From 00dd3b8d974dac4d03396332fe7dd6cf3ad34238 Mon Sep 17 00:00:00 2001
From: Boris Arzentar <borisarzentar@gmail.com>
Date: Fri, 4 Jul 2025 15:28:05 +0200
Subject: [PATCH] fix: run cognee distributed with modal

---
 cognee/api/v1/add/add.py                      |   2 +-
 .../databases/graph/neo4j_driver/adapter.py   |  16 +-
 .../infrastructure/databases/graph/utils.py   |  19 +++
 .../vector/pgvector/PGVectorAdapter.py        |  39 +++--
 .../files/utils/get_file_metadata.py          |  12 +-
 .../files/utils/guess_file_type.py            |   2 +-
 cognee/infrastructure/utils/run_sync.py       |  25 +++
 cognee/modules/ingestion/classify.py          |  10 --
 .../modules/pipelines/operations/pipeline.py  |   2 +-
 .../modules/pipelines/operations/run_tasks.py |  73 +++------
 .../operations/run_tasks_distributed.py       | 119 +++++++++++++++
 .../operations/run_tasks_with_telemetry.py    |  60 ++++++++
 .../methods/give_permission_on_dataset.py     |  15 +-
 cognee/tasks/ingestion/ingest_data.py         |  54 +------
 distributed/Dockerfile                        |   5 +-
 distributed/entrypoint.py                     | 144 +++---------------
 distributed/models/TextDocument.py            |  15 --
 distributed/tasks/extract_graph_from_data.py  |  41 -----
 distributed/tasks/queued_add_edges.py         |  12 ++
 distributed/tasks/queued_add_nodes.py         |  12 ++
 distributed/tasks/save_data_points.py         | 116 --------------
 distributed/tasks/summarize_text.py           |  88 -----------
 .../workers/data_point_saver_worker.py        |  25 ++-
 .../workers/graph_extraction_worker.py        |  42 -----
 poetry.lock                                   |  31 ++--
 pyproject.toml                                |   2 +-
 uv.lock                                       |  59 ++++---
 27 files changed, 431 insertions(+), 609 deletions(-)
 create mode 100644 cognee/infrastructure/databases/graph/utils.py
 create mode 100644 cognee/infrastructure/utils/run_sync.py
 create mode 100644 cognee/modules/pipelines/operations/run_tasks_distributed.py
 create mode 100644 cognee/modules/pipelines/operations/run_tasks_with_telemetry.py
 delete mode 100644 distributed/models/TextDocument.py
 delete mode 100644 distributed/tasks/extract_graph_from_data.py
 create mode 100644 distributed/tasks/queued_add_edges.py
 create mode 100644 distributed/tasks/queued_add_nodes.py
 delete mode 100644 distributed/tasks/save_data_points.py
 delete mode 100644 distributed/tasks/summarize_text.py
 delete mode 100644 distributed/workers/graph_extraction_worker.py

diff --git a/cognee/api/v1/add/add.py b/cognee/api/v1/add/add.py
index e1dafce5f..8f987743f 100644
--- a/cognee/api/v1/add/add.py
+++ b/cognee/api/v1/add/add.py
@@ -17,7 +17,7 @@ async def add(
     dataset_id: UUID = None,
 ):
     tasks = [
-        Task(resolve_data_directories),
+        Task(resolve_data_directories, include_subdirectories=True),
         Task(ingest_data, dataset_name, user, node_set, dataset_id),
     ]
 
diff --git a/cognee/infrastructure/databases/graph/neo4j_driver/adapter.py b/cognee/infrastructure/databases/graph/neo4j_driver/adapter.py
index e8bf6373f..74cae62eb 100644
--- a/cognee/infrastructure/databases/graph/neo4j_driver/adapter.py
+++ b/cognee/infrastructure/databases/graph/neo4j_driver/adapter.py
@@ -1,21 +1,27 @@
 """Neo4j Adapter for Graph Database"""
 
 import json
-from cognee.shared.logging_utils import get_logger, ERROR
 import asyncio
-from textwrap import dedent
-from typing import Optional, Any, List, Dict, Type, Tuple
-from contextlib import asynccontextmanager
 from uuid import UUID
+from textwrap import dedent
 from neo4j import AsyncSession
 from neo4j import AsyncGraphDatabase
 from neo4j.exceptions import Neo4jError
+from contextlib import asynccontextmanager
+from typing import Optional, Any, List, Dict, Type, Tuple
+
 from cognee.infrastructure.engine import DataPoint
+from cognee.shared.logging_utils import get_logger, ERROR
+from cognee.infrastructure.databases.graph.utils import override_distributed
 from cognee.infrastructure.databases.graph.graph_db_interface import (
     GraphDBInterface,
     record_graph_changes,
 )
 from cognee.modules.storage.utils import JSONEncoder
+
+from distributed.tasks.queued_add_nodes import queued_add_nodes
+from distributed.tasks.queued_add_edges import queued_add_edges
+
 from .neo4j_metrics_utils import (
     get_avg_clustering,
     get_edge_density,
@@ -166,6 +172,7 @@ class Neo4jAdapter(GraphDBInterface):
         return await self.query(query, params)
 
     @record_graph_changes
+    @override_distributed(queued_add_nodes)
     async def add_nodes(self, nodes: list[DataPoint]) -> None:
         """
         Add multiple nodes to the database in a single query.
@@ -404,6 +411,7 @@ class Neo4jAdapter(GraphDBInterface):
         return await self.query(query, params)
 
     @record_graph_changes
+    @override_distributed(queued_add_edges)
     async def add_edges(self, edges: list[tuple[str, str, str, dict[str, Any]]]) -> None:
         """
         Add multiple edges between nodes in a single query.
diff --git a/cognee/infrastructure/databases/graph/utils.py b/cognee/infrastructure/databases/graph/utils.py
new file mode 100644
index 000000000..2a6872655
--- /dev/null
+++ b/cognee/infrastructure/databases/graph/utils.py
@@ -0,0 +1,19 @@
+import os
+from functools import wraps
+
+
+def override_distributed(new_func):
+    def decorator(func):
+        @wraps(func)
+        async def wrapper(self, *args, distributed=None, **kwargs):
+            default_distributed_value = os.getenv("COGNEE_DISTRIBUTED", "False").lower() == "true"
+            distributed = default_distributed_value if distributed is None else distributed
+
+            if distributed:
+                return await new_func(*args, **kwargs)
+            else:
+                return await func(self, *args, **kwargs)
+
+        return wrapper
+
+    return decorator
diff --git a/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py b/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
index c512b6ccc..f22e287c2 100644
--- a/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
+++ b/cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py
@@ -1,10 +1,14 @@
 import asyncio
 from uuid import UUID, uuid4
-from typing import List, Optional, get_type_hints
+from sqlalchemy.inspection import inspect
+from typing import List, Optional, Union, get_type_hints
 
 from sqlalchemy.orm import Mapped, mapped_column
-from sqlalchemy import JSON, Column, Table, select, delete, MetaData, text
+from sqlalchemy.dialects.postgresql import insert
+from asyncpg import DeadlockDetectedError, DuplicateTableError, UniqueViolationError
+from sqlalchemy import JSON, Column, Table, select, delete, MetaData
 from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker
+from tenacity import retry, retry_if_exception_type, stop_after_attempt
 
 from cognee.exceptions import InvalidValueError
 from cognee.shared.logging_utils import get_logger
@@ -107,6 +111,11 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
             else:
                 return False
 
+    @retry(
+        retry=retry_if_exception_type(Union[DuplicateTableError, UniqueViolationError]),
+        stop=stop_after_attempt(3),
+        sleep=1,
+    )
     async def create_collection(self, collection_name: str, payload_schema=None):
         data_point_types = get_type_hints(DataPoint)
         vector_size = self.embedding_engine.get_vector_size()
@@ -123,7 +132,6 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                 - __init__(self, id, payload, vector): Initializes a new PGVectorDataPoint instance.
 
