diff --git a/cognee/infrastructure/databases/graph/networkx/adapter.py b/cognee/infrastructure/databases/graph/networkx/adapter.py
index f85ce5846..534c47947 100644
--- a/cognee/infrastructure/databases/graph/networkx/adapter.py
+++ b/cognee/infrastructure/databases/graph/networkx/adapter.py
@@ -243,6 +243,15 @@ class NetworkXAdapter(GraphDBInterface):
 
         await self.save_graph_to_file(self.filename)
 
+    async def create_empty_graph(self, file_path: str) -> None:
+        self.graph = nx.MultiDiGraph()
+
+        file_dir = os.path.dirname(file_path)
+        if not os.path.exists(file_dir):
+            os.makedirs(file_dir, exist_ok=True)
+
+        await self.save_graph_to_file(file_path)
+
     async def save_graph_to_file(self, file_path: str = None) -> None:
         """Asynchronously save the graph to a file in JSON format."""
         if not file_path:
@@ -322,19 +331,12 @@ class NetworkXAdapter(GraphDBInterface):
             else:
                 # Log that the file does not exist and an empty graph is initialized
                 logger.warning("File %s not found. Initializing an empty graph.", file_path)
-                self.graph = (
-                    nx.MultiDiGraph()
-                )  # Use MultiDiGraph to keep it consistent with __init__
+                await self.create_empty_graph(file_path)
 
-                file_dir = os.path.dirname(file_path)
-                if not os.path.exists(file_dir):
-                    os.makedirs(file_dir, exist_ok=True)
-
-                await self.save_graph_to_file(file_path)
-
-        except Exception as e:
+        except Exception:
             logger.error("Failed to load graph from file: %s", file_path)
-            raise e
+
+            await self.create_empty_graph(file_path)
 
