Add type checking of ragstack-llama-index

libs/llamaindex/pyproject.toml

@@ -44,6 +44,26 @@ google = ["llama-index-llms-gemini", "llama-index-multi-modal-llms-gemini", "lla
 azure = ["llama-index-llms-azure-openai", "llama-index-embeddings-azure-openai"]
 bedrock = ["llama-index-llms-bedrock", "llama-index-embeddings-bedrock"]
 
+[tool.poetry.group.dev.dependencies]
+mypy = "^1.11.0"
+
 [tool.poetry.group.test.dependencies]
 ragstack-ai-tests-utils = { path = "../tests-utils", develop = true }
 ragstack-ai-colbert = { path = "../colbert", develop = true }
+
+[tool.mypy]
+disallow_any_generics = true
+disallow_incomplete_defs = true
+disallow_untyped_calls = true
+disallow_untyped_decorators = true
+disallow_untyped_defs = true
+follow_imports = "normal"
+ignore_missing_imports = true
+no_implicit_reexport = true
+show_error_codes = true
+show_error_context = true
+strict_equality = true
+strict_optional = true
+warn_redundant_casts = true
+warn_return_any = true
+warn_unused_ignores = true

libs/llamaindex/ragstack_llamaindex/colbert/colbert_retriever.py

@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, List, Optional, Tuple
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
 
 from llama_index.core.callbacks.base import CallbackManager
 from llama_index.core.constants import DEFAULT_SIMILARITY_TOP_K
@@ -27,7 +27,7 @@ def __init__(
         retriever: ColbertBaseRetriever,
         similarity_top_k: int = DEFAULT_SIMILARITY_TOP_K,
         callback_manager: Optional[CallbackManager] = None,
-        object_map: Optional[dict] = None,
+        object_map: Optional[Dict[str, Any]] = None,
         verbose: bool = False,
         query_maxlen: int = -1,
     ) -> None:
@@ -51,6 +51,6 @@ def _retrieve(
             query_maxlen=self._query_maxlen,
         )
         return [
-            NodeWithScore(node=TextNode(text=c.text, metadata=c.metadata), score=s)
+            NodeWithScore(node=TextNode(text=c.text, extra_info=c.metadata), score=s)
             for (c, s) in chunk_scores
         ]

libs/llamaindex/tests/integration_tests/conftest.py

@@ -1,4 +1,5 @@
 import pytest
+from _pytest.fixtures import FixtureRequest
 from cassandra.cluster import Session
 from ragstack_tests_utils import AstraDBTestStore, LocalCassandraTestStore
 
@@ -17,7 +18,7 @@ def astra_db() -> AstraDBTestStore:
 
 
 @pytest.fixture()
-def session(request) -> Session:
+def session(request: FixtureRequest) -> Session:
     test_store = request.getfixturevalue(request.param)
     session = test_store.create_cassandra_session()
     session.default_timeout = 180

libs/llamaindex/tests/integration_tests/test_colbert.py

@@ -5,8 +5,9 @@
 from cassandra.cluster import Session
 from llama_index.core import Settings, get_response_synthesizer
 from llama_index.core.ingestion import IngestionPipeline
+from llama_index.core.llms import MockLLM
 from llama_index.core.query_engine import RetrieverQueryEngine
-from llama_index.core.schema import Document, NodeWithScore
+from llama_index.core.schema import Document, NodeWithScore, QueryBundle
 from llama_index.core.text_splitter import SentenceSplitter
 from ragstack_colbert import (
     CassandraDatabase,
@@ -20,7 +21,7 @@
 logging.getLogger("cassandra").setLevel(logging.ERROR)
 
 
-def validate_retrieval(results: List[NodeWithScore], key_value: str):
+def validate_retrieval(results: List[NodeWithScore], key_value: str) -> bool:
     passed = False
     for result in results:
         if key_value in result.text:
@@ -29,7 +30,7 @@ def validate_retrieval(results: List[NodeWithScore], key_value: str):
 
 
 @pytest.mark.parametrize("session", ["astra_db"], indirect=["session"])  # "cassandra",
-def test_sync(session: Session):
+def test_sync(session: Session) -> None:
     table_name = "LlamaIndex_colbert_sync"
 
     batch_size = 5  # 640 recommended for production use
@@ -47,15 +48,15 @@ def test_sync(session: Session):
         embedding_model=embedding_model,
     )
 
-    docs: List[Document] = []
+    docs = []
     docs.append(
         Document(
-            text=TestData.marine_animals_text(), metadata={"name": "marine_animals"}
+            text=TestData.marine_animals_text(), extra_info={"name": "marine_animals"}
         )
     )
     docs.append(
         Document(
-            text=TestData.nebula_voyager_text(), metadata={"name": "nebula_voyager"}
+            text=TestData.nebula_voyager_text(), extra_info={"name": "nebula_voyager"}
         )
     )
 
