SambaNova

LLM service implementation using SambaNova’s API with OpenAI-compatible interface

Overview

SambaNovaLLMService provides access to SambaNova’s language models through an OpenAI-compatible interface. It inherits from OpenAILLMService and supports streaming responses, function calling, and context management with SambaNova’s high-performance inference platform.

SambaNova LLM API Reference

Pipecat’s API methods for SambaNova integration

Example Implementation

Complete example with function calling

SambaNova Documentation

Official SambaNova API documentation and features

SambaNova Cloud

Access models and manage API keys

Installation

To use SambaNova services, install the required dependencies:

pip install "pipecat-ai[sambanova]"

Prerequisites

SambaNova Account Setup

Before using SambaNova LLM services, you need:

1. SambaNova Account: Sign up at SambaNova Cloud
2. API Key: Generate an API key from your account dashboard
3. Model Selection: Choose from available high-performance models

Required Environment Variables

• SAMBANOVA_API_KEY: Your SambaNova API key for authentication

Configuration

api_key · str · required

SambaNova API key for authentication.

model · str · default: "None" · deprecated

Deprecated in v0.0.105. Use settings=SambaNovaLLMService.Settings(model=...) instead.

settings · SambaNovaLLMService.Settings · default: "None"

Runtime-configurable settings. See Settings below.

base_url · str · default: "https://api.sambanova.ai/v1"

Base URL for SambaNova API endpoint.

Settings

Runtime-configurable settings passed via the settings constructor argument using SambaNovaLLMService.Settings(...). These can be updated mid-conversation with LLMUpdateSettingsFrame. See Service Settings for details.

This service uses the same settings as OpenAILLMService. See OpenAI LLM Settings for the full parameter reference.

Usage

Basic Setup

import os
from pipecat.services.sambanova import SambaNovaLLMService

llm = SambaNovaLLMService(
    api_key=os.getenv("SAMBANOVA_API_KEY"),
    model="Llama-4-Maverick-17B-128E-Instruct",
)

With Custom Settings

from pipecat.services.sambanova import SambaNovaLLMService

llm = SambaNovaLLMService(
    api_key=os.getenv("SAMBANOVA_API_KEY"),
    settings=SambaNovaLLMService.Settings(
        model="Llama-4-Maverick-17B-128E-Instruct",
        temperature=0.7,
        top_p=0.9,
        max_tokens=1024,
    ),
)

Notes

• SambaNova does not support frequency_penalty, presence_penalty, or seed parameters.
• SambaNova has custom handling for tool call indexing. The service includes compatibility logic for processing function calls from the SambaNova API.
• SambaNova is known for high-throughput inference on large language models.

The InputParams / params= pattern is deprecated as of v0.0.105. Use Settings / settings= instead. See the Service Settings guide for migration details.