfm.LocalGraph.from_data({ "users": users_df, "items": items_df, "orders": orders_df, }) # Initialize the KumoRFM model with the graph model = rfm.KumoRFM(graph) # Make a prediction (e.g., forecast 30-day product demand) query = "PREDICT SUM(orders.price, 0, 30, days) FOR items.item_id=1" result = model.predict(query) print("Prediction Result:") print(result.head())
Debug
Known issues
gotchaKumo AI requires an API key for authentication, which should be treated as sensitive. Free accounts typically have daily query limits (e.g., 1000/day). Exceeding these limits will result in HTTP 429 Too Many Requests errors.
fix
Generate your API key from the Kumo UI (kumorfm.ai/api-keys). Store it securely, preferably as an environment variable (e.g., `KUMO_API_KEY`). Monitor your usage to stay within rate limits, or upgrade your plan for higher limits.
affects: All
breakingThe Kumo AI SDK is under active development. Minor version updates can introduce breaking changes, particularly in submodules marked 'experimental'. Pay close attention to release notes for changes in API structure or required parameters.
fix
Always check the official documentation and release notes before upgrading, especially when moving between minor versions. Pin your `kumoai` dependency to a specific version (e.g., `kumoai==0.79.0`) to prevent unexpected breakage.
affects: All versions, especially between minor releases (e.g., 0.x to 0.y)
gotchaData quality significantly impacts prediction accuracy. Kumo expects genuinely missing values to be represented by completely blank entries. Using 'null', 'N/A', '-1', or similar strings for missing data will cause these to be treated as actual values, leading to erroneous model training and predictions.
fix
Ensure that your input data adheres to Kumo's data quality guidelines. Specifically, for missing values, leave fields entirely blank. Review Kumo's documentation on data types and semantic types for best practices.
affects: All
Errors
Common errors & fixes
HTTP 429 Too Many Requests
The client has sent too many requests within a given timeframe, exceeding the Kumo API's rate limits.
fix
Implement rate limiting or exponential backoff in your application. Check your Kumo account's daily query limit (e.g., 1000/day for free tier) and consider upgrading your plan if higher throughput is needed.
HTTP 403 Forbidden
The provided API key is invalid, expired, or the request is unauthorized for another reason.
fix
Verify that your `KUMO_API_KEY` is correct and current. Generate a new API key from the Kumo AI Admin tab if necessary, as old keys are invalidated upon rotation. Ensure no VPN or network policy is blocking access.
AttributeError: module 'kumoai' has no attribute 'LocalGraph'
Attempting to import `LocalGraph` directly from the top-level `kumoai` package or an incorrect submodule.
fix
The `LocalGraph` class (for KumoRFM) is located under `kumoai.experimental.rfm`. Use `from kumoai.experimental.rfm import LocalGraph` or `kumoai.experimental.rfm.LocalGraph`.
Upgrade
Version history
2.22.0latest on PyPI · released May 11, 2026
Audit
Dependencies
pandasoptionalCommonly used for data loading and manipulation in quickstart examples and typical ML workflows.
Agent activity
14 hits · last 30 days
node
12
Resources