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Documentation Index

Fetch the complete documentation index at: https://docs.gately.ai/llms.txt

Use this file to discover all available pages before exploring further.

SDK Installation

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Official SDKs

Gately AI provides official client libraries for Python and JavaScript to help you integrate with our API quickly and efficiently.

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Installation

pip install taam-cloud==1.0.0
Requirements:
  • Python 3.8+

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Basic Usage

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Python SDK

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

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Node.js SDK

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);

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Advanced Features

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Streaming Chat Responses

chat_stream = client.chat.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "user", "content": "Write a short poem about clouds"}
    ],
    stream=True
)

for chunk in chat_stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

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Web Service Integration

# 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")

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Versioning

The Node.js SDK is currently in alpha. API changes may occur before the stable release.
We follow semantic versioning for our SDKs:
  • Python SDK: Stable version 1.0.0
  • Node.js SDK: Alpha version 0.1.0-alpha.3

Looking for TypeScript support?

The Node.js SDK includes TypeScript type definitions.

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Need Help?

SDK Reference

View the complete SDK reference documentation

Community Support

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