                 Instance variables:
-                - primary_key: Unique identifier for the data point, generated by uuid4.
                 - id: Identifier for the data point, defined by data_point_types.
                 - payload: JSON data associated with the data point.
                 - vector: Vector representation of the data point, with size defined by vector_size.
@@ -132,8 +140,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                 __tablename__ = collection_name
                 __table_args__ = {"extend_existing": True}
                 # PGVector requires one column to be the primary key
-                primary_key: Mapped[UUID] = mapped_column(primary_key=True, default=uuid4)
-                id: Mapped[data_point_types["id"]]
+                id: Mapped[data_point_types["id"]] = mapped_column(primary_key=True)
                 payload = Column(JSON)
                 vector = Column(self.Vector(vector_size))
 
@@ -148,6 +155,11 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                         Base.metadata.create_all, tables=[PGVectorDataPoint.__table__]
                     )
 
+    @retry(
+        retry=retry_if_exception_type(DeadlockDetectedError),
+        stop=stop_after_attempt(3),
+        sleep=1,
+    )
     async def create_data_points(self, collection_name: str, data_points: List[DataPoint]):
         data_point_types = get_type_hints(DataPoint)
         if not await self.has_collection(collection_name):
@@ -168,7 +180,6 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
             the SQLAlchemy ORM.
 
             It contains the following public instance variables:
-            - primary_key: The primary key of the data point, generated automatically.
             - id: An identifier for the data point.
             - payload: A JSON object containing additional data related to the data point.
             - vector: A vector representation of the data point, configured to the specified size.
@@ -177,8 +188,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
             __tablename__ = collection_name
             __table_args__ = {"extend_existing": True}
             # PGVector requires one column to be the primary key
-            primary_key: Mapped[UUID] = mapped_column(primary_key=True, default=uuid4)
-            id: Mapped[data_point_types["id"]]
+            id: Mapped[data_point_types["id"]] = mapped_column(primary_key=True)
             payload = Column(JSON)
             vector = Column(self.Vector(vector_size))
 
@@ -213,7 +223,18 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                         )
                     )
 
-            session.add_all(pgvector_data_points)
+            def to_dict(obj):
+                return {
+                    column.key: getattr(obj, column.key)
+                    for column in inspect(obj).mapper.column_attrs
+                }
+
+            # session.add_all(pgvector_data_points)
+            insert_statement = insert(PGVectorDataPoint).values(
+                [to_dict(data_point) for data_point in pgvector_data_points]
+            )
+            insert_statement = insert_statement.on_conflict_do_nothing(index_elements=["id"])
+            await session.execute(insert_statement)
             await session.commit()
 
     async def create_vector_index(self, index_name: str, index_property_name: str):
diff --git a/cognee/infrastructure/files/utils/get_file_metadata.py b/cognee/infrastructure/files/utils/get_file_metadata.py
index e683fbee3..2742e3454 100644
--- a/cognee/infrastructure/files/utils/get_file_metadata.py
+++ b/cognee/infrastructure/files/utils/get_file_metadata.py
@@ -1,3 +1,4 @@
+import io
 from typing import BinaryIO, TypedDict
 from .guess_file_type import guess_file_type
 from cognee.shared.utils import get_file_content_hash
@@ -38,9 +39,14 @@ def get_file_metadata(file: BinaryIO) -> FileMetadata:
         - FileMetadata: A dictionary containing the file's name, path, MIME type, file
           extension, and content hash.
     """
-    file.seek(0)
-    content_hash = get_file_content_hash(file)
-    file.seek(0)
+    try:
+        file.seek(0)
+        content_hash = get_file_content_hash(file)
+        file.seek(0)
+    except io.UnsupportedOperation as error:
+        raise Exception(
+            f"Error retrieving metadata from file: {file.name} \n{str(error)}\n\n"
+        ) from error
 
     file_type = guess_file_type(file)
 
diff --git a/cognee/infrastructure/files/utils/guess_file_type.py b/cognee/infrastructure/files/utils/guess_file_type.py
index 7daa954ea..e7fa2a80f 100644
--- a/cognee/infrastructure/files/utils/guess_file_type.py
+++ b/cognee/infrastructure/files/utils/guess_file_type.py
@@ -125,6 +125,6 @@ def guess_file_type(file: BinaryIO) -> filetype.Type:
     file_type = filetype.guess(file)
 
     if file_type is None:
-        raise FileTypeException("Unknown file detected.")
+        raise FileTypeException(f"Unknown file detected: {file.name}.")
 
     return file_type
diff --git a/cognee/infrastructure/utils/run_sync.py b/cognee/infrastructure/utils/run_sync.py
new file mode 100644
index 000000000..4945b0b98
--- /dev/null
+++ b/cognee/infrastructure/utils/run_sync.py
@@ -0,0 +1,25 @@
+import asyncio
+import threading
+
+
+def run_sync(coro, timeout=None):
+    result = None
+    exception = None
+
+    def runner():
+        nonlocal result, exception
+        try:
+            result = asyncio.run(coro)
+        except Exception as e:
+            exception = e
+
+    thread = threading.Thread(target=runner)
+    thread.start()
+    thread.join(timeout)
+
+    if thread.is_alive():
+        raise asyncio.TimeoutError("Coroutine execution timed out.")
+    if exception:
+        raise exception
+
+    return result
diff --git a/cognee/modules/ingestion/classify.py b/cognee/modules/ingestion/classify.py
index d1650e5dc..44f1cf013 100644
--- a/cognee/modules/ingestion/classify.py
+++ b/cognee/modules/ingestion/classify.py
@@ -20,17 +20,7 @@ def classify(data: Union[str, BinaryIO], filename: str = None, s3fs: Optional[An
     if isinstance(data, BufferedReader) or isinstance(data, SpooledTemporaryFile):
         return BinaryData(data, str(data.name).split("/")[-1] if data.name else filename)
 
-    try:
-        from importlib import import_module
-
-        s3core = import_module("s3fs.core")
-        S3File = s3core.S3File
-    except ImportError:
-        S3File = None
-
     if S3File is not None:
-        from cognee.modules.ingestion.data_types.S3BinaryData import S3BinaryData
-
         if isinstance(data, S3File):
             derived_filename = str(data.full_name).split("/")[-1] if data.full_name else filename
             return S3BinaryData(s3_path=data.full_name, name=derived_filename, s3=s3fs)
diff --git a/cognee/modules/pipelines/operations/pipeline.py b/cognee/modules/pipelines/operations/pipeline.py
index ab2ccef67..8ffe33a8a 100644
--- a/cognee/modules/pipelines/operations/pipeline.py
+++ b/cognee/modules/pipelines/operations/pipeline.py
@@ -184,7 +184,7 @@ async def run_pipeline(
         if not isinstance(task, Task):
             raise ValueError(f"Task {task} is not an instance of Task")
 
