Managing Agents

Update, delete, clone, and list agents

Manage agents throughout their lifecycle with operations like update, delete, clone, and list.

Quick Start

from lyzr import Studio

studio = Studio(api_key="your-api-key")

# Get an existing agent
agent = studio.get_agent("agent_id")

# Update the agent
agent = agent.update(temperature=0.5)

# Clone the agent
cloned = agent.clone("My Cloned Agent")

# Delete the agent
agent.delete()

---

Get Agent

Retrieve an agent by its ID.

agent = studio.get_agent(agent_id: str) -> Agent

Parameters

Parameter	Type	Required	Description
agent_id	str	Yes	The agent’s unique identifier

Example

agent = studio.get_agent("agent_abc123")

print(f"Name: {agent.name}")
print(f"Model: {agent.provider}/{agent.model}")
print(f"Temperature: {agent.temperature}")

---

List Agents

List all agents in your account.

agents = studio.list_agents() -> AgentList

Example

agents = studio.list_agents()

print(f"Total agents: {len(agents)}")

for agent in agents:
    print(f"- {agent.id}: {agent.name} ({agent.model})")

Filtering Agents

agents = studio.list_agents()

# Find agents by name
support_agents = [a for a in agents if "support" in a.name.lower()]

# Find agents by provider
openai_agents = [a for a in agents if a.provider_id == "openai"]

# Find agents with memory
memory_agents = [a for a in agents if a.has_memory()]

---

Update Agent

Update an agent’s configuration.

agent.update(**kwargs) -> Agent

Parameters

Parameter	Type	Description
name	str	New agent name
description	str	New description
temperature	float	Creativity (0.0-2.0)
top_p	float	Nucleus sampling (0.0-1.0)
role	str	Agent role
goal	str	Agent goal
instructions	str	Agent instructions
response_model	BaseModel	Pydantic model for structured outputs
file_output	bool	Enable file generation
image_output_config	dict	Image generation config
memory	int	Memory message count
contexts	List[Context]	Background contexts
reflection	bool	Enable self-reflection
bias_check	bool	Enable bias detection
llm_judge	bool	Enable LLM judge
groundedness_facts	List[str]	Facts for validation
rai_policy	RAIPolicy	RAI guardrails policy
image_model	ImageModelConfig	Image generation model

Examples

Update Basic Properties

agent = agent.update(
    name="Updated Support Bot",
    description="Improved customer support agent",
    temperature=0.5
)

Update Instructions

agent = agent.update(
    role="Senior support specialist",
    goal="Resolve complex customer issues",
    instructions="""
    You are a senior support specialist. Follow these guidelines:
    1. Always greet the customer
    2. Ask clarifying questions
    3. Provide step-by-step solutions
    4. Confirm resolution before closing
    """
)

Enable Features

agent = agent.update(
    memory=50,           # Keep 50 messages
    reflection=True,     # Enable self-reflection
    file_output=True     # Enable file generation
)

Update with Structured Output

from pydantic import BaseModel

class Response(BaseModel):
    answer: str
    confidence: float

agent = agent.update(response_model=Response)

---

Delete Agent

Delete an agent permanently.

agent.delete() -> bool

Example

agent = studio.get_agent("agent_abc123")
success = agent.delete()

if success:
    print("Agent deleted successfully")

Delete by ID

studio.delete_agent("agent_abc123")

---

Bulk Delete

Delete multiple agents at once.

studio.bulk_delete_agents(agent_ids: List[str]) -> bool

Example

# Delete multiple agents
agent_ids = ["agent_1", "agent_2", "agent_3"]
studio.bulk_delete_agents(agent_ids)

Delete All Agents (Careful!)

# Get all agents and delete them
agents = studio.list_agents()
agent_ids = [agent.id for agent in agents]

if agent_ids:
    studio.bulk_delete_agents(agent_ids)
    print(f"Deleted {len(agent_ids)} agents")

---

Clone Agent

Create a copy of an agent with a new name.

agent.clone(new_name: str = None) -> Agent

Parameters

Parameter	Type	Required	Default	Description
new_name	str	No	” (Clone)“	Name for the cloned agent

Examples

Basic Clone

original = studio.get_agent("agent_abc123")
cloned = original.clone("My Cloned Agent")

print(f"Original ID: {original.id}")
print(f"Cloned ID: {cloned.id}")  # Different ID
print(f"Cloned Name: {cloned.name}")  # "My Cloned Agent"

Clone with Default Name

cloned = original.clone()
print(cloned.name)  # "Original Name (Clone)"

Clone and Modify

# Clone and immediately update
cloned = original.clone("Production Agent")
cloned = cloned.update(
    temperature=0.3,  # More deterministic for production
    reflection=True   # Add reflection
)

---

Agent Properties

Access agent properties directly:

agent = studio.get_agent("agent_id")

# Basic info
print(agent.id)
print(agent.name)
print(agent.description)

# Model config
print(agent.provider_id)      # "openai"
print(agent.model)            # "gpt-4o"
print(agent.provider)         # "openai/gpt-4o"
print(agent.temperature)
print(agent.top_p)

# Role/Goal/Instructions (with aliases)
print(agent.role)             # Alias for agent_role
print(agent.goal)             # Alias for agent_goal
print(agent.instructions)     # Alias for agent_instructions

# Feature checks
print(agent.has_memory())
print(agent.has_rai_policy())
print(agent.has_file_output())
print(agent.has_image_output())
print(agent.has_reflection())
print(agent.has_bias_check())
print(agent.has_llm_judge())
print(agent.has_groundedness())

# Timestamps
print(agent.created_at)
print(agent.updated_at)

---

Convert to Dictionary

agent = studio.get_agent("agent_id")

# Get as dictionary
data = agent.to_dict()

# Access fields
print(data["name"])
print(data["temperature"])

---

Error Handling

from lyzr.exceptions import NotFoundError, ValidationError, APIError

try:
    agent = studio.get_agent("nonexistent_id")
except NotFoundError:
    print("Agent not found")

try:
    agent = agent.update(temperature=5.0)  # Invalid value
except ValidationError as e:
    print(f"Validation error: {e}")

try:
    agent.delete()
except APIError as e:
    print(f"API error: {e}")

---

Examples

Agent Versioning Pattern

# Create versioned agents
v1 = studio.create_agent(
    name="Support Bot v1",
    provider="gpt-4o",
    role="Support agent",
    goal="Help customers",
    instructions="Version 1 instructions"
)

# Clone for v2
v2 = v1.clone("Support Bot v2")
v2 = v2.update(
    instructions="Version 2 instructions with improvements"
)

# Keep both versions for A/B testing

Agent Migration

# Get all agents
agents = studio.list_agents()

# Update all agents to new settings
for agent in agents:
    agent.update(
        reflection=True,
        temperature=0.5
    )
    print(f"Updated: {agent.name}")

Cleanup Old Agents

from datetime import datetime, timedelta

agents = studio.list_agents()

# Find agents older than 30 days
old_agents = []
cutoff = datetime.now() - timedelta(days=30)

for agent in agents:
    if agent.created_at:
        created = datetime.fromisoformat(agent.created_at.replace("Z", "+00:00"))
        if created < cutoff:
            old_agents.append(agent.id)

# Delete old agents
if old_agents:
    studio.bulk_delete_agents(old_agents)
    print(f"Deleted {len(old_agents)} old agents")