     async def delete_graph(self, file_path: str = None):
         """Asynchronously delete the graph file from the filesystem."""
diff --git a/notebooks/cognee_code_graph_demo.ipynb b/notebooks/cognee_code_graph_demo.ipynb
index b8abb710f..73e4fdd27 100644
--- a/notebooks/cognee_code_graph_demo.ipynb
+++ b/notebooks/cognee_code_graph_demo.ipynb
@@ -9,7 +9,8 @@
     "import os\n",
     "\n",
     "os.environ[\"GRAPHISTRY_USERNAME\"] = input(\"Please enter your graphistry username\")\n",
-    "os.environ[\"GRAPHISTRY_PASSWORD\"] = input(\"Please enter your graphistry password\")"
+    "os.environ[\"GRAPHISTRY_PASSWORD\"] = input(\"Please enter your graphistry password\")\n",
+    "os.environ[\"OPENAI_API_KEY\"] = input(\"Please enter your OpenAI API key\")"
    ]
   },
   {
@@ -70,19 +71,16 @@
    "outputs": [],
    "source": [
     "from cognee.tasks.repo_processor import (\n",
-    "    enrich_dependency_graph,\n",
-    "    expand_dependency_graph,\n",
     "    get_repo_file_dependencies,\n",
     ")\n",
     "from cognee.tasks.storage import add_data_points\n",
     "from cognee.modules.pipelines.tasks.Task import Task\n",
     "\n",
+    "detailed_extraction = True\n",
+    "\n",
     "tasks = [\n",
-    "    Task(get_repo_file_dependencies),\n",
-    "    Task(add_data_points, task_config={\"batch_size\": 50}),\n",
-    "    Task(enrich_dependency_graph, task_config={\"batch_size\": 50}),\n",
-    "    Task(expand_dependency_graph, task_config={\"batch_size\": 50}),\n",
-    "    Task(add_data_points, task_config={\"batch_size\": 50}),\n",
+    "    Task(get_repo_file_dependencies, detailed_extraction=detailed_extraction),\n",
+    "    Task(add_data_points, task_config={\"batch_size\": 100 if detailed_extraction else 500}),\n",
     "]"
    ]
   },
@@ -95,9 +93,6 @@
     "from cognee.modules.pipelines import run_tasks\n",
     "from uuid import uuid5, NAMESPACE_OID\n",
     "\n",
-    "notebook_path = os.path.abspath(\"\")\n",
-    "repo_clone_location = os.path.join(notebook_path, \".data/graphrag\")\n",
-    "\n",
     "pipeline = run_tasks(tasks, uuid5(NAMESPACE_OID, repo_clone_location), repo_clone_location, \"code_graph_pipeline\")\n",
     "\n",
     "async for result in pipeline:\n",
@@ -112,7 +107,7 @@
    "source": [
     "from cognee.shared.utils import render_graph\n",
     "\n",
-    "await render_graph(None, include_nodes=True, include_labels=True)"
+    "await render_graph()"
    ]
   },
   {
@@ -128,46 +123,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from evals.eval_on_hotpot import eval_on_hotpotQA\n",
-    "from evals.eval_on_hotpot import answer_with_cognee\n",
-    "from evals.eval_on_hotpot import answer_without_cognee\n",
-    "from evals.eval_on_hotpot import eval_answers\n",
-    "from cognee.base_config import get_base_config\n",
-    "from pathlib import Path\n",
-    "from tqdm import tqdm\n",
-    "import wget\n",
-    "import json\n",
-    "import statistics"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "answer_provider = answer_with_cognee  # For native LLM answers use answer_without_cognee\n",
-    "num_samples = 10  # With cognee, it takes ~1m10s per sample\n",
+    "from cognee import search, SearchType\n",
     "\n",
-    "base_config = get_base_config()\n",
-    "data_root_dir = base_config.data_root_directory\n",
+    "results = await search(query_type=SearchType.CODE, query_text=\"def create_graphrag_config\")\n",
     "\n",
-    "if not Path(data_root_dir).exists():\n",
-    "    Path(data_root_dir).mkdir()\n",
-    "\n",
-    "filepath = data_root_dir / Path(\"hotpot_dev_fullwiki_v1.json\")\n",
-    "if not filepath.exists():\n",
-    "    url = \"http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json\"\n",
-    "    wget.download(url, out=data_root_dir)\n",
-    "\n",
-    "with open(filepath, \"r\") as file:\n",
-    "    dataset = json.load(file)\n",
-    "\n",
-    "instances = dataset if not num_samples else dataset[:num_samples]\n",
-    "answers = []\n",
-    "for instance in tqdm(instances, desc=\"Getting answers\"):\n",
-    "    answer = answer_provider(instance)\n",
-    "    answers.append(answer)"
+    "print(results)\n"
    ]
   }
  ],
diff --git a/notebooks/cognee_graphiti_demo.ipynb b/notebooks/cognee_graphiti_demo.ipynb
index 857a72c16..ebc88c9cf 100644
--- a/notebooks/cognee_graphiti_demo.ipynb
+++ b/notebooks/cognee_graphiti_demo.ipynb
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-01-15T10:43:57.893763Z",
@@ -73,22 +73,15 @@
     "if \"OPENAI_API_KEY\" not in os.environ:\n",
     "    os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
     "\n",
-    "# Graphiti integration is only tested with neo4j + pgvector + postgres for now\n",
     "GRAPH_DATABASE_PROVIDER = \"neo4j\"\n",
-    "GRAPH_DATABASE_URL = \"bolt://localhost:7687\"\n",
     "GRAPH_DATABASE_USERNAME = \"neo4j\"\n",
     "GRAPH_DATABASE_PASSWORD = \"pleaseletmein\"\n",
+    "GRAPH_DATABASE_URL = \"bolt://localhost:7687\"\n",
     "\n",
-    "os.environ[\"VECTOR_DB_PROVIDER\"] = \"pgvector\"\n",
-    "\n",
-    "os.environ[\"DB_PROVIDER\"] = \"postgres\"\n",
-    "\n",
-    "os.environ[\"DB_NAME\"] = \"cognee_db\"\n",
-    "\n",
-    "os.environ[\"DB_HOST\"] = \"127.0.0.1\"\n",
-    "os.environ[\"DB_PORT\"] = \"5432\"\n",
-    "os.environ[\"DB_USERNAME\"] = \"cognee\"\n",
-    "os.environ[\"DB_PASSWORD\"] = \"cognee\""
+    "os.environ[\"GRAPH_DATABASE_PROVIDER\"] = GRAPH_DATABASE_PROVIDER\n",
+    "os.environ[\"GRAPH_DATABASE_USERNAME\"] = GRAPH_DATABASE_USERNAME\n",
+    "os.environ[\"GRAPH_DATABASE_PASSWORD\"] = GRAPH_DATABASE_PASSWORD\n",
+    "os.environ[\"GRAPH_DATABASE_URL\"] = GRAPH_DATABASE_URL\n"
    ]
   },
   {
@@ -100,7 +93,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-01-15T10:43:57.928664Z",
@@ -125,36 +118,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2025-01-15T10:44:25.008501Z",
      "start_time": "2025-01-15T10:43:57.932240Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Database deleted successfully.\n",
-      "Database deleted successfully.\n",
-      "User d3b51a32-38e1-4fe5-8270-6dc1d6ebfdf0 has registered.\n",
-      "Pipeline file_load_from_filesystem load step completed in 0.10 seconds\n",
-      "1 load package(s) were loaded to destination sqlalchemy and into dataset public\n",
-      "The sqlalchemy destination used postgresql://cognee:***@127.0.0.1:5432/cognee_db location to store data\n",
-      "Load package 1736937839.7739599 is LOADED and contains no failed jobs\n",
-      "Pipeline file_load_from_filesystem load step completed in 0.06 seconds\n",
-      "1 load package(s) were loaded to destination sqlalchemy and into dataset public\n",
-      "The sqlalchemy destination used postgresql://cognee:***@127.0.0.1:5432/cognee_db location to store data\n",
-      "Load package 1736937841.8467042 is LOADED and contains no failed jobs\n",
-      "Graph database initialized.\n",
-      "Added text: Kamala Harris is the Attorney Gener...\n",
-      "Added text: As AG, Harris was in office from Ja...\n",
-      "✅ Result Processed: <graphiti_core.graphiti.Graphiti object at 0x326fe0ce0>\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# 🔧 Setting Up Logging to Suppress Errors\n",
     "setup_logging(logging.ERROR)  # Keeping logs clean and focused\n",
@@ -202,15 +173,7 @@
      "start_time": "2025-01-15T10:44:25.013325Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "💡 Answer: Kamala Harris was in office as Attorney General of California from January 3, 2011, to January 3, 2017.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Step 1: Formulating the Query 🔍\n",
     "query = \"When was Kamala Harris in office?\"\n",
@@ -260,7 +223,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,
diff --git a/poetry.lock b/poetry.lock
index 39aadbcb5..18c6e3aed 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
 name = "aiofiles"
@@ -610,17 +610,17 @@ xyzservices = ">=2021.09.1"
 
