add entity type validation handling (#320)

* add entity type validation handling

* bump version
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Preston Rasmussen 2025-04-04 13:53:04 -04:00 committed by GitHub
parent fb37565112
commit f4dd39128c
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5 changed files with 86 additions and 27 deletions

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@ -65,3 +65,11 @@ class SearchRerankerError(GraphitiError):
def __init__(self, text: str):
self.message = text
super().__init__(self.message)
class EntityTypeValidationError(GraphitiError):
"""Raised when an entity type uses protected attribute names."""
def __init__(self, entity_type: str, entity_type_attribute: str):
self.message = f'{entity_type_attribute} cannot be used as an attribute for {entity_type} as it is a protected attribute name.'
super().__init__(self.message)

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@ -76,6 +76,7 @@ from graphiti_core.utils.maintenance.node_operations import (
resolve_extracted_nodes,
)
from graphiti_core.utils.maintenance.temporal_operations import get_edge_contradictions
from graphiti_core.utils.ontology_utils.entity_types_utils import validate_entity_types
logger = logging.getLogger(__name__)
@ -319,6 +320,8 @@ class Graphiti:
entity_edges: list[EntityEdge] = []
now = utc_now()
validate_entity_types(entity_types)
previous_episodes = (
await self.retrieve_episodes(
reference_time, last_n=RELEVANT_SCHEMA_LIMIT, group_ids=[group_id]

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@ -0,0 +1,37 @@
"""
Copyright 2024, Zep Software, Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from pydantic import BaseModel
from graphiti_core.errors import EntityTypeValidationError
from graphiti_core.nodes import EntityNode
def validate_entity_types(
entity_types: dict[str, BaseModel] | None,
) -> bool:
if entity_types is None:
return True
entity_node_field_names = EntityNode.model_fields.keys()
for entity_type_name, entity_type_model in entity_types.items():
entity_type_field_names = entity_type_model.model_fields.keys()
for entity_type_field_name in entity_type_field_names:
if entity_type_field_name in entity_node_field_names:
raise EntityTypeValidationError(entity_type_name, entity_type_field_name)
return True