-    pipeline_run = run_tasks(tasks, dataset_id, data, user, pipeline_name, context=context)
+    pipeline_run = run_tasks(tasks, dataset_id, data, user, pipeline_name, context)
 
     async for pipeline_run_info in pipeline_run:
         yield pipeline_run_info
diff --git a/cognee/modules/pipelines/operations/run_tasks.py b/cognee/modules/pipelines/operations/run_tasks.py
index 93171a556..45f5a75d8 100644
--- a/cognee/modules/pipelines/operations/run_tasks.py
+++ b/cognee/modules/pipelines/operations/run_tasks.py
@@ -1,8 +1,11 @@
-import json
+import os
+from uuid import UUID
 from typing import Any
-from uuid import UUID, uuid4
+from functools import wraps
 
 from cognee.infrastructure.databases.relational import get_relational_engine
+from cognee.modules.pipelines.operations.run_tasks_distributed import run_tasks_distributed
+from cognee.modules.users.models import User
 from cognee.shared.logging_utils import get_logger
 from cognee.modules.users.methods import get_default_user
 from cognee.modules.pipelines.utils import generate_pipeline_id
@@ -18,64 +21,34 @@ from cognee.modules.pipelines.operations import (
     log_pipeline_run_complete,
     log_pipeline_run_error,
 )
-from cognee.modules.settings import get_current_settings
-from cognee.modules.users.models import User
-from cognee.shared.utils import send_telemetry
-
-from .run_tasks_base import run_tasks_base
+from .run_tasks_with_telemetry import run_tasks_with_telemetry
 from ..tasks.task import Task
 
+
 logger = get_logger("run_tasks(tasks: [Task], data)")
 
 
-async def run_tasks_with_telemetry(
-    tasks: list[Task], data, user: User, pipeline_name: str, context: dict = None
-):
-    config = get_current_settings()
+def override_run_tasks(new_gen):
+    def decorator(original_gen):
+        @wraps(original_gen)
+        async def wrapper(*args, distributed=None, **kwargs):
+            default_distributed_value = os.getenv("COGNEE_DISTRIBUTED", "False").lower() == "true"
+            distributed = default_distributed_value if distributed is None else distributed
 
-    logger.debug("\nRunning pipeline with configuration:\n%s\n", json.dumps(config, indent=1))
+            print(f"run_tasks_distributed: {distributed}")
+            if distributed:
+                async for run_info in new_gen(*args, **kwargs):
+                    yield run_info
+            else:
+                async for run_info in original_gen(*args, **kwargs):
+                    yield run_info
 
-    try:
-        logger.info("Pipeline run started: `%s`", pipeline_name)
-        send_telemetry(
-            "Pipeline Run Started",
-            user.id,
-            additional_properties={
-                "pipeline_name": str(pipeline_name),
-            }
-            | config,
-        )
+        return wrapper
 
-        async for result in run_tasks_base(tasks, data, user, context):
-            yield result
-
-        logger.info("Pipeline run completed: `%s`", pipeline_name)
-        send_telemetry(
-            "Pipeline Run Completed",
-            user.id,
-            additional_properties={
-                "pipeline_name": str(pipeline_name),
-            },
-        )
-    except Exception as error:
-        logger.error(
-            "Pipeline run errored: `%s`\n%s\n",
-            pipeline_name,
-            str(error),
-            exc_info=True,
-        )
-        send_telemetry(
-            "Pipeline Run Errored",
-            user.id,
-            additional_properties={
-                "pipeline_name": str(pipeline_name),
-            }
-            | config,
-        )
-
-        raise error
+    return decorator
 
 
+@override_run_tasks(run_tasks_distributed)
 async def run_tasks(
     tasks: list[Task],
     dataset_id: UUID,
diff --git a/cognee/modules/pipelines/operations/run_tasks_distributed.py b/cognee/modules/pipelines/operations/run_tasks_distributed.py
new file mode 100644
index 000000000..012f52233
--- /dev/null
+++ b/cognee/modules/pipelines/operations/run_tasks_distributed.py
@@ -0,0 +1,119 @@
+try:
+    import modal
+except ModuleNotFoundError:
+    modal = None
+
+from cognee.infrastructure.databases.relational import get_relational_engine
+from cognee.modules.pipelines.models import (
+    PipelineRunStarted,
+    PipelineRunYield,
+    PipelineRunCompleted,
+)
+from cognee.modules.pipelines.operations import log_pipeline_run_start, log_pipeline_run_complete
+from cognee.modules.pipelines.utils.generate_pipeline_id import generate_pipeline_id
+from cognee.modules.users.methods import get_default_user
+from cognee.shared.logging_utils import get_logger
+
+from .run_tasks_with_telemetry import run_tasks_with_telemetry
+
+
+logger = get_logger("run_tasks_distributed()")
+
+
+if modal:
+    from distributed.app import app
+    from distributed.modal_image import image
+
+    @app.function(
+        image=image,
+        timeout=86400,
+        max_containers=100,
+        secrets=[modal.Secret.from_name("distributed_cognee")],
+    )
+    async def run_tasks_on_modal(tasks, data_item, user, pipeline_name, context):
+        pipeline_run = run_tasks_with_telemetry(tasks, data_item, user, pipeline_name, context)
+
+        run_info = None
+
+        async for pipeline_run_info in pipeline_run:
+            run_info = pipeline_run_info
+
+        return run_info
+
+
+async def run_tasks_distributed(tasks, dataset_id, data, user, pipeline_name, context):
+    if not user:
+        user = get_default_user()
+
+    db_engine = get_relational_engine()
+    async with db_engine.get_async_session() as session:
+        from cognee.modules.data.models import Dataset
+
+        dataset = await session.get(Dataset, dataset_id)
+
+    pipeline_id = generate_pipeline_id(user.id, dataset.id, pipeline_name)
+
+    pipeline_run = await log_pipeline_run_start(pipeline_id, pipeline_name, dataset_id, data)
+
+    pipeline_run_id = pipeline_run.pipeline_run_id
+
+    yield PipelineRunStarted(
+        pipeline_run_id=pipeline_run_id,
+        dataset_id=dataset.id,
+        dataset_name=dataset.name,
+        payload=data,
+    )
+
+    data_count = len(data) if isinstance(data, list) else 1
+
+    print(f"Data count: {data_count}")
+    print(f"Data item to process: {type(data)} - {data}")
+
+    arguments = [
+        [tasks] * data_count,
+        [[data_item] for data_item in data[:data_count]] if data_count > 1 else [data],
+        [user] * data_count,
+        [pipeline_name] * data_count,
+        [context] * data_count,
+    ]
+
+    async for result in run_tasks_on_modal.map.aio(*arguments):
+        logger.info(f"Received result: {result}")
+
+        yield PipelineRunYield(
+            pipeline_run_id=pipeline_run_id,
+            dataset_id=dataset.id,
+            dataset_name=dataset.name,
+            payload=result,
+        )
+
+    # producer_futures = []
+
+    # for data_item in data[:5]:
+    #     producer_future = run_tasks_distributed(
+    #         run_tasks_with_telemetry, tasks, [data_item], user, pipeline_name, context
+    #     )
+    #     producer_futures.append(producer_future)
+
+    # batch_results = []
+    # for producer_future in producer_futures:
+    #     try:
+    #         result = producer_future.get()
+    #     except Exception as e:
+    #         result = e
+    #     batch_results.append(result)
+
+    # yield PipelineRunYield(
+    #     pipeline_run_id=pipeline_run_id,
+    #     dataset_id=dataset.id,
+    #     dataset_name=dataset.name,
+    #     payload=result,
+    # )
+
+    await log_pipeline_run_complete(pipeline_run_id, pipeline_id, pipeline_name, dataset_id, data)
+
+    yield PipelineRunCompleted(
+        pipeline_run_id=pipeline_run_id,
+        dataset_id=dataset.id,
+        dataset_name=dataset.name,
+    )
diff --git a/cognee/modules/pipelines/operations/run_tasks_with_telemetry.py b/cognee/modules/pipelines/operations/run_tasks_with_telemetry.py
new file mode 100644
index 000000000..a2af18be6
--- /dev/null
+++ b/cognee/modules/pipelines/operations/run_tasks_with_telemetry.py
@@ -0,0 +1,60 @@
+import json
+
+from cognee.modules.settings import get_current_settings
+from cognee.modules.users.models import User
+from cognee.shared.logging_utils import get_logger
+from cognee.shared.utils import send_telemetry
+
+from .run_tasks_base import run_tasks_base
+from ..tasks.task import Task
+
+
+logger = get_logger("run_tasks_with_telemetry()")
+
+
+async def run_tasks_with_telemetry(
+    tasks: list[Task], data, user: User, pipeline_name: str, context: dict = None
+):
+    config = get_current_settings()
+
+    logger.debug("\nRunning pipeline with configuration:\n%s\n", json.dumps(config, indent=1))
+
+    try:
+        logger.info("Pipeline run started: `%s`", pipeline_name)
+        send_telemetry(
+            "Pipeline Run Started",
+            user.id,
+            additional_properties={
+                "pipeline_name": str(pipeline_name),
+            }
+            | config,
+        )
+
+        async for result in run_tasks_base(tasks, data, user, context):
+            yield result
+
+        logger.info("Pipeline run completed: `%s`", pipeline_name)
+        send_telemetry(
+            "Pipeline Run Completed",
+            user.id,
+            additional_properties={
+                "pipeline_name": str(pipeline_name),
+            },
+        )
+    except Exception as error:
+        logger.error(
+            "Pipeline run errored: `%s`\n%s\n",
+            pipeline_name,
+            str(error),
+            exc_info=True,
+        )
+        send_telemetry(
+            "Pipeline Run Errored",
+            user.id,
+            additional_properties={
+                "pipeline_name": str(pipeline_name),
+            }
+            | config,
+        )
+
+        raise error
diff --git a/cognee/modules/users/permissions/methods/give_permission_on_dataset.py b/cognee/modules/users/permissions/methods/give_permission_on_dataset.py
index afa8ef5b5..daa6aae6c 100644
--- a/cognee/modules/users/permissions/methods/give_permission_on_dataset.py
+++ b/cognee/modules/users/permissions/methods/give_permission_on_dataset.py
@@ -1,11 +1,20 @@
-from sqlalchemy.future import select
-from cognee.infrastructure.databases.relational import get_relational_engine
-from ...models import Principal, ACL, Permission
 from uuid import UUID
+from sqlalchemy.future import select
+from asyncpg import UniqueViolationError
+from tenacity import retry, retry_if_exception_type, stop_after_attempt
+
+from cognee.infrastructure.databases.relational import get_relational_engine
 from cognee.modules.users.permissions import PERMISSION_TYPES
 from cognee.modules.users.exceptions import PermissionNotFoundError
 
