support analyze article by ALI QWEN-PLUS
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@ -235,3 +235,5 @@ TWITTER_CONFIG = {
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TRUTH_SOCIAL_API = {"api_key": "FRfhlDHnmYc1PCCrVHZdWtqDENr2",
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"user_id": {"realDonaldTrump": "107780257626128497"}}
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ALI_API_KEY = "sk-216039fdd9ee4bc48667418b23e648d0"
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@ -17,6 +17,8 @@ class DBTruthSocialContent:
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"timestamp",
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"date_time",
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"text",
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"analysis_result",
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"analysis_token",
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"media_url",
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"media_type",
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"media_thumbnail"
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@ -1,6 +1,6 @@
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import core.logger as logging
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from core.db.db_truth_social_content import DBTruthSocialContent
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from config import TRUTH_SOCIAL_API, COIN_MYSQL_CONFIG, WECHAT_CONFIG
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from config import TRUTH_SOCIAL_API, COIN_MYSQL_CONFIG, WECHAT_CONFIG, ALI_API_KEY
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from core.wechat import Wechat
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import requests
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@ -11,9 +11,11 @@ import time
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from datetime import datetime
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import pytz
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import pandas as pd
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import dashscope
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logger = logging.logger
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class TruthSocialRetriever:
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def __init__(self) -> None:
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self.api_key = TRUTH_SOCIAL_API.get("api_key", "")
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@ -38,20 +40,28 @@ class TruthSocialRetriever:
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self.save_path = r"./output/media/truth_social/"
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os.makedirs(self.save_path, exist_ok=True)
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def get_user_id_from_page(self, handle='realDonaldTrump'):
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url = f'https://truthsocial.com/@{handle}'
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headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'} # 模拟浏览器
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self.ali_api_key = ALI_API_KEY
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instruction_file = r"./instructions/media_article_instructions.json"
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with open(instruction_file, "r", encoding="utf-8") as f:
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self.instruction = json.load(f)
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def get_user_id_from_page(self, handle="realDonaldTrump"):
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url = f"https://truthsocial.com/@{handle}"
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headers = {
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
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} # 模拟浏览器
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response = requests.get(url, headers=headers)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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soup = BeautifulSoup(response.text, "html.parser")
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# 查找嵌入的 JSON（Truth Social 使用 data 属性或 script 标签）
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scripts = soup.find_all('script')
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scripts = soup.find_all("script")
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for script in scripts:
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if script.string and 'id' in script.string and handle in script.string:
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if script.string and "id" in script.string and handle in script.string:
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# 简单提取（实际可能需正则匹配 JSON）
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import re
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match = re.search(r'"id"\s*:\s*"(\d+)"', script.string)
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if match:
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return match.group(1)
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@ -70,20 +80,17 @@ class TruthSocialRetriever:
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返回:
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- 帖子列表（JSON 格式）。
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"""
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headers = {
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'x-api-key': self.api_key,
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'Content-Type': 'application/json'
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}
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headers = {"x-api-key": self.api_key, "Content-Type": "application/json"}
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for user_name, user_id in self.user_info.items():
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params = {
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'handle': user_name, # 用户名
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'user_id': user_id, # 可选，用户 ID
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'next_max_id': None, # 分页时设置为上一次响应的 max_id
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'trim': 'false' # 保留完整内容
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"handle": user_name, # 用户名
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"user_id": user_id, # 可选，用户 ID
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"next_max_id": None, # 分页时设置为上一次响应的 max_id
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"trim": "false", # 保留完整内容
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}
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url = 'https://api.scrapecreators.com/v1/truthsocial/user/posts'
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url = "https://api.scrapecreators.com/v1/truthsocial/user/posts"
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logger.info(f"Searching contents for user: {user_name}")
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try:
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response = requests.get(url, headers=headers, params=params)
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@ -92,34 +99,36 @@ class TruthSocialRetriever:
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# 提取帖子列表（假设响应中 'posts' 是键，根据实际文档调整）
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if limit is not None and isinstance(limit, int):
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posts = data.get('posts', [])[:limit]
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posts = data.get("posts", [])[:limit]
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else:
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posts = data.get('posts', [])
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posts = data.get("posts", [])
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results = []
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if posts:
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logger.info(f"获取{user_name}帖子: {len(posts)}条")
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for post in posts:
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result = {}
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result["article_id"] = post.get('id')
