""" RAG smoke tests for AI Service. [AC-AISVC-17, AC-AISVC-18] Tests for retrieval-augmented generation scenarios. """ import json import pytest from unittest.mock import AsyncMock, MagicMock, patch from fastapi.testclient import TestClient from app.main import app from app.models import ChatRequest, ChannelType from app.services.orchestrator import OrchestratorService from app.services.retrieval.base import RetrievalContext, RetrievalHit, RetrievalResult class TestRAGSmokeScenarios: """ [AC-AISVC-17, AC-AISVC-18] Smoke tests for RAG scenarios. """ @pytest.fixture def client(self): return TestClient(app) @pytest.fixture def valid_headers(self): return {"X-Tenant-Id": "tenant_rag_test"} @pytest.fixture def valid_body(self): return { "sessionId": "rag_session", "currentMessage": "What is the product price?", "channelType": "wechat", } def test_rag_retrieval_hit_scenario(self, client, valid_headers, valid_body): """ [AC-AISVC-17] Test RAG scenario when retrieval has good hits. Expected behavior: - High confidence score - shouldTransfer = False - Response includes relevant information """ response = client.post( "/ai/chat", json=valid_body, headers=valid_headers, ) assert response.status_code == 200 data = response.json() assert "reply" in data assert "confidence" in data assert "shouldTransfer" in data assert isinstance(data["confidence"], (int, float)) assert 0 <= data["confidence"] <= 1 def test_rag_retrieval_miss_scenario(self, client, valid_headers): """ [AC-AISVC-17, AC-AISVC-18] Test RAG scenario when retrieval has no hits. Expected behavior: - Lower confidence score - may suggest transfer to human agent - Graceful fallback response """ body = { "sessionId": "rag_session_miss", "currentMessage": "Xyzzy plugh unknown query", "channelType": "wechat", } response = client.post( "/ai/chat", json=body, headers=valid_headers, ) assert response.status_code == 200 data = response.json() assert "reply" in data assert "confidence" in data assert "shouldTransfer" in data def test_rag_sse_with_retrieval(self, client, valid_headers, valid_body): """ [AC-AISVC-17] Test RAG with SSE streaming. """ headers = {**valid_headers, "Accept": "text/event-stream"} response = client.post( "/ai/chat", json=valid_body, headers=headers, ) assert response.status_code == 200 content = response.text assert "event:final" in content or "event: final" in content lines = content.split("\n") for line in lines: if line.startswith("data:") and "confidence" in line: data_str = line[5:].strip() try: data = json.loads(data_str) assert "confidence" in data assert 0 <= data["confidence"] <= 1 except json.JSONDecodeError: pass class TestRAGConfidenceScoring: """ [AC-AISVC-17, AC-AISVC-18] Tests for confidence scoring based on retrieval quality. """ @pytest.mark.asyncio async def test_high_confidence_with_good_retrieval(self): """ [AC-AISVC-17] High retrieval score should result in high confidence. Note: Without LLM client, fallback mode is used with lower confidence. """ orchestrator = OrchestratorService() request = ChatRequest( session_id="test", current_message="What is the price?", channel_type=ChannelType.WECHAT, ) response = await orchestrator.generate("tenant", request) assert response.confidence >= 0 assert response.confidence <= 1 @pytest.mark.asyncio async def test_low_confidence_with_poor_retrieval(self): """ [AC-AISVC-17, AC-AISVC-18] Poor retrieval should result in lower confidence. """ orchestrator = OrchestratorService() request = ChatRequest( session_id="test", current_message="Unknown topic xyzzy", channel_type=ChannelType.WECHAT, ) response = await orchestrator.generate("tenant", request) assert response.confidence >= 0 assert response.confidence <= 1 @pytest.mark.asyncio async def test_transfer_suggestion_on_very_low_confidence(self): """ [AC-AISVC-18] Very low confidence should suggest transfer to human. """ orchestrator = OrchestratorService() request = ChatRequest( session_id="test", current_message="Complex query requiring human expertise", channel_type=ChannelType.WECHAT, ) response = await orchestrator.generate("tenant", request) assert response.should_transfer is not None class TestRAGRetrievalDiagnostics: """ [AC-AISVC-17] Tests for retrieval diagnostics. """ @pytest.mark.asyncio async def test_retrieval_result_statistics(self): """ [AC-AISVC-17] Retrieval result should provide useful diagnostics. """ result = RetrievalResult( hits=[ RetrievalHit(text="Doc 1", score=0.9, source="kb"), RetrievalHit(text="Doc 2", score=0.7, source="kb"), ] ) assert result.hit_count == 2 assert result.max_score == 0.9 assert result.is_empty is False @pytest.mark.asyncio async def test_empty_retrieval_result(self): """ [AC-AISVC-17] Empty retrieval result should be detectable. """ result = RetrievalResult(hits=[]) assert result.is_empty is True assert result.hit_count == 0 assert result.max_score == 0.0 class TestRAGFallbackBehavior: """ [AC-AISVC-18] Tests for fallback behavior when retrieval fails. """ @pytest.fixture def client(self): return TestClient(app) def test_graceful_fallback_on_retrieval_error(self, client): """ [AC-AISVC-18] Should gracefully handle retrieval errors. """ response = client.post( "/ai/chat", json={ "sessionId": "fallback_session", "currentMessage": "Test fallback", "channelType": "wechat", }, headers={"X-Tenant-Id": "tenant_fallback"}, ) assert response.status_code == 200 data = response.json() assert "reply" in data def test_fallback_response_quality(self, client): """ [AC-AISVC-18] Fallback response should still be helpful. """ response = client.post( "/ai/chat", json={ "sessionId": "fallback_quality", "currentMessage": "I need help with my order", "channelType": "wechat", }, headers={"X-Tenant-Id": "tenant_fallback_quality"}, ) assert response.status_code == 200 data = response.json() assert len(data["reply"]) > 0 assert data["confidence"] >= 0 class TestRAGWithHistory: """ Tests for RAG with conversation history. """ @pytest.fixture def client(self): return TestClient(app) def test_rag_with_conversation_history(self, client): """ [AC-AISVC-14] RAG should consider conversation history. """ response = client.post( "/ai/chat", json={ "sessionId": "history_session", "currentMessage": "How much does it cost?", "channelType": "wechat", "history": [ {"role": "user", "content": "I'm interested in your product"}, {"role": "assistant", "content": "Great! Our product has many features."}, ], }, headers={"X-Tenant-Id": "tenant_history"}, ) assert response.status_code == 200 data = response.json() assert "reply" in data def test_rag_with_long_history(self, client): """ [AC-AISVC-14, AC-AISVC-15] RAG should handle long conversation history. """ long_history = [ {"role": "user" if i % 2 == 0 else "assistant", "content": f"Message {i}"} for i in range(20) ] response = client.post( "/ai/chat", json={ "sessionId": "long_history_session", "currentMessage": "Summary please", "channelType": "wechat", "history": long_history, }, headers={"X-Tenant-Id": "tenant_long_history"}, ) assert response.status_code == 200 data = response.json() assert "reply" in data