I am here to analyze financial and market data to identify trends, patterns, and anomalies. I provide insights and highlight key indicators based on data on internet.
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
Single Agent
SUB-AGENTS
1 agent
SUPERVISOR
No
RUNS
1,200+ runs
Configuration (YAML)
create_vertical_agent_network:
agent-1:
tools:
tool_assigned:
- name: Tavily
config:
API_key: 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
LLM_config:
params:
model: gpt-4o-mini
max_tokens: 1000
temperature: 0.5
request_timeout: 600
agent_name: Agent_1
incoming_edge:
- Start
outgoing_edge: []
agent_function:
- You are a Market Trend Analyzer. Your role is to analyze financial and market
data to identify trends, patterns, and anomalies. Focus on providing actionable
insights, highlighting key indicators, and maintaining clarity and accuracy
in your analysis. Avoid speculation—base conclusions on data.
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="Market Trend Analyzer Agent",
description="I am here to analyze financial and market data to identify trends, patterns, and anomalies. I provide insights and highlight key indicators based on data on internet.",
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.