> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Zep

> The ZepTools toolkit enables an Agent to interact with a Zep memory system, providing capabilities to store, retrieve, and search memory data associated with user sessions.

**ZepTools** enable an Agent to interact with a Zep memory system, providing capabilities to store, retrieve, and search memory data associated with user sessions.

## Prerequisites

The following example requires the `zep-cloud` and `openai` Python packages and a Zep API key.

```shell theme={null}
uv pip install zep-cloud openai
```

```shell theme={null}
export ZEP_API_KEY=your_api_key
```

## Example

The following example demonstrates how to create an agent with access to Zep memory:

```python cookbook/91_tools/zep_tools.py theme={null}
import time

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.zep import ZepTools

# Initialize the ZepTools
zep_tools = ZepTools(user_id="agno", session_id="agno-session", add_instructions=True)

# Initialize the Agent
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[zep_tools],
    dependencies={"memory": zep_tools.get_zep_memory(memory_type="context")},
    add_dependencies_to_context=True,
)

# Interact with the Agent so that it can learn about the user
agent.print_response("My name is John Billings")
agent.print_response("I live in NYC")
agent.print_response("I'm going to a concert tomorrow")

# Allow the memories to sync with Zep database
time.sleep(10)

# Refresh the context
agent.dependencies["memory"] = zep_tools.get_zep_memory(memory_type="context")

# Ask the Agent about the user
agent.print_response("What do you know about me?")
```

## Toolkit Params

| Parameter | Type | Default | Description |
| - | - | - | - |
| `session_id` | `Optional[str]` | `None` | Optional session ID. Auto-generated if not provided. |
| `user_id` | `Optional[str]` | `None` | Optional user ID. Auto-generated if not provided. |
| `api_key` | `Optional[str]` | `None` | Zep API key. If not provided, uses ZEP\_API\_KEY env var. |
| `ignore_assistant_messages` | `bool` | `False` | Whether to ignore assistant messages when adding to memory. |
| `enable_add_zep_message` | `bool` | `True` | Enables the `add_zep_message` tool. |
| `enable_get_zep_memory` | `bool` | `True` | Enables the `get_zep_memory` tool. |
| `enable_search_zep_memory` | `bool` | `True` | Enables the `search_zep_memory` tool. |
| `instructions` | `Optional[str]` | `None` | Custom instructions for using the Zep tools. |
| `add_instructions` | `bool` | `False` | Whether to add default instructions. |
| `all` | `bool` | `False` | Enables all tools when set to True. |

## Toolkit Functions

| Function | Description |
| - | - |
| `add_zep_message` | Adds a message to the current Zep session memory. Takes `role` (str) for the message sender and `content` (str) for the message text. Returns a confirmation or error message. |
| `get_zep_memory` | Retrieves memory for the current Zep session. Takes optional `memory_type` (str) parameter with options "context" (default) or "messages". Returns the requested memory content or an error. |
| `search_zep_memory` | Searches the Zep knowledge graph for relevant facts or nodes. Takes `query` (str) to find relevant results and optional `search_scope` (str) parameter with options "edges" (default, for facts) or "nodes". Returns search results or an error message. |

## Async Toolkit

The `ZepAsyncTools` class provides asynchronous versions of the toolkit functions. Its constructor takes plain booleans `add_zep_message`, `get_zep_memory`, and `search_zep_memory` instead of the `enable_*` names above, and it has no `all` parameter. Its `search_zep_memory` also takes `scope` and `limit` instead of `search_scope`.

## Developer Resources

* [Tools](https://github.com/agno-agi/agno/blob/main/libs/agno/agno/tools/zep.py)


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