diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/.gitignore b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/.gitignore
new file mode 100644
index 0000000000000..b79e9dc84ab00
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/.gitignore
@@ -0,0 +1,180 @@
+llama_index/_static
+.DS_Store
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+bin/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+etc/
+include/
+lib/
+lib64/
+parts/
+sdist/
+share/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+.ruff_cache
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+notebooks/
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# Poetry
+poetry.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+pyvenv.cfg
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Jetbrains
+.idea
+modules/
+*.swp
+
+# VsCode
+.vscode
+
+# pipenv
+Pipfile
+Pipfile.lock
+
+# pyright
+pyrightconfig.json
+
+# Cognee
+.data
+.env
+.local.env
+.prod.env
+cognee/.data/
+*.lance/
+.cognee_system/
+.data_storage/
+.anon_id
+SWE-bench_testsample/
+
+full_run.ipynb
+
+# Environments
+.env
+.env.local
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/BUILD b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/BUILD
new file mode 100644
index 0000000000000..0896ca890d8bf
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/BUILD
@@ -0,0 +1,3 @@
+poetry_requirements(
+    name="poetry",
+)
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/Makefile b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/Makefile
new file mode 100644
index 0000000000000..b9eab05aa3706
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/Makefile
@@ -0,0 +1,17 @@
+GIT_ROOT ?= $(shell git rev-parse --show-toplevel)
+
+help:	## Show all Makefile targets.
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}'
+
+format:	## Run code autoformatters (black).
+	pre-commit install
+	git ls-files | xargs pre-commit run black --files
+
+lint:	## Run linters: pre-commit (black, ruff, codespell) and mypy
+	pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files
+
+test:	## Run tests via pytest.
+	pytest tests
+
+watch-docs:	## Build and watch documentation.
+	sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/README.md b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/README.md
new file mode 100644
index 0000000000000..dfcce56ed606d
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/README.md
@@ -0,0 +1,67 @@
+# LlamaIndex Graph Rag Integration: Cognee
+
+Cognee assists developers in introducing greater predictability and management into their Retrieval-Augmented Generation (RAG) workflows through the use of graph architectures, vector stores, and auto-optimizing pipelines. Displaying information as a graph is the clearest way to grasp the content of your documents. Crucially, graphs allow systematic navigation and extraction of data from documents based on their hierarchy.
+
+For more information, visit [Cognee documentation](https://docs.cognee.ai/)
+
+## Installation
+
+```shell
+pip install llama-index-graph-rag-cognee
+```
+
+## Usage
+
+```python
+import os
+import pandas as pd
+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()
+    ]
+
+    # Instantiate cognee GraphRAG
+    cogneeRAG = CogneeGraphRAG(
+        llm_api_key=os.environ["OPENAI_API_KEY"],
+        llm_provider="openai",
+        llm_model="gpt-4o-mini",
+        graph_db_provider="networkx",
+        vector_db_provider="lancedb",
+        relational_db_provider="sqlite",
+        db_name="cognee_db",
+    )
+
+    # Add data to cognee
+    await cogneeRAG.add(documents, "test")
+
+    # Process data into a knowledge graph
+    await cogneeRAG.process_data("test")
+
+    # Answer prompt based on knowledge graph
+    search_results = await cogneeRAG.search("person")
+    print("\n\nExtracted sentences are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    # Search for related nodes
+    search_results = await cogneeRAG.get_related_nodes("person")
+    print("\n\nRelated nodes are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+
+if __name__ == "__main__":
+    asyncio.run(example_graph_rag_cognee())
+```
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/BUILD b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/BUILD
new file mode 100644
index 0000000000000..db46e8d6c978c
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/BUILD
@@ -0,0 +1 @@
+python_sources()
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/__init__.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/__init__.py
new file mode 100644
index 0000000000000..03a993e559537
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/__init__.py
@@ -0,0 +1,3 @@
+from llama_index.graph_rag.cognee.graph_rag import CogneeGraphRAG
+
+__all__ = ["CogneeGraphRAG"]
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/base.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/base.py
new file mode 100644
index 0000000000000..68b56e5b17e23
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/base.py
@@ -0,0 +1,54 @@
+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.
+
+    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:
+             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.
