Merge remote-tracking branch 'origin/main' into feat/COG-553-graph-memory-projection

.github/workflows/test_neo4j.yml

@@ -5,7 +5,7 @@ on:
   pull_request:
     branches:
       - main
-    types: [labeled]
+    types: [labeled, synchronize]
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -22,7 +22,7 @@ jobs:
   run_neo4j_integration_test:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ${{ github.event.label.name == 'run-checks' }}
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
 
     defaults:

.github/workflows/test_notebook.yml

@@ -5,7 +5,7 @@ on:
   pull_request:
     branches:
       - main
-    types: [labeled]
+    types: [labeled, synchronize]
 
 
 concurrency:
@@ -23,7 +23,7 @@ jobs:
   run_notebook_test:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ${{ github.event.label.name == 'run-checks' }}
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
     defaults:
       run:

.github/workflows/test_pgvector.yml

@@ -5,7 +5,7 @@ on:
   pull_request:
     branches:
       - main
-    types: [labeled]
+    types: [labeled, synchronize]
 
 
 concurrency:
@@ -23,7 +23,7 @@ jobs:
   run_pgvector_integration_test:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ${{ github.event.label.name == 'run-checks' }}
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
     defaults:
       run:

.github/workflows/test_python_3_10.yml

@@ -1,10 +1,11 @@
 name: test | python 3.10
 
 on:
+  workflow_dispatch:
   pull_request:
     branches:
       - main
-  workflow_dispatch:
+    types: [labeled, synchronize]
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -21,7 +22,7 @@ jobs:
   run_common:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true'
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false

.github/workflows/test_python_3_11.yml

@@ -1,10 +1,11 @@
 name: test | python 3.11
 
 on:
+  workflow_dispatch:
   pull_request:
     branches:
       - main
-  workflow_dispatch:
+    types: [labeled, synchronize]
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -21,7 +22,7 @@ jobs:
   run_common:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true'
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false

.github/workflows/test_python_3_9.yml

@@ -1,10 +1,11 @@
 name: test | python 3.9
 
 on:
+  workflow_dispatch:
   pull_request:
     branches:
       - main
-  workflow_dispatch:
+    types: [labeled, synchronize]
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -21,7 +22,7 @@ jobs:
   run_common:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true'
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false

.github/workflows/test_qdrant.yml

@@ -5,7 +5,7 @@ on:
   pull_request:
     branches:
       - main
-    types: [labeled]
+    types: [labeled, synchronize]
 
 
 concurrency:
@@ -23,7 +23,7 @@ jobs:
   run_qdrant_integration_test:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ${{ github.event.label.name == 'run-checks' }}
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
 
     defaults:

.github/workflows/test_weaviate.yml

@@ -5,7 +5,7 @@ on:
   pull_request:
     branches:
       - main
-    types: [labeled]
+    types: [labeled, synchronize]
 
 
 concurrency:
@@ -23,7 +23,7 @@ jobs:
   run_weaviate_integration_test:
     name: test
     needs: get_docs_changes
-    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' | ${{ github.event.label.name == 'run-checks' }}
+    if: needs.get_docs_changes.outputs.changes_outside_docs == 'true' && ${{ github.event.label.name == 'run-checks' }}
     runs-on: ubuntu-latest
 
     defaults:

.gitignore

@@ -177,5 +177,6 @@ cognee/cache/
 # Default cognee system directory, used in development
 .cognee_system/
 .data_storage/
+.anon_id
 
 node_modules/

README.md

@@ -109,24 +109,34 @@ import asyncio
 from cognee.api.v1.search import SearchType
 
 async def main():
-    await cognee.prune.prune_data()  # Reset cognee data
+    # Reset cognee data
-    await cognee.prune.prune_system(metadata=True)  # Reset cognee system state
+    await cognee.prune.prune_data()
+    # Reset cognee system state
+    await cognee.prune.prune_system(metadata=True)
 
     text = """
     Natural language processing (NLP) is an interdisciplinary
     subfield of computer science and information retrieval.
     """
 
-    await cognee.add(text)  # Add text to cognee
+    # Add text to cognee
-    await cognee.cognify()  # Use LLMs and cognee to create knowledge graph
+    await cognee.add(text)
 
-    search_results = await cognee.search(  # Search cognee for insights
+    # Use LLMs and cognee to create knowledge graph
+    await cognee.cognify()
+
+    # Search cognee for insights
+    search_results = await cognee.search(
         SearchType.INSIGHTS,
-        {'query': 'Tell me about NLP'}
+        "Tell me about NLP",
     )
 
