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hermes-agent/tests/run_agent/test_deepseek_v4_thinking_live.py

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7.9 KiB
Python

"""Live DeepSeek V4 thinking-mode tool-call replay smoke test.
Opt-in only:
HERMES_LIVE_TESTS=1 pytest tests/run_agent/test_deepseek_v4_thinking_live.py -q
Requires DEEPSEEK_API_KEY in the process environment. The key is captured at
module import time because tests/conftest.py intentionally removes credential
environment variables before each test body runs.
"""
from __future__ import annotations
import json
import os
import sys
from typing import Any
import pytest
LIVE = os.environ.get("HERMES_LIVE_TESTS") == "1"
DEEPSEEK_KEY = os.environ.get("DEEPSEEK_API_KEY", "")
LIVE_MODELS = ("deepseek-v4-flash", "deepseek-v4-pro")
LIVE_BASE_URL = "https://api.deepseek.com"
pytestmark = [
pytest.mark.skipif(not LIVE, reason="live-only: set HERMES_LIVE_TESTS=1"),
pytest.mark.skipif(not DEEPSEEK_KEY, reason="DEEPSEEK_API_KEY not configured"),
]
TOOL_NAME = "lookup_ticket_status"
TOOLS = [
{
"type": "function",
"function": {
"name": TOOL_NAME,
"description": "Return the status for a test ticket id.",
"parameters": {
"type": "object",
"properties": {
"ticket_id": {
"type": "string",
"description": "The ticket id to look up.",
},
},
"required": ["ticket_id"],
"additionalProperties": False,
},
},
}
]
def _thinking_kwargs() -> dict:
return {
"reasoning_effort": "high",
"extra_body": {"thinking": {"type": "enabled"}},
}
def _jsonable(value: Any) -> Any:
if hasattr(value, "model_dump"):
return value.model_dump(mode="json")
if isinstance(value, dict):
return {k: _jsonable(v) for k, v in value.items()}
if isinstance(value, list):
return [_jsonable(v) for v in value]
return value
def _print_trace(label: str, value: Any) -> None:
sys.__stdout__.write(f"\n--- {label} ---\n")
sys.__stdout__.write(
json.dumps(_jsonable(value), ensure_ascii=False, indent=2, sort_keys=True)
)
sys.__stdout__.write("\n")
sys.__stdout__.flush()
def _message_snapshot(message) -> dict:
return {
"content": getattr(message, "content", None),
"reasoning": getattr(message, "reasoning", None),
"reasoning_content": _raw_reasoning_content(message),
"model_extra": getattr(message, "model_extra", None),
"tool_calls": _jsonable(getattr(message, "tool_calls", None)),
}
def _make_live_client():
from openai import OpenAI
return OpenAI(api_key=DEEPSEEK_KEY, base_url=LIVE_BASE_URL)
def _make_agent_for_message_building(model: str):
from run_agent import AIAgent
agent = object.__new__(AIAgent)
agent.provider = "deepseek"
agent.model = model
agent.base_url = LIVE_BASE_URL
agent.verbose_logging = False
agent.reasoning_callback = None
agent.stream_delta_callback = None
agent._stream_callback = None
return agent
def _raw_reasoning_content(message):
direct = getattr(message, "reasoning_content", None)
if direct is not None:
return direct
model_extra = getattr(message, "model_extra", None) or {}
if isinstance(model_extra, dict) and "reasoning_content" in model_extra:
return model_extra["reasoning_content"]
return None
@pytest.mark.parametrize("live_model", LIVE_MODELS)
def test_deepseek_v4_thinking_tool_call_replay_round_trip(live_model: str):
"""Hit DeepSeek twice and replay the assistant tool-call turn.
The first request forces a tool call with thinking enabled. The second
request replays that assistant message with content, reasoning_content,
and tool_calls, then appends the tool result. DeepSeek accepting the
second request is the live guardrail for the V4 thinking replay contract.
"""
client = _make_live_client()
agent = _make_agent_for_message_building(live_model)
first_request = {
"model": live_model,
"messages": [
{
"role": "user",
"content": (
"You must use the provided lookup_ticket_status tool "
"exactly once with ticket_id 'DS-4242'. Do not answer "
"directly."
),
}
],
"tools": TOOLS,
"max_tokens": 1024,
"timeout": 90,
**_thinking_kwargs(),
}
_print_trace(f"{live_model} first request", first_request)
first = client.chat.completions.create(**first_request)
_print_trace(f"{live_model} first raw response", first)
first_choice = first.choices[0]
first_message = first_choice.message
_print_trace(
f"{live_model} first assistant message",
{
"finish_reason": first_choice.finish_reason,
**_message_snapshot(first_message),
},
)
assert first_message.tool_calls, "DeepSeek did not return a tool call"
first_tool_call = first_message.tool_calls[0]
assert first_tool_call.function.name == TOOL_NAME
assert isinstance(json.loads(first_tool_call.function.arguments or "{}"), dict)
raw_reasoning_content = _raw_reasoning_content(first_message)
assert raw_reasoning_content is not None, (
"DeepSeek did not return reasoning_content; the thinking payload may "
"not have been honored"
)
stored_assistant = agent._build_assistant_message(
first_message,
first_choice.finish_reason or "tool_calls",
)
_print_trace(f"{live_model} stored assistant message", stored_assistant)
assert stored_assistant["reasoning_content"] == raw_reasoning_content
replay_assistant = {
"role": "assistant",
"content": stored_assistant.get("content") or "",
"tool_calls": stored_assistant["tool_calls"],
}
agent._copy_reasoning_content_for_api(stored_assistant, replay_assistant)
_print_trace(f"{live_model} replay assistant message", replay_assistant)
tool_call_id = stored_assistant["tool_calls"][0]["id"]
messages = [
{
"role": "user",
"content": (
"You must use the provided lookup_ticket_status tool "
"exactly once with ticket_id 'DS-4242'. Do not answer "
"directly."
),
},
replay_assistant,
{
"role": "tool",
"tool_call_id": tool_call_id,
"content": json.dumps(
{"ticket_id": "DS-4242", "status": "green", "source": "live-test"},
separators=(",", ":"),
),
},
]
from agent.transports.chat_completions import ChatCompletionsTransport
api_messages = ChatCompletionsTransport().convert_messages(messages)
_print_trace(
f"{live_model} second request messages after transport conversion",
api_messages,
)
assert api_messages[1]["reasoning_content"] == raw_reasoning_content
assert "call_id" not in api_messages[1]["tool_calls"][0]
assert "response_item_id" not in api_messages[1]["tool_calls"][0]
second_request = {
"model": live_model,
"messages": api_messages,
"max_tokens": 1024,
"timeout": 90,
**_thinking_kwargs(),
}
_print_trace(f"{live_model} second request", second_request)
second = client.chat.completions.create(**second_request)
_print_trace(f"{live_model} second raw response", second)
_print_trace(
f"{live_model} second assistant message",
{
"finish_reason": second.choices[0].finish_reason,
**_message_snapshot(second.choices[0].message),
},
)
second_message = second.choices[0].message
final_content = second_message.content or ""
final_reasoning = _raw_reasoning_content(second_message) or ""
assert second.choices[0].finish_reason == "stop"
assert final_content.strip() or final_reasoning.strip(), (
"DeepSeek returned neither visible content nor reasoning_content"
)