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@ -1,8 +1,15 @@
# Graphiti MCP Server
Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents operating in dynamic environments. Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti continuously integrates user interactions, structured and unstructured enterprise data, and external information into a coherent, queryable graph. The framework supports incremental data updates, efficient retrieval, and precise historical queries without requiring complete graph recomputation, making it suitable for developing interactive, context-aware AI applications.
Graphiti is a framework for building and querying temporally-aware knowledge graphs, specifically tailored for AI agents
operating in dynamic environments. Unlike traditional retrieval-augmented generation (RAG) methods, Graphiti
continuously integrates user interactions, structured and unstructured enterprise data, and external information into a
coherent, queryable graph. The framework supports incremental data updates, efficient retrieval, and precise historical
queries without requiring complete graph recomputation, making it suitable for developing interactive, context-aware AI
applications.
This is an experimental Model Context Protocol (MCP) server implementation for Graphiti. The MCP server exposes Graphiti's key functionality through the MCP protocol, allowing AI assistants to interact with Graphiti's knowledge graph capabilities.
This is an experimental Model Context Protocol (MCP) server implementation for Graphiti. The MCP server exposes
Graphiti's key functionality through the MCP protocol, allowing AI assistants to interact with Graphiti's knowledge
graph capabilities.
## Features
@ -59,7 +66,7 @@ uv run graphiti_mcp_server.py
With options:
```bash
uv run graphiti_mcp_server.py --model gpt-4o --transport sse
uv run graphiti_mcp_server.py --model gpt-4o-mini --transport sse
```
Available arguments:
@ -72,7 +79,8 @@ Available arguments:
### Docker Deployment
The Graphiti MCP server can be deployed using Docker. The Dockerfile uses `uv` for package management, ensuring consistent dependency installation.
The Graphiti MCP server can be deployed using Docker. The Dockerfile uses `uv` for package management, ensuring
consistent dependency installation.
#### Environment Configuration
@ -80,25 +88,25 @@ Before running the Docker Compose setup, you need to configure the environment v
1. **Using a .env file** (recommended):
- Copy the provided `.env.example` file to create a `.env` file:
```bash
cp .env.example .env
```
- Edit the `.env` file to set your OpenAI API key and other configuration options:
```
# Required for LLM operations
OPENAI_API_KEY=your_openai_api_key_here
MODEL_NAME=gpt-4o
# Optional: OPENAI_BASE_URL only needed for non-standard OpenAI endpoints
# OPENAI_BASE_URL=https://api.openai.com/v1
```
- The Docker Compose setup is configured to use this file if it exists (it's optional)
- Copy the provided `.env.example` file to create a `.env` file:
```bash
cp .env.example .env
```
- Edit the `.env` file to set your OpenAI API key and other configuration options:
```
# Required for LLM operations
OPENAI_API_KEY=your_openai_api_key_here
MODEL_NAME=gpt-4o-mini
# Optional: OPENAI_BASE_URL only needed for non-standard OpenAI endpoints
# OPENAI_BASE_URL=https://api.openai.com/v1
```
- The Docker Compose setup is configured to use this file if it exists (it's optional)
2. **Using environment variables directly**:
- You can also set the environment variables when running the Docker Compose command:
```bash
OPENAI_API_KEY=your_key MODEL_NAME=gpt-4o docker compose up
```
- You can also set the environment variables when running the Docker Compose command:
```bash
OPENAI_API_KEY=your_key MODEL_NAME=gpt-4o-mini docker compose up
```
#### Neo4j Configuration
@ -154,7 +162,7 @@ To use the Graphiti MCP server with an MCP-compatible client, configure it to co
"NEO4J_USER": "neo4j",
"NEO4J_PASSWORD": "demodemo",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"MODEL_NAME": "gpt-4o"
"MODEL_NAME": "gpt-4o-mini"
}
}
}
@ -192,7 +200,7 @@ Or start the server with uv and connect to it:
"NEO4J_USER": "neo4j",
"NEO4J_PASSWORD": "demodemo",
"OPENAI_API_KEY": "${OPENAI_API_KEY}",
"MODEL_NAME": "gpt-4o"
"MODEL_NAME": "gpt-4o-mini"
}
}
}
@ -215,7 +223,8 @@ The Graphiti MCP server exposes the following tools:
## Working with JSON Data
The Graphiti MCP server can process structured JSON data through the `add_episode` tool with `source="json"`. This allows you to automatically extract entities and relationships from structured data:
The Graphiti MCP server can process structured JSON data through the `add_episode` tool with `source="json"`. This
allows you to automatically extract entities and relationships from structured data:
```
add_episode(
@ -236,7 +245,8 @@ To integrate the Graphiti MCP Server with the Cursor IDE, follow these steps:
python graphiti_mcp_server.py --transport sse --use-custom-entities --group-id <your_group_id>
```
Hint: specify a `group_id` to retain prior graph data. If you do not specify a `group_id`, the server will create a new graph
Hint: specify a `group_id` to retain prior graph data. If you do not specify a `group_id`, the server will create a new
graph
2. Configure Cursor to connect to the Graphiti MCP server.
@ -254,7 +264,8 @@ Hint: specify a `group_id` to retain prior graph data. If you do not specify a `
4. Kick off an agent session in Cursor.
The integration enables AI assistants in Cursor to maintain persistent memory through Graphiti's knowledge graph capabilities.
The integration enables AI assistants in Cursor to maintain persistent memory through Graphiti's knowledge graph
capabilities.
## Requirements

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@ -1,6 +1,6 @@
[tool.poetry]
name = "graphiti-core"
version = "0.8.7"
version = "0.8.8"
description = "A temporal graph building library"
authors = [
"Paul Paliychuk <paul@getzep.com>",