Canso - ML Platform
  • 👋Introduction
  • 🏛️Canso Architecture
  • 💻Getting Started
    • 🏁Overview
    • 🌌Provison K8s Clusters
    • 🚢Install Canso Helm Charts
    • 🐍🔗 Canso Python Client & Web App
    • 📊Health Metrics for Features in the Data Plane
  • 💡Feature Store
    • Data Sources
      • Data Spans
    • Data Sinks
    • ML Features
      • Raw ML Batch Feature
      • Derived ML Batch Feature
      • Raw ML Streaming Feature
      • Custom User Defined Function
  • 💡AI Agents
    • Introduction
    • Getting Started
    • Quickstart
    • Use Cases
      • Fraud Analyst Agent
    • Concepts
      • Task Server
      • Broker
      • Checkpoint DB
      • Memory
      • Conversation History
    • How Tos
      • Update the AI Agent
      • Delete the AI Agent
    • Toolkit
      • SQL Runner
      • Kubernetes Job
    • API Documentation
    • Memory API Documentation
  • 💡Risk
    • Overview
    • Workflows and Rules
    • Real Time Transaction Monitoring
    • API Documentation
  • 📝Guides
    • Registry
    • Dry Runs for Batch ML Features
    • Deployment
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  1. Getting Started

🐍🔗 Canso Python Client & Web App

Data Scientists, ML Engineers, Data Engineers can install the Canso Python client to interact with the Canso API Server to define and deploy ML pipelines and AI Agents.

The Python client is a pip installable python library. All you need to do is a pip install or a pip3 install and you're all set to access the API. Please note that prior to using this, you must have a Canso-compatible Kubernetes cluster and the Canso Helm charts installed on the cluster.

pip3 install gru

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Last updated 3 months ago

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