-    for result_text in search_results:  # Display results
+    # Display results
+    for result_text in search_results:
         print(result_text)
+        # natural_language_processing is_a field
+        # natural_language_processing is_subfield_of computer_science
+        # natural_language_processing is_subfield_of information_retrieval
 
 asyncio.run(main())
 ```

cognee/infrastructure/databases/graph/neo4j_driver/adapter.py

@@ -1,6 +1,7 @@
 """ Neo4j Adapter for Graph Database"""
 import logging
 import asyncio
+from textwrap import dedent
 from typing import Optional, Any, List, Dict
 from contextlib import asynccontextmanager
 from uuid import UUID
@@ -18,7 +19,7 @@ class Neo4jAdapter(GraphDBInterface):
         graph_database_url: str,
         graph_database_username: str,
         graph_database_password: str,
-        driver: Optional[Any] = None
+        driver: Optional[Any] = None,
     ):
         self.driver = driver or AsyncGraphDatabase.driver(
             graph_database_url,
@@ -26,6 +27,9 @@ class Neo4jAdapter(GraphDBInterface):
             max_connection_lifetime = 120
         )
 
+    async def close(self) -> None:
+        await self.driver.close()
+
     @asynccontextmanager
     async def get_session(self) -> AsyncSession:
         async with self.driver.session() as session:
@@ -59,11 +63,10 @@ class Neo4jAdapter(GraphDBInterface):
     async def add_node(self, node: DataPoint):
         serialized_properties = self.serialize_properties(node.model_dump())
 
-        query = """MERGE (node {id: $node_id})
+        query = dedent("""MERGE (node {id: $node_id})
-                ON CREATE SET node += $properties
+                ON CREATE SET node += $properties, node.updated_at = timestamp()
-                ON MATCH SET node += $properties
+                ON MATCH SET node += $properties, node.updated_at = timestamp()
-                ON MATCH SET node.updated_at = timestamp()
+                RETURN ID(node) AS internal_id, node.id AS nodeId""")
-                RETURN ID(node) AS internal_id, node.id AS nodeId"""
 
         params = {
             "node_id": str(node.id),
@@ -76,9 +79,8 @@ class Neo4jAdapter(GraphDBInterface):
         query = """
         UNWIND $nodes AS node
         MERGE (n {id: node.node_id})
-        ON CREATE SET n += node.properties
+        ON CREATE SET n += node.properties, n.updated_at = timestamp()
-        ON MATCH SET n += node.properties
+        ON MATCH SET n += node.properties, n.updated_at = timestamp()
-        ON MATCH SET n.updated_at = timestamp()
         WITH n, node.node_id AS label
         CALL apoc.create.addLabels(n, [label]) YIELD node AS labeledNode
         RETURN ID(labeledNode) AS internal_id, labeledNode.id AS nodeId
@@ -133,12 +135,19 @@ class Neo4jAdapter(GraphDBInterface):
         return await self.query(query, params)
 
     async def has_edge(self, from_node: UUID, to_node: UUID, edge_label: str) -> bool:
-        query = f"""
+        query = """
-            MATCH (from_node:`{str(from_node)}`)-[relationship:`{edge_label}`]->(to_node:`{str(to_node)}`)
+            MATCH (from_node)-[relationship]->(to_node)
+            WHERE from_node.id = $from_node_id AND to_node.id = $to_node_id AND type(relationship) = $edge_label
             RETURN COUNT(relationship) > 0 AS edge_exists
         """
 
-        edge_exists = await self.query(query)
+        params = {
+            "from_node_id": str(from_node),
+            "to_node_id": str(to_node),
+            "edge_label": edge_label,
+        }
+
+        edge_exists = await self.query(query, params)
         return edge_exists
 
     async def has_edges(self, edges):
@@ -165,22 +174,21 @@ class Neo4jAdapter(GraphDBInterface):
             raise error
 
 
-    async def add_edge(self, from_node: str, to_node: str, relationship_name: str, edge_properties: Optional[Dict[str, Any]] = {}):
+    async def add_edge(self, from_node: UUID, to_node: UUID, relationship_name: str, edge_properties: Optional[Dict[str, Any]] = {}):
         serialized_properties = self.serialize_properties(edge_properties)
-        from_node = from_node.replace(":", "_")
-        to_node = to_node.replace(":", "_")
 
-        query = f"""MATCH (from_node:`{str(from_node)}`
+        query = dedent("""MATCH (from_node {id: $from_node}),
-         {{id: $from_node}}), 
+            (to_node {id: $to_node})
-         (to_node:`{str(to_node)}` {{id: $to_node}})
+            MERGE (from_node)-[r]->(to_node)
-         MERGE (from_node)-[r:`{relationship_name}`]->(to_node)
+            ON CREATE SET r += $properties, r.updated_at = timestamp(), r.type = $relationship_name
-         ON CREATE SET r += $properties, r.updated_at = timestamp()
+            ON MATCH SET r += $properties, r.updated_at = timestamp()
-         ON MATCH SET r += $properties, r.updated_at = timestamp()
+            RETURN r
-         RETURN r"""
+        """)
 
         params = {
             "from_node": str(from_node),
             "to_node": str(to_node),
+            "relationship_name": relationship_name,
             "properties": serialized_properties
         }
 
@@ -347,8 +355,8 @@ class Neo4jAdapter(GraphDBInterface):
         """
 
         predecessors, successors = await asyncio.gather(
