agent_expanded.py

import json
import sys
from subprocess import getoutput as run_shell
from urllib.request import Request, urlopen

MODEL = "gpt-5.6"
CONTEXT_WINDOW_TOKENS = 1_050_000

endpoint_url = sys.argv[1]
history = []
request_body = dict(
    model=MODEL,
    input=history,
    tools=[dict(type="custom", name="sh")],
)

while user_prompt := input("> "):
    history += [dict(role="user", content=user_prompt)]
    headers = {"Content-Type": "application/json"}

    while True:
        output_items = (
            response := json.load(
                urlopen(
                    Request(
                        endpoint_url,
                        json.dumps(request_body).encode(),
                        headers,
                    )
                )
            )
        )["output"]
        history += output_items
        tool_calls = [
            item
            for item in output_items
            if item["type"] == "custom_tool_call"
        ]
        context_usage_percent = (
            response["usage"]["total_tokens"] / CONTEXT_WINDOW_TOKENS * 100
        )

        if not tool_calls:
            print(
                output_items[-1]["content"][0]["text"],
                f"\n[{context_usage_percent:06.3f}%]",
            )
            break

        history += [
            dict(
                type="custom_tool_call_output",
                call_id=tool_call["call_id"],
                output=run_shell(tool_call["input"]),
            )
            for tool_call in tool_calls
        ]

Claude and I wrote this version but we didn't test it. It uses http.client (std lib) which keeps the connection open, so less overhead.

import json
import sys
from subprocess import getoutput as run_shell
import http.client
from urllib.parse import urlsplit

url = urlsplit(sys.argv[1])
conn = http.client.HTTPSConnection(url.hostname)
history = []
body = {'model': 'gpt-5.6', 'input': history, 'tools': [{'type': 'custom', 'name': 'sh'}]}

while prompt := input('> '):
    history.append({'role': 'user', 'content': prompt})
    while True:
        conn.request('POST', url.path, json.dumps(body).encode(), {'Content-Type': 'application/json'})
        result = json.load(conn.getresponse())
        output = result['output']
        history.extend(output)
        tool_calls = [item for item in output if item['type'] == 'custom_tool_call']
        if not tool_calls:
            usage_pct = result['usage']['total_tokens'] / 10500
            print(output[-1]['content'][0]['text'], f'\n[{usage_pct:06.3f}%]')
            break
        history.extend({'type': 'custom_tool_call_output', 'call_id': item['call_id'], 'output': run_shell(item['input'])} for item in tool_calls)