 [[package]]
 name = "boto3"
-version = "1.36.18"
+version = "1.36.24"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.36.18-py3-none-any.whl", hash = "sha256:084ff25af2d7bda3102d6367f5453e2e83f8cde1da73079ea144595b03cb9400"},
-    {file = "boto3-1.36.18.tar.gz", hash = "sha256:be8e32c34d7b103a64fafdd277fa1ec136733b4bbfc11dcfa597efa36a820b37"},
+    {file = "boto3-1.36.24-py3-none-any.whl", hash = "sha256:c9055fe6a33f79c43053c06db432092cfcf88f4b4181950f5ca8f2f0cb6abb87"},
+    {file = "boto3-1.36.24.tar.gz", hash = "sha256:777ec08a6fe0ad77fa0607b431542c51d2d2e4145fecd512bee9f383ee4184f2"},
 ]
 
 [package.dependencies]
-botocore = ">=1.36.18,<1.37.0"
+botocore = ">=1.36.24,<1.37.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.11.0,<0.12.0"
 
@@ -629,13 +629,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.36.18"
+version = "1.36.24"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.36.18-py3-none-any.whl", hash = "sha256:7898d109affd9231c555e71fda88308c1da2db8d39e83d33eb8cb40ebf1ba82f"},
-    {file = "botocore-1.36.18.tar.gz", hash = "sha256:ddadafe460e91f11677720a2fcc3ea09c4abb914de2b000da7ba46b4c97da3d7"},
+    {file = "botocore-1.36.24-py3-none-any.whl", hash = "sha256:b8b2ad60e6545aaef3a40163793c39555fcfd67fb081a38695018026c4f4db25"},
+    {file = "botocore-1.36.24.tar.gz", hash = "sha256:7d35ba92ccbed7aa7e1563b12bb339bde612d5f845c89bfdd79a6db8c26b9f2e"},
 ]
 
