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1441fa0 | 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 | """Tests for conversation memory."""
from src.agent.memory import ConversationMemory, Turn
from src.models import DocumentChunk, QueryResult
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _qr(chunk_id: str = "c1", doc_id: str = "doc.pdf", score: float = 0.8) -> QueryResult:
chunk = DocumentChunk(
chunk_id=chunk_id, document_id=doc_id, text="text",
metadata={"page_number": 1},
)
return QueryResult(chunk=chunk, score=score, source="test")
# ---------------------------------------------------------------------------
# Basic operations
# ---------------------------------------------------------------------------
class TestConversationMemory:
def test_initially_empty(self) -> None:
mem = ConversationMemory()
assert mem.is_empty
assert mem.turns == []
assert mem.last_query() == ""
assert mem.last_sources() == []
def test_add_turn(self) -> None:
mem = ConversationMemory()
mem.add_turn("What is X?", "X is Y.", [_qr()])
assert not mem.is_empty
assert len(mem.turns) == 1
assert mem.last_query() == "What is X?"
def test_multiple_turns(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1")
mem.add_turn("Q2", "A2")
assert len(mem.turns) == 2
assert mem.last_query() == "Q2"
def test_clear(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1")
mem.clear()
assert mem.is_empty
def test_turns_returns_copy(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1")
turns = mem.turns
turns.append(Turn(query="fake", answer="fake"))
assert len(mem.turns) == 1 # original unaffected
# ---------------------------------------------------------------------------
# Eviction
# ---------------------------------------------------------------------------
class TestEviction:
def test_max_turns_eviction(self) -> None:
mem = ConversationMemory(max_turns=3)
for i in range(5):
mem.add_turn(f"Q{i}", f"A{i}")
assert len(mem.turns) == 3
# Oldest should be Q2 (Q0 and Q1 evicted)
assert mem.turns[0].query == "Q2"
def test_max_turns_one(self) -> None:
mem = ConversationMemory(max_turns=1)
mem.add_turn("Q1", "A1")
mem.add_turn("Q2", "A2")
assert len(mem.turns) == 1
assert mem.turns[0].query == "Q2"
# ---------------------------------------------------------------------------
# format_history
# ---------------------------------------------------------------------------
class TestFormatHistory:
def test_empty_history(self) -> None:
mem = ConversationMemory()
assert mem.format_history() == ""
def test_includes_query_and_answer(self) -> None:
mem = ConversationMemory()
mem.add_turn("What is X?", "X is a policy.")
text = mem.format_history()
assert "What is X?" in text
assert "X is a policy." in text
def test_includes_source_doc_ids(self) -> None:
mem = ConversationMemory()
sources = [_qr(doc_id="policy.pdf"), _qr(chunk_id="c2", doc_id="rules.pdf")]
mem.add_turn("Q", "A", sources)
text = mem.format_history()
assert "policy.pdf" in text
assert "rules.pdf" in text
def test_max_recent_limits_output(self) -> None:
mem = ConversationMemory()
for i in range(10):
mem.add_turn(f"Q{i}", f"A{i}")
text = mem.format_history(max_recent=2)
assert "Q8" in text
assert "Q9" in text
assert "Q0" not in text
def test_long_answer_truncated(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q", "x" * 1000)
text = mem.format_history()
# Answer should be truncated to 500 chars
assert len(text) < 1000
# ---------------------------------------------------------------------------
# get_prior_sources
# ---------------------------------------------------------------------------
class TestGetPriorSources:
def test_empty_returns_empty(self) -> None:
mem = ConversationMemory()
assert mem.get_prior_sources() == []
def test_collects_across_turns(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1", [_qr(chunk_id="c1", score=0.8)])
mem.add_turn("Q2", "A2", [_qr(chunk_id="c2", score=0.9)])
sources = mem.get_prior_sources()
assert len(sources) == 2
# Sorted by score descending
assert sources[0].score == 0.9
def test_deduplicates_by_chunk_id(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1", [_qr(chunk_id="c1", score=0.5)])
mem.add_turn("Q2", "A2", [_qr(chunk_id="c1", score=0.9)])
sources = mem.get_prior_sources()
assert len(sources) == 1
assert sources[0].score == 0.9 # keeps higher score
def test_no_sources_turns(self) -> None:
mem = ConversationMemory()
mem.add_turn("Q1", "A1") # no sources
assert mem.get_prior_sources() == []
# ---------------------------------------------------------------------------
# Integration: memory in PlanAndExecuteRouter
# ---------------------------------------------------------------------------
class TestMemoryIntegration:
def test_route_records_turn(self) -> None:
"""After route(), the conversation turn should be recorded in memory."""
from unittest.mock import MagicMock, patch
from langchain_core.messages import AIMessage
from src.agent.plan_and_execute import PlanAndExecuteRouter
llm = MagicMock()
retriever = MagicMock()
reranker = MagicMock()
vector_store = MagicMock()
memory = ConversationMemory()
plan_json = '[{"action": "search", "detail": "test"}]'
llm.invoke.side_effect = [plan_json, "The answer."]
mock_agent = MagicMock()
mock_agent.invoke.return_value = {"messages": [AIMessage(content="Found info.")]}
router = PlanAndExecuteRouter(
llm, retriever, reranker, vector_store, memory=memory,
)
with patch("src.agent.plan_and_execute.create_react_agent", return_value=mock_agent):
router.route("test question", top_k=5)
assert not memory.is_empty
assert memory.last_query() == "test question"
assert memory.turns[0].answer == "The answer."
def test_history_injected_into_planner(self) -> None:
"""On a follow-up query, conversation history should appear in the planner prompt."""
from unittest.mock import MagicMock, patch
from langchain_core.messages import AIMessage
from src.agent.plan_and_execute import PlanAndExecuteRouter
llm = MagicMock()
memory = ConversationMemory()
memory.add_turn("What is the exam policy?", "The exam policy says...")
plan_json = '[{"action": "search", "detail": "follow-up"}]'
llm.invoke.side_effect = [plan_json, "Follow-up answer."]
mock_agent = MagicMock()
mock_agent.invoke.return_value = {"messages": [AIMessage(content="More info.")]}
router = PlanAndExecuteRouter(
llm, MagicMock(), MagicMock(), MagicMock(), memory=memory,
)
with patch("src.agent.plan_and_execute.create_react_agent", return_value=mock_agent):
router.route("What about the grading?", top_k=5)
# The first LLM call is the planner — check it includes history
planner_prompt = llm.invoke.call_args_list[0][0][0]
assert "exam policy" in planner_prompt
assert "Conversation history" in planner_prompt
def test_multi_turn_accumulates(self) -> None:
"""Multiple route() calls should accumulate turns in memory."""
from unittest.mock import MagicMock, patch
from langchain_core.messages import AIMessage
from src.agent.plan_and_execute import PlanAndExecuteRouter
llm = MagicMock()
memory = ConversationMemory()
mock_agent = MagicMock()
mock_agent.invoke.return_value = {"messages": [AIMessage(content="info")]}
router = PlanAndExecuteRouter(
llm, MagicMock(), MagicMock(), MagicMock(), memory=memory,
)
for i in range(3):
plan_json = f'[{{"action": "search", "detail": "q{i}"}}]'
llm.invoke.side_effect = [plan_json, f"Answer {i}"]
with patch("src.agent.plan_and_execute.create_react_agent", return_value=mock_agent):
router.route(f"Question {i}", top_k=5)
assert len(memory.turns) == 3
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