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Baseten is an infrastructure platform for deploying and serving AI models. It provides OpenAI-compatible endpoints for popular open-source models (DeepSeek, Qwen, Nemotron, and more) with autoscaling and optimized inference.
Vision Agents requires a Stream account for real-time transport. Most providers offer free tiers to get started.

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Installation

Baseten uses an OpenAI-compatible API, so it works with the OpenAI plugin: 
uv add "vision-agents[openai]"

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Quick Start

import os
from vision_agents.core import Agent, User
from vision_agents.plugins import openai, deepgram, getstream

agent = Agent(
    edge=getstream.Edge(),
    agent_user=User(name="Assistant", id="agent"),
    instructions="You are a helpful assistant.",
    llm=openai.ChatCompletionsLLM(
        model="deepseek-ai/DeepSeek-V3.1",
        base_url="https://inference.baseten.co/v1",
        api_key=os.environ["BASETEN_API_KEY"],
    ),
    stt=deepgram.STT(),
    tts=deepgram.TTS(),
)
Set BASETEN_API_KEY in your environment. Create an API key at app.baseten.co/settings/api_keys.

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Using Self-Deployed Models

If you’ve deployed your own model on Baseten, use the model-specific endpoint: 
llm = openai.ChatCompletionsLLM(
    model="your-model-name",
    base_url="https://model-{MODEL_ID}.api.baseten.co/environments/production/sync/v1",
    api_key=os.environ["BASETEN_API_KEY"],
)

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Parameters

Since Baseten uses ChatCompletionsLLM, it accepts the same parameters:
NameTypeDefaultDescription
modelstr—Model slug (e.g., "deepseek-ai/DeepSeek-V3.1")
base_urlstr—"https://inference.baseten.co/v1" for Model APIs
api_keystrNoneAPI key (defaults to BASETEN_API_KEY env var)

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Available Models

Baseten’s Model APIs provide pre-deployed endpoints for popular open-source models. No deployment setup required — just call the API. See the Baseten documentation for the full list of available models.

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Next Steps

Build a Voice Agent

Get started with voice

Build a Video Agent

Add video processing