Configuration

This guide covers how to configure CAIS for different LLM providers, customize analysis parameters, and optimize performance for your specific use case. Proper configuration ensures reliable and efficient causal analysis workflows.

LLM Provider Configuration

CAIS supports multiple Large Language Model providers, each with different capabilities and pricing models. Choose the provider that best fits your needs in terms of performance, cost, and availability.

Supported Providers

OpenAI, Anthropic, Google Gemini, Together AI

OpenAI Configuration

Set up OpenAI as your LLM provider:

# Environment variables
export LLM_PROVIDER="openai"
export LLM_MODEL="gpt-4o-mini"  # or gpt-4o, gpt-4, gpt-3.5-turbo
export OPENAI_API_KEY="your-openai-api-key"

# Python configuration
import os
os.environ["LLM_PROVIDER"] = "openai"
os.environ["LLM_MODEL"] = "gpt-4o-mini"
os.environ["OPENAI_API_KEY"] = "your-openai-api-key"

from causal_agent import run_causal_analysis

result = run_causal_analysis(
    query="What is the effect of treatment on outcome?",
    dataset_path="data.csv"
)

# CLI usage
causal_agent run data.csv "What is the effect of treatment on outcome?" \
    --llm-provider openai \
    --llm-name gpt-4o-mini

Anthropic Configuration

Configure Anthropic Claude models:

# Environment variables
export LLM_PROVIDER="anthropic"
export LLM_MODEL="claude-3-5-sonnet-latest"  # or claude-3-haiku-latest, claude-3-opus-latest
export ANTHROPIC_API_KEY="your-anthropic-api-key"

# Python configuration
import os
os.environ["LLM_PROVIDER"] = "anthropic"
os.environ["LLM_MODEL"] = "claude-3-5-sonnet-latest"
os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-api-key"

Together AI Configuration

Set up Together AI:

# Environment variables
export LLM_PROVIDER="together"
export LLM_MODEL="deepseek-ai/DeepSeek-V3"  # or other available models
export TOGETHER_API_KEY="your-together-api-key"

Environment Configuration

Using .env Files

Create a .env file in your project directory for persistent configuration:

# .env file
LLM_PROVIDER=anthropic
LLM_MODEL=claude-3-5-sonnet-latest
ANTHROPIC_API_KEY=your-api-key-here

# No need to set environment variables manually
from causal_agent import run_causal_analysis

result = run_causal_analysis(
    query="What is the effect of treatment on outcome?",
    dataset_path="data.csv"
)

Next Steps