Removed check_permissions_on_dataset.py and related references

cognee/api/v1/cognify/cognify.py

@@ -19,7 +19,6 @@
 from cognee.modules.users.models import User
 
 from cognee.tasks.documents import (
-    check_permissions_on_dataset,
     classify_documents,
     extract_chunks_from_documents,
 )
@@ -78,12 +77,11 @@ async def cognify(
 
     Processing Pipeline:
         1. **Document Classification**: Identifies document types and structures
-        2. **Permission Validation**: Ensures user has processing rights
-        3. **Text Chunking**: Breaks content into semantically meaningful segments
-        4. **Entity Extraction**: Identifies key concepts, people, places, organizations
-        5. **Relationship Detection**: Discovers connections between entities
-        6. **Graph Construction**: Builds semantic knowledge graph with embeddings
-        7. **Content Summarization**: Creates hierarchical summaries for navigation
+        2. **Text Chunking**: Breaks content into semantically meaningful segments
+        3. **Entity Extraction**: Identifies key concepts, people, places, organizations
+        4. **Relationship Detection**: Discovers connections between entities
+        5. **Graph Construction**: Builds semantic knowledge graph with embeddings
+        6. **Content Summarization**: Creates hierarchical summaries for navigation
 
     Graph Model Customization:
         The `graph_model` parameter allows custom knowledge structures:
@@ -274,7 +272,6 @@ async def get_default_tasks(  # TODO: Find out a better way to do this (Boris's
 
     default_tasks = [
         Task(classify_documents),
-        Task(check_permissions_on_dataset, user=user, permissions=["write"]),
         Task(
             extract_chunks_from_documents,
             max_chunk_size=chunk_size or get_max_chunk_tokens(),
@@ -305,14 +302,13 @@ async def get_temporal_tasks(
 
     The pipeline includes:
     1. Document classification.
-    2. Dataset permission checks (requires "write" access).
-    3. Document chunking with a specified or default chunk size.
-    4. Event and timestamp extraction from chunks.
-    5. Knowledge graph extraction from events.
-    6. Batched insertion of data points.
+    2. Document chunking with a specified or default chunk size.
+    3. Event and timestamp extraction from chunks.
+    4. Knowledge graph extraction from events.
+    5. Batched insertion of data points.
 
     Args:
-        user (User, optional): The user requesting task execution, used for permission checks.
+        user (User, optional): The user requesting task execution.
         chunker (Callable, optional): A text chunking function/class to split documents. Defaults to TextChunker.
         chunk_size (int, optional): Maximum token size per chunk. If not provided, uses system default.
         chunks_per_batch (int, optional): Number of chunks to process in a single batch in Cognify
@@ -325,7 +321,6 @@ async def get_temporal_tasks(
 
     temporal_tasks = [
         Task(classify_documents),
-        Task(check_permissions_on_dataset, user=user, permissions=["write"]),
         Task(
             extract_chunks_from_documents,
             max_chunk_size=chunk_size or get_max_chunk_tokens(),

cognee/eval_framework/corpus_builder/task_getters/get_cascade_graph_tasks.py

@@ -8,7 +8,6 @@
 from cognee.shared.data_models import KnowledgeGraph
 from cognee.shared.utils import send_telemetry
 from cognee.tasks.documents import (
-    check_permissions_on_dataset,
     classify_documents,
     extract_chunks_from_documents,
 )
@@ -31,7 +30,6 @@ async def get_cascade_graph_tasks(
         cognee_config = get_cognify_config()
         default_tasks = [
             Task(classify_documents),
-            Task(check_permissions_on_dataset, user=user, permissions=["write"]),
             Task(
                 extract_chunks_from_documents, max_chunk_tokens=get_max_chunk_tokens()
             ),  # Extract text chunks based on the document type.

cognee/eval_framework/corpus_builder/task_getters/get_default_tasks_by_indices.py

@@ -30,8 +30,8 @@ async def get_no_summary_tasks(
     ontology_file_path=None,
 ) -> List[Task]:
     """Returns default tasks without summarization tasks."""
-    # Get base tasks (0=classify, 1=check_permissions, 2=extract_chunks)
-    base_tasks = await get_default_tasks_by_indices([0, 1, 2], chunk_size, chunker)
+    # Get base tasks (0=classify, 1=extract_chunks)
+    base_tasks = await get_default_tasks_by_indices([0, 1], chunk_size, chunker)
 
     ontology_adapter = RDFLibOntologyResolver(ontology_file=ontology_file_path)
 
@@ -51,8 +51,8 @@ async def get_just_chunks_tasks(
     chunk_size: int = None, chunker=TextChunker, user=None
 ) -> List[Task]:
     """Returns default tasks with only chunk extraction and data points addition."""
-    # Get base tasks (0=classify, 1=check_permissions, 2=extract_chunks)
-    base_tasks = await get_default_tasks_by_indices([0, 1, 2], chunk_size, chunker)
+    # Get base tasks (0=classify, 1=extract_chunks)
+    base_tasks = await get_default_tasks_by_indices([0, 1], chunk_size, chunker)
 
     add_data_points_task = Task(add_data_points, task_config={"batch_size": 10})
 

cognee/tasks/documents/__init__.py

@@ -1,3 +1,2 @@
 from .classify_documents import classify_documents
 from .extract_chunks_from_documents import extract_chunks_from_documents
-from .check_permissions_on_dataset import check_permissions_on_dataset

examples/python/simple_example.py

@@ -32,16 +32,13 @@ async def main():
     print("Cognify process steps:")
     print("1. Classifying the document: Determining the type and category of the input text.")
     print(
-        "2. Checking permissions: Ensuring the user has the necessary rights to process the text."
+        "2. Extracting text chunks: Breaking down the text into sentences or phrases for analysis."
     )
     print(
-        "3. Extracting text chunks: Breaking down the text into sentences or phrases for analysis."
+        "3. Generating knowledge graph: Extracting entities and relationships to form a knowledge graph."
     )
-    print("4. Adding data points: Storing the extracted chunks for processing.")
-    print(
-        "5. Generating knowledge graph: Extracting entities and relationships to form a knowledge graph."
-    )
-    print("6. Summarizing text: Creating concise summaries of the content for quick insights.\n")
+    print("4. Summarizing text: Creating concise summaries of the content for quick insights.")
+    print("5. Adding data points: Storing the extracted chunks for processing.\n")
 
     # Use LLMs and cognee to create knowledge graph
     await cognee.cognify()

notebooks/cognee_demo.ipynb

@@ -591,7 +591,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "7c431fdef4921ae0",
    "metadata": {
     "ExecuteTime": {
@@ -609,7 +609,6 @@
     "from cognee.modules.pipelines import run_tasks\n",
     "from cognee.modules.users.models import User\n",
     "from cognee.tasks.documents import (\n",
-    "    check_permissions_on_dataset,\n",
     "    classify_documents,\n",
     "    extract_chunks_from_documents,\n",
     ")\n",
@@ -627,7 +626,6 @@
     "\n",
     "        tasks = [\n",
     "            Task(classify_documents),\n",
-    "            Task(check_permissions_on_dataset, user=user, permissions=[\"write\"]),\n",
     "            Task(\n",
     "                extract_chunks_from_documents, max_chunk_size=get_max_chunk_tokens()\n",
     "            ),  # Extract text chunks based on the document type.\n",