+from ...models import Principal, ACL, Permission
 
+
+@retry(
+    retry=retry_if_exception_type(UniqueViolationError),
+    stop=stop_after_attempt(3),
+    sleep=1,
+)
 async def give_permission_on_dataset(
     principal: Principal,
     dataset_id: UUID,
diff --git a/cognee/tasks/ingestion/ingest_data.py b/cognee/tasks/ingestion/ingest_data.py
index 1e6181df2..9fd45434a 100644
--- a/cognee/tasks/ingestion/ingest_data.py
+++ b/cognee/tasks/ingestion/ingest_data.py
@@ -1,4 +1,3 @@
-import dlt
 import json
 import inspect
 from uuid import UUID
@@ -11,7 +10,6 @@ from cognee.modules.data.models.DatasetData import DatasetData
 from cognee.modules.users.models import User
 from cognee.modules.users.permissions.methods import give_permission_on_dataset
 from cognee.modules.users.permissions.methods import get_specific_user_permission_datasets
-from .get_dlt_destination import get_dlt_destination
 from .save_data_item_to_storage import save_data_item_to_storage
 
 
@@ -25,16 +23,9 @@ async def ingest_data(
     node_set: Optional[List[str]] = None,
     dataset_id: UUID = None,
 ):
-    destination = get_dlt_destination()
-
     if not user:
         user = await get_default_user()
 
-    pipeline = dlt.pipeline(
-        pipeline_name="metadata_extraction_pipeline",
-        destination=destination,
-    )
-
     s3_config = get_s3_config()
 
     fs = None
@@ -58,27 +49,6 @@ async def ingest_data(
         else:
             return {}
 
-    @dlt.resource(standalone=True, primary_key="id", merge_key="id")
-    async def data_resources(file_paths: List[str], user: User):
-        for file_path in file_paths:
-            with open_data_file(file_path) as file:
-                if file_path.startswith("s3://"):
-                    classified_data = ingestion.classify(file, s3fs=fs)
-                else:
-                    classified_data = ingestion.classify(file)
-                data_id = ingestion.identify(classified_data, user)
-                file_metadata = classified_data.get_metadata()
-                yield {
-                    "id": data_id,
-                    "name": file_metadata["name"],
-                    "file_path": file_metadata["file_path"],
-                    "extension": file_metadata["extension"],
-                    "mime_type": file_metadata["mime_type"],
-                    "content_hash": file_metadata["content_hash"],
-                    "owner_id": str(user.id),
-                    "node_set": json.dumps(node_set) if node_set else None,
-                }
-
     async def store_data_to_dataset(
         data: Any,
         dataset_name: str,
@@ -187,29 +157,7 @@ async def ingest_data(
 
         return file_paths
 
-    db_engine = get_relational_engine()
-
-    file_paths = await store_data_to_dataset(data, dataset_name, user, node_set, dataset_id)
-
-    # Note: DLT pipeline has its own event loop, therefore objects created in another event loop
-    # can't be used inside the pipeline
-    if db_engine.engine.dialect.name == "sqlite":
-        # To use sqlite with dlt dataset_name must be set to "main".
-        # Sqlite doesn't support schemas
-        pipeline.run(
-            data_resources(file_paths, user),
-            table_name="file_metadata",
-            dataset_name="main",
-            write_disposition="merge",
-        )
-    else:
-        # Data should be stored in the same schema to allow deduplication
-        pipeline.run(
-            data_resources(file_paths, user),
-            table_name="file_metadata",
-            dataset_name="public",
-            write_disposition="merge",
-        )
+    await store_data_to_dataset(data, dataset_name, user, node_set, dataset_id)
 
     datasets = await get_datasets_by_name(dataset_name, user.id)
 
diff --git a/distributed/Dockerfile b/distributed/Dockerfile
index efa3197e0..6ac818d45 100644
--- a/distributed/Dockerfile
+++ b/distributed/Dockerfile
@@ -1,4 +1,4 @@
-FROM python:3.12-bookworm-slim
+FROM python:3.11-slim
 
 # Set environment variables
 ENV PIP_NO_CACHE_DIR=true
@@ -6,6 +6,7 @@ ENV PATH="${PATH}:/root/.poetry/bin"
 ENV PYTHONPATH=/app
 ENV RUN_MODE=modal
 ENV SKIP_MIGRATIONS=true
+ENV COGNEE_DISTRIBUTED=true
 
 # System dependencies
 RUN apt-get update && apt-get install -y \
@@ -24,7 +25,7 @@ RUN pip install poetry
 
 RUN poetry config virtualenvs.create false
 
-RUN poetry install --extras neo4j --extras postgres --no-root
+RUN poetry install --extras neo4j --extras postgres --extras aws --extras distributed --no-root
 
