OpenAI Protocol

from ag_kit_py.server import AGKitAPIApp
from ag_kit_py.agents import LangGraphAgent
from langgraph.graph import StateGraph, MessagesState

def create_agent():
    # Use the actual chat workflow from examples
    from python_sdk.examples.langgraph import build_chat_workflow
    
    workflow = build_chat_workflow()
    agent = LangGraphAgent(
        name='openai-compatible-agent',
        description='You are a helpful assistant.',
        graph=workflow
    )
    return {'agent': agent}

AGKitAPIApp().run(create_agent, port=3000)
# OpenAI API available at http://localhost:3000/chat/completions

from ag_kit_py.agents import LangGraphAgent
from langgraph.graph import StateGraph, MessagesState

# Use the actual chat workflow from examples
from python_sdk.examples.langgraph import build_chat_workflow

workflow = build_chat_workflow()
# Note: External API integration would be configured in the LangGraph workflow
agent = LangGraphAgent(
    name='openai-client-agent',
    description='You are an agent using external OpenAI API.',
    graph=workflow
)

import openai

client = openai.OpenAI(
    api_key='your-api-key',
    base_url='http://localhost:3000'
)

response = client.chat.completions.create(
    model='gpt-4', # Model name (can be any string)
    messages=[
        {'role': 'user', 'content': 'Hello, Agent!'}
    ]
)

print(response.choices[0].message.content)

functions = [
    {
        'name': 'get_weather',
        'description': 'Get weather information for a location',
        'parameters': {
            'type': 'object',
            'properties': {
                'location': {
                    'type': 'string',
                    'description': 'The city and state, e.g. San Francisco, CA'
                }
            },
            'required': ['location']
        }
    }
]

response = client.chat.completions.create(
    model='gpt-4',
    messages=[
        {'role': 'user', 'content': 'What is the weather in New York?'}
    ],
    functions=functions,
    function_call='auto'
)

if response.choices[0].message.function_call:
    function_call = response.choices[0].message.function_call
    print('Function called:', function_call.name)

import requests

class SmartHomeController:
    def __init__(self, api_key: str, agent_url: str):
        self.api_key = api_key
        self.agent_url = agent_url
    
    async def process_voice_command(self, command: str):
        response = requests.post(
            f"{self.agent_url}/chat/completions",
            headers={
                'Content-Type': 'application/json',
                'Authorization': f'Bearer {self.api_key}'
            },
            json={
                'model': 'gpt-4',
                'messages': [
                    {'role': 'system', 'content': 'You are a smart home assistant.'},
                    {'role': 'user', 'content': command}
                ]
            }
        )
        
        data = response.json()
        return data['choices'][0]['message']['content']