314 lines
13 KiB
Python
314 lines
13 KiB
Python
import os
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from flask import Flask, request, render_template, send_file, jsonify, redirect, url_for, session
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from docx import Document
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from docx.shared import Inches
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import openai
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import io
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import json
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from config import config
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import time
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from functools import wraps
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try:
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from volcengine.maas import MaasService, MaasException
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except ImportError:
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MaasService = None
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MaasException = None
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try:
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from dashscope import Generation
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except ImportError:
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Generation = None
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app = Flask(__name__)
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app.secret_key = config.FLASK_CONFIG['secret_key']
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def login_required(f):
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# 登录态装饰器，未登录跳转到登录页
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@wraps(f)
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def decorated_function(*args, **kwargs):
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if not session.get('logged_in'):
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return redirect(url_for('login'))
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return f(*args, **kwargs)
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return decorated_function
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def generate_with_openai(prompt, api_key, model, max_tokens=800, temperature=0.7):
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"""使用OpenAI生成内容"""
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client = openai.OpenAI(api_key=api_key)
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response = client.chat.completions.create(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=max_tokens,
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temperature=temperature
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)
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return response.choices[0].message.content
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def generate_with_volcengine(prompt, api_key, model, max_tokens=800, temperature=0.7):
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"""使用火山引擎豆包生成内容"""
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if MaasService is None:
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raise ImportError("火山引擎SDK未安装，请运行: pip install volcengine")
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maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', api_key)
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messages = [{"role": "user", "content": prompt}]
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response = maas.chat(messages, model=model, max_tokens=max_tokens)
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return response['choices'][0]['message']['content']
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def generate_with_dashscope(prompt, api_key, model, max_tokens=800, temperature=0.7):
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"""使用阿里通义千问生成内容"""
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if Generation is None:
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return "阿里云DashScope SDK未安装，请运行: pip install dashscope"
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try:
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response = Generation.call(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=max_tokens,
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api_key=api_key
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)
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print("阿里云原始返回：", response)
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code = getattr(response, 'code', None)
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msg = getattr(response, 'message', None)
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if not response:
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return "阿里云API无响应，请检查网络或API Key。"
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if code and code != 200:
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return f"阿里云 API 错误: {msg or str(response)} (code={code})"
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# 兼容 output.choices 和 output.text
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if hasattr(response, 'output'):
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if hasattr(response.output, 'choices') and response.output.choices:
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return response.output.choices[0].message.content
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elif hasattr(response.output, 'text') and response.output.text:
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return response.output.text
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else:
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return f"阿里云API返回异常：output字段无choices或text，原始返回：{str(response)}"
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else:
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return f"阿里云API返回异常：无output字段，原始返回：{str(response)}"
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except Exception as e:
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import traceback
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print("阿里云API调用异常:", e)
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traceback.print_exc()
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return f"阿里云API调用异常: {str(e)}"
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def generate_news_content(description, style, model_type, topics=None, image=None):
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# topics: list of str, 最多3个
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topic_str = ''
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if topics:
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topics = [t for t in topics if t]
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if topics:
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topic_str = (
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"主题报道部分请围绕下列每个话题分别成段深入分析，每个话题都要有具体内容："
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f"{'、'.join(topics)}。\n"
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)
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image_str = ''
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if image is not None and getattr(image, 'filename', None):
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if image.filename:
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image_str = "如有上传的新闻图片，请结合图片内容进行适当描述。\n"
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prompt = (
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f"你是一名专业新闻记者，请以{style}风格，围绕下述新闻事件，撰写一篇结构完整、语言流畅、符合新闻报道规范的新闻稿。\n"
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f"结构要求：\n"
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f"1. 导语：简要概括新闻事件。\n"
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f"2. 品牌介绍：如涉及品牌，请介绍品牌的背景、定位、优势或发展愿景。\n"
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f"3. 主题报道：{topic_str}每个话题单独成段。\n"
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f"4. 结语：总结新闻意义或展望未来。\n"
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f"其它要求：\n"
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f"- 内容真实、客观，突出事件的背景、经过、影响。\n"
