Slopshop for
DeepSeek Agents

import os, json, requests
from openai import OpenAI

# DeepSeek is OpenAI-compatible — just swap base_url
client = OpenAI(
    api_key=os.environ["DEEPSEEK_API_KEY"],
    base_url="https://api.deepseek.com"
)

SLOP_KEY = os.environ["SLOPSHOP_API_KEY"]
SLOP_URL = "https://slopshop.gg"

# 1. Fetch Slopshop tools — already in OpenAI function format
def get_tools(slugs: list[str]) -> list[dict]:
    schema = requests.get(
        f"{SLOP_URL}/v1/openapi.json",
        headers={"Authorization": f"Bearer {SLOP_KEY}"}
    ).json()
    # Convert OpenAPI paths to OpenAI tool definitions
    tools = []
    for slug in slugs:
        path = schema["paths"].get(f"/v1/{slug}", {}).get("post", {})
        if path:
            tools.append({
                "type": "function",
                "function": {
                    "name": slug,
                    "description": path.get("summary", ""),
                    "parameters": path["requestBody"]["content"]
                                        ["application/json"]["schema"]
                }
            })
    return tools

# 2. Execute a Slopshop tool call
def call_tool(name: str, args: dict) -> str:
    res = requests.post(
        f"{SLOP_URL}/v1/{name}",
        json=args,
        headers={
            "Authorization": f"Bearer {SLOP_KEY}",
            "Content-Type": "application/json"
        }
    )
    return json.dumps(res.json())

# 3. Agentic loop — DeepSeek decides, Slopshop executes
def run_agent(user_message: str) -> str:
    tools = get_tools(["dns-lookup", "ssl-check", "http-request",
                       "whois", "hash", "memory-set", "memory-get"])
    messages = [{"role": "user", "content": user_message}]

    while True:
        response = client.chat.completions.create(
            model="deepseek-chat",
            messages=messages,
            tools=tools,
            tool_choice="auto"
        )
        msg = response.choices[0].message

        # DeepSeek signals done with finish_reason "stop"
        if response.choices[0].finish_reason == "stop":
            return msg.content

        # Append assistant message with tool_calls
        messages.append(msg)

        # Execute each tool call and append results
        for tc in msg.tool_calls:
            result = call_tool(
                tc.function.name,
                json.loads(tc.function.arguments)
            )
            messages.append({
                "role": "tool",
                "tool_call_id": tc.id,
                "content": result
            })

# Run it
answer = run_agent("Check DNS records for slopshop.gg and save results to memory")
print(answer)