 COPY cognee/ /app/cognee
 COPY distributed/ /app/distributed
diff --git a/distributed/entrypoint.py b/distributed/entrypoint.py
index 7124923f6..301867ea5 100644
--- a/distributed/entrypoint.py
+++ b/distributed/entrypoint.py
@@ -1,162 +1,50 @@
-import pathlib
-from os import path
+import asyncio
+import os
 
-# from cognee.api.v1.add import add
+import cognee
 from cognee.api.v1.prune import prune
-from cognee.infrastructure.databases.relational import get_relational_engine
-from cognee.infrastructure.llm.utils import get_max_chunk_tokens
-from cognee.modules.chunking.TextChunker import TextChunker
-from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
-from cognee.modules.data.models import Data
-from cognee.modules.data.processing.document_types import Document
-from cognee.modules.engine.operations.setup import setup
-from cognee.modules.ingestion.get_text_content_hash import get_text_content_hash
-from cognee.modules.pipelines.operations.run_tasks import run_tasks
-from cognee.modules.pipelines.tasks.task import Task
-from cognee.modules.users.methods.get_default_user import get_default_user
-# from cognee.modules.data.methods.get_dataset_data import get_dataset_data
-# from cognee.modules.data.methods.get_datasets_by_name import get_datasets_by_name
-
 from cognee.shared.logging_utils import get_logger
-from cognee.tasks.documents.extract_chunks_from_documents import extract_chunks_from_documents
+from cognee.modules.engine.operations.setup import setup
 
 from distributed.app import app
-from distributed.models.TextDocument import TextDocument
 from distributed.queues import save_data_points_queue
 from distributed.workers.data_point_saver_worker import data_point_saver_worker
-from distributed.workers.graph_extraction_worker import graph_extraction_worker
 
 logger = get_logger()
 
 
+os.environ["COGNEE_DISTRIBUTED"] = "True"
+
+
 @app.local_entrypoint()
 async def main():
     # Clear queues
-    save_data_points_queue.clear()
+    await save_data_points_queue.clear.aio()
 
-    # dataset_name = "main"
-    data_directory_name = ".data"
-    data_directory_path = path.join(pathlib.Path(__file__).parent, data_directory_name)
-
-    number_of_data_saving_workers = 1  # Total number of graph_extraction_worker functions to spawn
-    document_batch_size = 50  # Batch size for producers
+    number_of_data_saving_workers = 1  # Total number of data_point_saver_worker functions to spawn
 
     results = []
     consumer_futures = []
 
+    # await prune.prune_data()  # We don't want to delete files on s3
     # Delete DBs and saved files from metastore
-    await prune.prune_data()
     await prune.prune_system(metadata=True)
 
     await setup()
 
-    # Add files to the metastore
-    # await add(data=data_directory_path, dataset_name=dataset_name)
-
-    user = await get_default_user()
-    # datasets = await get_datasets_by_name(dataset_name, user.id)
-    # documents = await get_dataset_data(dataset_id=datasets[0].id)
-
-    import duckdb
-
-    connection = duckdb.connect()
-    dataset_file_name = "de-00000-of-00003-f8e581c008ccc7f2.parquet"
-    dataset_file_path = path.join(data_directory_path, dataset_file_name)
-    df = connection.execute(f"SELECT * FROM '{dataset_file_path}'").fetchdf()
-
-    documents = []
-
-    for _, row in df.iterrows():
-        file_id = str(row["id"])
-        content = row["text"]
-
-        documents.append(
-            TextDocument(
-                name=file_id,
-                content=content,
-                raw_data_location=f"{dataset_file_name}_{file_id}",
-                external_metadata="",
-            )
-        )
-
-    documents: list[TextDocument] = documents[0:100]
-    print(f"We have {len(documents)} documents in the dataset.")
-
-    data_documents = [
-        Data(
-            id=document.id,
-            name=document.name,
-            raw_data_location=document.raw_data_location,
-            extension="txt",
-            mime_type=document.mime_type,
-            owner_id=user.id,
-            content_hash=get_text_content_hash(document.content),
-            external_metadata=document.external_metadata,
-            node_set=None,
-            token_count=-1,
-        )
-        for document in documents
-    ]
-
-    db_engine = get_relational_engine()
-
-    async with db_engine.get_async_session() as session:
-        session.add_all(data_documents)
-        await session.commit()
-
     # Start data_point_saver_worker functions
     for _ in range(number_of_data_saving_workers):
         worker_future = data_point_saver_worker.spawn()
         consumer_futures.append(worker_future)
 
-    producer_futures = []
+    s3_bucket_name = "s3://s3-test-laszlo/Database for KG v1"
 
-    def process_chunks_remotely(document_chunks: list[DocumentChunk], document: Document):
-        producer_future = graph_extraction_worker.spawn(
-            user=user, document_name=document.name, document_chunks=document_chunks
-        )
-        producer_futures.append(producer_future)
-        return producer_future
+    await cognee.add(s3_bucket_name, dataset_name="s3-files")
 
-    # Produce chunks and spawn a graph_extraction_worker job for each batch of chunks
-    for i in range(0, len(documents), document_batch_size):
-        batch = documents[i : i + document_batch_size]
-
-        for item in batch:
-            async for worker_feature in run_tasks(
-                [
-                    Task(
-                        extract_chunks_from_documents,
-                        max_chunk_size=2000,
-                        chunker=TextChunker,
-                    ),
-                    Task(
-                        process_chunks_remotely,
-                        document=item,
-                        task_config={"batch_size": 10},
-                    ),
-                ],
-                data=[item],
-                user=user,
-                pipeline_name="chunk_processing",
-            ):
-                pass
-
-        batch_results = []
-
-        for producer_future in producer_futures:
-            try:
-                result = producer_future.get()
-            except Exception as e:
-                result = e
-
-            batch_results.append(result)
-
-        print(f"Number of documents processed: {len(results)}")
-        results.extend(batch_results)
+    await cognee.cognify(datasets=["s3-files"])
 
     # Push empty tuple into the queue to signal the end of data.
-    save_data_points_queue.put(())
+    await save_data_points_queue.put.aio(())
 
     for consumer_future in consumer_futures:
         try:
@@ -167,3 +55,7 @@ async def main():
             logger.error(e)
 
