Getting Started with Python SDK

pip install runagent

from runagent import RunAgentClient

# Initialize the client
client = RunAgentClient(agent_id="your-agent-id")

# Simple invocation
result = client.run_generic({
    "query": "What's the capital of France?",
    "context": "Geography question"
})

print(result)

from runagent import RunAgentClient

# Initialize with API key
client = RunAgentClient(
    agent_id="your-agent-id",
    api_key="your-api-key"  # Optional if set in environment
)

result = client.run_generic({
    "query": "Explain quantum computing",
    "max_length": 200
})

# Result is a dictionary
print(result["answer"])
print(result["confidence"])
print(result["sources"])

# Stream responses for real-time output
for chunk in client.run_generic_stream({
    "query": "Write a story about AI"
}):
    print(chunk, end="", flush=True)

from runagent import RunAgentClient, RunAgentError

client = RunAgentClient(agent_id="your-agent-id")

try:
    result = client.run_generic({"query": "Hello"})
except RunAgentError as e:
    print(f"RunAgent error: {e}")
    print(f"Error code: {e.code}")
    print(f"Error details: {e.details}")
except Exception as e:
    print(f"Unexpected error: {e}")

from runagent import RunAgentClient

client = RunAgentClient(
    agent_id="your-agent-id",
    api_key="your-api-key",
    base_url="https://api.run-agent.ai",  # Custom API endpoint
    timeout=30,  # Request timeout in seconds
    max_retries=3,  # Number of retry attempts
    verify_ssl=True  # SSL certificate verification
)

# This will raise ValidationError if required fields are missing
try:
    result = client.run_generic({})  # Missing required 'query' field
except ValidationError as e:
    print(f"Validation failed: {e}")

import logging

# Enable debug logging
logging.basicConfig(level=logging.DEBUG)

# Now SDK operations will print debug information
client = RunAgentClient(agent_id="your-agent-id")
result = client.run_generic({"query": "Test"})

from runagent import RunAgentClient

def ask_agent(question):
    client = RunAgentClient(agent_id="qa-bot-agent")
    
    try:
        result = client.run_generic({
            "query": question,
            "max_tokens": 500,
            "temperature": 0.7
        })
        return result.get("answer", "No answer available")
    except Exception as e:
        return f"Error: {str(e)}"

# Usage
answer = ask_agent("What is machine learning?")
print(answer)

from runagent import RunAgentClient

def chat_with_agent():
    client = RunAgentClient(agent_id="chat-agent")
    
    print("Chat started. Type 'quit' to exit.")
    
    while True:
        user_input = input("\nYou: ")
        if user_input.lower() == 'quit':
            break
        
        print("\nAgent: ", end="")
        for chunk in client.run_generic_stream({
            "query": user_input,
            "conversation_id": "session-123"
        }):
            print(chunk, end="", flush=True)
        print()  # New line after response

# Start chat
chat_with_agent()

from runagent import RunAgentClient
import json

def process_batch(items):
    client = RunAgentClient(agent_id="processor-agent")
    results = []
    
    for item in items:
        try:
            result = client.run_generic({
                "data": item,
                "operation": "analyze"
            })
            results.append({
                "input": item,
                "output": result,
                "status": "success"
            })
        except Exception as e:
            results.append({
                "input": item,
                "output": None,
                "status": "error",
                "error": str(e)
            })
    
    return results

# Process multiple items
items = ["data1", "data2", "data3"]
results = process_batch(items)
print(json.dumps(results, indent=2))