Merge branch 'dev' into multi-tenancy

.github/workflows/weighted_edges_tests.yml

@@ -2,7 +2,7 @@ name: Weighted Edges Tests
 
 on:
   push:
-    branches: [ main, weighted_edges ]
+    branches: [ main, dev, weighted_edges ]
     paths:
       - 'cognee/modules/graph/utils/get_graph_from_model.py'
       - 'cognee/infrastructure/engine/models/Edge.py'
@@ -10,7 +10,7 @@ on:
       - 'examples/python/weighted_edges_example.py'
       - '.github/workflows/weighted_edges_tests.yml'
   pull_request:
-    branches: [ main ]
+    branches: [ main, dev ]
     paths:
       - 'cognee/modules/graph/utils/get_graph_from_model.py'
       - 'cognee/infrastructure/engine/models/Edge.py'
@@ -32,7 +32,7 @@ jobs:
     env:
       LLM_PROVIDER: openai
       LLM_MODEL: gpt-5-mini
-      LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
+      LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
     steps:
       - name: Check out repository
@@ -67,14 +67,13 @@ jobs:
     env:
       LLM_PROVIDER: openai
       LLM_MODEL: gpt-5-mini
-      LLM_ENDPOINT: https://api.openai.com/v1/
+      LLM_ENDPOINT: https://api.openai.com/v1
-      LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
+      LLM_API_KEY: ${{ secrets.OPENAI_API_KEY  }}
       LLM_API_VERSION: "2024-02-01"
-      EMBEDDING_PROVIDER: openai
+      EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }}
-      EMBEDDING_MODEL: text-embedding-3-small
+      EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }}
-      EMBEDDING_ENDPOINT: https://api.openai.com/v1/
+      EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
-      EMBEDDING_API_KEY: ${{ secrets.LLM_API_KEY }}
+      EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
-      EMBEDDING_API_VERSION: "2024-02-01"
     steps:
       - name: Check out repository
         uses: actions/checkout@v4
@@ -108,14 +107,14 @@ jobs:
     env:
       LLM_PROVIDER: openai
       LLM_MODEL: gpt-5-mini
-      LLM_ENDPOINT: https://api.openai.com/v1/
+      LLM_ENDPOINT: https://api.openai.com/v1
-      LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
+      LLM_API_KEY: ${{ secrets.OPENAI_API_KEY  }}
       LLM_API_VERSION: "2024-02-01"
-      EMBEDDING_PROVIDER: openai
+      EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }}
-      EMBEDDING_MODEL: text-embedding-3-small
+      EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }}
-      EMBEDDING_ENDPOINT: https://api.openai.com/v1/
+      EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
-      EMBEDDING_API_KEY: ${{ secrets.LLM_API_KEY }}
+      EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
-      EMBEDDING_API_VERSION: "2024-02-01"
+
     steps:
       - name: Check out repository
         uses: actions/checkout@v4

cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py

@@ -416,6 +416,15 @@ class NeptuneAnalyticsAdapter(NeptuneGraphDB, VectorDBInterface):
         self._client.query(f"MATCH (n :{self._VECTOR_NODE_LABEL}) DETACH DELETE n")
         pass
 
+    async def is_empty(self) -> bool:
+        query = """
+        MATCH (n)
+        RETURN true
+        LIMIT 1;
+        """
+        query_result = await self._client.query(query)
+        return len(query_result) == 0
+
     @staticmethod
     def _get_scored_result(
         item: dict, with_vector: bool = False, with_score: bool = False

cognee/modules/retrieval/cypher_search_retriever.py

@@ -1,4 +1,6 @@
 from typing import Any, Optional
+from fastapi.encoders import jsonable_encoder
+
 from cognee.infrastructure.databases.graph import get_graph_engine
 from cognee.modules.retrieval.base_retriever import BaseRetriever
 from cognee.modules.retrieval.utils.completion import generate_completion
@@ -50,7 +52,7 @@ class CypherSearchRetriever(BaseRetriever):
                 logger.warning("Search attempt on an empty knowledge graph")
                 return []
 
-            result = await graph_engine.query(query)
+            result = jsonable_encoder(await graph_engine.query(query))
         except Exception as e:
             logger.error("Failed to execture cypher search retrieval: %s", str(e))
             raise CypherSearchError() from e