     print(results)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/distributed/models/TextDocument.py b/distributed/models/TextDocument.py
deleted file mode 100644
index 1603c70ef..000000000
--- a/distributed/models/TextDocument.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from cognee.modules.chunking.Chunker import Chunker
-from cognee.modules.data.processing.document_types import Document
-
-
-class TextDocument(Document):
-    type: str = "text"
-    mime_type: str = "text/plain"
-    content: str
-
-    def read(self, chunker_cls: Chunker, max_chunk_size: int):
-        def get_text():
-            yield self.content
-
-        chunker: Chunker = chunker_cls(self, max_chunk_size=max_chunk_size, get_text=get_text)
-        yield from chunker.read()
diff --git a/distributed/tasks/extract_graph_from_data.py b/distributed/tasks/extract_graph_from_data.py
deleted file mode 100644
index 6e4186cf1..000000000
--- a/distributed/tasks/extract_graph_from_data.py
+++ /dev/null
@@ -1,41 +0,0 @@
-import asyncio
-from typing import Type, List
-
-from pydantic import BaseModel
-
-from cognee.modules.graph.utils import (
-    expand_with_nodes_and_edges,
-    retrieve_existing_edges,
-)
-from cognee.shared.data_models import KnowledgeGraph
-from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
-from cognee.modules.ontology.rdf_xml.OntologyResolver import OntologyResolver
-from cognee.modules.data.extraction.knowledge_graph import extract_content_graph
-
-
-async def extract_graph_from_data(
-    data_chunks: list[DocumentChunk],
-    graph_model: Type[BaseModel],
-    ontology_adapter: OntologyResolver = OntologyResolver(),
-) -> List[DocumentChunk]:
-    """Extracts and integrates a knowledge graph from the text content of document chunks using a specified graph model."""
-    chunk_graphs = await asyncio.gather(
-        *[extract_content_graph(chunk.text, graph_model) for chunk in data_chunks]
-    )
-
-    if graph_model is not KnowledgeGraph:
-        for chunk_index, chunk_graph in enumerate(chunk_graphs):
-            data_chunks[chunk_index].contains = chunk_graph
-
-        return data_chunks
-
-    existing_edges_map = await retrieve_existing_edges(
-        data_chunks,
-        chunk_graphs,
-    )
-
-    graph_nodes, graph_edges = expand_with_nodes_and_edges(
-        data_chunks, chunk_graphs, ontology_adapter, existing_edges_map
-    )
-
-    return data_chunks, graph_nodes, graph_edges
diff --git a/distributed/tasks/queued_add_edges.py b/distributed/tasks/queued_add_edges.py
new file mode 100644
index 000000000..44a0c4530
--- /dev/null
+++ b/distributed/tasks/queued_add_edges.py
@@ -0,0 +1,12 @@
+async def queued_add_edges(edge_batch):
+    from ..queues import save_data_points_queue
+
+    try:
+        await save_data_points_queue.put.aio(([], edge_batch))
+    except Exception:
+        first_half, second_half = (
+            edge_batch[: len(edge_batch) // 2],
+            edge_batch[len(edge_batch) // 2 :],
+        )
+        await save_data_points_queue.put.aio(([], first_half))
+        await save_data_points_queue.put.aio(([], second_half))
diff --git a/distributed/tasks/queued_add_nodes.py b/distributed/tasks/queued_add_nodes.py
new file mode 100644
index 000000000..44278c734
--- /dev/null
+++ b/distributed/tasks/queued_add_nodes.py
@@ -0,0 +1,12 @@
+async def queued_add_nodes(node_batch):
+    from ..queues import save_data_points_queue
+
+    try:
+        await save_data_points_queue.put.aio((node_batch, []))
+    except Exception:
+        first_half, second_half = (
+            node_batch[: len(node_batch) // 2],
+            node_batch[len(node_batch) // 2 :],
+        )
+        await save_data_points_queue.put.aio((first_half, []))
+        await save_data_points_queue.put.aio((second_half, []))
diff --git a/distributed/tasks/save_data_points.py b/distributed/tasks/save_data_points.py
deleted file mode 100644
index 23039f6b6..000000000
--- a/distributed/tasks/save_data_points.py
+++ /dev/null
@@ -1,116 +0,0 @@
-# import json
-# import asyncio
-from pympler import asizeof
-
-# from cognee.modules.storage.utils import JSONEncoder
-from distributed.queues import save_data_points_queue
-# from cognee.modules.graph.utils import get_graph_from_model
-
-
-async def save_data_points(data_points_and_relationships: tuple[list, list]):
-    # data_points = data_points_and_relationships[0]
-    # data_point_connections = data_points_and_relationships[1]
-
-    # added_nodes = {}
-    # added_edges = {}
-    # visited_properties = {}
-
-    # nodes_and_edges: list[tuple] = await asyncio.gather(
-    #     *[
-    #         get_graph_from_model(
-    #             data_point,
-    #             added_nodes=added_nodes,
-    #             added_edges=added_edges,
-    #             visited_properties=visited_properties,
-    #         )
-    #         for data_point in data_points
-    #     ]
-    # )
-
-    # graph_data_deduplication = GraphDataDeduplication()
-    # deduplicated_nodes_and_edges = [graph_data_deduplication.deduplicate_nodes_and_edges(nodes, edges + data_point_connections) for nodes, edges in nodes_and_edges]
-
-    node_batch = []
-    edge_batch = []
-
-    for nodes, edges in data_points_and_relationships:
-        for node in nodes:
-            if asizeof.asizeof(node) >= 500000:
-                try_pushing_nodes_to_queue([node])
-                continue
-                # print(f"Node too large:\n{node.id}\n")
-
-            node_batch.append(node)
-
-            if asizeof.asizeof(node_batch) >= 500000:
-                try_pushing_nodes_to_queue(node_batch)
-                node_batch = []
-
-        if len(node_batch) > 0:
-            try_pushing_nodes_to_queue(node_batch)
-            node_batch = []
-
-        for edge in edges:
-            edge_batch.append(edge)
-
-            if asizeof.asizeof(edge_batch) >= 500000:
-                try_pushing_edges_to_queue(edge_batch)
-                edge_batch = []
-
-        if len(edge_batch) > 0:
-            try_pushing_edges_to_queue(edge_batch)
-            edge_batch = []
-
-    # graph_data_deduplication.reset()
-
-
-class GraphDataDeduplication:
-    nodes_and_edges_map: dict
-
-    def __init__(self):
-        self.reset()
-
-    def reset(self):
-        self.nodes_and_edges_map = {}
-
-    def deduplicate_nodes_and_edges(self, nodes: list, edges: list):
-        final_nodes = []
-        final_edges = []
-
-        for node in nodes:
-            node_key = str(node.id)
-            if node_key not in self.nodes_and_edges_map:
-                self.nodes_and_edges_map[node_key] = True
-                final_nodes.append(node)
-
-        for edge in edges:
-            edge_key = str(edge[0]) + str(edge[2]) + str(edge[1])
-            if edge_key not in self.nodes_and_edges_map:
-                self.nodes_and_edges_map[edge_key] = True
-                final_edges.append(edge)
-
-        return final_nodes, final_edges
-
-
-def try_pushing_nodes_to_queue(node_batch):
-    try:
-        save_data_points_queue.put((node_batch, []))
-    except Exception:
-        first_half, second_half = (
-            node_batch[: len(node_batch) // 2],
-            node_batch[len(node_batch) // 2 :],
-        )
-        save_data_points_queue.put((first_half, []))
-        save_data_points_queue.put((second_half, []))
-
-
-def try_pushing_edges_to_queue(edge_batch):
-    try:
-        save_data_points_queue.put(([], edge_batch))
-    except Exception:
-        first_half, second_half = (
-            edge_batch[: len(edge_batch) // 2],
-            edge_batch[len(edge_batch) // 2 :],
-        )
-        save_data_points_queue.put(([], first_half))
-        save_data_points_queue.put(([], second_half))
diff --git a/distributed/tasks/summarize_text.py b/distributed/tasks/summarize_text.py
deleted file mode 100644
index 72ad36e49..000000000
--- a/distributed/tasks/summarize_text.py
+++ /dev/null
@@ -1,88 +0,0 @@
-import asyncio
-from typing import Type
-from uuid import uuid5
-from pydantic import BaseModel
-from cognee.modules.graph.utils import get_graph_from_model
-from cognee.tasks.summarization.models import TextSummary
-from cognee.infrastructure.engine.models.DataPoint import DataPoint
-from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
-from cognee.modules.data.extraction.extract_summary import extract_summary
-
-
-async def summarize_text(
-    data_points_and_relationships: tuple[list[DocumentChunk], list[DataPoint], list],
-    summarization_model: Type[BaseModel],
-):
-    document_chunks = data_points_and_relationships[0]
-    nodes = data_points_and_relationships[1]
-    relationships = data_points_and_relationships[2]
-
-    if len(document_chunks) == 0:
-        return document_chunks
-
-    chunk_summaries = await asyncio.gather(
-        *[extract_summary(chunk.text, summarization_model) for chunk in document_chunks]
-    )
-
-    summaries = [
-        TextSummary(
-            id=uuid5(chunk.id, "TextSummary"),
-            made_from=chunk,
-            text=chunk_summaries[chunk_index].summary,
-        )
-        for (chunk_index, chunk) in enumerate(document_chunks)
-    ]
-
-    data_points = summaries + nodes
-
-    added_nodes = {}
-    added_edges = {}
-    visited_properties = {}
-
-    nodes_and_edges: list[tuple] = await asyncio.gather(
-        *[
-            get_graph_from_model(
-                data_point,
-                added_nodes=added_nodes,
-                added_edges=added_edges,
-                visited_properties=visited_properties,
-            )
-            for data_point in data_points
-        ]
-    )
-
-    graph_data_deduplication = GraphDataDeduplication()
-    deduplicated_nodes_and_edges = [
-        graph_data_deduplication.deduplicate_nodes_and_edges(nodes, edges + relationships)
-        for nodes, edges in nodes_and_edges
-    ]
-
-    return deduplicated_nodes_and_edges
-
-
-class GraphDataDeduplication:
-    nodes_and_edges_map: dict
-
-    def __init__(self):
-        self.reset()
-
-    def reset(self):
-        self.nodes_and_edges_map = {}
-
-    def deduplicate_nodes_and_edges(self, nodes: list, edges: list):
-        final_nodes = []
-        final_edges = []
-
-        for node in nodes:
-            node_key = str(node.id)
-            if node_key not in self.nodes_and_edges_map:
-                self.nodes_and_edges_map[node_key] = True
-                final_nodes.append(node)
-
-        for edge in edges:
-            edge_key = str(edge[0]) + str(edge[2]) + str(edge[1])
-            if edge_key not in self.nodes_and_edges_map:
-                self.nodes_and_edges_map[edge_key] = True
-                final_edges.append(edge)
-
-        return final_nodes, final_edges
diff --git a/distributed/workers/data_point_saver_worker.py b/distributed/workers/data_point_saver_worker.py
index bf0035c2a..8db8f32ee 100644
--- a/distributed/workers/data_point_saver_worker.py
+++ b/distributed/workers/data_point_saver_worker.py
@@ -1,20 +1,35 @@
+import modal
 import asyncio
 
