Files
WulaFallenEmpireRW/MCP/gemini_image_test.py
2025-12-08 12:43:33 +08:00

108 lines
5.0 KiB
Python

import json
import requests
import re
# ================= 配置区域 =================
# 1. 认证令牌 (Authorization Token)
# 每次运行前,请确保从浏览器开发者工具中获取一个新的令牌
AUTH_TOKEN = "Bearer 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.eyJpc3MiOiJodHRwczovL2J1c2luZXNzLmdlbWluaS5nb29nbGUiLCJhdWQiOiJodHRwczovL2Jpei1kaXNjb3ZlcnllbmdpbmUuZ29vZ2xlYXBpcy5jb20iLCJzdWIiOiJjc2VzaWR4LzMyNjAzOTY4OCIsImlhdCI6MTc2NTE2NzM4NiwiZXhwIjoxNzY1MTY3Njg2LCJuYmYiOjE3NjUxNjczODZ9.urQLDoUDAEjQhX8c42hJfKU28WoKn8-0tGjgX5RqhtY"
# 2. 接口地址
TARGET_URL = "https://biz-discoveryengine.googleapis.com/v1alpha/locations/global/widgetStreamAssist"
# 3. 会话 ID 和 Config ID (使用图片生成时的固定值)
SESSION_ID = "collections/default_collection/engines/agentspace-engine/sessions/16190456916940072265"
CONFIG_ID = "36cc1840-8078-4a90-ad0a-6f995a52af32"
# ===============================================================
def parse_gemini_response(text):
"""
根据真实的流式响应,精确解析并拼接 Gemini 的文本和图片文件回复。
"""
print("------ 原始响应 ------")
print(text)
print("--------------------")
try:
full_response_parts = []
# 响应体是由换行符分隔的一系列JSON对象
lines = text.strip().split('\n')
for line in lines:
try:
data = json.loads(line)
replies = data.get("streamAssistResponse", {}).get("answer", {}).get("replies", [])
for reply in replies:
content = reply.get("groundedContent", {}).get("content", {})
# 检查并提取文本内容
if "text" in content:
full_response_parts.append(content["text"])
# 检查并提取文件(图片)内容
if "file" in content and "fileId" in content["file"]:
file_id = content["file"]["fileId"]
# 将 fileId 构造成一个 Markdown 图片链接。
image_markdown = f"\n![Generated Image](https://business.gemini.google.com/file/{file_id})\n"
full_response_parts.append(image_markdown)
except (json.JSONDecodeError):
# 忽略无法解析为JSON的行
continue
if full_response_parts:
return "".join(full_response_parts)
return "未能从响应流中提取有效内容。"
except Exception as e:
return f"解析响应时发生未知错误: {e}"
def send_test_request(prompt: str):
"""
发送一次测试请求并返回结果。
"""
if "在此处粘贴" in AUTH_TOKEN:
return "错误: 请在脚本中填入真实的 AUTH_TOKEN"
payload = {
"configId": CONFIG_ID,
"additionalParams": {"token": "-"},
"streamAssistRequest": {
"session": SESSION_ID,
"query": {"parts": [{"text": "\n" + prompt}]},
"answerGenerationMode": "NORMAL",
"assistGenerationConfig": {"modelId": "gemini-3-pro-preview"},
"assistSkippingMode": "REQUEST_ASSIST",
"languageCode": "zh-CN",
"userMetadata": {"timeZone": "Asia/Shanghai"}
}
}
headers = {
"accept": "*/*",
"authorization": AUTH_TOKEN,
"content-type": "application/json",
"origin": "https://business.gemini.google",
"referer": "https://business.gemini.google/",
"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0",
}
try:
print(f"正在发送图片生成测试请求: {prompt[:100]}...")
resp = requests.post(TARGET_URL, headers=headers, json=payload)
if resp.status_code != 200:
return f"请求失败! 状态码: {resp.status_code}\n响应内容:\n{resp.text}"
return parse_gemini_response(resp.text)
except Exception as e:
return f"发生异常: {e}"
if __name__ == '__main__':
test_prompt = "画一只戴着宇航员头盔的猫"
result = send_test_request(test_prompt)
print("\n====== 图片生成测试结果 ======")
print(result)
print("==============================")