how can i query from non-empty graph which is created manully?

[zuitbjc1096]

🐛 Describe the bug

I creat a graph mannully. Then I want to use mem0 to search from this non-empty graph. But result in empty.
"graph_store": {
"provider": "neo4j",
"config": {
"url": "bolt://localhost:7687",
"username": "neo4j",
"password": "neo4j123"
}
},
"version": "v1.1"

[Cirr0e]

Hi there! I understand you're having trouble querying a manually created graph in Mem0 with Neo4j, and your searches are returning empty results. Let me help you troubleshoot this.

Based on the documentation and the error context, here are some specific recommendations:

1. Configuration Verification

   • Ensure your configuration exactly matches the documentation:

     config = {
         "graph_store": {
             "provider": "neo4j",
             "config": {
                 "url": "bolt://localhost:7687",
                 "username": "neo4j",
                 "password": "neo4j123"
             }
         },
         "version": "v1.1"  # Critical: Must be exactly "v1.1"
     }

2. Pre-Requisites for Searching

   • Before searching, you MUST add memories to the graph
   • Example of adding memories:

     m.add("Your first memory text", user_id="alice")
     m.add("Another memory", user_id="alice")

3. APOC Plugins Requirement

   • For local Neo4j, install APOC plugins
   • This enables advanced graph functionality

4. Search Methodology

   • Always specify a user_id when searching
   • Example:

     results = m.search("Your query", user_id="alice")

5. Potential Neo4j Setup Checks

   • Verify Neo4j is running
   • Check connection parameters
   • Ensure APOC plugins are properly installed

The key is ensuring you've:
✅ Used version "v1.1"
✅ Added memories before searching
✅ Specified a consistent user_id
✅ Have APOC plugins installed for local Neo4j

Would you mind sharing your exact code for adding memories and searching? That would help me diagnose the specific issue more precisely.

[zuitbjc1096]

Above all is all my code. I need to search something from the neo4j graph which is created manully before Memory is initialized , which means that graph is not build by m.add(). In other words, Can i directly search from a graph not build by mem0?

[Cirr0e]

Hi there! I understand you want to search a manually created Neo4j graph that wasn't built using Mem0's standard m.add() method.

Based on the documentation and your specific requirement, here are a few approaches you can consider:

1. Direct Neo4j Querying:
   Since Mem0 uses Neo4j as its graph provider, you might be able to use direct Neo4j Cypher queries. Here's a potential approach:

from mem0 import Memory
from neo4j import GraphDatabase

config = {
    "graph_store": {
        "provider": "neo4j",
        "config": {
            "url": "bolt://localhost:7687",
            "username": "neo4j",
            "password": "neo4j123"
        }
    },
    "version": "v1.1"
}

m = Memory.from_config(config_dict=config)

# Direct Neo4j Driver Access
neo4j_driver = GraphDatabase.driver(
    "bolt://localhost:7687", 
    auth=("neo4j", "neo4j123")
)

def custom_graph_search(query):
    with neo4j_driver.session() as session:
        result = session.run(query)
        return [record for record in result]

# Example Cypher query
results = custom_graph_search("MATCH (n) RETURN n LIMIT 10")

2. Custom Prompt Configuration:
   Mem0 allows custom prompts for entity extraction. You might leverage this to adapt to your manually created graph:

config = {
    "graph_store": {
        "provider": "neo4j",
        "config": {
            "url": "bolt://localhost:7687",
            "username": "neo4j",
            "password": "neo4j123",
            "custom_prompt": "Extract entities specifically from my pre-existing graph structure"
        }
    },
    "version": "v1.1"
}

Key Recommendations:
✅ Ensure Neo4j is running with APOC plugins
✅ Use Bolt URL for local connections
✅ Set version to "v1.1"
✅ Have a consistent user_id when searching

Potential Risks:

• Custom graph might not fully integrate with Mem0's automatic relationship extraction
• May require manual mapping of graph entities
• Performance could vary based on graph complexity

Would you be willing to share more details about:

1. Your graph's structure
2. The specific type of queries you want to run
3. How the graph was initially created in Neo4j

This will help me provide a more tailored solution! 🕵️‍♂️🔍

[zuitbjc1096]

Thanks! You help me a lot!
Details about Graph:

1. created by self-exploring an android app
2. page nodes' properties:

element node‘s properties:

4. type of nodes include page-node, elment-node, app-node
5. graph is a representation of app, nodes is elements and edge is operation between nodes

my query may be:
which elements can be long_press ?
how can i search a city?

[Cirr0e]

Hi there! Thanks for providing those additional details about your graph structure. I can help you query your manually created graph for both the long_press operations and city searches.

For your specific queries, here's how you can approach this using direct Neo4j queries since you're working with a custom graph structure:

1. To find elements that can be long_pressed:

from mem0 import Memory
from neo4j import GraphDatabase

config = {
    "graph_store": {
        "provider": "neo4j",
        "config": {
            "url": "bolt://localhost:7687",
            "username": "neo4j",
            "password": "neo4j123"
        }
    },
    "version": "v1.1"
}

# Initialize Neo4j driver
driver = GraphDatabase.driver(
    "bolt://localhost:7687",
    auth=("neo4j", "neo4j123")
)

def find_long_pressable_elements():
    with driver.session() as session:
        # Query elements where operation_long_press property exists and is not null/empty
        query = """
        MATCH (n:element_node)
        WHERE n.operation_long_press IS NOT NULL 
        AND n.operation_long_press <> ''
        RETURN n.name, n.operation_long_press, n.page_name
        """
        result = session.run(query)
        return [dict(record["n"]) for record in result]

# For city search, assuming cities might be in text or name properties:
def search_city(city_name):
    with driver.session() as session:
        query = """
        MATCH (n:element_node)
        WHERE n.text CONTAINS $city_name 
        OR n.name CONTAINS $city_name
        RETURN n
        """
        result = session.run(query, city_name=city_name)
        return [dict(record["n"]) for record in result]

To use these functions:

# Find long-pressable elements
long_press_elements = find_long_pressable_elements()
print("Elements that can be long-pressed:", long_press_elements)

# Search for a specific city
city_results = search_city("New York")
print("City search results:", city_results)

Important notes:

1. Make sure to adjust the node labels and property names if they're different in your graph
2. The city search function assumes cities might be found in either the text or name properties
3. You may need to modify the queries based on your specific graph structure and relationships

Potential risks to be aware of:

• These queries will return all matching results, which might be large for big graphs
• Case sensitivity might affect search results
• Performance might vary depending on whether you have appropriate indexes set up

Would you like me to:

1. Modify these queries to include additional properties in the results?
2. Add support for searching through relationships between nodes?
3. Include additional filtering criteria?

Let me know if you need any clarification or have questions about implementing these queries!