Purple Flea for Together AI

import together
import requests

# Initialize Together AI client
client = together.Together(api_key="your_together_api_key")
PF_API_KEY = "your_purple_flea_api_key"
PF_BASE = "https://purpleflea.com/api/v1"

# Define Purple Flea tools for the agent
tools = [
    {
        "type": "function",
        "function": {
            "name": "place_trade",
            "description": "Open or close a perpetual futures position",
            "parameters": {
                "type": "object",
                "properties": {
                    "market": {"type": "string", "description": "e.g. BTC-PERP"},
                    "side":   {"type": "string", "enum": ["buy", "sell"]},
                    "size":   {"type": "number", "description": "Position size in USD"}
                },
                "required": ["market", "side", "size"]
            }
        }
    },
    {
        "type": "function",
        "function": {
            "name": "wallet_balance",
            "description": "Get balances across all supported chains",
            "parameters": {
                "type": "object",
                "properties": {
                    "agent_id": {"type": "string", "description": "Your agent's registered ID"}
                },
                "required": ["agent_id"]
            }
        }
    }
]

# Tool execution handler
def execute_tool(name, args):
    headers = {"Authorization": f"Bearer {PF_API_KEY}"}
    if name == "place_trade":
        resp = requests.post(
            f"{PF_BASE}/trading/order", json=args, headers=headers
        )
        return resp.json()
    elif name == "wallet_balance":
        resp = requests.get(
            f"{PF_BASE}/wallet/balances", params=args, headers=headers
        )
        return resp.json()

# Run agent with Llama 3.1 405B
messages = [{"role": "user", "content": "Check my BTC balance then open a $100 long on BTC-PERP"}]

response = client.chat.completions.create(
    model="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
    messages=messages,
    tools=tools,
    tool_choice="auto"
)

# Process tool calls from the model
while response.choices[0].finish_reason == "tool_calls":
    tool_calls = response.choices[0].message.tool_calls
    messages.append(response.choices[0].message)

    for tc in tool_calls:
        result = execute_tool(tc.function.name, tc.function.arguments)
        messages.append({
            "role": "tool",
            "tool_call_id": tc.id,
            "content": str(result)
        })

    response = client.chat.completions.create(
        model="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
        messages=messages,
        tools=tools,
        tool_choice="auto"
    )

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