feat: add DeepSearch multi-agent researcher with async jobs, vector store, and RAG chat

This commit is contained in:
2026-06-14 01:57:17 +00:00
parent 4ae0b0db5d
commit 33d17db79a
8 changed files with 444 additions and 3 deletions
+55
View File
@@ -0,0 +1,55 @@
# retoor <retoor@molodetz.nl>
import asyncio
from devplacepy.services.deepsearch import chat as chat_module
from devplacepy.services.deepsearch.chat import DeepsearchChat
from devplacepy.services.deepsearch.embeddings import local_embed
from devplacepy.services.deepsearch.store import Chunk, VectorStore
def _seed(collection):
store = VectorStore(collection)
chunks = [
Chunk(uid="c0", text="The transistor was invented at Bell Labs.", url="https://a.example", title="A"),
Chunk(uid="c1", text="Silicon wafers are used to make chips.", url="https://b.example", title="B"),
]
vectors = local_embed([c.text for c in chunks]).vectors
store.add(chunks, vectors)
def test_answer_is_grounded_and_cited(monkeypatch):
collection = "ds_chat_test_grounded"
_seed(collection)
try:
async def fake_embed(texts, api_key, **kwargs):
return local_embed(texts)
async def fake_complete(messages, api_key, **kwargs):
return "The transistor was invented at Bell Labs [1]."
monkeypatch.setattr(chat_module, "embed_texts", fake_embed)
monkeypatch.setattr(chat_module, "complete_chat", fake_complete)
chat = DeepsearchChat(collection, "k")
answer = asyncio.run(chat.answer("where was the transistor invented"))
assert "Bell Labs" in answer.text
assert answer.citations
assert answer.citations[0]["url"].startswith("https://")
finally:
VectorStore(collection).drop()
def test_answer_when_no_chunks(monkeypatch):
collection = "ds_chat_test_empty"
try:
async def fake_embed(texts, api_key, **kwargs):
return local_embed(texts)
monkeypatch.setattr(chat_module, "embed_texts", fake_embed)
chat = DeepsearchChat(collection, "k")
answer = asyncio.run(chat.answer("anything"))
assert answer.citations == []
assert "did not capture" in answer.text
finally:
VectorStore(collection).drop()
+52
View File
@@ -0,0 +1,52 @@
# retoor <retoor@molodetz.nl>
from devplacepy.services.deepsearch.embeddings import local_embed
from devplacepy.services.deepsearch.store import Chunk, VectorStore
def _chunks():
texts = [
"The transistor was invented at Bell Labs in nineteen forty seven.",
"Silicon is the primary semiconductor material used in chips.",
"Quantum tunnelling limits how small a transistor can become.",
]
chunks = [
Chunk(uid=f"c{i}", text=text, url=f"https://s{i}.example", title=f"Source {i}")
for i, text in enumerate(texts)
]
return chunks
def test_add_and_count():
store = VectorStore("ds_store_test_count")
try:
chunks = _chunks()
vectors = local_embed([c.text for c in chunks]).vectors
store.add(chunks, vectors)
assert store.count() == 3
finally:
store.drop()
def test_hybrid_search_returns_relevant_chunk():
store = VectorStore("ds_store_test_hybrid")
try:
chunks = _chunks()
vectors = local_embed([c.text for c in chunks]).vectors
store.add(chunks, vectors)
query = "where was the transistor invented"
query_vector = local_embed([query]).vectors[0]
results = store.hybrid_search(query, query_vector, top_k=2)
assert results
assert any("transistor" in r.text.lower() for r in results)
finally:
store.drop()
def test_keyword_scores_rank_match_higher():
store = VectorStore("ds_store_test_keyword")
chunks = _chunks()
scores = store.keyword_scores("silicon semiconductor", chunks)
assert scores
best = max(scores, key=scores.get)
assert "silicon" in next(c.text for c in chunks if c.uid == best).lower()