Dify

About Dify

Dify is a comprehensive, open-source LLMOps platform that combines Backend-as-a-Service (BaaS) with low-code orchestration for building production-ready generative AI applications. Think of Dify as a well-designed scaffolding system that provides intuitive visual prompt orchestration, a high-quality RAG engine, and a flexible AI Agent framework, letting you focus on creating innovative solutions instead of reinventing the wheel.

The Power of Featherless + Dify

This integration creates a powerful synergy that transforms how you build AI applications. Dify's user-friendly visual environment encourages experimentation with different models and complex agentic patterns, while Featherless's massive model catalog makes Dify's advanced features exponentially more powerful.

Accelerated Prototyping

Finding the right model for a specific task typically takes days of setup and testing. With our integration, this process shrinks to minutes. Test a dozen different models simply by changing the name in a Dify LLM node and re-running the workflow.

Future-Proofing Your Applications

The open-source AI landscape evolves at breakneck speed. Because Featherless constantly expands its catalog, applications built with our Dify plugin are effectively future-proofed. When a new state-of-the-art model releases, it becomes available through our API, allowing you to upgrade applications with zero code changes.

Multi-Specialist AI Agents

Build sophisticated agents that don't rely on a single jack-of-all-trades model but instead intelligently delegate sub-tasks to highly specialized models. Create an agent that autonomously calls upon a creative writing model to draft content, a coding model to generate supporting scripts, and a powerful reasoning model to synthesize results into final reports.

Getting Started

Step 1: Get Your Featherless API Key

Sign up for a Featherless.ai account, choose a subscription plan, and grab your API key from the dashboard.

Step 2: Install the Plugin

Navigate to the "Plugins" section in your Dify workspace. Search the marketplace for "FeatherlessAI" and click "Install". This adds our entire model catalog as a native provider.

Step 3: Configure the Provider

Go to Settings → Model Providers. You'll now see FeatherlessAI listed as an available provider. Simply add your API key to activate it.

Step 4: Start Building

When adding an LLM node to any Dify workflow, select "FeatherlessAI" as your provider and enter the Hugging Face model name from our catalog (e.g., meta-llama/Meta-Llama-3.1-8B-Instruct) into the model field.

Configuration Guide

Setting Up Your First Model

Model Type: Set to "LLM" (typically pre-selected)

Model Name: Enter the exact model name as it appears in our catalog. You can browse available models at featherless.ai/models. Popular examples include:

• deepseek-ai/DeepSeek-V3-0324 for advanced reasoning

• mistralai/Mistral-Nemo-Instruct-2407 for balanced performance

• meta-llama/Meta-Llama-3.1-8B-Instruct for general-purpose tasks

• Qwen/Qwen3-32B for multilingual capabilities

• Qwen/QwQ-32B for complex problem-solving

API Key: Enter your Featherless API key from the dashboard

Completion Mode: Set to "Chat" for conversational AI applications

Context Size: Configure based on your chosen model's specifications. Common values include 16384, 32768, or higher. Check the model page for accurate context limits.

Token Limit: Set the upper bound for max tokens, typically matching or less than the context size (e.g., 4096 for models with 4K+ context).

Important Notes

Ensure you have an active subscription on your Featherless account before using the plugin. Model names must match exactly what's available in our catalog, and context sizes vary between models, so always verify the specifications on the model page.

Advanced Features

Dynamic Model Selection

Build workflows that automatically select the best model for each task based on content type, language, or complexity requirements.

Model Cascading

Create fallback systems where simpler, faster models handle routine tasks while complex queries automatically route to more powerful models.

A/B Testing Models

Easily compare model performance by running identical workflows with different models and analyzing the results.

Support and Community