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result["article_id"] = post.get("id")
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result["user_id"] = user_id
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result["user_name"] = user_name
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datetime_text = post.get('created_at')
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datetime_text = post.get("created_at")
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datetime_dict = self.transform_datetime(datetime_text)
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timestamp_ms = datetime_dict["timestamp_ms"]
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result["timestamp"] = timestamp_ms
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beijing_time_str = datetime_dict["beijing_time_str"]
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result["date_time"] = beijing_time_str
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result["text"] = post.get('text', '无内容')
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media_attachments = post.get('media_attachments', [])
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result["text"] = post.get("text", "无内容")
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media_attachments = post.get("media_attachments", [])
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result["media_url"] = ""
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result["media_type"] = ""
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result["media_thumbnail"] = ""
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if media_attachments:
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for media_attachment in media_attachments:
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result["media_url"] = media_attachment.get('url')
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result["media_type"] = media_attachment.get('type')
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result["media_thumbnail"] = media_attachment.get('preview_url')
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result["media_url"] = media_attachment.get("url")
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result["media_type"] = media_attachment.get("type")
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result["media_thumbnail"] = media_attachment.get(
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"preview_url"
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)
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break
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results.append(result)
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else:
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@ -136,10 +145,28 @@ class TruthSocialRetriever:
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# logger.info(f"已将{len(results)}条数据保存到: {json_file_name}")
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result_df = pd.DataFrame(results)
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result_df = self.remove_duplicate_posts(result_df)
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result_df["analysis_result"] = ""
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result_df["analysis_token"] = 0
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if len(result_df) > 0:
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result_df = self.send_wechat_message(result_df)
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result_df = result_df[
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[
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"article_id",
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"user_id",
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"user_name",
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"timestamp",
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"date_time",
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"text",
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"analysis_result",
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"analysis_token",
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"media_url",
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"media_type",
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"media_thumbnail",
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]
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]
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self.db_truth_social_content.insert_data_to_mysql(result_df)
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logger.info(f"已将{len(result_df)}条数据插入到数据库")
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self.send_wechat_message(result_df)
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else:
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logger.info(f"没有数据需要插入到数据库和发送企业微信消息")
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except requests.exceptions.RequestException as e:
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@ -148,7 +175,7 @@ class TruthSocialRetriever:
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print(f"JSON 解析错误: {e}")
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def send_message_by_json_file(self, json_file_name: str):
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with open(json_file_name, 'r', encoding='utf-8') as f:
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with open(json_file_name, "r", encoding="utf-8") as f:
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results = json.load(f)
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result_df = pd.DataFrame(results)
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result_df = self.remove_duplicate_posts(result_df)
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@ -162,7 +189,9 @@ class TruthSocialRetriever:
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duplicate_index_list = []
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for index, row in result_df.iterrows():
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article_id = row["article_id"]
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exist_data = self.db_truth_social_content.query_data_by_article_id(article_id)
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exist_data = self.db_truth_social_content.query_data_by_article_id(
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article_id
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)
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if exist_data:
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duplicate_index_list.append(index)
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# 删除重复的行
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@ -188,18 +217,73 @@ class TruthSocialRetriever:
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self.wechat.send_image(media_thumbnail)
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else:
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contents = []
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contents.append(f"### 川普推文")
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contents.append(f"## 川普推文")
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contents.append(text)
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contents.append(f"### 推文时间")
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contents.append(f"## 推文时间")
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contents.append(date_time)
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mark_down_text = "\n\n".join(contents)
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analysis_result, analysis_token = self.analyze_truth_social_content(
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text
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)
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result_df.at[index, "analysis_result"] = analysis_result
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result_df.at[index, "analysis_token"] = analysis_token
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analysis_text = f"\n\n## 分析结果\n\n{analysis_result}"
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analysis_text += f"\n\n## 分析token\n\n{analysis_token}"
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if self.calculate_bytes(mark_down_text + analysis_text) > 4096:
