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For Developers

This documentation covers:
  • Python SDK - Integrate Claro into your Python applications
  • REST API - Direct API access for any language
  • Code Examples - Production-ready patterns and examples
  • Guides - Best practices for testing, security, and performance

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Quick Example

from baytos.claro import BaytClient

# Initialize once
client = BaytClient(api_key="your_api_key")

# Get the latest version of your prompt
prompt = client.get_prompt("@workspace/customer-support:v1")

# Use it in your application
response = llm.generate(prompt.generator, context=user_message)
When your team updates the prompt in the Claro dashboard, your next API call automatically gets the new version. No code changes required.

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Key Features

Version Control

Version your prompts like code. Roll back, compare versions, and maintain prompt history.

Workspace Collaboration

Teams work together on prompts with proper access control and permissions.

Context Attachments

Attach files and URLs to prompts. The SDK handles downloading and caching automatically.

Package Naming

Organize prompts with semantic versioning: @workspace/name:version

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Getting Started

Quickstart

Get up and running in 5 minutes

Python SDK

Install and configure the Python SDK

API Reference

Explore the REST API endpoints

Examples

View production-ready code examples

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Why Claro?

Problem: Every prompt change requires a code deployment
  • Marketing wants to update the chatbot message → 3-day deployment cycle
  • Product needs to adjust tone → Full CI/CD pipeline
  • Support wants to add context → Code review + release
Solution: Claro decouples AI instructions from your codebase
  • Non-technical teams update prompts directly
  • Developers integrate once using the SDK
  • Changes go live in seconds, not days

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Next Steps

  1. Get your API key from the Claro platform
  2. Follow the quickstart to make your first API call
  3. Explore examples for common use cases
  4. Read the guides for best practices

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