@@ -64,20 +65,20 @@ def test_sync(session: Session):
 
     nodes = pipeline.run(documents=docs)
 
-    docs: Dict[str, Tuple[List[str], List[Metadata]]] = {}
+    docs2: Dict[str, Tuple[List[str], List[Metadata]]] = {}
 
     for node in nodes:
         doc_id = node.metadata["name"]
-        if doc_id not in docs:
-            docs[doc_id] = ([], [])
-        docs[doc_id][0].append(node.text)
-        docs[doc_id][1].append(node.metadata)
+        if doc_id not in docs2:
+            docs2[doc_id] = ([], [])
+        docs2[doc_id][0].append(node.text)
+        docs2[doc_id][1].append(node.metadata)
 
     logging.debug("Starting to embed ColBERT docs and save them to the database")
 
-    for doc_id in docs:
-        texts = docs[doc_id][0]
-        metadatas = docs[doc_id][1]
+    for doc_id in docs2:
+        texts = docs2[doc_id][0]
+        metadatas = docs2[doc_id][1]
 
         logging.debug("processing %s that has %s chunks", doc_id, len(texts))
 
@@ -87,22 +88,24 @@ def test_sync(session: Session):
         retriever=vector_store.as_retriever(), similarity_top_k=5
     )
 
-    Settings.llm = None
+    Settings.llm = MockLLM()
 
     response_synthesizer = get_response_synthesizer()
 
-    pipeline = RetrieverQueryEngine(
+    pipeline2 = RetrieverQueryEngine(
         retriever=retriever,
         response_synthesizer=response_synthesizer,
     )
 
-    results = pipeline.retrieve("Who developed the Astroflux Navigator?")
+    results = pipeline2.retrieve(QueryBundle("Who developed the Astroflux Navigator?"))
     assert validate_retrieval(results, key_value="Astroflux Navigator")
 
-    results = pipeline.retrieve(
-        "Describe the phenomena known as 'Chrono-spatial Echoes'"
+    results = pipeline2.retrieve(
+        QueryBundle("Describe the phenomena known as 'Chrono-spatial Echoes'")
     )
     assert validate_retrieval(results, key_value="Chrono-spatial Echoes")
 
-    results = pipeline.retrieve("How do anglerfish adapt to the deep ocean's darkness?")
+    results = pipeline2.retrieve(
+        QueryBundle("How do anglerfish adapt to the deep ocean's darkness?")
+    )
     assert validate_retrieval(results, key_value="anglerfish")

libs/llamaindex/tests/unit_tests/test_import.py

@@ -1,7 +1,8 @@
 import importlib
+from typing import Any, Callable
 
 
-def test_import():
+def test_import() -> None:
     import astrapy  # noqa: F401
     import cassio  # noqa: F401
     import openai  # noqa: F401
@@ -11,25 +12,25 @@ def test_import():
     from llama_index.vector_stores.cassandra import CassandraVectorStore  # noqa: F401
 
 
-def check_no_import(fn: callable):
+def check_no_import(fn: Callable[[], Any]) -> None:
     try:
         fn()
         raise RuntimeError("Should have failed to import")
     except ImportError:
         pass
 
 
-def test_not_import():
+def test_not_import() -> None:
     check_no_import(lambda: importlib.import_module("langchain.vectorstores"))
     check_no_import(lambda: importlib.import_module("langchain_astradb"))
     check_no_import(lambda: importlib.import_module("langchain_core"))
     check_no_import(lambda: importlib.import_module("langsmith"))
 
 
-def test_meta():
+def test_meta() -> None:
     from importlib import metadata
 
-    def check_meta(package: str):
+    def check_meta(package: str) -> None:
         meta = metadata.metadata(package)
         assert meta["version"]
         assert meta["license"] == "BUSL-1.1"

libs/llamaindex/tox.ini

@@ -1,24 +1,30 @@
 [tox]
 min_version = 4.0
-envlist = py311
+envlist = type, unit-tests, integration-tests
+
+[testenv]
+description = install dependencies
+skip_install = true
+allowlist_externals = poetry
+commands_pre =
+    poetry env use system
+    poetry install -E colbert
 
 [testenv:unit-tests]
 description = run unit tests
-deps =
-    poetry
 commands =
-    poetry install
-    poetry build
     poetry run pytest --disable-warnings {toxinidir}/tests/unit_tests
 
 [testenv:integration-tests]
 description = run integration tests
-deps =
-    poetry
 pass_env =
     ASTRA_DB_TOKEN
     ASTRA_DB_ID
     ASTRA_DB_ENV
 commands =
-    poetry install -E colbert
     poetry run pytest --disable-warnings {toxinidir}/tests/integration_tests
+
+[testenv:type]
+description = run type checking
+commands =
+    poetry run mypy {toxinidir}