Neo4j

import os

from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.neo4j import Neo4jTools
from dotenv import load_dotenv

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    load_dotenv()

    # Optionally load from environment or hardcode here
    uri = os.getenv("NEO4J_URI", "bolt://localhost:7687")
    user = os.getenv("NEO4J_USERNAME", "neo4j")
    password = os.getenv("NEO4J_PASSWORD", "password")

    # Example 1: All functions enabled (default)
    neo4j_toolkit_all = Neo4jTools(
        uri=uri,
        user=user,
        password=password,
        all=True,
    )

    # Example 2: Specific functions only
    neo4j_toolkit_specific = Neo4jTools(
        uri=uri,
        user=user,
        password=password,
        enable_list_labels=True,
        enable_get_schema=True,
        enable_list_relationships=False,
        enable_run_cypher=False,
    )

    # Example 3: Default behavior
    neo4j_toolkit = Neo4jTools(
        uri=uri,
        user=user,
        password=password,
    )

    description = """You are a Neo4j expert assistant who can help with all operations in a Neo4j database by understanding natural language context and translating it into Cypher queries."""

    instructions = [
        "Analyze the user's context and convert it into Cypher queries that respect the database's current schema.",
        "Before performing any operation, query the current schema (e.g., check for existing nodes or relationships).",
        "If the necessary schema elements are missing, dynamically create or extend the schema using best practices, ensuring data integrity and consistency.",
        "If properties are required or provided for nodes or relationships, ensure that they are added correctly do not overwrite existing ones and do not create duplicates and do not create extra nodes.",
        "Optionally, use or implement a dedicated function to retrieve the current schema (e.g., via a 'get_schema' function).",
        "Ensure that all operations maintain data integrity and follow best practices.",
        "Intelligently create relationships if bi-directional relationships are required, and understand the users intent and create relationships accordingly.",
        "Intelligently handle queries that involve multiple nodes and relationships, understand has to be nodes, properties, and relationships and maintain best practices.",
        "Handle errors gracefully and provide clear feedback to the user.",
    ]

    # Example: Use with AGNO Agent
    agent = Agent(
        model=OpenAIChat(id="o3-mini"),
        tools=[neo4j_toolkit],
        markdown=True,
        description=description,
        instructions=instructions,
    )

    # Agent handles tool usage automatically via LLM reasoning
    agent.print_response(
        "Add some nodes in my graph to represent a person with the name John Doe and a person with the name Jane Doe, and they belong to company 'X' and they are friends."
    )

    agent.print_response("What is the schema of my graph?")

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno
git checkout d703c34f3abf3c41275d3fb2da6e0518a8881f24

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

uv pip install agno neo4j openai python-dotenv

# Export relevant API keys
export NEO4J_PASSWORD="password"
export NEO4J_URI="bolt://localhost:7687"
export NEO4J_USERNAME="neo4j"
export OPENAI_API_KEY="***"

python cookbook/91_tools/neo4j_tools.py