clarifai
Decision gist · record as of 2026-08-14
Yes, if you are building on the Clarifai platform and need a Python interface to its managed AI services. Low install friction, active maintenance, permissive Apache 2.0 license, and zero known vulnerabilities make it safe to adopt. However, you are committing to Clarifai's ecosystem and pricing model; this is not a general-purpose ML library but a client for a specific commercial platform.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- CLARIFAI_PAT environment variable or pat constructor argument required; Clarifai account and Personal Access Token must be created in advance
- Low friction installation as a pure-Python wheel.
- Active maintenance with a recent release and ongoing repository activity.
License · maintenance · safety
Apache 2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include a copy of the license and note any changes.
last release 2026-05-08 (98 days) · last repo commit 2026-06-25 · 46 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 76,734 downloads/mo, #14,594 on PyPI
Alternatives
Verify before relying
pip install clarifai
from clarifai.client.user import User
client = User(user_id="user_id", pat="your_personal_access_token")
apps_generator = client.list_apps()
apps = list(apps_generator)- Whether all 22 dependencies are required for basic usage or if some are optional for specific features
- Performance characteristics and rate limits when making concurrent requests through aiohttp
- Specific Python version constraints beyond the stated >=3.9 requirement
What it is and what it does
Clarifai is the official Python SDK for Clarifai's AI platform, a service that provides pre-trained and custom machine learning models for both vision and language tasks. It wraps Clarifai's gRPC API (via clarifai-grpc and clarifai-protocol) and exposes high-level Python classes to manage datasets, models, workflows, and inference jobs. The SDK handles authentication via Personal Access Tokens, manages data upload and retrieval, orchestrates model training and deployment across compute clusters, and provides search and retrieval-augmented generation capabilities.
The package is designed for developers integrating AI capabilities into applications without building models from scratch. It abstracts away gRPC protocol details and provides a Pythonic interface for common tasks: uploading images or text, running predictions, training custom models, and composing multi-step workflows. With 22 runtime dependencies—including numpy for array handling, requests and aiohttp for HTTP communication, and openai for LLM integration—it is a feature-complete client for a managed AI platform.
Use it for
- Upload images to a Clarifai dataset and train a custom classification model for domain-specific recognition
- Run batch predictions on image or text inputs using pre-trained models without managing infrastructure
- Build multi-step workflows combining vision detection, segmentation, and NLP to process complex media
- Implement semantic search over a dataset of images or documents using Clarifai's embedding models
- Orchestrate model training and deployment across distributed compute clusters with automatic scaling
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building on the Clarifai platform and need a Python interface to its managed AI services.
Low install friction, active maintenance, permissive Apache 2.0 license, and zero known vulnerabilities make it safe to adopt. However, you are committing to Clarifai's ecosystem and pricing model; this is not a general-purpose ML library but a client for a specific commercial platform.
Install
clarifai on PyPI
Before you install
Low friction installation as a pure-Python wheel. Active maintenance with a recent release and ongoing repository activity. Requires 22 runtime dependencies including numpy, requests, aiohttp, and openai, which adds complexity to the dependency graph but are all standard ecosystem packages.
CLARIFAI_PAT environment variable or pat constructor argument required; Clarifai account and Personal Access Token must be created in advance
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you include a copy of the license and note any changes.
Quickstart
pip install clarifai
from clarifai.client.user import User
client = User(user_id="user_id", pat="your_personal_access_token")
apps_generator = client.list_apps()
apps = list(apps_generator)Verify before relying
- Whether all 22 dependencies are required for basic usage or if some are optional for specific features
- Performance characteristics and rate limits when making concurrent requests through aiohttp
- Specific Python version constraints beyond the stated >=3.9 requirement
Package facts
| License | Apache 2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 22 packagesclarifai-grpcclarifai-protocolnumpytqdmPyYAMLschemaPillowtabulatefsspecclickclick-option-grouprequestsaiohttppsutilpygmentspydantic_corepackagingtenacityhttpxopenaihuggingface_hubhf-transfer |
| Maintenance | Actively maintained 98 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 76,734 / month, #14,594 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.9Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: clarifai-12.5.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “clarifai API integration”
- clarifaiOfficial Python client for Clarifai's AI platform, enabling computer…
- clarifai-protocolProvides the protocol layer for Clarifai's Python runners to…
- clarifai-grpcA gRPC client library for the Clarifai AI platform, enabling Python…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also clarifai-grpc · clarifai-protocol · pydo · lightning-cloud · osfclient · civis · matrice · athina-client · roboflow · fal-client