Backend SDKs Overview

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Introduction

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Available SDKs

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Core Features

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🔐 Authentication & Security

import { Suada } from '@suada/node';

const suada = new Suada({
  apiKey: process.env.SUADA_API_KEY,
  privacyMode: true  // Optional enhanced security
});

from suada import Suada, SuadaConfig

suada = Suada(
    config=SuadaConfig(
        api_key=os.getenv("SUADA_API_KEY"),
        privacy_mode=True  # Optional enhanced security
    )
)

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🤖 LangChain Integration

import { Suada } from '@suada/node';
import { AgentExecutor, createOpenAIFunctionsAgent } from 'langchain/agents';
import { ChatOpenAI } from 'langchain/chat_models/openai';

const suada = new Suada({
  apiKey: process.env.SUADA_API_KEY
});

const suadaTool = suada.createTool({
  name: 'business_analyst',
  description: 'Use this tool for business insights'
});

const agent = await createOpenAIFunctionsAgent({
  llm: new ChatOpenAI({ temperature: 0 }),
  tools: [suadaTool]
});

const executor = AgentExecutor.fromAgentAndTools({
  agent,
  tools: [suadaTool]
});

from suada import Suada, SuadaConfig
from langchain.agents import AgentExecutor, create_openai_functions_agent
from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationBufferMemory

suada = Suada(
    config=SuadaConfig(
        api_key="your-api-key"
    )
)

suada_tool = suada.create_tool(
    name="business_analyst",
    description="Use this tool for business insights"
)

agent = create_openai_functions_agent(
    llm=ChatOpenAI(temperature=0),
    tools=[suada_tool]
)

memory = ConversationBufferMemory(
    memory_key="chat_history",
    return_messages=True
)

executor = AgentExecutor.from_agent_and_tools(
    agent=agent,
    tools=[suada_tool],
    memory=memory
)

​

💬 Chat Interface

interface SuadaResponse {
    // Main response text
    answer: string;
    
    // Optional fields
    thoughts?: string;
    actions?: Array<{
        tool: string;
        toolInput: string;
        log: string;
    }>;
    followUpQuestion?: string;
    reasoning?: string;
    sources?: string[];
    conversationId?: string;
    timestamp: number;
}

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👤 User Context Management

const suada = new Suada({
  apiKey: process.env.SUADA_API_KEY,
  passthroughMode: true
});

const response = await suada.chat({
  message: "What's our performance?",
  externalUserIdentifier: "user-123"
});

suada = Suada(
    config=SuadaConfig(
        api_key=os.getenv("SUADA_API_KEY"),
        passthrough_mode=True
    )
)

response = suada.chat(
    message="What's our performance?",
    external_user_identifier="user-123"
)

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Key Benefits

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Type Safety

• Built-in TypeScript definitions (Node.js)
• Pydantic model validation (Python)
• IDE autocompletion support
• Runtime type checking

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LangChain Support

• Tool creation for LangChain agents
• Memory management for conversations
• Custom agent configurations
• Structured prompt templates

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Error Handling

• Structured error types
• Detailed error messages
• Automatic retry mechanisms
• Rate limit handling

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Performance

• Connection pooling
• Automatic retries
• Concurrent request support
• Efficient resource management

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Security

• Secure API key handling
• Privacy mode option
• User isolation in passthrough mode
• Rate limiting protection

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Getting Started

1. Choose Your SDK
   • Node.js: Modern JavaScript/TypeScript applications and web backends
   • Python: Data science, AI/ML, or Python web applications
2. Installation
   # Node.js
   npm install @suada/node langchain
   
   # Python
   pip install suada langchain
   
3. Configure Environment
   # .env file
   SUADA_API_KEY=your-api-key
   OPENAI_API_KEY=your-openai-key  # Required for LangChain integration
   
4. Initialize Client
   • Follow SDK-specific initialization
   • Configure optional features
   • Set up error handling
   • Initialize LangChain tools if needed
5. Make Your First Request
   • Send a test message
   • Handle the response
   • Implement error handling

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Best Practices

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Security

• Store API keys in environment variables
• Enable privacy mode for sensitive data
• Implement proper error handling
• Use secure user identification

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LangChain Integration

• Use clear tool descriptions
• Implement proper memory management
• Handle agent errors gracefully
• Monitor agent performance

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Performance

• Reuse SDK and agent instances
• Implement appropriate timeouts
• Handle rate limits gracefully
• Use async/await where available

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Development

• Use type checking tools
• Write comprehensive tests
• Follow SDK-specific conventions
• Keep dependencies updated

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FAQ

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Which SDK should I choose?

• Choose Node.js for JavaScript/TypeScript applications and modern web backends
• Choose Python for data science, AI/ML applications, or Python web services

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How do I handle rate limits?

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Can I use the SDKs in serverless environments?

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How do I debug SDK issues?

• Node.js: Debug environment variable
• Python: Standard logging module

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Is local development supported?

• Custom base URLs
• Debug logging
• Test environments
• Mock responses

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Support & Resources

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Documentation

• Node.js SDK Documentation
• Python SDK Documentation
• LangChain Documentation (JavaScript)
• LangChain Documentation (Python)

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Support

• Email: support@suada.ai