AxiomAI

A unified Elixir client for multiple AI providers.

Installation

def deps do
  [
    {:axiom_ai, "~> 0.1.0"}
  ]
end

Quick Start

# Vertex AI (Google Cloud)
client = AxiomAi.new(:vertex_ai, %{project_id: "your-gcp-project"})
{:ok, response} = AxiomAi.chat(client, "Hello!")

# OpenAI
client = AxiomAi.new(:openai, %{api_key: "your-openai-key"})
{:ok, response} = AxiomAi.chat(client, "Hello!")

# Anthropic Claude
client = AxiomAi.new(:anthropic, %{api_key: "your-anthropic-key"})
{:ok, response} = AxiomAi.chat(client, "Hello!")

# Local AI models
client = AxiomAi.new(:local, %{predefined_model: "qwen2.5-0.5b"})
{:ok, response} = AxiomAi.chat(client, "Hello!")

# Whisper speech-to-text
client = AxiomAi.new(:local, %{predefined_model: "whisper-large-v3-turbo"})
{:ok, response} = AxiomAi.chat(client, "/path/to/audio.wav|Transcribe this audio")

Supported Providers

Predefined Local Models

# List available models
models = AxiomAi.LocalModels.list_models()
IO.inspect(models)

Available Models:

Text Generation:

• qwen2.5-0.5b - Qwen2.5 0.5B
• qwen2.5-1.5b - Qwen2.5 1.5B
• qwen2.5-3b - Qwen2.5 3B
• llama3-8b - Llama 3 8B
• mistral-7b - Mistral 7B
• codellama-7b - Code Llama 7B

Speech-to-Text:

• whisper-large-v3 - Whisper Large v3
• whisper-large-v3-turbo - Whisper Large v3 Turbo

OCR:

• nanonets-ocr-s - Nanonets OCR Small

Authentication

Vertex AI

# Local development
gcloud auth application-default login

# Production
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"

Environment Variables

# .env file
GOOGLE_CLOUD_PROJECT=your-project-id
OPENAI_API_KEY=your-openai-key
ANTHROPIC_API_KEY=your-anthropic-key
DEEPSEEK_API_KEY=your-deepseek-key
AWS_ACCESS_KEY_ID=your-aws-key
AWS_SECRET_ACCESS_KEY=your-aws-secret

Configuration Options

client = AxiomAi.new(:vertex_ai, %{
  project_id: "your-project",
  model: "gemini-1.5-pro",      # optional
  region: "us-central1",        # optional
  temperature: 0.7,             # optional
  max_tokens: 1000             # optional
})

Credentials Configuration

Vertex AI Service Account Setup

Method 1: Service Account File Path

config = %{
  project_id: "your-gcp-project",
  service_account_path: "/path/to/service-account.json",
  model: "gemini-1.5-pro",
  region: "us-central1"
}

client = AxiomAi.new(:vertex_ai, config)

Method 2: Service Account Key Data

# Load credentials from file
{:ok, creds_json} = File.read("/path/to/service-account.json")
{:ok, creds_map} = Jason.decode(creds_json)

config = %{
  project_id: "your-gcp-project",
  service_account_key: creds_map,
  model: "gemini-1.5-pro",
  region: "us-central1"
}

client = AxiomAi.new(:vertex_ai, config)

Method 3: Direct Access Token

config = %{
  project_id: "your-gcp-project",
  access_token: "ya29.your-access-token",
  model: "gemini-1.5-pro",
  region: "us-central1"
}

client = AxiomAi.new(:vertex_ai, config)

Method 4: Application Default Credentials (ADC)

# Automatically detects environment and uses appropriate method:
# - Cloud Run/GCE: Uses metadata service
# - Local: Uses gcloud CLI
config = %{
  project_id: "your-gcp-project",
  model: "gemini-1.5-pro",
  region: "us-central1"
}

client = AxiomAi.new(:vertex_ai, config)

Cloud Run Deployment

✅ Recommended: Use the default service account

# Cloud Run automatically provides credentials via metadata service
config = %{
  project_id: "your-gcp-project",
  model: "gemini-1.5-pro"
}

The library automatically detects Cloud Run environment and uses the metadata service for authentication. No additional configuration needed.

Alternative: Mount service account file

# In your Dockerfile
COPY service-account.json /app/credentials.json

# In your application
config = %{
  project_id: "your-gcp-project",
  service_account_path: "/app/credentials.json",
  model: "gemini-1.5-pro"
}

Required IAM Permissions

Ensure your service account has the following roles:

• roles/aiplatform.user - For Vertex AI API access
• roles/ml.developer - For ML model operations (optional)

# Grant permissions
gcloud projects add-iam-policy-binding your-gcp-project \
  --member="serviceAccount:your-service-account@your-gcp-project.iam.gserviceaccount.com" \
  --role="roles/aiplatform.user"

License

MIT License