-            self.query(predecessors_query, dict(node_id = node_id)),
+            self.query(predecessors_query, dict(node_id = str(node_id))),
-            self.query(successors_query, dict(node_id = node_id)),
+            self.query(successors_query, dict(node_id = str(node_id))),
         )
 
         connections = []

cognee/infrastructure/databases/graph/networkx/adapter.py

@@ -270,7 +270,7 @@ class NetworkXAdapter(GraphDBInterface):
                         except:
                           pass
 
-                        if "updated_at" in node:
+                        if "updated_at" in edge:
                             edge["updated_at"] = datetime.strptime(edge["updated_at"], "%Y-%m-%dT%H:%M:%S.%f%z")
 
                     self.graph = nx.readwrite.json_graph.node_link_graph(graph_data)

cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py

@@ -112,18 +112,10 @@ class LanceDBAdapter(VectorDBInterface):
                 for (data_point_index, data_point) in enumerate(data_points)
         ]
 
-        # TODO: This enables us to work with pydantic version but shouldn't
+        await collection.merge_insert("id") \
-        #  stay like this, existing rows should be updated
+            .when_matched_update_all() \
-
+            .when_not_matched_insert_all() \
-        await collection.delete("id IS NOT NULL")
+            .execute(lance_data_points)
-
-        original_size = await collection.count_rows()
-        await collection.add(lance_data_points)
-        new_size = await collection.count_rows()
-
-        if new_size <= original_size:
-            raise ValueError(
-                "LanceDB create_datapoints error: data points did not get added.")
         
 
     async def retrieve(self, collection_name: str, data_point_ids: list[str]):

cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py

@@ -54,7 +54,6 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         vector_size = self.embedding_engine.get_vector_size()
 
         if not await self.has_collection(collection_name):
-
             class PGVectorDataPoint(Base):
                 __tablename__ = collection_name
                 __table_args__ = {"extend_existing": True}
@@ -80,44 +79,44 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
     async def create_data_points(
         self, collection_name: str, data_points: List[DataPoint]
     ):
-        async with self.get_async_session() as session:
+        if not await self.has_collection(collection_name):
-            if not await self.has_collection(collection_name):
+            await self.create_collection(
-                await self.create_collection(
+                collection_name = collection_name,
-                    collection_name=collection_name,
+                payload_schema = type(data_points[0]),
-                    payload_schema=type(data_points[0]),
-                )
-
-            data_vectors = await self.embed_data(
-                [data_point.get_embeddable_data() for data_point in data_points]
             )
 
-            vector_size = self.embedding_engine.get_vector_size()
+        data_vectors = await self.embed_data(
+            [data_point.get_embeddable_data() for data_point in data_points]
+        )
 
-            class PGVectorDataPoint(Base):
+        vector_size = self.embedding_engine.get_vector_size()
-                __tablename__ = collection_name
-                __table_args__ = {"extend_existing": True}
-                # PGVector requires one column to be the primary key
-                primary_key: Mapped[int] = mapped_column(
-                    primary_key=True, autoincrement=True
-                )
-                id: Mapped[type(data_points[0].id)]
-                payload = Column(JSON)
-                vector = Column(Vector(vector_size))
 
-                def __init__(self, id, payload, vector):
+        class PGVectorDataPoint(Base):
-                    self.id = id
+            __tablename__ = collection_name
-                    self.payload = payload
+            __table_args__ = {"extend_existing": True}
-                    self.vector = vector
+            # PGVector requires one column to be the primary key
+            primary_key: Mapped[int] = mapped_column(
+                primary_key=True, autoincrement=True
+            )
+            id: Mapped[type(data_points[0].id)]
+            payload = Column(JSON)
+            vector = Column(Vector(vector_size))
 
-            pgvector_data_points = [
+            def __init__(self, id, payload, vector):
-                PGVectorDataPoint(
+                self.id = id
-                    id=data_point.id,
+                self.payload = payload
-                    vector=data_vectors[data_index],
+                self.vector = vector
-                    payload=serialize_data(data_point.model_dump()),
-                )
-                for (data_index, data_point) in enumerate(data_points)
-            ]
 
+        pgvector_data_points = [
+            PGVectorDataPoint(
+                id = data_point.id,
+                vector = data_vectors[data_index],
+                payload = serialize_data(data_point.model_dump()),
+            )
+            for (data_index, data_point) in enumerate(data_points)
+        ]
+
