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Feat/research tab agent skills (#5)
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from __future__ import annotations
import numpy as np
from researchmind.config import ResearchMindConfig
from researchmind.store import MemRAGStore
def test_store_dedup_and_chunks(tmp_path):
cfg = ResearchMindConfig(
data_dir=tmp_path,
embed_model="test",
auto_search=False,
top_k=3,
max_context_chunks=8,
chunk_size=512,
chunk_overlap=128,
)
store = MemRAGStore(cfg)
emb = np.array([1.0, 0.0, 0.0], dtype=np.float32)
chunks = [("c1", 0, "hello world", emb, {})]
doc_id, is_new = store.add_document(
source_type="test",
uri="test://a",
title="A",
text="hello world",
chunks=chunks,
)
assert is_new
doc_id2, is_new2 = store.add_document(
source_type="test",
uri="test://a",
title="A",
text="hello world",
chunks=chunks,
)
assert not is_new2
assert doc_id == doc_id2
assert store.count_chunks() == 1
def test_session_messages(tmp_path):
cfg = ResearchMindConfig(
data_dir=tmp_path,
embed_model="test",
auto_search=False,
top_k=3,
max_context_chunks=8,
chunk_size=512,
chunk_overlap=128,
)
store = MemRAGStore(cfg)
session = store.create_session(topic="test topic")
store.add_message(session.id, "user", "hi", [])
msgs = store.get_messages(session.id)
assert len(msgs) == 1
assert msgs[0]["role"] == "user"