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f"- 字数不少于500字。\n"
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f"- {image_str}"
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f"\n新闻事件描述：\n{description}\n"
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)
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model_config = config.get_model_config(model_type)
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if not model_config:
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return "不支持的模型类型", {}
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api_key = model_config['api_key']
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model = model_config['model']
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max_tokens = model_config['max_tokens']
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temperature = model_config['temperature']
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api_info = {}
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start_time = time.time()
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try:
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if model_type == 'openai':
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client = openai.OpenAI(api_key=api_key)
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response = client.chat.completions.create(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=max_tokens,
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temperature=temperature
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)
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content = response.choices[0].message.content
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usage = getattr(response, 'usage', None)
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if usage:
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api_info['提示tokens'] = usage.prompt_tokens
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api_info['生成tokens'] = usage.completion_tokens
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api_info['总tokens'] = usage.total_tokens
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# 费用估算（OpenAI gpt-4 价格为例，实际可根据模型动态调整）
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# gpt-4-1106-preview: $0.01/1K prompt, $0.03/1K completion
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price_prompt = 0.01 / 1000
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price_completion = 0.03 / 1000
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fee = usage.prompt_tokens * price_prompt + usage.completion_tokens * price_completion
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api_info['费用'] = f"${fee:.4f}"
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else:
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api_info['费用'] = '--'
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api_info['模型'] = model
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elif model_type == 'volcengine':
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if MaasService is None:
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return "火山引擎SDK未安装，请运行: pip install volcengine", {}
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maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', api_key)
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messages = [{"role": "user", "content": prompt}]
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response = maas.chat(messages, model=model, max_tokens=max_tokens)
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content = response['choices'][0]['message']['content']
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if 'usage' in response:
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api_info['提示tokens'] = response['usage'].get('prompt_tokens')
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api_info['生成tokens'] = response['usage'].get('completion_tokens')
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api_info['总tokens'] = response['usage'].get('total_tokens')
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# 费用估算（假设0.005元/1K token，实际需查官方文档）
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price = 0.005 / 1000
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total = response['usage'].get('total_tokens') or 0
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fee = total * price
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api_info['费用'] = f"¥{fee:.4f}"
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else:
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api_info['费用'] = '--'
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api_info['模型'] = model
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elif model_type == 'dashscope':
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if Generation is None:
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return "阿里云DashScope SDK未安装，请运行: pip install dashscope", {}
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response = Generation.call(
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model=model,
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messages=[{"role": "user", "content": prompt}],
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max_tokens=max_tokens,
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api_key=api_key
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)
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# 兼容 output.choices 和 output.text
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if hasattr(response, 'output'):
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if hasattr(response.output, 'choices') and response.output.choices:
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content = response.output.choices[0].message.content
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elif hasattr(response.output, 'text') and response.output.text:
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content = response.output.text
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else:
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content = f"阿里云API返回异常：output字段无choices或text，原始返回：{str(response)}"
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else:
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content = f"阿里云API返回异常：无output字段，原始返回：{str(response)}"
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# tokens统计
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if hasattr(response, 'usage'):
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usage = response.usage
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api_info['提示tokens'] = getattr(usage, 'input_tokens', None) or getattr(usage, 'prompt_tokens', None)
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api_info['生成tokens'] = getattr(usage, 'output_tokens', None) or getattr(usage, 'completion_tokens', None)
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api_info['总tokens'] = getattr(usage, 'total_tokens', None)
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# 费用估算（假设0.012元/1K token，实际需查官方文档）
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price = 0.012 / 1000
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total = getattr(usage, 'total_tokens', None) or 0
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fee = total * price
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api_info['费用'] = f"¥{fee:.4f}"
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else:
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api_info['费用'] = '--'
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api_info['模型'] = model
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else:
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return f"不支持的模型类型: {model_type}", {}
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except Exception as e:
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content = f"生成内容时出错: {str(e)}"
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api_info['响应时间'] = f"{(time.time() - start_time):.2f}s"
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return content, api_info
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def create_word_doc(news_content, image_stream, image_filename):
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doc = Document()
