Merge with main

Author: nonprofittechy

formfyxer/integration_tests/interactive_test_passive_voice_detection.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python3
+"""Test script for passive voice detection module.
+
+This script tests the passive_voice_detection module to ensure it works correctly
+with the simplified OpenAI responses API approach.
+"""
+
+import sys
+from pathlib import Path
+
+# Add the formfyxer package to the path so we can import it
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+# Import the passive voice detection module directly
+from formfyxer.passive_voice_detection import detect_passive_voice_segments
+
+
+def test_basic_functionality():
+    """Test basic passive voice detection with simple examples."""
+    print("🔬 Testing basic functionality...")
+
+    # Test clearly passive sentences
+    test_cases = [
+        ("The ball was thrown by John.", True),
+        ("The president was impeached by Congress.", True),
+        ("Letters were sent to all customers.", True),
+        ("The door is being opened.", True),
+        ("The work has been completed.", True),
+        (
+            "The politics being discussed were causing a scene.",
+            True,
+        ),  # Tricky case from our tests
+    ]
+
+    for sentence, should_be_passive in test_cases:
+        try:
+            result = detect_passive_voice_segments(sentence)
+
+            if not result:
+                print(f"❌ No result returned for: {sentence}")
+                continue
+
+            sentence_result, fragments = result[0]
+            is_passive = len(fragments) > 0
+
+            status = "✅" if is_passive == should_be_passive else "❌"
+            voice_type = "passive" if is_passive else "active"
+            expected_type = "passive" if should_be_passive else "active"
+
+            print(f"{status} '{sentence}' → {voice_type} (expected {expected_type})")
+            if fragments:
+                print(f"   Fragments: {fragments}")
+
+        except Exception as e:
+            print(f"❌ Error processing '{sentence}': {e}")
+
+
+def test_active_voice():
+    """Test sentences that should be classified as active voice."""
+    print("\n🔬 Testing active voice detection...")
+
+    active_sentences = [
+        "John threw the ball.",
+        "The President gave a speech about COVID relief.",
+        "I don't usually participate in discussions about politics.",
+        "The world of politics is quite fascinating.",
+        "Sanders fights for the working class.",
+        "Politics is a topic for the commoners.",
+    ]
+
+    for sentence in active_sentences:
+        try:
+            result = detect_passive_voice_segments(sentence)
+
+            if not result:
+                print(f"❌ No result returned for: {sentence}")
+                continue
+
+            sentence_result, fragments = result[0]
+            is_passive = len(fragments) > 0
+
+            status = "✅" if not is_passive else "❌"
+            voice_type = "passive" if is_passive else "active"
+
+            print(f"{status} '{sentence}' → {voice_type} (expected active)")
+            if fragments:
+                print(f"   Unexpected fragments: {fragments}")
+
+        except Exception as e:
+            print(f"❌ Error processing '{sentence}': {e}")
+
+
+def test_multiple_sentences():
+    """Test processing multiple sentences at once."""
+    print("\n🔬 Testing multiple sentence processing...")
+
+    text = """
+    The ball was thrown by John. 
+    John threw the ball back. 
+    The game was enjoyed by everyone.
+    Everyone enjoyed the game.
+    """
+
+    try:
+        results = detect_passive_voice_segments(text)
+
+        print(f"Processed {len(results)} sentences:")
+        for sentence, fragments in results:
+            voice_type = "passive" if fragments else "active"
+            print(f"  • '{sentence.strip()}' → {voice_type}")
+            if fragments:
+                print(f"    Fragments: {fragments}")
+
+    except Exception as e:
+        print(f"❌ Error processing multiple sentences: {e}")
+
+
+def test_edge_cases():
+    """Test edge cases and error conditions."""
+    print("\n🔬 Testing edge cases...")
+
+    # Test empty input
+    try:
+        result = detect_passive_voice_segments("")
+        print("❌ Empty string should raise ValueError")
+    except ValueError:
+        print("✅ Empty string correctly raises ValueError")
+    except Exception as e:
+        print(f"❌ Unexpected error for empty string: {e}")
+
+    # Test very short sentences (should be filtered out)
+    try:
+        result = detect_passive_voice_segments("Hi. Yes.")
+        print("❌ Short sentences should raise ValueError")
+    except ValueError:
+        print("✅ Short sentences correctly raises ValueError")
+    except Exception as e:
+        print(f"❌ Unexpected error for short sentences: {e}")
+
+    # Test list input
+    try:
+        sentences = [
+            "The document was reviewed carefully.",
+            "We reviewed the document carefully.",
+        ]
+        results = detect_passive_voice_segments(sentences)
+
+        print(f"✅ List input processed {len(results)} sentences:")
+        for sentence, fragments in results:
+            voice_type = "passive" if fragments else "active"
+            print(f"  • '{sentence}' → {voice_type}")
+
+    except Exception as e:
+        print(f"❌ Error processing list input: {e}")
+
+
+def test_api_availability():
+    """Test if the OpenAI API is properly configured."""
+    print("\n🔬 Testing API availability...")
+
+    try:
+        # Try a simple test
+        result = detect_passive_voice_segments("This is a simple test sentence.")
+
+        if result:
+            sentence, fragments = result[0]
+            voice_type = "passive" if fragments else "active"
+            print(
+                f"✅ API connection successful! Test sentence classified as: {voice_type}"
+            )
+        else:
+            print("❌ API returned empty result")
+
+    except Exception as e:
+        print(f"❌ API connection failed: {e}")
+        print("💡 Make sure OPENAI_API_KEY is set in your environment or .env file")
+
+
+def main():
+    """Run all tests."""
+    print("🧪 Testing FormFyxer Passive Voice Detection Module")
+    print("=" * 55)
+
+    test_api_availability()
+    test_basic_functionality()
+    test_active_voice()
+    test_multiple_sentences()
+    test_edge_cases()
+
+    print("\n" + "=" * 55)
+    print("🏁 Test suite completed!")
+    print("\n💡 Tips:")
+    print("   - If API tests fail, check your OPENAI_API_KEY environment variable")
+    print("   - Compare results with the promptfoo evaluation for consistency")
+    print("   - Check that the model (gpt-5-nano) is accessible with your API key")
+
+
+if __name__ == "__main__":
+    main()