Use Sessions for Stateful Agents

orpheus run my-agent '{"query": "step 1"}' --session user-123
orpheus run my-agent '{"query": "step 2"}' --session user-123

curl -X POST http://localhost:7777/v1/agents/my-agent/run \
  -H "Content-Type: application/json" \
  -H "X-Session-ID: user-123" \
  -d '{"input": {"query": "step 1"}}'

# In-memory conversation history (per worker)
conversations = {}

def handler(input_data):
    session_id = input_data.get('session_id', 'default')
    query = input_data.get('query', '')

    # Get or create conversation
    if session_id not in conversations:
        conversations[session_id] = []

    history = conversations[session_id]

    # Add user message
    history.append({"role": "user", "content": query})

    # Generate response (your LLM call here)
    response = generate_response(history)

    # Add assistant message
    history.append({"role": "assistant", "content": response})

    return {
        'response': response,
        'turn': len(history) // 2
    }

def generate_response(history):
    # Replace with your LLM API call
    return f"Response to turn {len(history) // 2}"

# First request
orpheus run my-agent '{"query": "My name is Alice"}' --session alice

# Second request (same worker, has context)
orpheus run my-agent '{"query": "What is my name?"}' --session alice

import json
import os

def handler(input_data):
    session_id = input_data.get('session_id', 'default')

    # Load from workspace (durable)
    history_file = f'/workspace/sessions/{session_id}.json'

    if os.path.exists(history_file):
        with open(history_file) as f:
            history = json.load(f)
    else:
        history = []

    # ... process request ...

    # Save to workspace
    os.makedirs('/workspace/sessions', exist_ok=True)
    with open(history_file, 'w') as f:
        json.dump(history, f)

    return {'response': response}