 [package.dependencies]
@@ -1411,6 +1411,17 @@ files = [
     {file = "dirtyjson-1.0.8.tar.gz", hash = "sha256:90ca4a18f3ff30ce849d100dcf4a003953c79d3a2348ef056f1d9c22231a25fd"},
 ]
 
+[[package]]
+name = "diskcache"
+version = "5.6.3"
+description = "Disk Cache -- Disk and file backed persistent cache."
+optional = true
+python-versions = ">=3"
+files = [
+    {file = "diskcache-5.6.3-py3-none-any.whl", hash = "sha256:5e31b2d5fbad117cc363ebaf6b689474db18a1f6438bc82358b024abd4c2ca19"},
+    {file = "diskcache-5.6.3.tar.gz", hash = "sha256:2c3a3fa2743d8535d832ec61c2054a1641f41775aa7c556758a109941e33e4fc"},
+]
+
 [[package]]
 name = "distlib"
 version = "0.3.9"
@@ -1435,13 +1446,13 @@ files = [
 
 [[package]]
 name = "dlt"
-version = "1.6.1"
+version = "1.7.0"
 description = "dlt is an open-source python-first scalable data loading library that does not require any backend to run."
 optional = false
 python-versions = "<3.14,>=3.9"
 files = [
-    {file = "dlt-1.6.1-py3-none-any.whl", hash = "sha256:30a2b9ac6d93f38289c85c305ab6f19cf50e6457d4891346260969d36b735e6b"},
-    {file = "dlt-1.6.1.tar.gz", hash = "sha256:df3afccf41c6ff028f7d1ba6b9c84e404b27d815c9c0623ba1b9f22990cf24c4"},
+    {file = "dlt-1.7.0-py3-none-any.whl", hash = "sha256:557bc636af801e3ad726ce876597c49c71b46de3ff96539e907c9140c6b5de94"},
+    {file = "dlt-1.7.0.tar.gz", hash = "sha256:9f4a47a703d2dd7a2542bbaac12f4d0ee3008c7b0af417ed2e1a7aa066966103"},
 ]
 
 [package.dependencies]
@@ -2139,13 +2150,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.160.0"
+version = "2.161.0"
 description = "Google API Client Library for Python"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "google_api_python_client-2.160.0-py2.py3-none-any.whl", hash = "sha256:63d61fb3e4cf3fb31a70a87f45567c22f6dfe87bbfa27252317e3e2c42900db4"},
-    {file = "google_api_python_client-2.160.0.tar.gz", hash = "sha256:a8ccafaecfa42d15d5b5c3134ced8de08380019717fc9fb1ed510ca58eca3b7e"},
+    {file = "google_api_python_client-2.161.0-py2.py3-none-any.whl", hash = "sha256:9476a5a4f200bae368140453df40f9cda36be53fa7d0e9a9aac4cdb859a26448"},
+    {file = "google_api_python_client-2.161.0.tar.gz", hash = "sha256:324c0cce73e9ea0a0d2afd5937e01b7c2d6a4d7e2579cdb6c384f9699d6c9f37"},
 ]
 
 [package.dependencies]
@@ -2219,13 +2230,13 @@ dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "py
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.66.0"
+version = "1.67.0"
 description = "Common protobufs used in Google APIs"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis_common_protos-1.66.0-py2.py3-none-any.whl", hash = "sha256:d7abcd75fabb2e0ec9f74466401f6c119a0b498e27370e9be4c94cb7e382b8ed"},
-    {file = "googleapis_common_protos-1.66.0.tar.gz", hash = "sha256:c3e7b33d15fdca5374cc0a7346dd92ffa847425cc4ea941d970f13680052ec8c"},
+    {file = "googleapis_common_protos-1.67.0-py2.py3-none-any.whl", hash = "sha256:579de760800d13616f51cf8be00c876f00a9f146d3e6510e19d1f4111758b741"},
+    {file = "googleapis_common_protos-1.67.0.tar.gz", hash = "sha256:21398025365f138be356d5923e9168737d94d46a72aefee4a6110a1f23463c86"},
 ]
 