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doc.add_heading(config.DOCUMENT_CONFIG['title'], 0)
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if image_stream:
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doc.add_picture(image_stream, width=Inches(config.DOCUMENT_CONFIG['image_width']))
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doc.add_paragraph(news_content)
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output = io.BytesIO()
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doc.save(output)
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output.seek(0)
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return output
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def get_valid_models(models):
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"""过滤掉结构不完整的模型配置"""
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return {
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k: v for k, v in models.items()
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if v.get('name') and v.get('model')
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}
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@app.route('/login', methods=['GET', 'POST'])
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def login():
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# 登录页面，支持GET和POST
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if request.method == 'POST':
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username = request.form.get('username')
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password = request.form.get('password')
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# 这里简单写死用户名密码，实际可接数据库
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if username == 'admin' and password == '123456':
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session['logged_in'] = True
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return redirect(url_for('index'))
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else:
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return render_template('login.html', error='用户名或密码错误')
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return render_template('login.html')
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@app.route('/logout')
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def logout():
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# 注销登录
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session.pop('logged_in', None)
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return redirect(url_for('login'))
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@app.route('/', methods=['GET', 'POST'])
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@login_required
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def index():
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news_content = ''
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selected_model = request.form.get('model', 'dashscope')
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if request.method == 'POST':
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action = request.form.get('action')
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if action == 'generate':
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description = request.form['description']
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style = request.form['style']
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model_type = request.form['model']
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image = request.files.get('image')
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topics = [request.form.get('topic1', '').strip(), request.form.get('topic2', '').strip(), request.form.get('topic3', '').strip()]
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news_content, api_info = generate_news_content(description, style, model_type, topics, image)
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selected_model = model_type
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# 生成后渲染页面，右侧显示news_content
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return render_template(
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'index.html',
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styles=config.STYLES,
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models=get_valid_models(config.MODELS),
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api_key_status=config.validate_api_keys(),
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news_content=news_content,
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selected_model=selected_model,
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api_info=api_info
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)
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elif action == 'download':
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news_content = request.form.get('news_content', '')
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image = request.files.get('image')
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word_file = create_word_doc(news_content, image.stream if image else None, image.filename if image else None)
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return send_file(word_file, as_attachment=True, download_name=config.DOCUMENT_CONFIG['default_filename'])
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# GET 或首次访问
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return render_template(
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'index.html',
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styles=config.STYLES,
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models=get_valid_models(config.MODELS),
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api_key_status=config.validate_api_keys(),
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news_content=news_content,
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selected_model=selected_model
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)
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@app.route('/api/config', methods=['GET'])
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@login_required
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def get_config():
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"""获取配置信息API"""
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return jsonify({
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'models': config.MODELS,
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'styles': config.STYLES,
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'available_models': config.get_available_models(),
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'api_key_status': config.validate_api_keys()
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})
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@app.route('/api/generate', methods=['POST'])
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@login_required
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def api_generate():
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description = request.form['description']
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style = request.form['style']
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model_type = request.form['model']
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topics = [request.form.get('topic1', '').strip(), request.form.get('topic2', '').strip(), request.form.get('topic3', '').strip()]
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image = request.files.get('image')
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news_content, api_info = generate_news_content(description, style, model_type, topics, image)
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return jsonify({'news_content': news_content, 'api_info': api_info})
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if __name__ == '__main__':
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app.run(
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debug=config.FLASK_CONFIG['debug'],
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host=config.FLASK_CONFIG['host'],
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port=config.FLASK_CONFIG['port']
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) |