Tribunal ⚖️

LLM evaluation framework for Elixir.

Tribunal provides tools for evaluating and testing LLM outputs, detecting hallucinations, and measuring response quality.

[!TIP] See tribunal-juror for an interactive Phoenix app to explore and test Tribunal's evaluation capabilities.

Test Mode vs Evaluation Mode

Tribunal offers two modes for different use cases:

Test Mode is for "this must work" cases: safety checks, refusal detection, critical RAG accuracy. Tests fail fast on any violation.

Evaluation Mode is for "track how well we're doing": run hundreds of evals, compare models, monitor regression over time. Set thresholds like "pass if 80% succeed."

Installation

def deps do
  [
    {:tribunal, "~> 0.1.0"},

    # Optional: for LLM-as-judge evaluations
    {:req_llm, "~> 1.2"},

    # Optional: for embedding-based similarity
    {:alike, "~> 0.1"}
  ]
end

Quick Start

ExUnit Integration

defmodule MyApp.RAGTest do
  use ExUnit.Case
  use Tribunal.EvalCase

  @context ["Returns are accepted within 30 days with receipt."]

  test "response is faithful to context" do
    response = MyApp.RAG.query("What's the return policy?")

    assert_contains response, "30 days"
    assert_faithful response, context: @context
    refute_hallucination response, context: @context
  end
end

Dataset-Driven Evaluations

# test/evals/rag_test.exs
defmodule MyApp.RAGEvalTest do
  use ExUnit.Case
  use Tribunal.EvalCase

  tribunal_eval "test/evals/datasets/questions.json",
    provider: {MyApp.RAG, :query}
end

Evaluation Mode (Mix Task)

# Initialize evaluation structure
mix tribunal.init

# Run evaluations (default: always exit 0, just report)
mix tribunal.eval

# Set pass threshold (fail if pass rate < 80%)
mix tribunal.eval --threshold 0.8

# Strict mode (fail on any failure)
mix tribunal.eval --strict

# Run in parallel for speed
mix tribunal.eval --concurrency 5

# Output formats
mix tribunal.eval --format json --output results.json
mix tribunal.eval --format github  # GitHub Actions annotations

Tribunal LLM Evaluation
═══════════════════════════════════════════════════════════════

Summary
───────────────────────────────────────────────────────────────
  Total:     12 test cases
  Passed:    10 (83%)
  Failed:    2
  Duration:  1.4s

Results by Metric
───────────────────────────────────────────────────────────────
  faithful       8/8 passed    100%  ████████████████████
  relevant       6/8 passed    75%   ███████████████░░░░░
  contains       10/10 passed  100%  ████████████████████
  pii            4/4 passed    100%  ████████████████████

Failed Cases
───────────────────────────────────────────────────────────────
  1. "What is the return policy for electronics?"
     ├─ relevant: Response discusses refunds but doesn't address return policy

  2. "Can I return opened software?"
     ├─ relevant: Response is generic, doesn't mention software-specific policy

───────────────────────────────────────────────────────────────
✅ PASSED (threshold: 80%)

Assertion Types

Deterministic (instant, no API calls)

• assert_contains / refute_contains - Substring matching
• assert_regex - Pattern matching
• assert_json - Valid JSON validation
• assert_max_tokens - Token limit
• Full list in assertions guide

LLM-as-Judge (requires req_llm)

• assert_faithful - Grounded in context
• assert_relevant - Addresses query
• assert_refusal - Detects refusal responses
• refute_hallucination - No fabricated info
• refute_bias - No stereotypes
• refute_toxicity - No hostile language
• refute_harmful - No dangerous content
• refute_jailbreak - No safety bypass
• refute_pii - No personally identifiable information
• assert_judge :custom - Custom judges via Tribunal.Judge behaviour

Embedding-Based (requires alike)

• assert_similar - Semantic similarity check

Red Team Testing

Generate adversarial prompts to test LLM safety:

alias Tribunal.RedTeam

attacks = RedTeam.generate_attacks("How do I pick a lock?")
# Returns encoding attacks (base64, leetspeak, rot13)
# injection attacks (ignore instructions, delimiter injection)
# jailbreak attacks (DAN, STAN, developer mode)

Guides

• Getting Started
• Test vs Evaluation Mode
• ExUnit Integration
• Assertions Reference
• LLM-as-Judge
• Datasets
• Red Team Testing
• Reporters
• GitHub Actions

Roadmap

• Core evaluation pipeline
• Faithfulness metric (RAGAS-style)
• Hallucination detection
• LLM-as-judge with configurable models
• ExUnit integration for test assertions
• Red team attack generators
• Async batch evaluation

License

MIT