+        async with self.get_async_session() as session:
             session.add_all(pgvector_data_points)
             await session.commit()
 
@@ -128,7 +127,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         await self.create_data_points(f"{index_name}_{index_property_name}", [
             IndexSchema(
                 id = data_point.id,
-                text = getattr(data_point, data_point._metadata["index_fields"][0]),
+                text = data_point.get_embeddable_data(),
             ) for data_point in data_points
         ])
 
@@ -146,10 +145,10 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                 raise ValueError(f"Table '{collection_name}' not found.")
 
     async def retrieve(self, collection_name: str, data_point_ids: List[str]):
-        async with self.get_async_session() as session:
+        # Get PGVectorDataPoint Table from database
-            # Get PGVectorDataPoint Table from database
+        PGVectorDataPoint = await self.get_table(collection_name)
-            PGVectorDataPoint = await self.get_table(collection_name)
 
+        async with self.get_async_session() as session:
             results = await session.execute(
                 select(PGVectorDataPoint).where(PGVectorDataPoint.c.id.in_(data_point_ids))
             )
@@ -177,11 +176,13 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         if query_text and not query_vector:
             query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
 
+        # Get PGVectorDataPoint Table from database
+        PGVectorDataPoint = await self.get_table(collection_name)
+
+        closest_items = []
+
         # Use async session to connect to the database
         async with self.get_async_session() as session:
-            # Get PGVectorDataPoint Table from database
-            PGVectorDataPoint = await self.get_table(collection_name)
-
             # Find closest vectors to query_vector
             closest_items = await session.execute(
                 select(
@@ -194,20 +195,21 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
                 .limit(limit)
             )
 
-            vector_list = []
+        vector_list = []
-            # Extract distances and find min/max for normalization
-            for vector in closest_items:
-                # TODO: Add normalization of similarity score
-                vector_list.append(vector)
 
-            # Create and return ScoredResult objects
+        # Extract distances and find min/max for normalization
-            return [
+        for vector in closest_items:
-                ScoredResult(
+            # TODO: Add normalization of similarity score
-                    id = UUID(str(row.id)),
+            vector_list.append(vector)
-                    payload = row.payload,
+
-                    score = row.similarity
+        # Create and return ScoredResult objects
-                ) for row in vector_list
+        return [
-            ]
+            ScoredResult(
+                id = UUID(str(row.id)),
+                payload = row.payload,
+                score = row.similarity
+            ) for row in vector_list
+        ]
 
     async def batch_search(
         self,

cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py

@@ -1,7 +1,9 @@
 import logging
+from uuid import UUID
 from typing import List, Dict, Optional
 from qdrant_client import AsyncQdrantClient, models
 
+from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
 from cognee.infrastructure.engine import DataPoint
 from ..vector_db_interface import VectorDBInterface
 from ..embeddings.EmbeddingEngine import EmbeddingEngine
@@ -153,7 +155,7 @@ class QDrantAdapter(VectorDBInterface):
 
         client = self.get_qdrant_client()
 
-        result = await client.search(
+        results = await client.search(
             collection_name = collection_name,
             query_vector = models.NamedVector(
                 name = "text",
@@ -165,7 +167,16 @@ class QDrantAdapter(VectorDBInterface):
 
         await client.close()
 
-        return result
+        return [
+            ScoredResult(
+                id = UUID(result.id),
+                payload = {
+                    **result.payload,
+                    "id": UUID(result.id),
+                },
+                score = 1 - result.score,
+            ) for result in results
+        ]
 
 
     async def batch_search(self, collection_name: str, query_texts: List[str], limit: int = None, with_vectors: bool = False):

cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py

@@ -11,7 +11,6 @@ from ..embeddings.EmbeddingEngine import EmbeddingEngine
 logger = logging.getLogger("WeaviateAdapter")
 
 class IndexSchema(DataPoint):
-    uuid: str
     text: str
 
     _metadata: dict = {
@@ -58,18 +57,21 @@ class WeaviateAdapter(VectorDBInterface):
 
         future = asyncio.Future()
 
-        future.set_result(
+        if not self.client.collections.exists(collection_name):
-            self.client.collections.create(
+            future.set_result(
-                name=collection_name,
+                self.client.collections.create(
-                properties=[
+                    name = collection_name,
-                    wvcc.Property(
+                    properties = [
