mypy fix: Fix ChromaDBAdapter mypy errors

cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py

@@ -1,12 +1,13 @@
 import json
 import asyncio
 from uuid import UUID
-from typing import List, Optional
+from typing import List, Optional, Dict, Any
 from chromadb import AsyncHttpClient, Settings
 
 from cognee.shared.logging_utils import get_logger
 from cognee.modules.storage.utils import get_own_properties
 from cognee.infrastructure.engine import DataPoint
+from cognee.infrastructure.engine.models.DataPoint import MetaData
 from cognee.infrastructure.engine.utils import parse_id
 from cognee.infrastructure.databases.vector.exceptions import CollectionNotFoundError
 from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
@@ -35,9 +36,9 @@ class IndexSchema(DataPoint):
 
     text: str
 
-    metadata: dict = {"index_fields": ["text"]}
+    metadata: MetaData = {"index_fields": ["text"], "type": "IndexSchema"}
 
-    def model_dump(self):
+    def model_dump(self, **kwargs: Any) -> Dict[str, Any]:
         """
         Serialize the instance data for storage.
 
@@ -49,11 +50,11 @@ class IndexSchema(DataPoint):
 
             A dictionary containing serialized data processed for ChromaDB storage.
         """
-        data = super().model_dump()
+        data = super().model_dump(**kwargs)
         return process_data_for_chroma(data)
 
 
-def process_data_for_chroma(data):
+def process_data_for_chroma(data: Dict[str, Any]) -> Dict[str, Any]:
     """
     Convert complex data types to a format suitable for ChromaDB storage.
 
@@ -73,7 +74,7 @@ def process_data_for_chroma(data):
 
         A dictionary containing the processed key-value pairs suitable for ChromaDB storage.
     """
-    processed_data = {}
+    processed_data: Dict[str, Any] = {}
     for key, value in data.items():
         if isinstance(value, UUID):
             processed_data[key] = str(value)
@@ -90,7 +91,7 @@ def process_data_for_chroma(data):
     return processed_data
 
 
-def restore_data_from_chroma(data):
+def restore_data_from_chroma(data: Dict[str, Any]) -> Dict[str, Any]:
     """
     Restore original data structure from ChromaDB storage format.
 
@@ -152,8 +153,8 @@ class ChromaDBAdapter(VectorDBInterface):
     """
 
     name = "ChromaDB"
-    url: str
+    url: str | None
-    api_key: str
+    api_key: str | None
     connection: AsyncHttpClient = None
 
     def __init__(
@@ -216,7 +217,7 @@ class ChromaDBAdapter(VectorDBInterface):
         collections = await self.get_collection_names()
         return collection_name in collections
 
-    async def create_collection(self, collection_name: str, payload_schema=None):
+    async def create_collection(self, collection_name: str, payload_schema: Optional[Any] = None) -> None:
         """
         Create a new collection in ChromaDB if it does not already exist.
 
@@ -254,7 +255,7 @@ class ChromaDBAdapter(VectorDBInterface):
         client = await self.get_connection()
         return await client.get_collection(collection_name)
 
-    async def create_data_points(self, collection_name: str, data_points: list[DataPoint]):
+    async def create_data_points(self, collection_name: str, data_points: List[DataPoint]) -> None:
         """
         Create and upsert data points into the specified collection in ChromaDB.
 
@@ -282,7 +283,7 @@ class ChromaDBAdapter(VectorDBInterface):
             ids=ids, embeddings=embeddings, metadatas=metadatas, documents=texts
         )
 
-    async def create_vector_index(self, index_name: str, index_property_name: str):
+    async def create_vector_index(self, index_name: str, index_property_name: str) -> None:
         """
         Create a vector index as a ChromaDB collection based on provided names.
 
@@ -296,7 +297,7 @@ class ChromaDBAdapter(VectorDBInterface):
 
     async def index_data_points(
         self, index_name: str, index_property_name: str, data_points: list[DataPoint]
-    ):
+    ) -> None:
         """
         Index the provided data points based on the specified index property in ChromaDB.
 
@@ -312,13 +313,17 @@ class ChromaDBAdapter(VectorDBInterface):
             [
                 IndexSchema(
                     id=data_point.id,
-                    text=getattr(data_point, data_point.metadata["index_fields"][0]),
+                    text=getattr(
+                        data_point, 
+                        data_point.metadata["index_fields"][0]
+                    ),
                 )
                 for data_point in data_points
+                if data_point.metadata and len(data_point.metadata["index_fields"]) > 0
             ],
         )
 
-    async def retrieve(self, collection_name: str, data_point_ids: list[str]):
+    async def retrieve(self, collection_name: str, data_point_ids: List[str]) -> List[ScoredResult]:
         """
         Retrieve data points by their IDs from a ChromaDB collection.
 
@@ -350,12 +355,12 @@ class ChromaDBAdapter(VectorDBInterface):
     async def search(
         self,
         collection_name: str,
-        query_text: str = None,
+        query_text: Optional[str] = None,
-        query_vector: List[float] = None,
+        query_vector: Optional[List[float]] = None,
         limit: int = 15,
         with_vector: bool = False,
         normalized: bool = True,
-    ):
+    ) -> List[ScoredResult]:
         """
         Search for items in a collection using either a text or a vector query.
 
@@ -437,7 +442,7 @@ class ChromaDBAdapter(VectorDBInterface):
         query_texts: List[str],
         limit: int = 5,
         with_vectors: bool = False,
-    ):
+    ) -> List[List[ScoredResult]]:
         """
         Perform multiple searches in a single request for efficiency, returning results for each
         query.
@@ -507,7 +512,7 @@ class ChromaDBAdapter(VectorDBInterface):
 
         return all_results
 
-    async def delete_data_points(self, collection_name: str, data_point_ids: list[str]):
+    async def delete_data_points(self, collection_name: str, data_point_ids: List[str]) -> bool:
         """
         Remove data points from a collection based on their IDs.
 
@@ -528,7 +533,7 @@ class ChromaDBAdapter(VectorDBInterface):
         await collection.delete(ids=data_point_ids)
         return True
 
-    async def prune(self):
+    async def prune(self) -> bool:
         """
         Delete all collections in the ChromaDB database.
 
@@ -538,12 +543,12 @@ class ChromaDBAdapter(VectorDBInterface):
             Returns True upon successful deletion of all collections.
         """
         client = await self.get_connection()
-        collections = await self.list_collections()
+        collection_names = await self.get_collection_names()
-        for collection_name in collections:
+        for collection_name in collection_names:
             await client.delete_collection(collection_name)
         return True
 
-    async def get_collection_names(self):
+    async def get_collection_names(self) -> List[str]:
         """
         Retrieve the names of all collections in the ChromaDB database.
 

cognee/infrastructure/databases/vector/models/ScoredResult.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict
+from typing import Any, Dict, List, Optional
 from uuid import UUID
 from pydantic import BaseModel
 
@@ -14,8 +14,10 @@ class ScoredResult(BaseModel):
     better outcome.
     - payload (Dict[str, Any]): Additional information related to the score, stored as
     key-value pairs in a dictionary.
+    - vector (Optional[List[float]]): Optional vector embedding associated with the result.
     """
 
     id: UUID
     score: float  # Lower score is better
     payload: Dict[str, Any]
+    vector: Optional[List[float]] = None