 [package.dependencies]
@@ -2272,6 +2283,26 @@ test = ["flake8 (>=5.0)", "ipython", "mock", "mypy", "pandas-stubs", "pytest", "
 testai = ["numba (>=0.57.1)"]
 umap-learn = ["dirty-cat (==0.2.0)", "scikit-learn (>=1.0)", "umap-learn"]
 
+[[package]]
+name = "graphiti-core"
+version = "0.7.0"
+description = "A temporal graph building library"
+optional = true
+python-versions = "<4.0,>=3.10"
+files = [
+    {file = "graphiti_core-0.7.0-py3-none-any.whl", hash = "sha256:0bddaf9b319bcc99999008d0a8f1a1c92714ada4d02b6cd25228d33359a3ae88"},
+    {file = "graphiti_core-0.7.0.tar.gz", hash = "sha256:22f420e67d7cd471f486eea6b789b853c79d2a9f52c63b4ae23293a378283c1e"},
+]
+
+[package.dependencies]
+diskcache = ">=5.6.3,<6.0.0"
+neo4j = ">=5.23.0,<6.0.0"
+numpy = ">=1.0.0"
+openai = ">=1.53.0,<2.0.0"
+pydantic = ">=2.8.2,<3.0.0"
+python-dotenv = ">=1.0.1,<2.0.0"
+tenacity = "9.0.0"
+
 [[package]]
 name = "greenlet"
 version = "3.1.1"
@@ -2735,13 +2766,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.28.1"
+version = "0.29.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.28.1-py3-none-any.whl", hash = "sha256:aa6b9a3ffdae939b72c464dbb0d7f99f56e649b55c3d52406f49e0a5a620c0a7"},
-    {file = "huggingface_hub-0.28.1.tar.gz", hash = "sha256:893471090c98e3b6efbdfdacafe4052b20b84d59866fb6f54c33d9af18c303ae"},
+    {file = "huggingface_hub-0.29.0-py3-none-any.whl", hash = "sha256:c02daa0b6bafbdacb1320fdfd1dc7151d0940825c88c4ef89837fdb1f6ea0afe"},
+    {file = "huggingface_hub-0.29.0.tar.gz", hash = "sha256:64034c852be270cac16c5743fe1f659b14515a9de6342d6f42cbb2ede191fc80"},
 ]
 
 [package.dependencies]
@@ -2783,13 +2814,13 @@ pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_ve
 
 [[package]]
 name = "humanize"
-version = "4.11.0"
+version = "4.12.1"
 description = "Python humanize utilities"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "humanize-4.11.0-py3-none-any.whl", hash = "sha256:b53caaec8532bcb2fff70c8826f904c35943f8cecaca29d272d9df38092736c0"},
-    {file = "humanize-4.11.0.tar.gz", hash = "sha256:e66f36020a2d5a974c504bd2555cf770621dbdbb6d82f94a6857c0b1ea2608be"},
+    {file = "humanize-4.12.1-py3-none-any.whl", hash = "sha256:86014ca5c52675dffa1d404491952f1f5bf03b07c175a51891a343daebf01fea"},
+    {file = "humanize-4.12.1.tar.gz", hash = "sha256:1338ba97415c96556758a6e2f65977ed406dddf4620d4c6db9bbdfd07f0f1232"},
 ]
 
 [package.extras]
@@ -3647,13 +3678,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.35"
+version = "0.3.37"
 description = "Building applications with LLMs through composability"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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-    {file = "langchain_core-0.3.35.tar.gz", hash = "sha256:328688228ece259da734417d477994a69cf8202dea9ed4271f2d792e3575c6fc"},
+    {file = "langchain_core-0.3.37-py3-none-any.whl", hash = "sha256:8202fd6506ce139a3a1b1c4c3006216b1c7fffa40bdd1779f7d2c67f75eb5f79"},
+    {file = "langchain_core-0.3.37.tar.gz", hash = "sha256:cda8786e616caa2f68f7cc9e811b9b50e3b63fb2094333318b348e5961a7ea01"},
 ]
 
