Add mypy support

packages/ragbits-dev-kit/src/ragbits/dev_kit/app/main.py

@@ -5,10 +5,10 @@
 import jinja2
 import typer
 from pydantic import BaseModel
-from ragbits.dev_kit.discovery.prompt_discovery import PromptDiscovery
 
 from ragbits.common.llms import LiteLLM
 from ragbits.common.llms.clients import LiteLLMOptions
+from ragbits.dev_kit.discovery.prompt_discovery import PromptDiscovery
 
 
 class PromptState:

packages/ragbits-document-search/examples/simple_text.py

@@ -1,11 +1,10 @@
 import asyncio
 
+from ragbits.common.embeddings.litellm import LiteLLMEmbeddings
 from ragbits.document_search import DocumentSearch
 from ragbits.document_search.documents.document import DocumentMeta
 from ragbits.document_search.vector_store.in_memory import InMemoryVectorStore
 
-from ragbits.common.embeddings.litellm import LiteLLMEmbeddings
-
 documents = [
     DocumentMeta.create_text_document_from_literal("RIP boiled water. You will be mist."),
     DocumentMeta.create_text_document_from_literal(

packages/ragbits-document-search/src/ragbits/document_search/_main.py

@@ -1,3 +1,4 @@
+from ragbits.common.embeddings.base import Embeddings
 from ragbits.document_search.documents.document import DocumentMeta
 from ragbits.document_search.documents.element import Element
 from ragbits.document_search.ingestion.document_processor import DocumentProcessor
@@ -7,8 +8,6 @@
 from ragbits.document_search.retrieval.rerankers.noop import NoopReranker
 from ragbits.document_search.vector_store.base import VectorStore
 
-from ragbits.common.embeddings.base import Embeddings
-
 
 class DocumentSearch:
     """

packages/ragbits-document-search/src/ragbits/document_search/documents/document.py

@@ -4,6 +4,7 @@
 from typing import Union
 
 from pydantic import BaseModel, Field
+
 from ragbits.document_search.documents.sources import LocalFileSource
 
 

packages/ragbits-document-search/src/ragbits/document_search/documents/element.py

@@ -2,6 +2,7 @@
 from typing import ClassVar
 
 from pydantic import BaseModel
+
 from ragbits.document_search.documents.document import DocumentMeta
 from ragbits.document_search.vector_store.base import VectorDBEntry
 
@@ -26,7 +27,7 @@ def get_key(self) -> str:
         """
 
     @classmethod
-    def __pydantic_init_subclass__(cls, **kwargs):  # pylint: disable=unused-argument
+    def __pydantic_init_subclass__(cls, **kwargs: dict) -> None:  # pylint: disable=unused-argument
         element_type_default = cls.model_fields["element_type"].default
 
         if element_type_default is None:

packages/ragbits-document-search/src/ragbits/document_search/vector_store/in_memory.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from ragbits.document_search.vector_store.base import VectorDBEntry, VectorStore
 
 
@@ -7,8 +8,8 @@ class InMemoryVectorStore(VectorStore):
     A simple in-memory implementation of Vector Store, storing vectors in memory.
     """
 
-    def __init__(self):
-        self._storage = {}
+    def __init__(self) -> None:
+        self._storage: dict[str, VectorDBEntry] = {}
 
     async def store(self, entries: list[VectorDBEntry]) -> None:
         """

pyproject.toml

@@ -81,7 +81,12 @@ warn_unused_ignores = false
 show_error_codes = true
 check_untyped_defs = true
 no_implicit_optional = true
-mypy_path = ['packages']
+explicit_package_bases = true
+mypy_path = [
+    'packages/ragbits-common/src',
+    'packages/ragbits-dev-kit/src',
+    'packages/ragbits-document-search/src',
+]
 
 [[tool.mypy.overrides]]
 module = "ragbits.*"