 
 from distributed.app import app
 from distributed.modal_image import image
 from distributed.queues import save_data_points_queue
+
+from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.databases.graph import get_graph_engine
 
 
-@app.function(image=image, timeout=86400, max_containers=100)
+logger = get_logger("data_point_saver_worker")
+
+
+@app.function(
+    image=image,
+    timeout=86400,
+    max_containers=100,
+    secrets=[modal.Secret.from_name("distributed_cognee")],
+)
 async def data_point_saver_worker():
     print("Started processing of nodes and edges; starting graph engine queue.")
     graph_engine = await get_graph_engine()
 
     while True:
-        if save_data_points_queue.len() != 0:
-            nodes_and_edges = save_data_points_queue.get(block=False)
+        if await save_data_points_queue.len.aio() != 0:
+            try:
+                nodes_and_edges = await save_data_points_queue.get.aio(block=False)
+            except modal.exception.DeserializationError as error:
+                logger.error(f"Deserialization error: {str(error)}")
+                continue
 
             if len(nodes_and_edges) == 0:
                 print("Finished processing all nodes and edges; stopping graph engine queue.")
@@ -28,10 +43,10 @@ async def data_point_saver_worker():
                 edges = nodes_and_edges[1]
 
                 if nodes:
-                    await graph_engine.add_nodes(nodes)
+                    await graph_engine.add_nodes(nodes, distributed=False)
 
                 if edges:
-                    await graph_engine.add_edges(edges)
+                    await graph_engine.add_edges(edges, distributed=False)
                 print("Finished processing nodes and edges.")
 
         else:
diff --git a/distributed/workers/graph_extraction_worker.py b/distributed/workers/graph_extraction_worker.py
deleted file mode 100644
index 698521405..000000000
--- a/distributed/workers/graph_extraction_worker.py
+++ /dev/null
@@ -1,42 +0,0 @@
-# ------------------------------------------------------------------------------
-# Producer function that produces data points from documents and pushes them into the queue.
-# ------------------------------------------------------------------------------
-from cognee.modules.cognify.config import get_cognify_config
-from cognee.modules.pipelines.operations.run_tasks import run_tasks
-from cognee.modules.pipelines.tasks.task import Task
-from cognee.shared.data_models import KnowledgeGraph
-
-from distributed.app import app
-from distributed.modal_image import image
-from distributed.tasks.summarize_text import summarize_text
-from distributed.tasks.extract_graph_from_data import extract_graph_from_data
-from distributed.tasks.save_data_points import save_data_points
-
-
-@app.function(image=image, timeout=86400, max_containers=100)
-async def graph_extraction_worker(user, document_name: str, document_chunks: list):
-    cognee_config = get_cognify_config()
-
-    tasks = [
-        Task(
-            extract_graph_from_data,
-            graph_model=KnowledgeGraph,
-        ),
-        Task(
-            summarize_text,
-            summarization_model=cognee_config.summarization_model,
-        ),
-        Task(save_data_points),
-    ]
-
-    async for _ in run_tasks(
-        tasks,
-        data=document_chunks,
-        pipeline_name=f"modal_execution_file_{document_name}",
-        user=user,
-    ):
-        pass
-
-    print(f"File execution finished: {document_name}")
-
-    return document_name
diff --git a/poetry.lock b/poetry.lock
index 344a0ba2d..2d3eb60c2 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1114,14 +1114,14 @@ uvicorn = {version = ">=0.18.3", extras = ["standard"]}
 
 [[package]]
 name = "click"
-version = "8.2.1"
+version = "8.1.8"
 description = "Composable command line interface toolkit"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "click-8.2.1-py3-none-any.whl", hash = "sha256:61a3265b914e850b85317d0b3109c7f8cd35a670f963866005d6ef1d5175a12b"},
-    {file = "click-8.2.1.tar.gz", hash = "sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202"},
+    {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"},
+    {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"},
 ]
 
 [package.dependencies]
@@ -5841,26 +5841,25 @@ type = ["mypy (==1.14.1)"]
 
 [[package]]
 name = "modal"
-version = "0.74.15"
+version = "1.0.5"
 description = "Python client library for Modal"
 optional = true
 python-versions = ">=3.9"
 groups = ["main"]
 markers = "extra == \"distributed\""
 files = [
-    {file = "modal-0.74.15-py3-none-any.whl", hash = "sha256:084e898ab202ccd698fd277d9dc9e9cec8d4b0954a1c09d4ba529f0446ab3526"},
-    {file = "modal-0.74.15.tar.gz", hash = "sha256:95512811ebd42a52fa03724f60d0d1c32259788351e798d0d695974d94b2e49c"},
+    {file = "modal-1.0.5-py3-none-any.whl", hash = "sha256:e575414b7e10c5ad97ae0a77149456f021e9f2c457559bb4a5af70771f481c09"},
+    {file = "modal-1.0.5.tar.gz", hash = "sha256:1c6927dd5eb9bd8d86d83ee499b87d64366525f1dd3e5b31d1ac1ed62090f72a"},
 ]
 