 [package.dependencies]
@@ -3670,17 +3701,17 @@ typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
-version = "0.3.5"
+version = "0.3.6"
 description = "An integration package connecting OpenAI and LangChain"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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+    {file = "langchain_openai-0.3.6-py3-none-any.whl", hash = "sha256:05f0869f6cc963e2ec9e2e54ea1038d9c2af784c67f0e217040dfc918b31649a"},
+    {file = "langchain_openai-0.3.6.tar.gz", hash = "sha256:7daf92e1cd98865ab5213ec5bec2cbd6c28f011e250714978b3a99c7e4fc88ce"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.34,<1.0.0"
+langchain-core = ">=0.3.35,<1.0.0"
 openai = ">=1.58.1,<2.0.0"
 tiktoken = ">=0.7,<1"
 
@@ -3714,13 +3745,13 @@ six = "*"
 
 [[package]]
 name = "langfuse"
-version = "2.59.2"
+version = "2.59.3"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -3792,13 +3823,13 @@ proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "
 
 [[package]]
 name = "llama-index-core"
-version = "0.12.17"
+version = "0.12.19"
 description = "Interface between LLMs and your data"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -4301,13 +4332,13 @@ opencv = ["opencv-python-headless (>=4.0.0)"]
 
 [[package]]
 name = "mistune"
-version = "3.1.1"
+version = "3.1.2"
 description = "A sane and fast Markdown parser with useful plugins and renderers"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4789,20 +4820,20 @@ files = [
 
 [[package]]
 name = "narwhals"
-version = "1.26.0"
+version = "1.27.1"
 description = "Extremely lightweight compatibility layer between dataframe libraries"
 optional = true
 python-versions = ">=3.8"
 files = [
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 [package.extras]
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 dask = ["dask[dataframe] (>=2024.8)"]
-dev = ["covdefaults", "hypothesis", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-randomly", "typing-extensions"]
+dev = ["covdefaults", "hypothesis", "mypy (>=1.15.0,<1.16.0)", "pandas-stubs", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-randomly", "typing-extensions"]
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 duckdb = ["duckdb (>=1.0)"]
 extra = ["scikit-learn"]
@@ -4812,6 +4843,8 @@ pandas = ["pandas (>=0.25.3)"]
 polars = ["polars (>=0.20.3)"]
 pyarrow = ["pyarrow (>=11.0.0)"]
 pyspark = ["pyspark (>=3.5.0)"]
+tests = ["covdefaults", "hypothesis", "pytest", "pytest-cov", "pytest-env", "pytest-randomly", "typing-extensions"]
+typing = ["mypy (>=1.15.0,<1.16.0)", "pandas-stubs", "typing-extensions"]
 
 [[package]]
 name = "nbclient"
@@ -5510,8 +5543,8 @@ files = [
 [package.dependencies]
 numpy = [
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-    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
     {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -5900,13 +5933,13 @@ tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "p
 
 [[package]]
 name = "posthog"
-version = "3.13.0"
+version = "3.14.1"
 description = "Integrate PostHog into any python application."
 optional = true
 python-versions = "*"
 files = [
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 [package.dependencies]
@@ -6098,32 +6131,25 @@ files = [
 
 [[package]]
 name = "psutil"
-version = "6.1.1"
-description = "Cross-platform lib for process and system monitoring in Python."
+version = "7.0.0"
+description = "Cross-platform lib for process and system monitoring in Python.  NOTE: the syntax of this script MUST be kept compatible with Python 2.7."
 optional = true
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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 ]
 
 [package.extras]
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+dev = ["abi3audit", "black (==24.10.0)", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest", "pytest-cov", "pytest-xdist", "requests", "rstcheck", "ruff", "setuptools", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "vulture", "wheel"]
 test = ["pytest", "pytest-xdist", "setuptools"]
 
 [[package]]
@@ -6190,117 +6216,127 @@ bcrypt = ["bcrypt (>=4.1.2,<5)"]
 
 [[package]]
 name = "py-rust-stemmers"
-version = "0.1.3"
+version = "0.1.5"
 description = "Fast and parallel snowball stemmer"
 optional = true
 python-versions = "*"
 files = [
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+version = "2.22.0"
 description = "Python client for Sentry (https://sentry.io)"
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 sqlalchemy = ["sqlalchemy (>=1.2)"]
 starlette = ["starlette (>=0.19.1)"]
 starlite = ["starlite (>=1.48)"]
+statsig = ["statsig (>=0.55.3)"]
 tornado = ["tornado (>=6)"]
 unleash = ["UnleashClient (>=6.0.1)"]
 
