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7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 1521cd2 7ab7df1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 | """Tests for input validation and edge cases."""
from unittest.mock import MagicMock, Mock, patch
import pytest
from qa_chain import QAChainWrapper
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.documents import Document
from ui.handlers import create_stream_chat_response, create_respond_handler
@pytest.fixture
def qa_chain_wrapper(mock_vectorstore):
"""Create a QAChainWrapper instance."""
prompt = ChatPromptTemplate.from_template("Test: {question}")
return QAChainWrapper(mock_vectorstore, prompt)
@patch("qa_chain.create_llm")
@patch("qa_chain.format_chat_history")
def test_very_long_query(mock_format_history, mock_create_llm, qa_chain_wrapper):
"""Test handling of extremely long queries (>10k characters)."""
very_long_query = "What is " + "RAG? " * 2000 # ~10k+ characters
mock_format_history.return_value = ""
mock_llm = MagicMock()
mock_chunk = MagicMock()
mock_chunk.content = "Response"
mock_llm.stream.return_value = [mock_chunk]
mock_create_llm.return_value = mock_llm
mock_retriever = MagicMock()
mock_retriever.invoke.return_value = [Document(page_content="Test", metadata={})]
qa_chain_wrapper._retriever = mock_retriever
mock_chain = MagicMock()
mock_chain.stream.return_value = [mock_chunk]
qa_chain_wrapper._prompt.__or__ = MagicMock(return_value=mock_chain)
inputs = {
"question": very_long_query,
"chat_history": [],
}
# Should handle long query without crashing
results = list(qa_chain_wrapper.stream(inputs))
assert len(results) > 0
def test_empty_whitespace_query():
"""Test handling of whitespace-only queries."""
from ui.handlers import create_respond_handler
stream_fn = MagicMock()
respond_fn = create_respond_handler(stream_fn)
# Empty string
results = list(respond_fn("", [], False, "mmr", "All Documents", False, False, 70))
assert results[0][0] == "" # Should return empty immediately
# Whitespace only - now also returns empty (treated as empty after strip)
results = list(respond_fn(" ", [], False, "mmr", "All Documents", False, False, 70))
assert results[0][0] == "" # Should return empty immediately
# Newlines only - also returns empty
results = list(respond_fn("\n\n\n", [], False, "mmr", "All Documents", False, False, 70))
assert results[0][0] == "" # Should return empty immediately
@patch("qa_chain.create_llm")
@patch("qa_chain.format_chat_history")
def test_special_characters_in_query(mock_format_history, mock_create_llm, qa_chain_wrapper):
"""Test handling of special characters in queries."""
special_chars_query = "What is RAG? @#$%^&*()[]{}|\\/<>?~`"
mock_format_history.return_value = ""
mock_llm = MagicMock()
mock_chunk = MagicMock()
mock_chunk.content = "Response"
mock_llm.stream.return_value = [mock_chunk]
mock_create_llm.return_value = mock_llm
mock_retriever = MagicMock()
mock_retriever.invoke.return_value = [Document(page_content="Test", metadata={})]
qa_chain_wrapper._retriever = mock_retriever
mock_chain = MagicMock()
mock_chain.stream.return_value = [mock_chunk]
qa_chain_wrapper._prompt.__or__ = MagicMock(return_value=mock_chain)
inputs = {
"question": special_chars_query,
"chat_history": [],
}
# Should handle special characters without crashing
results = list(qa_chain_wrapper.stream(inputs))
assert len(results) > 0
@patch("qa_chain.create_llm")
@patch("qa_chain.format_chat_history")
def test_unicode_emoji_in_query(mock_format_history, mock_create_llm, qa_chain_wrapper):
"""Test handling of Unicode and emoji in queries."""
unicode_query = "What is RAG? π δ½ ε₯½ Ω
Ψ±ΨΨ¨Ψ§"
mock_format_history.return_value = ""
mock_llm = MagicMock()
mock_chunk = MagicMock()
mock_chunk.content = "Response"
mock_llm.stream.return_value = [mock_chunk]
mock_create_llm.return_value = mock_llm
mock_retriever = MagicMock()
mock_retriever.invoke.return_value = [Document(page_content="Test", metadata={})]
qa_chain_wrapper._retriever = mock_retriever
mock_chain = MagicMock()
mock_chain.stream.return_value = [mock_chunk]
qa_chain_wrapper._prompt.__or__ = MagicMock(return_value=mock_chain)
inputs = {
"question": unicode_query,
"chat_history": [],
}
# Should handle Unicode/emoji without crashing
results = list(qa_chain_wrapper.stream(inputs))
assert len(results) > 0
def test_invalid_document_filter():
"""Test handling of invalid document filter selection."""