-                        name="text",
+                        wvcc.Property(
-                        data_type=wvcc.DataType.TEXT,
+                            name = "text",
-                        skip_vectorization=True
+                            data_type = wvcc.DataType.TEXT,
-                    )
+                            skip_vectorization = True
-                ]
+                        )
+                    ]
+                )
             )
-        )
+        else:
+            future.set_result(self.get_collection(collection_name))
 
         return await future
 
@@ -80,13 +82,16 @@ class WeaviateAdapter(VectorDBInterface):
         from weaviate.classes.data import DataObject
 
         data_vectors = await self.embed_data(
-            list(map(lambda data_point: data_point.get_embeddable_data(), data_points)))
+            [data_point.get_embeddable_data() for data_point in data_points]
+        )
 
         def convert_to_weaviate_data_points(data_point: DataPoint):
             vector = data_vectors[data_points.index(data_point)]
             properties = data_point.model_dump()
-            properties["uuid"] = properties["id"]
+
-            del properties["id"]
+            if "id" in properties:
+                properties["uuid"] = str(data_point.id)
+                del properties["id"]
 
             return DataObject(
                 uuid = data_point.id,
@@ -94,22 +99,28 @@ class WeaviateAdapter(VectorDBInterface):
                 vector = vector
             )
 
-        data_points = list(map(convert_to_weaviate_data_points, data_points))
+        data_points = [convert_to_weaviate_data_points(data_point) for data_point in data_points]
 
         collection = self.get_collection(collection_name)
 
         try:
             if len(data_points) > 1:
-                return collection.data.insert_many(data_points)
+                with collection.batch.dynamic() as batch:
+                    for data_point in data_points:
+                        batch.add_object(
+                            uuid = data_point.uuid,
+                            vector = data_point.vector,
+                            properties = data_point.properties,
+                            references = data_point.references,
+                        )
             else:
-                return collection.data.insert(data_points[0])
+                data_point: DataObject = data_points[0]
-            # with collection.batch.dynamic() as batch:
+                return collection.data.update(
-            #     for point in data_points:
+                    uuid = data_point.uuid,
-            #         batch.add_object(
+                    vector = data_point.vector,
-            #             uuid = point.uuid,
+                    properties = data_point.properties,
-            #             properties = point.properties,
+                    references = data_point.references,
-            #             vector = point.vector
+                )
-            #         )
         except Exception as error:
             logger.error("Error creating data points: %s", str(error))
             raise error
@@ -120,8 +131,8 @@ class WeaviateAdapter(VectorDBInterface):
     async def index_data_points(self, index_name: str, index_property_name: str, data_points: list[DataPoint]):
         await self.create_data_points(f"{index_name}_{index_property_name}", [
             IndexSchema(
-                uuid = str(data_point.id),
+                id = data_point.id,
-                text = getattr(data_point, data_point._metadata["index_fields"][0]),
+                text = data_point.get_embeddable_data(),
             ) for data_point in data_points
         ])
 
@@ -168,9 +179,9 @@ class WeaviateAdapter(VectorDBInterface):
 
         return [
             ScoredResult(
-                id = UUID(result.uuid),
+                id = UUID(str(result.uuid)),
                 payload = result.properties,
-                score = float(result.metadata.score)
+                score = 1 - float(result.metadata.score)
             ) for result in search_result.objects
         ]
 

cognee/modules/engine/utils/__init__.py

@@ -1,2 +1,3 @@
 from .generate_node_id import generate_node_id
 from .generate_node_name import generate_node_name
+from .generate_edge_name import generate_edge_name

cognee/modules/engine/utils/generate_edge_name.py

@@ -0,0 +1,2 @@
+def generate_edge_name(name: str) -> str:
+    return name.lower().replace(" ", "_").replace("'", "")

cognee/modules/engine/utils/generate_node_name.py

@@ -1,2 +1,2 @@
 def generate_node_name(name: str) -> str:
-    return name.lower().replace(" ", "_").replace("'", "")
+    return name.lower().replace("'", "")

cognee/shared/utils.py

@@ -9,9 +9,29 @@ import matplotlib.pyplot as plt
 import tiktoken
 import nltk
 from posthog import Posthog
+
 from cognee.base_config import get_base_config
 from cognee.infrastructure.databases.graph import get_graph_engine
 
+from uuid import uuid4
+import pathlib
+
+def get_anonymous_id():
+    """Creates or reads a anonymous user id"""
+    home_dir = str(pathlib.Path(pathlib.Path(__file__).parent.parent.parent.resolve()))
+
+    if not os.path.isdir(home_dir):
+        os.makedirs(home_dir, exist_ok=True)
