LangChain + Jarvis SDK

from langchain.tools import tool
from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_tool_calling_agent
from langchain_core.prompts import ChatPromptTemplate
import requests

JARVIS_API_KEY = "jsk_your_api_key_here"
JARVIS_BASE = "https://jarvissdk.com/api/v1"

@tool
def jarvis_execute(module: str, action: str, params: str) -> str:
    """Execute a Jarvis SDK module action.
    Args:
        module: Module name (e.g., 'text-toolkit')
        action: Action name (e.g., 'summarize')
        params: JSON string of parameters
    """
    import json
    resp = requests.post(
        f"{JARVIS_BASE}/modules/{module}/execute",
        headers={"x-api-key": JARVIS_API_KEY, "Content-Type": "application/json"},
        json={"action": action, "params": json.loads(params)},
    )
    return resp.json().get("result", resp.text)

@tool
def jarvis_arm(mission: str) -> str:
    """Self-equip: describe your mission and get the best tools."""
    resp = requests.post(
        f"{JARVIS_BASE}/agent/arm",
        headers={"x-api-key": JARVIS_API_KEY, "Content-Type": "application/json"},
        json={"mission": mission},
    )
    return str(resp.json())

# Create agent with Jarvis SDK tools
llm = ChatOpenAI(model="gpt-4o")
tools = [jarvis_execute, jarvis_arm]
prompt = ChatPromptTemplate.from_messages([
    ("system", "You have access to 700+ tools via Jarvis SDK. Use jarvis_arm to discover tools, then jarvis_execute to run them."),
    ("human", "{input}"),
    ("placeholder", "{agent_scratchpad}"),
])

agent = create_tool_calling_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
result = executor.invoke({"input": "Summarize this text: 'Jarvis SDK is awesome!'"})