An intelligent multi-agent system designed to autonomously validate and extract structured content from URL
Deploy / Run AgentAPI & SDK Integration
Load, run, and interact with this agent programmatically using standard HTTP curl requests or the SVAHNAR SDK.
Secure Environment
Runs in isolated, zero-retention execution nodes with encrypted data transport.
Models Used (1)
Tools Attached (1)
MCP Connections (0)
No Model Context Protocol servers connected.
Specifications
AGENT TYPE
Multi-Agent System
SUB-AGENTS
3 agents
SUPERVISOR
Yes
RUNS
1,200+ runs
Configuration (YAML)
create_vertical_agent_network:
agent-1:
LLM_config:
params:
model: gpt-4o-mini
max_tokens: 1000
temperature: 0.5
request_timeout: 600
agent_name: Agent_1
incoming_edge:
- Supervisor_agent_1
outgoing_edge:
- Supervisor_agent_1
agent_function:
- You are a URL validator agent which can validate and verify the URL format is
correct or not.
agent-2:
tools:
tool_assigned:
- name: Webpage_Search
LLM_config:
params:
model: gpt-4o-mini
max_tokens: 1000
temperature: 0.5
request_timeout: 600
agent_name: Agent_2
incoming_edge:
- Supervisor_agent_1
outgoing_edge:
- Supervisor_agent_1
agent_function:
- You are web scraper agent which can scrape the content from provided valid URL.
agent-3:
Role: supervisor
LLM_config:
params:
model: gpt-4o-mini
max_tokens: 1000
temperature: 0.5
request_timeout: 600
agent_name: Supervisor_agent_1
incoming_edge:
- Start
- Agent_1
- Agent_2
outgoing_edge:
- Agent_1
- Agent_2
agent_function:
- 'You are a supervisor agent whose task is to decide which agent to call next
based on requirement. '
Developer Quick Start
1. Install the SDK
pip install svahnar2. Configure your API key
export SVAHNAR_API_KEY="your_api_key_here"3. Save the Configuration YAML
Copy the YAML configuration box above and save it locally as agent.yaml.
4. Deploy the Agent (Python)
from svahnar import Svahnar
from pathlib import Path
client = Svahnar()
# Deploy the agent configuration
agent = client.agents.create(
name="Web scraper Agent",
description="An intelligent multi-agent system designed to autonomously validate and extract structured content from URL",
deploy_to="Organization",
yaml_content=Path("agent.yaml")
)
print(f"Created Agent ID: {agent.id}")5. Run the Agent (Python)
from svahnar import Svahnar
client = Svahnar()
# Run the agent using its ID
response = client.agents.run(
agent_id="YOUR_DEPLOYED_AGENT_ID", # Replace with your agent ID from Step 4
message="Your input message here"
)
print(response)For advanced features, Human-in-the-Loop configurations, and guides, visit the Developer Documentation.