123 lines
4.8 KiB
Python
123 lines
4.8 KiB
Python
import json
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import requests
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from flask import Flask, request, Response
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import re
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# ================= 配置区域 =================
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AUTH_TOKEN = "Bearer 在此处粘贴您的最新Authorization令牌"
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TARGET_URL = "https://biz-discoveryengine.googleapis.com/v1alpha/locations/global/widgetStreamAssist"
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SESSION_ID = "collections/default_collection/engines/agentspace-engine/sessions/16190456916940072265"
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CONFIG_ID = "36cc1840-8078-4a90-ad0a-6f995a52af32"
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# ===============================================================
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app = Flask(__name__)
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def parse_gemini_response(text):
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"""
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最终版精确解析器。
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"""
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try:
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full_response_parts = []
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lines = text.strip().split('\n')
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for line in lines:
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try:
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if line.strip().startswith('{') and line.strip().endswith('}'):
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data = json.loads(line)
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replies = data.get("streamAssistResponse", {}).get("answer", {}).get("replies", [])
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for reply in replies:
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content = reply.get("groundedContent", {}).get("content", {})
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if isinstance(content, dict) and "text" in content:
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full_response_parts.append(content["text"])
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if isinstance(content, dict) and "file" in content and "fileId" in content.get("file", {}):
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file_id = content["file"]["fileId"]
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image_markdown = f"\n\n"
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full_response_parts.append(image_markdown)
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except (json.JSONDecodeError):
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continue
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if full_response_parts:
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return "".join(full_response_parts)
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return "未能从响应流中提取有效内容。"
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except Exception as e:
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return f"解析响应时发生未知错误: {e}"
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@app.route('/v1/chat/completions', methods=['POST'])
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def proxy():
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if "在此处粘贴" in AUTH_TOKEN:
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return Response('{"error": "请在 gemini_proxy.py 脚本中配置 AUTH_TOKEN"}', status=500, mimetype='application/json')
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openai_request = request.json
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messages = openai_request.get('messages', [])
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# 恢复到原始状态：简单拼接所有消息内容
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prompt = ""
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for msg in messages:
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role = msg.get('role', 'user')
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content = msg.get('content', '')
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prompt += f"{role}: {str(content)}\n"
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print(f"收到请求: {prompt[:100]}...")
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payload = {
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"configId": CONFIG_ID,
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"additionalParams": {"token": "-"},
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"streamAssistRequest": {
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"session": SESSION_ID,
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"query": {"parts": [{"text": "\n" + prompt}]},
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"answerGenerationMode": "NORMAL",
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"assistGenerationConfig": {"modelId": "gemini-3-pro-preview"},
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"assistSkippingMode": "REQUEST_ASSIST",
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"languageCode": "zh-CN",
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"userMetadata": {"timeZone": "Asia/Shanghai"}
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}
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}
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headers = {
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"accept": "*/*",
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"authorization": AUTH_TOKEN,
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"content-type": "application/json",
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"origin": "https://business.gemini.google",
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"referer": "https://business.gemini.google/",
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"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",
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}
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try:
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resp = requests.post(TARGET_URL, headers=headers, json=payload)
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if resp.status_code != 200:
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return Response(f'{{"error": "Gemini 请求失败", "status_code": {resp.status_code}, "details": "{resp.text}"}}', status=500, mimetype='application/json')
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gemini_text = parse_gemini_response(resp.text)
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openai_resp = {
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"id": "chatcmpl-gemini-enterprise-proxy",
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"object": "chat.completion",
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"created": 0,
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"choices": [{
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"index": 0,
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"message": {
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"role": "assistant",
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"content": gemini_text
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},
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"finish_reason": "stop"
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}],
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"usage": {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}
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}
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return Response(json.dumps(openai_resp), mimetype='application/json')
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except Exception as e:
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return Response(f'{{"error": "代理服务器内部错误", "details": "{str(e)}"}}', status=500, mimetype='application/json')
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if __name__ == '__main__':
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print("Gemini Enterprise to OpenAI Proxy")
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print("服务已启动: http://localhost:5000/v1/chat/completions")
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print("请注意：每次启动前，您可能都需要更新脚本中的 AUTH_TOKEN。")
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app.run(port=5000, debug=False) |