from ui.handlers import create_stream_chat_response
mock_qa_chain = MagicMock()
mock_qa_chain.stream.return_value = [
{
"chunk": "Response",
"source_documents": [],
"docs_with_scores": None,
"rewritten_query": None,
"hybrid_scores": None,
}
]
# Pass valid sources - nonexistent.pdf is NOT in the list
stream_fn = create_stream_chat_response(mock_qa_chain, available_sources=["valid.pdf"])
# Invalid filter (document that doesn't exist in available_sources)
results = list(
stream_fn(
"test question",
[],
"RAG",
doc_filter="nonexistent.pdf", # Invalid filter - not in available_sources
search_type="mmr",
)
)
# Should handle invalid filter gracefully
assert len(results) > 0
# Invalid filter should be ignored (no filter passed to chain)
call_args = mock_qa_chain.stream.call_args[0][0]
assert "filter" not in call_args # Filter is NOT passed for invalid sources
def test_malformed_chat_history():
"""Test handling of malformed chat history."""
from ui.handlers import messages_to_tuples
# Missing role - should handle gracefully
try:
malformed_history1 = [
{"content": "Message without role"},
]
tuples1 = messages_to_tuples(malformed_history1)
assert isinstance(tuples1, list)
# Should return empty (no valid user/assistant pairs)
assert tuples1 == []
except (KeyError, TypeError):
# Exception is acceptable for malformed input
pass
# Missing content - should handle gracefully
try:
malformed_history2 = [
{"role": "user"},
]
tuples2 = messages_to_tuples(malformed_history2)
assert isinstance(tuples2, list)
except (KeyError, TypeError):
# Exception is acceptable for malformed input
pass
# Invalid role - should handle gracefully
malformed_history3 = [
{"role": "invalid", "content": "Message"},
]
tuples3 = messages_to_tuples(malformed_history3)
# Should return empty (only processes user/assistant pairs)
assert isinstance(tuples3, list)
assert tuples3 == []
@patch("qa_chain.create_llm")
def test_query_rewriting_with_very_short_query(mock_create_llm, qa_chain_wrapper):
"""Test query rewriting with very short query."""
very_short_query = "RAG?"
mock_llm = MagicMock()
mock_response = MagicMock()
# Make rewritten query shorter than 30% of original
# "RAG?" is 4 chars, 30% = 1.2, so "R" (1 char) should trigger fallback
mock_response.content = "R"
mock_llm.invoke.return_value = mock_response
mock_create_llm.return_value = mock_llm
result = qa_chain_wrapper.rewrite_query(very_short_query)
# Should return original if rewritten is too short (< 30% of original length)
assert result == very_short_query
@patch("qa_chain.create_llm")
@patch("qa_chain.format_chat_history")
def test_hybrid_search_with_extreme_alpha(mock_format_history, mock_create_llm, qa_chain_wrapper):
"""Test hybrid search with extreme alpha values."""
from langchain_core.documents import Document
mock_format_history.return_value = ""
mock_llm = MagicMock()
mock_chunk = MagicMock()
mock_chunk.content = "Response"
mock_llm.stream.return_value = [mock_chunk]
mock_create_llm.return_value = mock_llm
mock_retriever = MagicMock()
mock_retriever.invoke.return_value = [Document(page_content="Test", metadata={})]
qa_chain_wrapper._retriever = mock_retriever
mock_chain = MagicMock()
mock_chain.stream.return_value = [mock_chunk]
qa_chain_wrapper._prompt.__or__ = MagicMock(return_value=mock_chain)
# Test with alpha = 0.0 (pure keyword)
inputs = {
"question": "test",
"chat_history": [],
"search_type": "hybrid",
"hybrid_alpha": 0.0,
}
results = list(qa_chain_wrapper.stream(inputs))
assert len(results) > 0
# Test with alpha = 1.0 (pure semantic)
inputs["hybrid_alpha"] = 1.0
results = list(qa_chain_wrapper.stream(inputs))
assert len(results) > 0
def test_rerank_with_very_few_documents(qa_chain_wrapper, sample_documents):
"""Test re-ranking with very few documents."""
# Re-rank with only 1 document
result = qa_chain_wrapper.rerank_documents("query", sample_documents[:1], top_k=5)
# Should return the single document
assert len(result) == 1
# Re-rank with more documents than top_k
result = qa_chain_wrapper.rerank_documents("query", sample_documents[:10], top_k=3)
# Should return only top_k documents
assert len(result) == 3
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