Graph memory example throws error with Neo4j

[except-pass]

🐛 Describe the bug

What happened:
In the Graph memory example notebook (https://colab.research.google.com/drive/1PfIGVHnliIlG2v8cx0g45TF0US-jRPZ1?usp=sharing) attempting to add a memory throws this error

m.add("I like painting", user_id=user_id), display_graph()

WARNING:neo4j.notifications:Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: embedding)} {position: line: 16, column: 84, offset: 1070} for query: '\n            MATCH (n)\n            WHERE n.embedding IS NOT NULL AND n.user_id = $user_id\n            WITH n, \n                round(reduce(dot = 0.0, i IN range(0, size(n.embedding)-1) | dot + n.embedding[i] * $n_embedding[i]) / \n                (sqrt(reduce(l2 = 0.0, i IN range(0, size(n.embedding)-1) | l2 + n.embedding[i] * n.embedding[i])) * \n                sqrt(reduce(l2 = 0.0, i IN range(0, size($n_embedding)-1) | l2 + $n_embedding[i] * $n_embedding[i]))), 4) AS similarity\n            WHERE similarity >= $threshold\n            MATCH (n)-[r]->(m)\n            RETURN n.name AS source, elementId(n) AS source_id, type(r) AS relation, elementId(r) AS relation_id, m.name AS destination, elementId(m) AS destination_id, similarity\n            UNION\n            MATCH (n)\n            WHERE n.embedding IS NOT NULL AND n.user_id = $user_id\n            WITH n, \n                round(reduce(dot = 0.0, i IN range(0, size(n.embedding)-1) | dot + n.embedding[i] * $n_embedding[i]) / \n                (sqrt(reduce(l2 = 0.0, i IN range(0, size(n.embedding)-1) | l2 + n.embedding[i] * n.embedding[i])) * \n                sqrt(reduce(l2 = 0.0, i IN range(0, size($n_embedding)-1) | l2 + $n_embedding[i] * $n_embedding[i]))), 4) AS similarity\n            WHERE similarity >= $threshold\n            MATCH (m)-[r]->(n)\n            RETURN m.name AS source, elementId(m) AS source_id, type(r) AS relation, elementId(r) AS relation_id, n.name AS destination, elementId(n) AS destination_id, similarity\n            ORDER BY similarity DESC\n            '

How to recreate:
I set my OPENAI_API_KEY, NEO4J_URI, NEO4J_USER, and NEO4J_PASSWORD environment variables. I can confirm I can log into Neo4j.

I am running Mem0 locally with a Neo4j docker container. My neo4j container is

services:
  neo4j:
    container_name: neo4j
    image: neo4j:latest 
    ports:
      - 7474:7474
      - 7687:7687
    environment:
      - NEO4J_AUTH=neo4j/${NEO4J_PASSWORD}
      - NEO4J_apoc_export_file_enabled=true
      - NEO4J_apoc_import_file_enabled=true
      - NEO4J_apoc_import_file_use__neo4j__config=true
      - NEO4J_PLUGINS=["apoc", "graph-data-science"]
    volumes:
      - ./neo4j_db/data:/data
      - ./neo4j_db/logs:/logs
      - ./neo4j_db/import:/var/lib/neo4j/import
      - ./neo4j_db/plugins:/plugins

My pip freeze is

aiohappyeyeballs==2.4.0
aiohttp==3.10.6
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.6.0
asttokens==2.4.1
async-timeout==4.0.3
attrs==24.2.0
backoff==2.2.1
certifi==2024.8.30
charset-normalizer==3.3.2
comm==0.2.2
contourpy==1.3.0
cycler==0.12.1
dataclasses-json==0.6.7
debugpy==1.8.6
decorator==5.1.1
distro==1.9.0
exceptiongroup==1.2.2
executing==2.1.0
fonttools==4.54.1
frozenlist==1.4.1
grandalf==0.8
greenlet==3.1.1
grpcio==1.66.1
grpcio-tools==1.66.1
h11==0.14.0
h2==4.1.0
hpack==4.0.0
httpcore==1.0.5
httpx==0.27.2
hyperframe==6.0.1
idna==3.10
interchange==2021.0.4
ipykernel==6.29.5
ipython==8.27.0
jedi==0.19.1
jiter==0.5.0
jsonpatch==1.33
jsonpointer==3.0.0
jupyter_client==8.6.3
jupyter_core==5.7.2
kiwisolver==1.4.7
langchain==0.2.16
langchain-community==0.2.17
langchain-core==0.2.41
langchain-text-splitters==0.2.4
langsmith==0.1.128
marshmallow==3.22.0
matplotlib==3.9.2
matplotlib-inline==0.1.7
mem0ai==0.1.16
monotonic==1.6
multidict==6.1.0
mypy-extensions==1.0.0
neo4j==5.24.0
nest-asyncio==1.6.0
netgraph==4.13.2
networkx==3.3
numpy==1.26.4
openai==1.48.0
orjson==3.10.7
packaging==24.1
pansi==2020.7.3
parso==0.8.4
pexpect==4.9.0
pillow==10.4.0
platformdirs==4.3.6
portalocker==2.10.1
posthog==3.6.6
prompt_toolkit==3.0.48
protobuf==5.28.2
psutil==6.0.0
ptyprocess==0.7.0
pure_eval==0.2.3
py2neo==2021.2.4
pydantic==2.9.2
pydantic_core==2.23.4
Pygments==2.18.0
pyparsing==3.1.4
python-dateutil==2.9.0.post0
python-dotenv==1.0.1
pytz==2024.2
PyYAML==6.0.2
pyzmq==26.2.0
qdrant-client==1.11.3
rank-bm25==0.2.2
rectangle-packer==2.0.2
requests==2.32.3
scipy==1.14.1
six==1.16.0
sniffio==1.3.1
SQLAlchemy==2.0.35
stack-data==0.6.3
tenacity==8.5.0
tornado==6.4.1
tqdm==4.66.5
traitlets==5.14.3
typing-inspect==0.9.0
typing_extensions==4.12.2
urllib3==2.2.3
wcwidth==0.2.13
yarl==1.12.1