+        """
+
+    @abstractmethod
+    async def process_data(self, dataset_name: str):
+        """Process and structure data in the dataset and make a knowledge graph out of it.
+
+        Args:
+            dataset_name (str): The dataset name to process.
+        """
+
+    @abstractmethod
+    async def search(self, query: str):
+        """Search the graph for relevant information based on a query.
+
+        Args:
+            query (str): The query string to match against data from the graph.
+        """
+
+    @abstractmethod
+    async def get_related_nodes(self, node_id: str):
+        """Search the graph for relevant nodes or relationships based on node id.
+
+        Args:
+            node_id (str): The name of the node to match against nodes in the graph.
+        """
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/graph_rag.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/graph_rag.py
new file mode 100644
index 0000000000000..6b4e91250ab62
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/llama_index/graph_rag/cognee/graph_rag.py
@@ -0,0 +1,142 @@
+import os
+import pathlib
+from typing import List, Union
+
+import cognee
+
+from llama_index.core import Document
+
+from .base import GraphRAG
+
+
+class CogneeGraphRAG(GraphRAG):
+    """Cognee GraphRAG, handles adding, storing, processing and retrieving information from knowledge graphs.
+
+    Unlike traditional RAG models that retrieve unstructured text snippets, graphRAG utilizes knowledge graphs.
+    A knowledge graph represents entities as nodes and their relationships as edges, often in a structured semantic format.
+    This enables the system to retrieve more precise and structured information about an entity, its relationships, and its properties.
+
+    Attributes:
+    llm_api_key: str: Api key for desired llm.
+    llm_provider: str: Provider for desired llm.
+    llm_model: str: Model 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.
+    """
+
+    def __init__(
+        self,
+        llm_api_key: str,
+        llm_provider: str = "openai",
+        llm_model: str = "gpt-4o-mini",
+        graph_db_provider: str = "networkx",
+        vector_db_provider: str = "lancedb",
+        relational_db_provider: str = "sqlite",
+        db_name: str = "cognee_db",
+    ) -> None:
+        cognee.config.set_llm_config(
+            {
+                "llm_api_key": llm_api_key,
+                "llm_provider": llm_provider,
+                "llm_model": llm_model,
+            }
+        )
+
+        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}
+        )
+        cognee.config.set_graph_database_provider(graph_db_provider)
+
+        data_directory_path = str(
+            pathlib.Path(
+                os.path.join(pathlib.Path(__file__).parent, ".data_storage/")
+            ).resolve()
+        )
+
+        cognee.config.data_root_directory(data_directory_path)
+        cognee_directory_path = str(
+            pathlib.Path(
+                os.path.join(pathlib.Path(__file__).parent, ".cognee_system/")
+            ).resolve()
+        )
+        cognee.config.system_root_directory(cognee_directory_path)
+
+    async def add(
+        self, data: Union[Document, List[Document]], dataset_name: str
+    ) -> None:
+        """Add data to the specified dataset.
+        This data will later be processed and made into a knowledge graph.
+
+        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.
+        """
+        # Convert LlamaIndex Document type to text
+        if isinstance(data, List) and len(data) > 0:
+            data = [data.text for data in data if type(data) == Document]
+        elif type(data) == Document:
+            data = [data.text]
+
+        await cognee.add(data, dataset_name)
+
+    async def process_data(self, dataset_names: str) -> None:
+        """Process and structure data in the dataset and make a knowledge graph out of it.
+
+        Args:
+            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
+        )
+        await cognee.cognify(datasets, user)
+
+    async def get_graph_url(self, graphistry_password, graphistry_username) -> str:
+        """Retrieve the URL or endpoint for visualizing or interacting with the graph.
+
+        Returns:
+            str: The URL endpoint of the graph.
+        """
+        if graphistry_password and graphistry_username:
+            cognee.config.set_graphistry_config(
+                {"username": graphistry_username, "password": graphistry_password}
+            )
+
+        from cognee.shared.utils import render_graph
+        from cognee.infrastructure.databases.graph import get_graph_engine
+        import graphistry
+
+        graphistry.login(
+            username=graphistry_username,
+            password=graphistry_password,
+        )
+        graph_engine = await get_graph_engine()
+
+        graph_url = await render_graph(graph_engine.graph)
+        print(graph_url)
+        return graph_url
+
+    async def search(self, query: str) -> list:
+        """Search the graph for relevant information based on a query.
