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An assistant is a configured instance of a LangGraph graph. While graphs define the agent logic, assistants let you create multiple configurations of the same graph with different names, metadata, and settings.

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Default assistants

When the server starts, Aegra automatically creates a default assistant for each graph defined in aegra.json. The default assistant uses the graph ID as its assistant ID, so you can use graph IDs directly in runs without creating assistants manually. 
{
  "graphs": {
    "agent": "./src/my_agent/graph.py:graph"
  }
}
This automatically creates an assistant with ID "agent" that you can use immediately.

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Creating assistants

Create custom assistants with specific configurations: 
from langgraph_sdk import get_client

client = get_client(url="http://localhost:8000")

assistant = await client.assistants.create(
    graph_id="agent",
    name="Customer Support Agent",
    description="Handles customer inquiries with web search",
    metadata={"department": "support", "tier": "premium"},
)

print(assistant["assistant_id"])

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Idempotent creation

Use if_exists to avoid errors when the assistant already exists: 
assistant = await client.assistants.create(
    graph_id="agent",
    name="My Agent",
    if_exists="do_nothing",  # Returns existing if already created
)

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Listing and searching

# List all assistants
assistants = await client.assistants.search()

# Search by graph ID
results = await client.assistants.search(graph_id="agent")

# Search by metadata
results = await client.assistants.search(
    metadata={"department": "support"},
)

# Search by name
results = await client.assistants.search(name="Customer Support")

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Updating assistants

assistant = await client.assistants.update(
    assistant_id="your-assistant-id",
    name="Updated Name",
    metadata={"department": "engineering"},
)

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Versioning

Assistants are versioned. Each update creates a new version while preserving the history: 
# List all versions
versions = await client.assistants.get_versions(assistant_id)

# Set a specific version as the latest
await client.assistants.set_latest(assistant_id, version=2)

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Graph schemas

Retrieve the input, output, state, and config schemas for an assistant’s graph: 
schemas = await client.assistants.get_schemas(assistant_id)
print(schemas["input_schema"])
print(schemas["output_schema"])
print(schemas["state_schema"])
print(schemas["config_schema"])

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Graph visualization

Get the graph structure for visualization: 
# Basic graph structure (nodes and edges)
graph = await client.assistants.get_graph(assistant_id)

# Detailed view with xray (expands subgraphs)
graph = await client.assistants.get_graph(assistant_id, xray=True)

# Control xray depth
graph = await client.assistants.get_graph(assistant_id, xray=2)
The response includes nodes and edges that can be rendered by LangGraph Studio or custom visualizers.

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Subgraphs

If your graph uses subgraphs, you can inspect them: 
subgraphs = await client.assistants.get_subgraphs(assistant_id)

# Recursively list all nested subgraphs
subgraphs = await client.assistants.get_subgraphs(assistant_id, recurse=True)

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Deleting assistants

await client.assistants.delete(assistant_id)
When authentication is enabled, you can restrict deletion to admin users using authorization handlers. See the authentication guide.