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self.wechat.send_markdown(mark_down_text)
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if self.calculate_bytes(analysis_text) > 4096:
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half_analysis_text_length = len(analysis_text) // 2
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analysis_1st = analysis_text[:half_analysis_text_length].strip()
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analysis_2nd = analysis_text[half_analysis_text_length:].strip()
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self.wechat.send_markdown(
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f"## 分析结果第一部分\n\n{analysis_1st}"
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)
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self.wechat.send_markdown(
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f"## 分析结果第二部分\n\n{analysis_2nd}"
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)
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else:
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self.wechat.send_markdown(f"## 分析结果\n\n{analysis_text}")
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else:
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self.wechat.send_markdown(mark_down_text + analysis_text)
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except Exception as e:
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logger.error(f"发送企业微信消息失败: {e}")
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continue
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return result_df
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def calculate_bytes(self, text: str):
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return len(text.encode("utf-8"))
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def analyze_truth_social_content(self, text: str):
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try:
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context = text
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instructions = self.instruction.get("Instructions", "")
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output = self.instruction.get("Output", "")
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prompt = f"# Context\n\n{context}\n\n# Instructions\n\n{instructions}\n\n# Output\n\n{output}"
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response = dashscope.Generation.call(
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api_key=self.ali_api_key,
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model="qwen-plus",
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messages=[{"role": "user", "content": prompt}],
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enable_search=True,
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search_options={"forced_search": True}, # 强制联网搜索
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result_format="message",
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)
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response_contents = (
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response.get("output", {})
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.get("choices", [])[0]
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.get("message", {})
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.get("content", "")
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)
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# 获取response的token
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token = response.get("usage", {}).get("total_tokens", 0)
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return response_contents, token
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except Exception as e:
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logger.error(f"分析推文失败: {e}")
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return None
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def transform_datetime(self, datetime_text: str):
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utc_time = datetime.strptime(datetime_text, "%Y-%m-%dT%H:%M:%S.%fZ").replace(tzinfo=pytz.UTC)
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utc_time = datetime.strptime(datetime_text, "%Y-%m-%dT%H:%M:%S.%fZ").replace(
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tzinfo=pytz.UTC
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)
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# 1. 转换为时间戳（毫秒）
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timestamp_ms = int(utc_time.timestamp() * 1000)
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@ -209,9 +293,5 @@ class TruthSocialRetriever:
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beijing_time_str = beijing_time.strftime("%Y-%m-%dT%H:%M:%S%z")
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# 插入冒号到时区偏移（如 +0800 -> +08:00）
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beijing_time_str = beijing_time_str[:-2] + ":" + beijing_time_str[-2:]
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result = {
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"timestamp_ms": timestamp_ms,
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"beijing_time_str": beijing_time_str
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}
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result = {"timestamp_ms": timestamp_ms, "beijing_time_str": beijing_time_str}
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return result
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@ -0,0 +1,5 @@
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{
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"Context": "{0}\n\n",
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"Instructions": "你是一个专业的时政与金融分析师，你的任务是分析推文，结合推文时间（北京时间），联网搜索，并给出分析结果。\n要求：1. 翻译推文为中文，要求符合中文表达习惯；\n2. 分析推文内容，给出推文的核心观点；\n3. 人物分析：分析推文涉及人物以及人物简介；4. 区域分析：包括国家与地区；5. 行业以及影响分析；6. 经济与金融分析：分析涉及经济与金融影响，包括美股、虚拟货币以及中国A股；\n\n",
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"Output": "## 输出要求\n\n除了翻译之外，核心观点+人物分析+区域分析+行业及影响分析+经济与金融分析，不超过1000汉字。\n\n## 输出格式\n\n### 翻译\n\n### 人物分析\n\n### 区域分析\n\n### 行业及影响分析\n\n### 经济与金融分析\n\n"
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}
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@ -12,3 +12,4 @@ openpyxl >= 3.1.5
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cryptography >= 3.4.8
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mplfinance
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schedule
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dashscope >= 1.24.7
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@ -5,6 +5,8 @@ CREATE TABLE `truth_social_content` (
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`timestamp` BIGINT NOT NULL,
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`date_time` VARCHAR(50) NOT NULL,
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`text` TEXT NOT NULL,
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`analysis_result` TEXT NULL,
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`analysis_token` INT NULL,
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`media_url` TEXT NULL,
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`media_type` VARCHAR(50) NULL,
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`media_thumbnail` TEXT NULL,
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@ -14,6 +16,10 @@ CREATE TABLE `truth_social_content` (
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-- 对于 MySQL 8.0.29 之前的版本不支持 "ADD COLUMN IF NOT EXISTS"
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-- 如需在已有表上添加列，请分别执行以下语句（每条仅需执行一次）
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ALTER TABLE `truth_social_content`
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ADD COLUMN `analysis_result` TEXT NULL DEFAULT NULL AFTER `text`;
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ALTER TABLE `truth_social_content`
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ADD COLUMN `analysis_token` INT NULL DEFAULT NULL AFTER `analysis_result`;
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ALTER TABLE `truth_social_content`
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ADD COLUMN `media_url` TEXT NULL DEFAULT NULL AFTER `text`;
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ALTER TABLE `truth_social_content`
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