docs: Fixed linting and formatting issues

Added lint and formatting changes

Docs

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/.gitignore

@@ -174,4 +174,4 @@ env/
 venv/
 ENV/
 env.bak/
-venv.bak/
+venv.bak/

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/README.md

@@ -4,7 +4,6 @@ Cognee assists developers in introducing greater predictability and management i
 
 For more information, visit [Cognee documentation](https://docs.cognee.ai/)
 
-
 ## Installation
 
 ```shell
@@ -21,14 +20,16 @@ import asyncio
 from llama_index.core import Document
 from llama_index.graph_rag.cognee import CogneeGraphRAG
 
+
 async def example_graph_rag_cognee():
     # Gather documents to add to GraphRAG
     news = pd.read_csv(
         "https://raw.githubusercontent.com/tomasonjo/blog-datasets/main/news_articles.csv"
     )[:5]
     news.head()
     documents = [
-        Document(text=f"{row['title']}: {row['text']}") for i, row in news.iterrows()
+        Document(text=f"{row['title']}: {row['text']}")
+        for i, row in news.iterrows()
     ]
 
     # Instantiate cognee GraphRAG
@@ -42,7 +43,7 @@ async def example_graph_rag_cognee():
 
     # Add data to cognee
     await cogneeRAG.add(documents, "test")
-    
+
     # Process data into a knowledge graph
     await cogneeRAG.process_data("test")
 
@@ -61,4 +62,4 @@ async def example_graph_rag_cognee():
 
 if __name__ == "__main__":
     asyncio.run(example_graph_rag_cognee())
-```
+```

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/__init__.py

@@ -1,3 +1,3 @@
 from llama_index.graph_rag.cognee.graph_rag import CogneeGraphRAG
 
-__all__ = ['CogneeGraphRAG']
+__all__ = ["CogneeGraphRAG"]

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/base.py

@@ -1,32 +1,33 @@
 from abc import abstractmethod
 from typing import Protocol
 
+
 # NOTE: This is a bare-bone suggestion for an abstract protocol to define GraphRAG for llama-index
 # This should be expanded upon and integrated to llama-index-core to support multiple different GraphRAG
 # libraries in the future
 class GraphRAG(Protocol):
     """Abstract graph RAG protocol.
 
-        This protocol defines the interface for a graphRAG, which is responsible
-        for adding, storing, processing and retrieving information from knowledge graphs.
+    This protocol defines the interface for a graphRAG, which is responsible
+    for adding, storing, processing and retrieving information from knowledge graphs.
+
+    Attributes:
+        llm_api_key: str: Api key for desired llm.
+        graph_db_provider: str: The graph database provider.
+        vector_db_provider: str: The vector database provider.
+        relational_db_provider: str: The relational database provider.
+        db_name: str: The name of the databases.
+    """
 
-        Attributes:
-            llm_api_key: str: Api key for desired llm.
-            graph_db_provider: str: The graph database provider.
-            vector_db_provider: str: The vector database provider.
-            relational_db_provider: str: The relational database provider.
-            db_name: str: The name of the databases.
-        """
     @abstractmethod
     async def add(self, data, dataset_name):
         """Add data to the specified dataset.
         This data will later be processed and made into a knowledge graph.
 
-         Args:
+        Args:
              data (Any): The data to be added to the graph.
              dataset_name (str): Name of the dataset or node set where the data will be added.
         """
-        pass
 
     @abstractmethod
     async def process_data(self, dataset_name: str):
@@ -35,7 +36,6 @@ async def process_data(self, dataset_name: str):
         Args:
             dataset_name (str): The dataset name to process.
         """
-        pass
 
     @abstractmethod
     async def search(self, query: str):
@@ -44,7 +44,6 @@ async def search(self, query: str):
         Args:
             query (str): The query string to match against data from the graph.
         """
-        pass
 
     @abstractmethod
     async def get_related_nodes(self, node_id: str):
@@ -53,4 +52,3 @@ async def get_related_nodes(self, node_id: str):
         Args:
             node_id (str): The name of the node to match against nodes in the graph.
         """
-        pass

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/graph_rag.py

@@ -2,30 +2,25 @@
 import pathlib
 from typing import List
 
-from cognee.modules.users.methods import get_default_user
-from cognee.modules.data.methods import get_datasets_by_name
-from cognee.api.v1.search import SearchType
 import cognee
 
 from llama_index.core import Document
 
 from .base import GraphRAG
 
+
 class CogneeGraphRAG(GraphRAG):
     def __init__(
         self,
         llm_api_key,
         graph_db_provider,
         vector_db_provider,
         relational_db_provider,
-        db_name
-    ):
-
+        db_name,
+    ) -> None:
         cognee.config.set_llm_config({"llm_api_key": llm_api_key})
 
-        cognee.config.set_vector_db_config(
-            {"vector_db_provider": vector_db_provider}
-        )
+        cognee.config.set_vector_db_config({"vector_db_provider": vector_db_provider})
         cognee.config.set_relational_db_config(
             {"db_provider": relational_db_provider, "db_name": db_name}
         )
@@ -49,7 +44,7 @@ async def add(self, data, dataset_name: str):
         """Add data to the specified dataset.
         This data will later be processed and made into a knowledge graph.
 
-         Args:
+        Args:
              data (Any): The data to be added to the graph.
              dataset_name (str): Name of the dataset or node set where the data will be added.
         """
@@ -68,7 +63,9 @@ async def process_data(self, dataset_names: str):
             dataset_name (str): The dataset name to process.
         """
         user = await cognee.modules.users.methods.get_default_user()
-        datasets = await cognee.modules.data.methods.get_datasets_by_name(dataset_names, user.id)
+        datasets = await cognee.modules.data.methods.get_datasets_by_name(
+            dataset_names, user.id
+        )
         await cognee.cognify(datasets, user)
 
     async def get_graph_url(self, graphistry_password, graphistry_username) -> str:
@@ -103,7 +100,9 @@ async def search(self, query: str):
             query (str): The query string to match against data from the graph.
         """
         user = await cognee.modules.users.methods.get_default_user()
-        return await cognee.search(cognee.api.v1.search.SearchType.SUMMARIES, query, user)
+        return await cognee.search(
+            cognee.api.v1.search.SearchType.SUMMARIES, query, user
+        )
 
     async def get_related_nodes(self, node_id: str):
         """Search the graph for relevant nodes or relationships based on node id.
@@ -112,4 +111,6 @@ async def get_related_nodes(self, node_id: str):
             node_id (str): The name of the node to match against nodes in the graph.
         """
         user = await cognee.modules.users.methods.get_default_user()
-        return await cognee.search(cognee.api.v1.search.SearchType.INSIGHTS, node_id, user)
+        return await cognee.search(
+            cognee.api.v1.search.SearchType.INSIGHTS, node_id, user
+        )

llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_graph_rag_cognee.py

@@ -49,4 +49,4 @@ async def test_graph_rag_cognee():
 
 
 if __name__ == "__main__":
-    asyncio.run(test_graph_rag_cognee())
+    asyncio.run(test_graph_rag_cognee())