+    anonymous_id_file = os.path.join(home_dir, ".anon_id")
+    if not os.path.isfile(anonymous_id_file):
+        anonymous_id = str(uuid4())
+        with open(anonymous_id_file, "w", encoding="utf-8") as f:
+            f.write(anonymous_id)
+    else:
+        with open(anonymous_id_file, "r", encoding="utf-8") as f:
+            anonymous_id = f.read()
+    return anonymous_id
+
 def send_telemetry(event_name: str, user_id, additional_properties: dict = {}):
     if os.getenv("TELEMETRY_DISABLED"):
         return
@@ -28,11 +48,15 @@ def send_telemetry(event_name: str, user_id, additional_properties: dict = {}):
     current_time = datetime.now(timezone.utc)
     properties = {
         "time": current_time.strftime("%m/%d/%Y"),
+        "user_id": user_id,
         **additional_properties,
     }
 
+    # Needed to forward properties to PostHog along with id
+    posthog.identify(get_anonymous_id(), properties)
+
     try:
-        posthog.capture(user_id, event_name, properties)
+        posthog.capture(get_anonymous_id(), event_name, properties)
     except Exception as e:
         print("ERROR sending telemetric data to Posthog. See exception: %s", e)
 

cognee/tasks/graph/extract_graph_from_data.py

@@ -5,7 +5,7 @@ from cognee.infrastructure.databases.graph import get_graph_engine
 from cognee.modules.data.extraction.knowledge_graph import extract_content_graph
 from cognee.modules.chunking.models.DocumentChunk import DocumentChunk
 from cognee.modules.engine.models import EntityType, Entity
-from cognee.modules.engine.utils import generate_node_id, generate_node_name
+from cognee.modules.engine.utils import generate_edge_name, generate_node_id, generate_node_name
 from cognee.tasks.storage import add_data_points
 
 async def extract_graph_from_data(data_chunks: list[DocumentChunk], graph_model: Type[BaseModel]):
@@ -95,7 +95,7 @@ async def extract_graph_from_data(data_chunks: list[DocumentChunk], graph_model:
         for edge in graph.edges:
             source_node_id = generate_node_id(edge.source_node_id)
             target_node_id = generate_node_id(edge.target_node_id)
-            relationship_name = generate_node_name(edge.relationship_name)
+            relationship_name = generate_edge_name(edge.relationship_name)
 
             edge_key = str(source_node_id) + str(target_node_id) + relationship_name
 
@@ -105,7 +105,7 @@ async def extract_graph_from_data(data_chunks: list[DocumentChunk], graph_model:
                     target_node_id,
                     edge.relationship_name,
                     dict(
-                        relationship_name = generate_node_name(edge.relationship_name),
+                        relationship_name = generate_edge_name(edge.relationship_name),
                         source_node_id = source_node_id,
                         target_node_id = target_node_id,
                     ),

cognee/tasks/graph/query_graph_connections.py

@@ -37,7 +37,7 @@ async def query_graph_connections(query: str, exploration_levels = 1) -> list[(s
             return []
 
         node_connections_results = await asyncio.gather(
-            *[graph_engine.get_connections(str(result.id)) for result in relevant_results]
+            *[graph_engine.get_connections(result.id) for result in relevant_results]
         )
 
         node_connections = []

cognee/tests/test_neo4j.py

@@ -36,7 +36,7 @@ async def main():
 
     from cognee.infrastructure.databases.vector import get_vector_engine
     vector_engine = get_vector_engine()
-    random_node = (await vector_engine.search("Entity_name", "AI"))[0]
+    random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
     random_node_name = random_node.payload["text"]
 
     search_results = await cognee.search(SearchType.INSIGHTS, query = random_node_name)

cognee/tests/test_pgvector.py

@@ -41,7 +41,7 @@ async def main():
     cognee.config.system_root_directory(cognee_directory_path)
 
     await cognee.prune.prune_data()
-    await cognee.prune.prune_system(metadata=True)
+    await cognee.prune.prune_system(metadata = True)
 
     dataset_name = "cs_explanations"
 
@@ -65,7 +65,7 @@ async def main():
     from cognee.infrastructure.databases.vector import get_vector_engine
 
     vector_engine = get_vector_engine()
-    random_node = (await vector_engine.search("Entity_name", "AI"))[0]
+    random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
     random_node_name = random_node.payload["text"]
 
     search_results = await cognee.search(SearchType.INSIGHTS, query=random_node_name)

cognee/tests/test_qdrant.py

@@ -37,7 +37,7 @@ async def main():
 
     from cognee.infrastructure.databases.vector import get_vector_engine
     vector_engine = get_vector_engine()
-    random_node = (await vector_engine.search("Entity_name", "AI"))[0]
+    random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
     random_node_name = random_node.payload["text"]
 
     search_results = await cognee.search(SearchType.INSIGHTS, query = random_node_name)

cognee/tests/test_weaviate.py

@@ -35,7 +35,7 @@ async def main():
 
     from cognee.infrastructure.databases.vector import get_vector_engine
     vector_engine = get_vector_engine()
-    random_node = (await vector_engine.search("Entity_name", "AI"))[0]
