Neo4j Agent Memory

async with MemoryClient(settings) as memory:
    # Short-term: store conversations
    await memory.short_term.add_message(session_id, "user", "Find Italian restaurants near me")

    # Long-term: build a knowledge graph
    await memory.long_term.add_entity("La Trattoria", "ORGANIZATION", subtype="COMPANY")

    # Reasoning: record how the agent solved problems
    trace = await memory.reasoning.start_trace(session_id, task="Restaurant search")
    await memory.reasoning.record_tool_call(step.id, "search_api", {"query": "Italian"}, results)
    await memory.reasoning.complete_trace(trace.id, outcome="Recommended La Trattoria", success=True)

    # Get unified context for LLM prompts
    context = await memory.get_context("restaurant recommendation", session_id=session_id)

pip install neo4j-agent-memory[openai]

import asyncio
from pydantic import SecretStr
from neo4j_agent_memory import MemoryClient, MemorySettings

async def main():
    settings = MemorySettings(
        neo4j={"uri": "bolt://localhost:7687", "password": SecretStr("password")}
    )

    async with MemoryClient(settings) as memory:
        # Store a conversation
        await memory.short_term.add_message("user-123", "user", "I love Italian food!")

        # Build knowledge automatically
        await memory.long_term.add_preference("food", "Loves Italian cuisine", importance=0.9)

        # Get combined context for your LLM
        context = await memory.get_context("restaurant recommendation", session_id="user-123")
        print(context)

asyncio.run(main())

                         ┌─────────────────────────────────────────────┐
                         │              MemoryClient                   │
                         ├───────────────┬──────────────┬──────────────┤
                         │  Short-Term   │  Long-Term   │  Reasoning   │
                         │  Memory       │  Memory      │  Memory      │
                         ├───────────────┴──────────────┴──────────────┤
                         │          Extraction Pipeline                 │
                         │  ┌───────┬─────────┬────────┬─────┐        │
                         │  │ spaCy │ GLiNER2 │ GLiREL │ LLM │        │
                         │  └───────┴─────────┴────────┴─────┘        │
                         ├─────────────────────────────────────────────┤
                         │        Neo4j Graph Database                  │
                         │   Nodes · Relationships · Vectors · Spatial │
                         └─────────────────────────────────────────────┘