# Example: Using Local Ollama
#
# This configuration demonstrates using Ondine with Ollama running locally.
# Ollama is a free, open-source LLM runner that supports many models.
#
# Setup:
# 1. Install Ollama: https://ollama.ai/
# 2. Pull a model: ollama pull llama3.1:70b
# 3. Run this config!
#
# Benefits:
# - 100% Free (no API costs)
# - Privacy (data never leaves your machine)
# - Fast inference (local GPU)
# - No API key needed

dataset:
  source_type: csv
  source_path: examples/sample_data.csv
  input_columns:
    - text
  output_columns:
    - sentiment

prompt:
  template: |
    Analyze the sentiment of the following text.
    Respond with only: positive, negative, or neutral.

    Text: {text}

    Sentiment:

llm:
  provider: openai_compatible
  provider_name: "Ollama-Local"
  model: llama3.1:70b  # or any model you've pulled
  base_url: http://localhost:11434/v1
  # No API key needed for local Ollama
  temperature: 0.0
  max_tokens: 10
  # Local models are free!
  input_cost_per_1k_tokens: 0.0
  output_cost_per_1k_tokens: 0.0

processing:
  batch_size: 10
  concurrency: 1  # Local models usually work best with concurrency=1
  error_policy: skip

output:
  destination_type: csv
  destination_path: examples/ollama_output.csv