+    random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
     random_node_name = random_node.payload["text"]
 
     search_results = await cognee.search(SearchType.INSIGHTS, query = random_node_name)

notebooks/cognee_demo.ipynb

@@ -265,7 +265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "df16431d0f48b006",
    "metadata": {
     "ExecuteTime": {
@@ -304,7 +304,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "9086abf3af077ab4",
    "metadata": {
     "ExecuteTime": {
@@ -349,7 +349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "a9de0cc07f798b7f",
    "metadata": {
     "ExecuteTime": {
@@ -393,7 +393,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "185ff1c102d06111",
    "metadata": {
     "ExecuteTime": {
@@ -437,7 +437,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "id": "d55ce4c58f8efb67",
    "metadata": {
     "ExecuteTime": {
@@ -479,7 +479,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "ca4ecc32721ad332",
    "metadata": {
     "ExecuteTime": {
@@ -572,7 +572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "9f1a1dbd",
    "metadata": {},
    "outputs": [],
@@ -758,7 +758,7 @@
     "from cognee.infrastructure.databases.vector import get_vector_engine\n",
     "\n",
     "vector_engine = get_vector_engine()\n",
-    "results = await search(vector_engine, \"entities\", \"sarah.nguyen@example.com\")\n",
+    "results = await search(vector_engine, \"Entity_name\", \"sarah.nguyen@example.com\")\n",
     "for result in results:\n",
     "    print(result)"
    ]
@@ -788,8 +788,8 @@
    "source": [
     "from cognee.api.v1.search import SearchType\n",
     "\n",
-    "node = (await vector_engine.search(\"entities\", \"sarah.nguyen@example.com\"))[0]\n",
+    "node = (await vector_engine.search(\"Entity_name\", \"sarah.nguyen@example.com\"))[0]\n",
-    "node_name = node.payload[\"name\"]\n",
+    "node_name = node.payload[\"text\"]\n",
     "\n",
     "search_results = await cognee.search(SearchType.SUMMARIES, query = node_name)\n",
     "print(\"\\n\\Extracted summaries are:\\n\")\n",
@@ -881,7 +881,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,

poetry.lock

@@ -597,17 +597,17 @@ css = ["tinycss2 (>=1.1.0,<1.5)"]
 
 [[package]]
 name = "boto3"
-version = "1.35.55"
+version = "1.35.57"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.35.55-py3-none-any.whl", hash = "sha256:c7a0a0bc5ae3bed5d38e8bfe5a56b31621e79bdd7c1ea6e5ba4326d820cde3a5"},
+    {file = "boto3-1.35.57-py3-none-any.whl", hash = "sha256:9edf49640c79a05b0a72f4c2d1e24dfc164344b680535a645f455ac624dc3680"},
-    {file = "boto3-1.35.55.tar.gz", hash = "sha256:82fa8cdb00731aeffe7a5829821ae78d75c7ae959b638c15ff3b4681192ace90"},
+    {file = "boto3-1.35.57.tar.gz", hash = "sha256:db58348849a5af061f0f5ec9c3b699da5221ca83354059fdccb798e3ddb6b62a"},
 ]
 
 [package.dependencies]
-botocore = ">=1.35.55,<1.36.0"
+botocore = ">=1.35.57,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -616,13 +616,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.55"
+version = "1.35.57"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.35.55-py3-none-any.whl", hash = "sha256:3d54739e498534c9d7a6e9732ae2d17ed29c7d5e29fe36c956d8488b859538b0"},
+    {file = "botocore-1.35.57-py3-none-any.whl", hash = "sha256:92ddd02469213766872cb2399269dd20948f90348b42bf08379881d5e946cc34"},
-    {file = "botocore-1.35.55.tar.gz", hash = "sha256:61ae18f688250372d7b6046e35c86f8fd09a7c0f0064b52688f3490b4d6c9d6b"},
+    {file = "botocore-1.35.57.tar.gz", hash = "sha256:d96306558085baf0bcb3b022d7a8c39c93494f031edb376694d2b2dcd0e81327"},
 ]
 
 [package.dependencies]
@@ -2606,22 +2606,22 @@ colors = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "jedi"
-version = "0.19.1"
+version = "0.19.2"
 description = "An autocompletion tool for Python that can be used for text editors."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
+    {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"},
-    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
+    {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"},
 ]
 
 [package.dependencies]
-parso = ">=0.8.3,<0.9.0"
+parso = ">=0.8.4,<0.9.0"
 
 [package.extras]
 docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
-testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<9.0.0)"]
 
 [[package]]
 name = "jinja2"
@@ -2755,15 +2755,18 @@ files = [
 
 [[package]]
 name = "json5"
-version = "0.9.25"
+version = "0.9.27"
 description = "A Python implementation of the JSON5 data format."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.8.0"
 files = [
-    {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"},
+    {file = "json5-0.9.27-py3-none-any.whl", hash = "sha256:17b43d78d3a6daeca4d7030e9bf22092dba29b1282cc2d0cfa56f6febee8dc93"},
-    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
+    {file = "json5-0.9.27.tar.gz", hash = "sha256:5a19de4a6ca24ba664dc7d50307eb73ba9a16dea5d6bde85677ae85d3ed2d8e0"},
 ]
 
+[package.extras]
+dev = ["build (==1.2.1)", "coverage (==7.5.3)", "mypy (==1.10.0)", "pip (==24.1)", "pylint (==3.2.3)", "ruff (==0.5.1)", "twine (==5.1.1)", "uv (==0.2.13)"]
+
 [[package]]
 name = "jsonpatch"
 version = "1.33"
@@ -4360,13 +4363,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "24.1"
