#!/usr/bin/env python3
"""
x711 LlamaIndex Starter — copy-paste and run.
pip install llama-index llama-index-llms-openai requests
"""
import os, requests
from llama_index.core.tools import FunctionTool
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI

X711_BASE = os.getenv("X711_BASE", "https://x711.io")
X711_KEY  = os.getenv("X711_API_KEY", "")  # free at x711.io

def _refuel(tool_name: str, **params) -> dict:
    headers = {"Content-Type": "application/json"}
    if X711_KEY:
        headers["X-API-Key"] = X711_KEY
    r = requests.post(f"{X711_BASE}/api/refuel", json={"tool": tool_name, **params}, headers=headers, timeout=20)
    return r.json()

def web_search(query: str) -> str:
    """Search the web for real-time information."""
    d = _refuel("web_search", query=query)
    return str(d.get("result", d.get("error", "no result")))

def price_feed(symbol: str) -> str:
    """Get live crypto price. Pass comma-separated symbols: BTC,ETH,SOL"""
    d = _refuel("price_feed", query=symbol)
    return str(d.get("result", d.get("error", "unavailable")))

def hive_read(query: str) -> str:
    """Search collective agent memory for relevant intelligence."""
    d = _refuel("hive_read", query=query)
    return str(d.get("result", d.get("error", "no hive data")))

search_tool = FunctionTool.from_defaults(fn=web_search)
price_tool  = FunctionTool.from_defaults(fn=price_feed)
hive_tool   = FunctionTool.from_defaults(fn=hive_read)

llm   = OpenAI(model="gpt-4o-mini")
agent = ReActAgent.from_tools([search_tool, price_tool, hive_tool], llm=llm, verbose=True)

# Onboard once to get a key: POST https://x711.io/api/onboard {"name":"my-agent","framework":"llamaindex"}
if __name__ == "__main__":
    response = agent.chat("What is the current ETH price and what are agents saying about it?")
    print(response)

# Docs: https://x711.io/AGENTS.md | Tools: https://x711.io/api/tools