+
+        Args:
+            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
+        )
+
+    async def get_related_nodes(self, node_id: str) -> list:
+        """Search the graph for relevant nodes or relationships based on node id.
+
+        Args:
+            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
+        )
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/pyproject.toml b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/pyproject.toml
new file mode 100644
index 0000000000000..7e03fdaa6a858
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/pyproject.toml
@@ -0,0 +1,69 @@
+[build-system]
+build-backend = "poetry.core.masonry.api"
+requires = ["poetry-core"]
+
+[tool.codespell]
+check-filenames = true
+check-hidden = true
+skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
+
+[tool.llamahub]
+contains_example = false
+import_path = "llama_index.graph_rag.cognee"
+
+[tool.llamahub.class_authors]
+GraphRag = "llama-index"
+
+[tool.mypy]
+disallow_untyped_defs = true
+exclude = ["_static", "build", "examples", "notebooks", "venv"]
+ignore_missing_imports = true
+python_version = "3.8"
+
+[tool.poetry]
+authors = ["Your Name <you@example.com>"]
+description = "llama-index graph rag cognee integration"
+exclude = ["**/BUILD"]
+license = "MIT"
+name = "llama-index-graph-rag-cognee"
+readme = "README.md"
+version = "0.1.0"
+
+[tool.poetry.dependencies]
+python = ">=3.10,<3.12"
+cognee = "^0.1.20"
+httpx = "~=0.27.0"
+llama-index-core = "^0.12.5"
+pytest-cov = "^6.0.0"
+
+[tool.poetry.group.dev.dependencies]
+ipython = "8.10.0"
+jupyter = "^1.0.0"
+mypy = "0.991"
+pre-commit = "3.2.0"
+pylint = "2.15.10"
+pytest = "8.2"
+pytest-asyncio = "^0.25.0"
+pytest-mock = "3.11.1"
+ruff = "0.0.292"
+tree-sitter-languages = "^1.8.0"
+types-Deprecated = ">=0.1.0"
+types-PyYAML = "^6.0.12.12"
+types-protobuf = "^4.24.0.4"
+types-redis = "4.5.5.0"
+types-requests = "2.28.11.8"
+types-setuptools = "67.1.0.0"
+
+[tool.poetry.group.dev.dependencies.black]
+extras = ["jupyter"]
+version = "<=23.9.1,>=23.7.0"
+
+[tool.poetry.group.dev.dependencies.codespell]
+extras = ["toml"]
+version = ">=v2.2.6"
+
+[[tool.poetry.packages]]
+include = "llama_index/"
+
+[tool.pytest.ini_options]
+asyncio_default_fixture_loop_scope = "function"
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/BUILD b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/BUILD
new file mode 100644
index 0000000000000..1f617359f48aa
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/BUILD
@@ -0,0 +1,3 @@
+python_tests(
+  interpreter_constraints=["==3.10.*", "==3.11.*", "==3.12.*"]
+)
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/__init__.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/__init__.py
new file mode 100644
index 0000000000000..e69de29bb2d1d
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_add_data.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_add_data.py
new file mode 100644
index 0000000000000..c0e41af04a5ae
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_add_data.py
@@ -0,0 +1,43 @@
+from llama_index.core import Document
+import asyncio
+import pytest
+from llama_index.graph_rag.cognee import CogneeGraphRAG
+
+
+@pytest.mark.asyncio()
+async def test_add_data(monkeypatch):
+    # Instantiate cognee GraphRAG
+    cogneeGraphRAG = CogneeGraphRAG(
+        llm_api_key="",
+        llm_provider="openai",
+        llm_model="gpt-4o-mini",
+        graph_db_provider="networkx",
+        vector_db_provider="lancedb",
+        relational_db_provider="sqlite",
+        db_name="cognee_db",
+    )
+
+    # Mock logging to graphistry
+    async def mock_add_return(add, dataset_name):
+        return True
+
+    import cognee
+
+    monkeypatch.setattr(cognee, "add", mock_add_return)
+
+    # Gather documents to add to GraphRAG
+    documents = [
+        Document(
+            text="Jessica Miller, Experienced Sales Manager with a strong track record in driving sales growth and building high-performing teams."
