Files
--/test/test_v1_chat_completions.py
T
2026-09-18 03:46:58 +08:00

126 lines
4.5 KiB
Python

from __future__ import annotations
import json
import time
import unittest
import requests
from utils.helper import save_images_from_text
AUTH_KEY = "chatgpt2api"
BASE_URL = "http://localhost:8000"
class ChatCompletionsTests(unittest.TestCase):
def test_text_completion_http(self):
"""测试文本对话的非流式 HTTP 调用。"""
response = requests.post(
f"{BASE_URL}/v1/chat/completions",
headers={"Authorization": f"Bearer {AUTH_KEY}"},
json={
"model": "auto",
"messages": [
{"role": "user", "content": "你好。"},
{"role": "assistant", "content": "你好,我可以帮助你处理文本和图片相关请求。"},
{"role": "user", "content": "那你再简单介绍一下你自己。"},
],
},
timeout=300,
)
print("text non-stream status:")
print(response.status_code)
print("text non-stream result:")
print(json.dumps(response.json(), ensure_ascii=False, indent=2))
def test_text_completion_stream_http(self):
"""测试文本对话的流式 HTTP 调用。"""
response = requests.post(
f"{BASE_URL}/v1/chat/completions",
headers={"Authorization": f"Bearer {AUTH_KEY}"},
json={
"model": "auto",
"stream": True,
"messages": [
{"role": "user", "content": "你好。"},
{"role": "assistant", "content": "你好,我的名字是Claude。"},
{"role": "user", "content": "那你再简单介绍一下你自己,比如你的名字是什么。"},
],
},
stream=True,
timeout=300,
)
print("text stream status:")
print(response.status_code)
print("text stream result:")
for line in response.iter_lines():
if line:
print(line.decode("utf-8", errors="replace"))
def test_image_completion_http(self):
"""测试图片对话的非流式 HTTP 调用。"""
response = requests.post(
f"{BASE_URL}/v1/chat/completions",
headers={"Authorization": f"Bearer {AUTH_KEY}"},
json={
"model": "gpt-image-2",
"messages": [
{"role": "user", "content": "我想做一张南京城市宣传海报图。"},
],
"n": 1,
},
timeout=300,
)
payload = response.json()
content = str((((payload.get("choices") or [{}])[0].get("message") or {}).get("content") or ""))
saved_paths = save_images_from_text(content, "chat_completions_image_non_stream")
print("image non-stream status:")
print(response.status_code)
print("image non-stream saved files:")
for path in saved_paths:
print(path)
def test_image_completion_stream_http(self):
"""测试图片对话的流式 HTTP 调用。"""
response = requests.post(
f"{BASE_URL}/v1/chat/completions",
headers={"Authorization": f"Bearer {AUTH_KEY}"},
json={
"model": "gpt-image-2",
"stream": True,
"messages": [
{"role": "user", "content": "我想做一张南京城市宣传海报图。"},
],
"n": 1,
},
stream=True,
timeout=300,
)
parts: list[str] = []
started_at = time.time()
print("image stream status:")
print(response.status_code)
print("image stream chunks:")
for line in response.iter_lines():
if not line:
continue
text = line.decode("utf-8", errors="replace")
print(f"{time.time() - started_at:6.2f}s {text}")
if not text.startswith("data:"):
continue
payload = text[5:].strip()
if payload == "[DONE]":
break
try:
chunk = json.loads(payload)
except Exception:
continue
delta = ((chunk.get("choices") or [{}])[0].get("delta") or {})
content = str(delta.get("content") or "")
if content:
parts.append(content)
saved_paths = save_images_from_text("".join(parts), "chat_completions_image_stream")
print("image stream saved files:")
for path in saved_paths:
print(path)