 [package.dependencies]
 aiohttp = "*"
 certifi = "*"
-click = ">=8.1.0"
-fastapi = "*"
-grpclib = "0.4.7"
-protobuf = ">=3.19,<4.24.0 || >4.24.0,<6.0"
+click = ">=8.1.0,<8.2.0"
+grpclib = ">=0.4.7,<0.4.9"
+protobuf = ">=3.19,<4.24.0 || >4.24.0,<7.0"
 rich = ">=12.0.0"
-synchronicity = ">=0.9.10,<0.10.0"
+synchronicity = ">=0.9.15,<0.10.0"
 toml = "*"
 typer = ">=0.9"
 types-certifi = "*"
@@ -10492,15 +10491,15 @@ dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
 [[package]]
 name = "synchronicity"
-version = "0.9.12"
+version = "0.9.16"
 description = "Export blocking and async library versions from a single async implementation"
 optional = true
 python-versions = ">=3.8"
 groups = ["main"]
 markers = "extra == \"distributed\""
 files = [
-    {file = "synchronicity-0.9.12-py3-none-any.whl", hash = "sha256:b006f57bd216d55e578316096a11b6dc16016d6b48e2766bcffabe40c88f9793"},
-    {file = "synchronicity-0.9.12.tar.gz", hash = "sha256:977f3ed8f6e35de4d1a3f0aeee4937143ba8d913f531d33e8df7c539b2792fb8"},
+    {file = "synchronicity-0.9.16-py3-none-any.whl", hash = "sha256:79dd3451c063a06489d466b0585808e1d5d257fc3c2304f5f733a142ef269e97"},
+    {file = "synchronicity-0.9.16.tar.gz", hash = "sha256:bc174b756d12330b1e6027f8293c3b944cf3684dec241af009cb7bb169a0072f"},
 ]
 
 [package.dependencies]
@@ -12237,4 +12236,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<=3.13"
-content-hash = "963b6d6541a74c8d063e8acc529489f3876c38cab3616a12a17cbe4e48fa40b6"
+content-hash = "ca2a3e8260092933419793efe202d50ae7b1c6ce738750876fd5f64a31718790"
diff --git a/pyproject.toml b/pyproject.toml
index 7b72095d3..a0f74e5aa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -69,7 +69,7 @@ api = [
     "websockets>=15.0.1"
 ]
 distributed = [
-    "modal==0.74.15",
+    "modal==1.0.5",
 ]
 weaviate = ["weaviate-client==4.9.6"]
 qdrant = ["qdrant-client>=1.14.2,<2"]
diff --git a/uv.lock b/uv.lock
index b2cf6d573..29243545d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -58,7 +58,6 @@ dependencies = [
     { name = "aiohappyeyeballs" },
     { name = "aiosignal" },
     { name = "async-timeout", version = "4.0.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
-    { name = "async-timeout", version = "5.0.1", source = { registry = "https://pypi.org/simple" }, marker = "python_version < '0'" },
     { name = "attrs" },
     { name = "frozenlist" },
     { name = "multidict" },
@@ -346,7 +345,6 @@ version = "0.30.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "async-timeout", version = "4.0.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
-    { name = "async-timeout", version = "5.0.1", source = { registry = "https://pypi.org/simple" }, marker = "python_version < '0'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/2f/4c/7c991e080e106d854809030d8584e15b2e996e26f16aee6d757e387bc17d/asyncpg-0.30.0.tar.gz", hash = "sha256:c551e9928ab6707602f44811817f82ba3c446e018bfe1d3abecc8ba5f3eac851", size = 957746, upload-time = "2024-10-20T00:30:41.127Z" }
 wheels = [
@@ -795,14 +793,14 @@ wheels = [
 
 [[package]]
 name = "click"
-version = "8.2.1"
+version = "8.1.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "colorama", marker = "sys_platform == 'win32'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/60/6c/8ca2efa64cf75a977a0d7fac081354553ebe483345c734fb6b6515d96bbc/click-8.2.1.tar.gz", hash = "sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202", size = 286342, upload-time = "2025-05-20T23:19:49.832Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593, upload-time = "2024-12-21T18:38:44.339Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/85/32/10bb5764d90a8eee674e9dc6f4db6a0ab47c8c4d0d83c27f7c39ac415a4d/click-8.2.1-py3-none-any.whl", hash = "sha256:61a3265b914e850b85317d0b3109c7f8cd35a670f963866005d6ef1d5175a12b", size = 102215, upload-time = "2025-05-20T23:19:47.796Z" },
+    { url = "https://files.pythonhosted.org/packages/7e/d4/7ebdbd03970677812aac39c869717059dbb71a4cfc033ca6e5221787892c/click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2", size = 98188, upload-time = "2024-12-21T18:38:41.666Z" },
 ]
 
 [[package]]
@@ -1072,7 +1070,7 @@ requires-dist = [
     { name = "mkdocs-material", marker = "extra == 'dev'", specifier = ">=9.5.42,<10" },
     { name = "mkdocs-minify-plugin", marker = "extra == 'dev'", specifier = ">=0.8.0,<0.9" },
     { name = "mkdocstrings", extras = ["python"], marker = "extra == 'dev'", specifier = ">=0.26.2,<0.27" },
-    { name = "modal", marker = "extra == 'distributed'", specifier = "==0.74.15" },
+    { name = "modal", marker = "extra == 'distributed'", specifier = "==1.0.5" },
     { name = "mypy", marker = "extra == 'dev'", specifier = ">=1.7.1,<2" },
     { name = "neo4j", marker = "extra == 'neo4j'", specifier = ">=5.20.0,<6" },
     { name = "networkx", specifier = ">=3.4.2,<4" },
@@ -1791,17 +1789,17 @@ name = "fastembed"
 version = "0.6.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "huggingface-hub" },
-    { name = "loguru" },
-    { name = "mmh3" },
+    { name = "huggingface-hub", marker = "python_full_version < '3.13'" },
+    { name = "loguru", marker = "python_full_version < '3.13'" },
+    { name = "mmh3", marker = "python_full_version < '3.13'" },
     { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
-    { name = "numpy", version = "2.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
-    { name = "onnxruntime" },
-    { name = "pillow" },
-    { name = "py-rust-stemmers" },
-    { name = "requests" },
-    { name = "tokenizers" },
-    { name = "tqdm" },
+    { name = "numpy", version = "2.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.12.*'" },
+    { name = "onnxruntime", marker = "python_full_version < '3.13'" },
+    { name = "pillow", marker = "python_full_version < '3.13'" },
+    { name = "py-rust-stemmers", marker = "python_full_version < '3.13'" },
+    { name = "requests", marker = "python_full_version < '3.13'" },
+    { name = "tokenizers", marker = "python_full_version < '3.13'" },
+    { name = "tqdm", marker = "python_full_version < '3.13'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/c6/f4/036a656c605f63dc25f11284f60f69900a54a19c513e1ae60d21d6977e75/fastembed-0.6.0.tar.gz", hash = "sha256:5c9ead25f23449535b07243bbe1f370b820dcc77ec2931e61674e3fe7ff24733", size = 50731, upload-time = "2025-02-26T13:50:33.031Z" }
 wheels = [
@@ -3794,8 +3792,8 @@ name = "loguru"
 version = "0.7.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
-    { name = "win32-setctime", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "python_full_version < '3.13' and sys_platform == 'win32'" },
+    { name = "win32-setctime", marker = "python_full_version < '3.13' and sys_platform == 'win32'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/3a/05/a1dae3dffd1116099471c643b8924f5aa6524411dc6c63fdae648c4f1aca/loguru-0.7.3.tar.gz", hash = "sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6", size = 63559, upload-time = "2024-12-06T11:20:56.608Z" }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/99/b6/3a7971aa05b7be7dfebc7ab57262ec527775c2c3c5b2f43675cac0458cad/lxml-6.0.0-cp312-cp312-manylinux_2_27_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:d6e200909a119626744dd81bae409fc44134389e03fbf1d68ed2a55a2fb10991", size = 5657016, upload-time = "2025-07-03T19:19:06.008Z" },
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