[prateekchhikara]

I think it is not an error, just a warning. Did you try checking whether the nodes are getting created or not? @except-pass

[except-pass]

The nodes were not created.

…

On Wed, Sep 25, 2024, 5:23 PM Prateek Chhikara ***@***.***> wrote: I think it is not an error, just a warning. Did you try checking whether the nodes are getting created or not? @except-pass <https://github.com/except-pass> — Reply to this email directly, view it on GitHub <#1906 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AUTRZXGCMQG66SRA77AZ6LDZYMSTXAVCNFSM6AAAAABO3BVBGWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGNZVGI4DOMZTGM> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[prateekchhikara]

Let me take a look. We never faced this problem before.

[Ashoka74]

Hello, just to mention I have the same issue. I can see the graph/nodes on my collab nb. I can query on Neo4j workspace 'query' section but I can't see the graph on the 'explore' section

[prateekchhikara]

@except-pass if you are using Neo4j locally, you need to install APOC plugins. Please check the docs https://docs.mem0.ai/open-source/graph_memory/overview

[prateekchhikara]

@Ashoka74 you can check out Neo4j documentation about explore. https://neo4j.com/docs/aura/preview/explore/introduction/

[bpuskarevic]

Hi, I have a same problem when trying to call:

result = m.add("Likes to play cricket on weekends", user_id="alice", metadata={"category": "hobbies"})

WARNING:neo4j.notifications:Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name)} {position: line: 20, column: 22, offset: 1336} for query: '\n MATCH (n)\n WHERE n.embedding IS NOT NULL AND n.user_id = $user_id\n WITH n, \n round(reduce(dot = 0.0, i IN range(0, size(n.embedding)-1) | dot + n.embedding[i] * $n_embedding[i]) / \n (sqrt(reduce(l2 = 0.0, i IN range(0, size(n.embedding)-1) | l2 + n.embedding[i] * n.embedding[i])) * \n sqrt(reduce(l2 = 0.0, i IN range(0, size($n_embedding)-1) | l2 + $n_embedding[i] * $n_embedding[i]))), 4) AS similarity\n WHERE similarity >= $threshold\n MATCH (n)-[r]->(m)\n RETURN n.name AS source, elementId(n) AS source_id, type(r) AS relation, elementId(r) AS relation_id, m.name AS destination, elementId(m) AS destination_id, similarity\n UNION\n MATCH (n)\n WHERE n.embedding IS NOT NULL AND n.user_id = $user_id\n WITH n, \n round(reduce(dot = 0.0, i IN range(0, size(n.embedding)-1) | dot + n.embedding[i] * $n_embedding[i]) / \n (sqrt(reduce(l2 = 0.0, i IN range(0, size(n.embedding)-1) | l2 + n.embedding[i] * n.embedding[i])) * \n sqrt(reduce(l2 = 0.0, i IN range(0, size($n_embedding)-1) | l2 + $n_embedding[i] * $n_embedding[i]))), 4) AS similarity\n WHERE similarity >= $threshold\n MATCH (m)-[r]->(n)\n RETURN m.name AS source, elementId(m) AS source_id, type(r) AS relation, elementId(r) AS relation_id, n.name AS destination, elementId(n) AS destination_id, similarity\n ORDER BY similarity DESC\n

I am using neo4j Aura.

Any help is welcome!