Python SDK Quickstart

Get started with the Claro Python SDK in just a few lines of code.

Prerequisites

Python 3.8 or higher
Claro SDK installed (pip install baytos-claro)
API key from Claro settings

Installation

Install the SDK using pip:

pip install baytos-claro

Basic Usage

import os
from baytos.claro import BaytClient

# Initialize the client
client = BaytClient(api_key=os.getenv("BAYT_API_KEY"))

# Get a prompt
prompt = client.get_prompt("@workspace/my-prompt:v1")

# Access prompt content
print(prompt.title)
print(prompt.generator)  # The main prompt content

Understanding Package Names

Claro uses semantic versioning for prompts:

@workspace/prompt-name:version

@workspace - Your workspace identifier
prompt-name - The prompt’s name (lowercase, hyphenated)
version - The version (e.g., v1, v2, latest)

Find a prompt’s package name in the Claro dashboard under the prompt’s settings.

Working with Prompt Versions

# Get a specific version
prompt_v1 = client.get_prompt("@workspace/customer-support:v1")

# Get the latest version
prompt_latest = client.get_prompt("@workspace/customer-support:latest")

# Compare versions
if prompt_v1.version != prompt_latest.version:
    print(f"New version available: {prompt_latest.version}")

Using Prompts with LLMs

OpenAI Example

import os
from baytos.claro import BaytClient
from openai import OpenAI

# Initialize clients
claro_client = BaytClient(api_key=os.getenv("BAYT_API_KEY"))
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# Get prompt from Claro
prompt = claro_client.get_prompt("@workspace/assistant:v1")

# Use with OpenAI
response = openai_client.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "system", "content": prompt.generator},
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Anthropic Example

import os
from baytos.claro import BaytClient
import anthropic

# Initialize clients
claro_client = BaytClient(api_key=os.getenv("BAYT_API_KEY"))
anthropic_client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))

# Get prompt from Claro
prompt = claro_client.get_prompt("@workspace/assistant:v1")

# Use with Claude
response = anthropic_client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    system=prompt.generator,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.content[0].text)

Listing Prompts

# List all prompts in your workspace
result = client.list_prompts(limit=20)

for prompt in result['prompts']:
    print(f"{prompt.title} - {prompt.package_name}")

# Pagination
if result.get('next_cursor'):
    next_page = client.list_prompts(limit=20, cursor=result['next_cursor'])

Error Handling

from baytos.claro import BaytClient, BaytNotFoundError, BaytAuthError

client = BaytClient(api_key=os.getenv("BAYT_API_KEY"))

try:
    prompt = client.get_prompt("@workspace/my-prompt:v1")
    print(prompt.generator)
except BaytNotFoundError:
    print("Prompt not found - check the package name")
except BaytAuthError:
    print("Authentication failed - check your API key")
except Exception as e:
    print(f"Unexpected error: {e}")

Complete Example

Here’s a complete working example:

#!/usr/bin/env python3
"""
Complete Claro SDK example showing common patterns
"""

import os
from baytos.claro import BaytClient, BaytNotFoundError
from openai import OpenAI

def main():
    # Initialize clients
    claro_client = BaytClient(api_key=os.getenv("BAYT_API_KEY"))
    openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

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

        print(f"Using prompt: {prompt.title} (v{prompt.version})")

        # Use it with OpenAI
        response = openai_client.chat.completions.create(
            model="gpt-4",
            messages=[
                {"role": "system", "content": prompt.generator},
                {"role": "user", "content": "How do I reset my password?"}
            ],
            temperature=0.7,
            max_tokens=500
        )

        print("\nResponse:")
        print(response.choices[0].message.content)

    except BaytNotFoundError:
        print("Error: Prompt not found. Check the package name.")
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    main()

Environment Variables

Create a .env file for local development:

.env

BAYT_API_KEY=your_claro_api_key
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key

Load it with python-dotenv:

from dotenv import load_dotenv
load_dotenv()

Always add .env to your .gitignore to avoid committing secrets

Next Steps

Client Configuration

Configure timeouts, retries, and connection pooling

Working with Prompts

Learn about prompt metadata and versioning

Context Files

Handle file attachments and URLs

Error Handling

Robust error handling patterns

Getting Started

Python SDK

Examples

Guides

Python SDK Quickstart

Python SDK Quickstart

Prerequisites

Installation

Basic Usage

Understanding Package Names

Working with Prompt Versions

Using Prompts with LLMs

OpenAI Example

Anthropic Example

Listing Prompts

Error Handling

Complete Example

Environment Variables

Next Steps

Client Configuration

Working with Prompts

Context Files

Error Handling

​Python SDK Quickstart

​Prerequisites

​Installation

​Basic Usage

​Understanding Package Names

​Working with Prompt Versions

​Using Prompts with LLMs

​OpenAI Example

​Anthropic Example

​Listing Prompts

​Error Handling

​Complete Example

​Environment Variables

​Next Steps

Client Configuration

Working with Prompts

Context Files

Error Handling

Python SDK Quickstart

Prerequisites

Installation

Basic Usage

Understanding Package Names

Working with Prompt Versions

Using Prompts with LLMs

OpenAI Example

Anthropic Example

Listing Prompts

Error Handling

Complete Example

Environment Variables

Next Steps