Welcome to xpander.ai

xpander.ai is a backend for AI Agents - it allows you to build, enhance, and deploy AI agents that can interact with 1000s of users from multiple human interfaces (Voice, Chat, Web, etc) and that can use multiple tools (API, Web, File, etc) and that can have complex state and conversation history using AI state management.

The platform provides real-time event streaming capabilities for live updates and monitoring of agent activities, along with robust multi-user session management to handle concurrent interactions across different users and contexts.

The platform natively supports multiple LLMs (OpenAI, Claude, Gemini, etc) and multiple frameworks (LlamaIndex, Smoleagents (HuggingFace), etc).

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Get started

Scenario : You want to build a simple agent that uses a single LLM and a single framework , and use xpander.ai to manage the state and conversation history, add tools and interact with your agent via Slack/ Voice/ Chat/ Web

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Installation

pip install xpander-sdk
xpander login
xpander agent new
xpander agent get

Example response:

> xpander login
✓ Successfully logged in to xpander.ai

> xpander agent new
? Agent name: my-first-agent
? Select LLM: OpenAI GPT-4
? Select framework: OpenAI
✓ Created new agent: my-first-agent
✓ Agent URL: https://amethyst-basilisk.agents.xpander.ai/
✓ Agent ID: ag_01h8x9j2p6q5r7k8m9n0
✓ API Key: xpd_sk_01h8x9j2p6q5r7k8m9n0p1q2r3s4t5u6v7w8x9y0

> xpander agent get
NAME           LLM     FRAMEWORK    STATUS    SOURCE NODES
my-first-agent GPT-4   OpenAI       Active    web

You can now interact with your agent via the web interface: https://amethyst-basilisk.agents.xpander.ai/

And load the agent in your local environment using the API key:

from xpander_sdk import XpanderClient
from openai import OpenAI
from dotenv import load_dotenv
from os import environ

# Load environment variables
load_dotenv()

OPENAI_API_KEY = environ["OPENAI_API_KEY"]
XPANDER_API_KEY = environ["XPANDER_API_KEY"]
XPANDER_AGENT_ID = environ["XPANDER_AGENT_ID"]

xpander_agent = XpanderClient(api_key=XPANDER_API_KEY).agents.get(agent_id=XPANDER_AGENT_ID)

xpander_agent.add_task("What is the weather in Tokyo?")

response = openai_client.chat.completions.create(
    model="gpt-4o",
    messages=agent.messages, ## this is the conversation history and state of the agent
    tools=agent.get_tools(llm_provider=LLMProvider.OPENAI), ## this is the list of tools available to the agent
    tool_choice="auto", ## this is the tool choice for the agent
)

# Process and execute tools
xpander_agent.process_llm_response(
    response.model_dump(), 
    llm_provider=LLMProvider.OPENAI
)

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Next Steps