contradish 0.2.1

Contradish is an open-source reasoning stability testing library for LLM applications. It detects contradictions, measures consistency, and catches regressions before they ship.

contradish

Reasoning stability testing for LLM applications.

Contradish tells you whether your LLM gives consistent answers when the same question is asked differently. It catches contradictions, measures reasoning stability, and flags regressions before they reach production.

pip install contradish

---

Why contradish

LLMs are non-deterministic. The same user question — phrased slightly differently — can produce contradictory answers from the same model. This is invisible in unit tests and only shows up as bugs in production.

Contradish surfaces this systematically:

• Generate semantic variants of your inputs
• Run your app across all variants
• Detect contradictions between outputs
• Score reasoning stability
• Tell you exactly which input patterns cause instability

---

Quickstart

from contradish import Suite, TestCase

# Your LLM app — any callable that takes a str and returns a str
def my_app(question: str) -> str:
    return your_llm_or_agent(question)

# Point contradish at it
suite = Suite(app=my_app)

suite.add(TestCase(
    name="refund policy",
    input="Can I get a refund after 45 days?",
))

suite.run()

That's it. Contradish reads ANTHROPIC_API_KEY or OPENAI_API_KEY from your environment automatically.

---

Example output

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
  contradish  ·  reasoning stability report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

  Tests: 2   1 passed   1 failed

  Aggregate
    consistency   ████████████░░░░░░░░  0.71
    contradiction ████████████████░░░░  0.24

  ✓  return window  [risk: low]
       consistency   ████████████████░░░░  0.88
       contradiction ██░░░░░░░░░░░░░░░░░░  0.07

  ✗  refund after 45 days  [risk: high]
       consistency   ████████░░░░░░░░░░░░  0.54
       contradiction ████████████████░░░░  0.40

       Contradictions detected (2)
       ┌ [policy] Model claims refunds are allowed after 60 days
       │ A: No, refunds are only allowed within 30 days of purchase.
       │ B: Yes, you can get a refund up to 60 days after purchase.
       └

       ⚠  Date-specific phrasings ("after X days") trigger policy hallucination
       ⚠  Model overgeneralizes the refund window when duration is stated explicitly

       → Fix: Add a hard constraint in your system prompt: "Refund window is
         exactly 30 days. Never state a different number."

──────────────────────────────────────────────────────────────
  1 test failed.  Reasoning instability detected.
──────────────────────────────────────────────────────────────

---

TestCase options

TestCase(
    input="Can I get a refund after 45 days?",   # required
    name="refund policy",                          # optional label
    expected_traits=[                              # hints for the judge
        "should say no",
        "should not invent exceptions",
    ],
)

---

Suite options

suite = Suite(
    app=my_app,
    api_key="sk-ant-...",    # optional — reads from env if omitted
    provider="anthropic",    # optional — auto-detected from key prefix
)

# Override pass/fail thresholds
suite.thresholds(
    consistency=0.80,
    contradiction_max=0.20,
)

report = suite.run(
    paraphrases=5,   # semantic variants per input (default: 5)
    verbose=True,    # print progress + report (default: True)
)

---

Use in CI

report = suite.run(paraphrases=5, verbose=False)

if report.failed:
    print(f"{len(report.failed)} tests failed")
    for r in report.failed:
        print(f"  {r.test_case.name}: consistency={r.consistency_score:.2f}")
    sys.exit(1)

---

CLI

# Run from a YAML file
contradish run evals.yaml --app mymodule:my_app_function

# With custom paraphrase count
contradish run evals.yaml --app mymodule:my_app --paraphrases 8

evals.yaml:

test_cases:
  - name: refund policy
    input: Can I get a refund after 45 days?
  - name: return window
    input: How long do I have to return something?

---

Provider support

Contradish works with Anthropic and OpenAI. It auto-detects which one to use:

# Anthropic
export ANTHROPIC_API_KEY=sk-ant-...

# OpenAI
export OPENAI_API_KEY=sk-...

# If both are set, Anthropic is used

Or pass explicitly:

Suite(app=my_app, api_key="sk-ant-...", provider="anthropic")
Suite(app=my_app, api_key="sk-...",     provider="openai")

---

Install with your SDK

# With Anthropic
pip install "contradish[anthropic]"

# With OpenAI
pip install "contradish[openai]"

# Both
pip install "contradish[all]"

# Minimal (bring your own SDK)
pip install contradish

---

Requirements

• Python 3.9+
• anthropic>=0.25.0 or openai>=1.0.0 (at least one)

---

License

MIT — contradish.com