fix: remove unnecessary files

.gitignore

@@ -165,3 +165,5 @@ cython_debug/
 .vscode/
 database/data/
 cognee/data/
+
+.DS_Store

cognee.ipynb

@@ -68,6 +68,30 @@
         "graph_url = await render_graph(graph, graph_type = \"networkx\")\n",
         "print(graph_url)\n"
       ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "6edb9cac",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client\n",
+        "from cognee.shared.data_models import GraphDBType\n",
+        "from cognee import search, SearchType\n",
+        "\n",
+        "graph_client = get_graph_client(GraphDBType.NETWORKX)\n",
+        "await graph_client.load_graph_from_file()\n",
+        "\n",
+        "graph = graph_client.graph\n",
+        "\n",
+        "query_params = {\n",
+        "    SearchType.SIMILARITY: {'query': 'nacin vrsenja kontrole tehnicke dokumentacije'}\n",
+        "}\n",
+        "\n",
+        "results = await search(graph, query_params)\n",
+        "print(results)"
+      ]
     }
   ],
   "metadata": {
@@ -91,4 +115,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 5
-}
+}

cognee/__init__.py

@@ -1,4 +1,4 @@
 from .api.v1.add.add import add
 from .api.v1.cognify.cognify import cognify
 from .api.v1.list_datasets.list_datasets import list_datasets
-from .api.v1.search import search
+from .api.v1.search.search import search, SearchType

cognee/api/v1/cognify/cognify.py

@@ -35,7 +35,7 @@ aclient = instructor.patch(OpenAI())
 
 USER_ID = "default_user"
 
-async def cognify(dataset_name: str):
+async def cognify(dataset_name: str = "root"):
     """This function is responsible for the cognitive processing of the content."""
 
     db = DuckDBAdapter()

cognee/api/v1/search/search.py

@@ -1,13 +1,12 @@
 """ This module contains the search function that is used to search for nodes in the graph."""
+import asyncio
 from enum import Enum, auto
 from typing import Dict, Any, Callable, List
 
-from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client
 from cognee.modules.search.graph.search_adjacent import search_adjacent
 from cognee.modules.search.vector.search_similarity import search_similarity
 from cognee.modules.search.graph.search_categories import search_categories
 from cognee.modules.search.graph.search_neighbour import search_neighbour
-from cognee.shared.data_models import GraphDBType
 
 
 class SearchType(Enum):
@@ -17,7 +16,7 @@ class SearchType(Enum):
     NEIGHBOR = auto()
 
 
-async def complex_search(graph, query_params: Dict[SearchType, Dict[str, Any]]) -> List:
+async def search(graph, query_params: Dict[SearchType, Dict[str, Any]]) -> List:
     search_functions: Dict[SearchType, Callable] = {
         SearchType.ADJACENT: search_adjacent,
         SearchType.SIMILARITY: search_similarity,
@@ -47,21 +46,18 @@ async def complex_search(graph, query_params: Dict[SearchType, Dict[str, Any]])
 
     return results
 
-if __name__ == "__main__":
+# if __name__ == "__main__":
-    import asyncio
+#     import asyncio
 
+#     query_params = {
+#         SearchType.SIMILARITY: {'query': 'your search query here'}
+#     }
+#     async def main():
+#         graph_client = get_graph_client(GraphDBType.NETWORKX)
 
+#         await graph_client.load_graph_from_file()
+#         graph = graph_client.graph
+#         results = await complex_search(graph, query_params)
+#         print(results)
 
-
+#     asyncio.run(main())
-    query_params = {
-        SearchType.SIMILARITY: {'query': 'your search query here'}
-    }
-    async def main():
-        graph_client = get_graph_client(GraphDBType.NETWORKX)
-
-        await graph_client.load_graph_from_file()
-        graph = graph_client.graph
-        results = await complex_search(graph, query_params)
-        print(results)
-
-    asyncio.run(main())

cognee/data/cognee/cognee.db/.lock

@@ -1 +0,0 @@
-tmp lock file

cognee/data/cognee/cognee.db/meta.json

@@ -1 +0,0 @@
-{"collections": {"7480d8b3-140d-48d4-a374-1152458cf249": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}, "b1d1fd8a-d890-442d-9e69-6ae5a9b97a0e": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}, "375f689c-92aa-489a-ad35-2655f7017f30": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}, "f0a288e0-48eb-46e2-81da-a7f1da560593": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}, "7b4568f4-1e3f-42f3-8831-6b2d569fb384": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}, "80de74b2-7ef5-4f66-a34d-5ff13ab44882": {"vectors": {"content": {"size": 3072, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}}, "shard_number": null, "sharding_method": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null, "sparse_vectors": null}}, "aliases": {}}

poetry.lock

@@ -8048,7 +8048,6 @@ notebook = ["overrides"]
 parquet = ["pyarrow"]
 pinecone = []
 postgres = []
-qdrant = ["qdrant-client"]
 redshift = []
 s3 = []
 snowflake = []
@@ -8058,4 +8057,4 @@ weaviate = []
 [metadata]
 lock-version = "2.0"
 python-versions = "~3.10"
-content-hash = "48d8cbd3319b1370abddeb2ff6c32cf6be01bdaff150d466129a1667b8cce94f"
+content-hash = "37a0db9a6a86b71a35c91ac5ef86204d76529033260032917906a907bffc8216"

pyproject.toml

@@ -72,7 +72,6 @@ athena = ["pyathena", "pyarrow", "s3fs", "botocore"]
 weaviate = ["weaviate-client"]
 mssql = ["pyodbc"]
 synapse = ["pyodbc", "adlfs", "pyarrow"]
-qdrant = ["qdrant-client"]
 databricks = ["databricks-sql-connector"]
 lancedb = ["lancedb"]
 pinecone = ["pinecone-client"]