SDK Installation

import os
from taam_cloud import TaamCloud

# Initialize the client
client = TaamCloud(api_key=os.environ.get("TAAM_API_KEY"))

# Chat completion
response = client.chat.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is artificial intelligence?"}
    ]
)

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

# Generate embeddings
embeddings = client.embeddings.create(
    model="text-embedding-3-small",
    input="Represent this text as an embedding vector"
)

print(embeddings.data[0].embedding[:5])  # Print first 5 values

import { TaamCloud } from 'taam-cloud';

// Initialize the client
const client = new TaamCloud({
  apiKey: process.env.TAAM_API_KEY
});

async function main() {
  // Chat completion
  const chatResponse = await client.chat.completions.create({
    model: "gpt-4-turbo",
    messages: [
      {role: "system", content: "You are a helpful assistant."},
      {role: "user", content: "What is artificial intelligence?"}
    ]
  });
  
  console.log(chatResponse.choices[0].message.content);
  
  // Generate embeddings
  const embeddingResponse = await client.embeddings.create({
    model: "text-embedding-3-small",
    input: "Represent this text as an embedding vector"
  });
  
  console.log(embeddingResponse.data[0].embedding.slice(0, 5));  // Print first 5 values
}

main().catch(console.error);

# Scrape a webpage
scrape_result = client.web.scrape(
    url="https://example.com",
    formats=["markdown", "links"]
)

print(f"Page content: {scrape_result.data.markdown[:100]}...")
print(f"Found {len(scrape_result.data.links)} links")