diff --git a/.github/workflows/weighted_edges_tests.yml b/.github/workflows/weighted_edges_tests.yml index 874ef6ea4..2b4a043bf 100644 --- a/.github/workflows/weighted_edges_tests.yml +++ b/.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_API_KEY: ${{ secrets.LLM_API_KEY }} + LLM_ENDPOINT: https://api.openai.com/v1 + LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} LLM_API_VERSION: "2024-02-01" - EMBEDDING_PROVIDER: openai - EMBEDDING_MODEL: text-embedding-3-small - EMBEDDING_ENDPOINT: https://api.openai.com/v1/ - EMBEDDING_API_KEY: ${{ secrets.LLM_API_KEY }} - EMBEDDING_API_VERSION: "2024-02-01" + EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }} + EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }} + EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }} + EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }} 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_API_KEY: ${{ secrets.LLM_API_KEY }} + LLM_ENDPOINT: https://api.openai.com/v1 + LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} LLM_API_VERSION: "2024-02-01" - EMBEDDING_PROVIDER: openai - EMBEDDING_MODEL: text-embedding-3-small - EMBEDDING_ENDPOINT: https://api.openai.com/v1/ - EMBEDDING_API_KEY: ${{ secrets.LLM_API_KEY }} - EMBEDDING_API_VERSION: "2024-02-01" + EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }} + EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }} + EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }} + EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }} + steps: - name: Check out repository uses: actions/checkout@v4 diff --git a/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py b/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py index 5357f3d7c..1e16642b5 100644 --- a/cognee/infrastructure/databases/hybrid/neptune_analytics/NeptuneAnalyticsAdapter.py +++ b/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 diff --git a/cognee/modules/retrieval/cypher_search_retriever.py b/cognee/modules/retrieval/cypher_search_retriever.py index 9978f2536..01816f3df 100644 --- a/cognee/modules/retrieval/cypher_search_retriever.py +++ b/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