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+dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "av", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
 dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.21,<0.22)", "urllib3 (<2.0.0)"]
 dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "beautifulsoup4", "codecarbon (>=2.8.1)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "libcst", "librosa", "nltk (<=3.8.1)", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-asyncio", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=1.0.11)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
@@ -8769,8 +8812,8 @@ tokenizers = ["tokenizers (>=0.21,<0.22)"]
 torch = ["accelerate (>=0.26.0)", "torch (>=2.0)"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.24.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"]
-video = ["av (==9.2.0)"]
+torchhub = ["filelock", "huggingface-hub (>=0.26.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.21,<0.22)", "torch (>=2.0)", "tqdm (>=4.27)"]
+video = ["av"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
 [[package]]
@@ -9023,13 +9066,13 @@ files = [
 
 [[package]]
 name = "unstructured"
-version = "0.16.20"
+version = "0.16.21"
 description = "A library that prepares raw documents for downstream ML tasks."
 optional = true
 python-versions = ">=3.9.0"
 files = [
-    {file = "unstructured-0.16.20-py3-none-any.whl", hash = "sha256:9749f4310dde0973f4732ee68f9e98d4a673bb06e455e98bc9522027a99c77cd"},
-    {file = "unstructured-0.16.20.tar.gz", hash = "sha256:95e8b604fae908cfd53b5bf05c4683e0041aa6c914627bb0226edb4530bbfa44"},
+    {file = "unstructured-0.16.21-py3-none-any.whl", hash = "sha256:c17e86bc934672838f3ed38c1b21ed6ff4c336e4931603110766f206cec03de0"},
+    {file = "unstructured-0.16.21.tar.gz", hash = "sha256:31d5e213389ed0d4fa2ebb70b53bb15f4116e97f7c28be40590589b7e4a1e225"},
 ]
 
 [package.dependencies]
@@ -9064,19 +9107,19 @@ wrapt = "*"
 xlrd = {version = "*", optional = true, markers = "extra == \"xlsx\""}
 
 [package.extras]
-all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.7)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 csv = ["pandas"]
 doc = ["python-docx (>=1.1.2)"]
 docx = ["python-docx (>=1.1.2)"]
 epub = ["pypandoc"]
 huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"]
-image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)"]
-local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
+image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.7)", "unstructured.pytesseract (>=0.3.12)"]
+local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.7)", "unstructured.pytesseract (>=0.3.12)", "xlrd"]
 md = ["markdown"]
 odt = ["pypandoc", "python-docx (>=1.1.2)"]
 org = ["pypandoc"]
 paddleocr = ["paddlepaddle (==3.0.0b1)", "unstructured.paddleocr (==2.8.1.0)"]
-pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)"]
+pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.7)", "unstructured.pytesseract (>=0.3.12)"]
 ppt = ["python-pptx (>=1.0.1)"]
 pptx = ["python-pptx (>=1.0.1)"]
 rst = ["pypandoc"]
@@ -9744,6 +9787,7 @@ evals = ["gdown", "plotly"]
 falkordb = ["falkordb"]
 filesystem = ["botocore"]
 gemini = ["google-generativeai"]
+graphiti = ["graphiti-core"]
 groq = ["groq"]
 gui = ["pyside6", "qasync"]
 huggingface = ["transformers"]
@@ -9761,4 +9805,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10.0,<3.13"
-content-hash = "d384b6028d84b344b40b6c7e047d592700227409aa3a4d961e157cd824fa50b5"
+content-hash = "a4770f156e1b097f3a71e847cbd5d16865e0733b3395b15df4127d90d728de4a"
diff --git a/pyproject.toml b/pyproject.toml
index 122c51737..1744ccbea 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -86,6 +86,7 @@ plotly = {version = "^6.0.0", optional = true}
 gdown = {version = "^5.2.0", optional = true}
 pyside6 = {version = "^6.8.2.1", optional = true}
 qasync = {version = "^0.27.1", optional = true}
+graphiti-core = {version = "^0.7.0", optional = true}
 
 
 [tool.poetry.extras]
@@ -109,6 +110,7 @@ docs = ["unstructured"]
 codegraph = ["fastembed", "tree-sitter", "tree-sitter-python"]
 evals = ["plotly", "gdown"]
 gui = ["pyside6", "qasync"]
+graphiti = ["graphiti-core"]
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.0"