| """ |
| Unit tests for LawSLM Chat Engine: |
| - IntentDetector: classifies user prompts into correct intent categories |
| - KnowledgeEngine: generates natural, dynamic responses (no generic templates) |
| - ConversationMemory: tracks multi-turn history and resolves coreferences |
| - ResponseValidator: validates quality and rejects template artifacts |
| """ |
|
|
| import pytest |
| from slm.chat.intent import IntentDetector, KnowledgeEngine, IntentType |
| from slm.chat.memory import ConversationMemory |
| from slm.chat.validator import ResponseValidator |
|
|
|
|
| class TestIntentDetector: |
| def test_identity(self): |
| assert IntentDetector.detect_intent("Who created you?") == IntentType.IDENTITY |
| assert IntentDetector.detect_intent("who made you") == IntentType.IDENTITY |
|
|
| def test_about_self(self): |
| assert IntentDetector.detect_intent("Who are you?") == IntentType.ABOUT_SELF |
| assert IntentDetector.detect_intent("Tell me about yourself") == IntentType.ABOUT_SELF |
| assert IntentDetector.detect_intent("What can you do?") == IntentType.ABOUT_SELF |
|
|
| def test_greeting(self): |
| assert IntentDetector.detect_intent("Hello") == IntentType.GREETING |
| assert IntentDetector.detect_intent("hi") == IntentType.GREETING |
|
|
| def test_thanks(self): |
| assert IntentDetector.detect_intent("Thank you") == IntentType.THANKS |
| assert IntentDetector.detect_intent("thanks") == IntentType.THANKS |
|
|
| def test_farewell(self): |
| assert IntentDetector.detect_intent("goodbye") == IntentType.FAREWELL |
|
|
| def test_pdf_generation(self): |
| assert IntentDetector.detect_intent("Generate a PDF report") == IntentType.PDF_GENERATION |
|
|
| def test_legal(self): |
| assert IntentDetector.detect_intent("Explain Section 420 IPC") == IntentType.LEGAL |
|
|
| def test_programming(self): |
| assert IntentDetector.detect_intent("Write Python code for sorting") == IntentType.PROGRAMMING |
|
|
| def test_finance(self): |
| assert IntentDetector.detect_intent("Calculate loan interest for 10 lakh at 12%") == IntentType.FINANCE |
|
|
| def test_math(self): |
| assert IntentDetector.detect_intent("Calculate 25 * 4 + 10") == IntentType.MATH |
|
|
| def test_science(self): |
| assert IntentDetector.detect_intent("Explain photosynthesis") == IntentType.SCIENCE |
|
|
|
|
| class TestKnowledgeEngine: |
| def test_identity_response_mentions_amit(self): |
| result = KnowledgeEngine.generate_response("Who created you?", IntentType.IDENTITY) |
| assert "Amit Kumar" in result["content"] |
| assert result["has_pdf"] is False |
|
|
| def test_about_self_response(self): |
| result = KnowledgeEngine.generate_response("Who are you?", IntentType.ABOUT_SELF) |
| assert "LawSLM" in result["content"] |
|
|
| def test_greeting_response_is_natural(self): |
| result = KnowledgeEngine.generate_response("Hello", IntentType.GREETING) |
| assert "Hello" in result["content"] |
| |
| assert "Analysis & Assistance" not in result["content"] |
| assert "Core Concept" not in result["content"] |
|
|
| def test_thanks_response(self): |
| result = KnowledgeEngine.generate_response("Thank you", IntentType.THANKS) |
| assert "welcome" in result["content"].lower() |
|
|
| def test_pdf_has_metadata(self): |
| result = KnowledgeEngine.generate_response("Generate PDF report", IntentType.PDF_GENERATION) |
| assert result["has_pdf"] is True |
| assert result["pdf_meta"] is not None |
|
|
| def test_finance_with_numbers(self): |
| result = KnowledgeEngine.generate_response( |
| "Calculate loan interest for 100000 at 12% for 2 years", IntentType.FINANCE |
| ) |
| assert "₹" in result["content"] or "Interest" in result["content"] |
|
|
| def test_math_calculation(self): |
| result = KnowledgeEngine.generate_response("Calculate 25 * 4 + 10", IntentType.MATH) |
| content = result["content"] |
| assert "110" in content |
|
|
| def test_legal_section_420(self): |
| result = KnowledgeEngine.generate_response("Explain Section 420 IPC", IntentType.LEGAL) |
| assert "420" in result["content"] |
| assert "cheat" in result["content"].lower() or "Cheating" in result["content"] |
|
|
| def test_python_explanation(self): |
| result = KnowledgeEngine.generate_response("What is Python?", IntentType.GENERAL_QA) |
| assert "Python" in result["content"] |
|
|
| def test_no_generic_template_in_any_response(self): |
| """Verify no response uses banned template phrases.""" |
| test_prompts = [ |
| ("Hello", IntentType.GREETING), |
| ("Who are you?", IntentType.ABOUT_SELF), |
| ("Explain gravity", IntentType.SCIENCE), |
| ("Write Python code", IntentType.PROGRAMMING), |
| ] |
| banned = ["Analysis & Assistance", "Core Concept", "Key Consideration"] |
| for prompt, intent in test_prompts: |
| result = KnowledgeEngine.generate_response(prompt, intent) |
| for phrase in banned: |
| assert phrase not in result["content"], ( |
| f"Banned phrase '{phrase}' found in response to '{prompt}'" |
| ) |
|
|
|
|
| class TestConversationMemory: |
| def test_add_and_retrieve(self): |
| mem = ConversationMemory() |
| mem.add_message("user", "Hello") |
| mem.add_message("assistant", "Hi! How can I help?") |
| history = mem.get_history() |
| assert len(history) == 2 |
| assert history[0]["role"] == "user" |
| assert history[1]["role"] == "assistant" |
|
|
| def test_coreference_resolution(self): |
| mem = ConversationMemory() |
| mem.add_message("user", "What is Python?") |
| mem.add_message("assistant", "Python is a programming language.") |
| resolved = mem.resolve_coreference("Tell me more about this") |
| assert "python" in resolved.lower() or "this" in resolved.lower() |
|
|
|
|
| class TestResponseValidator: |
| def test_valid_text_passes(self): |
| is_valid, cleaned = ResponseValidator.validate_response("Hello! I am LawSLM.") |
| assert is_valid is True |
| assert "LawSLM" in cleaned |
|
|
| def test_empty_text_fails(self): |
| is_valid, _ = ResponseValidator.validate_response("") |
| assert is_valid is False |
|
|
| def test_unk_tokens_removed(self): |
| is_valid, cleaned = ResponseValidator.validate_response("Hello <unk> world <pad>") |
| assert is_valid is True |
| assert "<unk>" not in cleaned |
| assert "<pad>" not in cleaned |
|
|
| def test_repetitive_loop_cleaned(self): |
| is_valid, cleaned = ResponseValidator.validate_response("the the the the the answer") |
| assert is_valid is True |
| assert cleaned.count("the") < 4 |
|
|
| def test_template_phrases_stripped(self): |
| is_valid, cleaned = ResponseValidator.validate_response( |
| "Analysis & Assistance\n\nHello, I am LawSLM." |
| ) |
| assert is_valid is True |
| assert "Analysis & Assistance" not in cleaned |
|
|
| def test_unbalanced_code_fence_fixed(self): |
| is_valid, cleaned = ResponseValidator.validate_response("```python\nprint('hello')") |
| assert is_valid is True |
| assert cleaned.count("```") % 2 == 0 |
|
|