+version = "24.2"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "packaging-24.1-py3-none-any.whl", hash = "sha256:5b8f2217dbdbd2f7f384c41c628544e6d52f2d0f53c6d0c3ea61aa5d1d7ff124"},
+    {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"},
-    {file = "packaging-24.1.tar.gz", hash = "sha256:026ed72c8ed3fcce5bf8950572258698927fd1dbda10a5e981cdf0ac37f4f002"},
+    {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"},
 ]
 
 [[package]]
@@ -4432,8 +4435,8 @@ files = [
 [package.dependencies]
 numpy = [
     {version = ">=1.20.3", markers = "python_version < \"3.10\""},
-    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
     {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -5007,7 +5010,7 @@ test = ["pytest", "pytest-xdist", "setuptools"]
 name = "psycopg2"
 version = "2.9.10"
 description = "psycopg2 - Python-PostgreSQL Database Adapter"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "psycopg2-2.9.10-cp310-cp310-win32.whl", hash = "sha256:5df2b672140f95adb453af93a7d669d7a7bf0a56bcd26f1502329166f4a61716"},
@@ -7032,13 +7035,13 @@ test = ["vcrpy (>=1.10.3)"]
 
 [[package]]
 name = "typer"
-version = "0.12.5"
+version = "0.13.0"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "typer-0.12.5-py3-none-any.whl", hash = "sha256:62fe4e471711b147e3365034133904df3e235698399bc4de2b36c8579298d52b"},
+    {file = "typer-0.13.0-py3-none-any.whl", hash = "sha256:d85fe0b777b2517cc99c8055ed735452f2659cd45e451507c76f48ce5c1d00e2"},
-    {file = "typer-0.12.5.tar.gz", hash = "sha256:f592f089bedcc8ec1b974125d64851029c3b1af145f04aca64d69410f0c9b722"},
+    {file = "typer-0.13.0.tar.gz", hash = "sha256:f1c7198347939361eec90139ffa0fd8b3df3a2259d5852a0f7400e476d95985c"},
 ]
 
 [package.dependencies]
@@ -7333,19 +7336,15 @@ validators = "0.33.0"
 
 [[package]]
 name = "webcolors"
-version = "24.8.0"
+version = "24.11.1"
 description = "A library for working with the color formats defined by HTML and CSS."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "webcolors-24.8.0-py3-none-any.whl", hash = "sha256:fc4c3b59358ada164552084a8ebee637c221e4059267d0f8325b3b560f6c7f0a"},
+    {file = "webcolors-24.11.1-py3-none-any.whl", hash = "sha256:515291393b4cdf0eb19c155749a096f779f7d909f7cceea072791cb9095b92e9"},
-    {file = "webcolors-24.8.0.tar.gz", hash = "sha256:08b07af286a01bcd30d583a7acadf629583d1f79bfef27dd2c2c5c263817277d"},
+    {file = "webcolors-24.11.1.tar.gz", hash = "sha256:ecb3d768f32202af770477b8b65f318fa4f566c22948673a977b00d589dd80f6"},
 ]
 
-[package.extras]
-docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"]
-tests = ["coverage[toml]"]
-
 [[package]]
 name = "webencodings"
 version = "0.5.1"
@@ -7375,13 +7374,13 @@ test = ["websockets"]
 
 [[package]]
 name = "wheel"
-version = "0.44.0"
+version = "0.45.0"
 description = "A built-package format for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "wheel-0.44.0-py3-none-any.whl", hash = "sha256:2376a90c98cc337d18623527a97c31797bd02bad0033d41547043a1cbfbe448f"},
+    {file = "wheel-0.45.0-py3-none-any.whl", hash = "sha256:52f0baa5e6522155090a09c6bd95718cc46956d1b51d537ea5454249edb671c7"},
-    {file = "wheel-0.44.0.tar.gz", hash = "sha256:a29c3f2817e95ab89aa4660681ad547c0e9547f20e75b0562fe7723c9a2a9d49"},
+    {file = "wheel-0.45.0.tar.gz", hash = "sha256:a57353941a3183b3d5365346b567a260a0602a0f8a635926a7dede41b94c674a"},
 ]
 
 [package.extras]
@@ -7718,13 +7717,13 @@ propcache = ">=0.2.0"
 
 [[package]]
 name = "zipp"
-version = "3.20.2"
+version = "3.21.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+    {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"},
-    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
+    {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"},
 ]
 
 [package.extras]
@@ -7740,11 +7739,11 @@ cli = []
 filesystem = ["botocore"]
 neo4j = ["neo4j"]
 notebook = []
-postgres = ["psycopg2"]
+postgres = ["asyncpg", "pgvector", "psycopg2"]
 qdrant = ["qdrant-client"]
 weaviate = ["weaviate-client"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9.0,<3.12"
-content-hash = "426fa990f2bdd15fa5be55392beb4cf77dba320f2e95cc503d1c0549d9758d64"
+content-hash = "fb09733ff7a70fb91c5f72ff0c8a8137b857557930a7aa025aad3154de4d8ceb"

pyproject.toml

@@ -42,7 +42,7 @@ aiosqlite = "^0.20.0"
 pandas = "2.0.3"
 filetype = "^1.2.0"
 nltk = "^3.8.1"
-dlt = {extras = ["sqlalchemy"], version = "^1.2.0"}
+dlt = {extras = ["sqlalchemy"], version = "^1.3.0"}
 aiofiles = "^23.2.1"
 qdrant-client = "^1.9.0"
 graphistry = "^0.33.5"
@@ -66,10 +66,10 @@ pydantic-settings = "^2.2.1"
 anthropic = "^0.26.1"
 sentry-sdk = {extras = ["fastapi"], version = "^2.9.0"}
 fastapi-users = {version = "*", extras = ["sqlalchemy"]}
-asyncpg = "^0.29.0"
 alembic = "^1.13.3"
+asyncpg = "^0.29.0"
 pgvector = "^0.3.5"
-psycopg2 = {version = "^2.9.10", optional = true}
+psycopg2 = "^2.9.10"
 
 [tool.poetry.extras]
 filesystem = ["s3fs", "botocore"]
@@ -77,9 +77,10 @@ cli = ["pipdeptree", "cron-descriptor"]
 weaviate = ["weaviate-client"]
 qdrant = ["qdrant-client"]
 neo4j = ["neo4j"]
-postgres = ["psycopg2"]
+postgres = ["psycopg2", "pgvector", "asyncpg"]
 notebook = ["ipykernel", "overrides", "ipywidgets", "jupyterlab", "jupyterlab_widgets", "jupyterlab-server", "jupyterlab-git"]
 
+
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.0"
 pytest-asyncio = "^0.21.1"