+        ),
+        Document(
+            text="David Thompson, Creative Graphic Designer with over 8 years of experience in visual design and branding."
+        ),
+    ]
+
+    await cogneeGraphRAG.add(documents, "test")
+    await cogneeGraphRAG.add(documents[0], "test")
+
+
+if __name__ == "__main__":
+    asyncio.run(test_add_data())
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_get_graph_url.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_get_graph_url.py
new file mode 100644
index 0000000000000..22ee4f6872ec9
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_get_graph_url.py
@@ -0,0 +1,48 @@
+import asyncio
+import pytest
+from llama_index.graph_rag.cognee import CogneeGraphRAG
+
+
+@pytest.mark.asyncio()
+async def test_get_graph_url(monkeypatch):
+    # Instantiate cognee GraphRAG
+    cogneeRAG = CogneeGraphRAG(
+        llm_api_key="",
+        llm_provider="openai",
+        llm_model="gpt-4o-mini",
+        graph_db_provider="networkx",
+        vector_db_provider="lancedb",
+        relational_db_provider="sqlite",
+        db_name="cognee_db",
+    )
+
+    # Mock logging to graphistry
+    def mock_graphistry_return(username, password):
+        return True
+
+    import graphistry
+
+    monkeypatch.setattr(graphistry, "login", mock_graphistry_return)
+
+    # Mock render of graph
+    async def mock_render_return(graph):
+        return "link"
+
+    from cognee.shared import utils
+
+    monkeypatch.setattr(utils, "render_graph", mock_render_return)
+
+    await cogneeRAG.get_graph_url("password", "username")
+
+    from cognee.base_config import get_base_config
+
+    assert (
+        get_base_config().graphistry_password == "password"
+    ), "Password was not set properly"
+    assert (
+        get_base_config().graphistry_username == "username"
+    ), "Username was not set properly"
+
+
+if __name__ == "__main__":
+    asyncio.run(test_get_graph_url())
diff --git a/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_graph_rag_cognee.py b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_graph_rag_cognee.py
new file mode 100644
index 0000000000000..3573b18b7e591
--- /dev/null
+++ b/llama-index-integrations/graph_rag/llama-index-graph-rag-cognee/tests/test_graph_rag_cognee.py
@@ -0,0 +1,64 @@
+import os
+import asyncio
+
+import cognee
+import pytest
+from llama_index.core import Document
+from llama_index.graph_rag.cognee import CogneeGraphRAG
+
+
+@pytest.mark.skipif(
+    os.getenv("OPENAI_API_KEY") is None,
+    reason="OPENAI_API_KEY not available to test Cognee integration",
+)
+@pytest.mark.asyncio()
+async def test_graph_rag_cognee():
+    documents = [
+        Document(
+            text="Jessica Miller, Experienced Sales Manager with a strong track record in driving sales growth and building high-performing teams."
+        ),
+        Document(
+            text="David Thompson, Creative Graphic Designer with over 8 years of experience in visual design and branding."
+        ),
+    ]
+
+    # Instantiate cognee GraphRAG
+    cogneeRAG = CogneeGraphRAG(
+        llm_api_key=os.environ["OPENAI_API_KEY"],
+        llm_provider="openai",
+        llm_model="gpt-4o-mini",
+        graph_db_provider="networkx",
+        vector_db_provider="lancedb",
+        relational_db_provider="sqlite",
+        db_name="cognee_db",
+    )
+
+    # Add data to cognee
+    await cogneeRAG.add(documents, "test")
+    # Process data into a knowledge graph
+    await cogneeRAG.process_data("test")
+
+    # Answer prompt based on knowledge graph
+    search_results = await cogneeRAG.search("person")
+
+    assert len(search_results) > 0, "No search results found"
+
+    print("\n\nExtracted sentences are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    # Search for related nodes
+    search_results = await cogneeRAG.get_related_nodes("person")
+    print("\n\nRelated nodes are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    assert len(search_results) > 0, "No search results found"
+
+    # Clean all data from previous runs
+    await cognee.prune.prune_data()
+    await cognee.prune.prune_system(metadata=True)
+
+
+if __name__ == "__main__":
+    asyncio.run(test_graph_rag_cognee())