Configure AI Providers

Configure API Access

To run pipelines with LLMs, you need to configure API access. You have three options - choose what works best for you:

Option 1: Pipelex Inference (Easiest for Getting Started)

Get free credits for testing and development with a single API key that works with all major LLM providers:

Benefits:

No credit card required
Access to OpenAI, Anthropic, Google, Mistral, and more
Perfect for development and testing
Single API key for all models

Setup:

Join our Discord community to get your free API key:

Visit https://go.pipelex.com/discord
Request your key in the appropriate channel

Create a .env file in your project root:

PIPELEX_INFERENCE_API_KEY=your-key-here

That's it! Your pipelines can now access any supported LLM.

Option 2: Bring Your Own API Keys

Use your existing API keys from LLM providers. This is ideal if you:

Already have API keys from providers
Need to use specific accounts for billing
Have negotiated rates or enterprise agreements

Setup:

Create a .env file in your project root with your provider keys:

# OpenAI
OPENAI_API_KEY=sk-...

# Anthropic
ANTHROPIC_API_KEY=sk-ant-...

# Google
GOOGLE_API_KEY=...

# Mistral
MISTRAL_API_KEY=...

# FAL (for image generation)
FAL_API_KEY=...

# XAI
XAI_API_KEY=...

# Azure OpenAI
AZURE_API_KEY=...
AZURE_API_BASE=...
AZURE_API_VERSION=...

# Amazon Bedrock
AWS_ACCESS_KEY_ID=...
AWS_SECRET_ACCESS_KEY=...
AWS_REGION=...

You only need to add keys for the providers you plan to use.

Enable Your Providers:

When using your own keys, enable the corresponding backends:

Initialize configuration:
```
pipelex init config
```
Edit .pipelex/inference/backends.toml:

[google]
enabled = true

[openai]
enabled = true

# Enable any providers you have keys for

See Inference Backend Configuration for all options.

Option 3: Local AI (No API Keys Required)

Run AI models locally without any API keys. This is perfect if you:

Want complete privacy and control
Have capable hardware (GPU recommended)
Need offline capabilities
Want to avoid API costs

Supported Local Options:

Ollama (Recommended):

Install Ollama
Pull a model: ollama pull llama2
No API key needed! Configure Ollama backend in .pipelex/inference/backends.toml

Other Local Providers:

vLLM: High-performance inference server
LM Studio: User-friendly local model interface
llama.cpp: Lightweight C++ inference

Configure these in .pipelex/inference/backends.toml. See our Inference Backend Configuration for details.

Backend Configuration Files

To set up Pipelex configuration files, run:

pipelex init config

This creates a .pipelex/ directory with:

.pipelex/
├── pipelex.toml              # Feature flags, logging, cost reporting
└── inference/                # LLM configuration and model presets
    ├── backends.toml         # Enable/disable model providers
    ├── deck/
    │   └── base_deck.toml    # LLM presets and aliases
    └── routing_profiles.toml # Model routing configuration

Learn more in our Inference Backend Configuration guide.

Next Steps

Now that you have your backend configured:

Organize your project: Project Organization
Learn the concepts: Writing Workflows Tutorial
Explore examples: Cookbook Repository
Deep dive: Build Reliable AI Workflows

Advanced Configuration

For detailed backend configuration options, see Inference Backend Configuration.