From 868df96e68d702a89bc41bfad3f31bacf8cf53ab Mon Sep 17 00:00:00 2001
From: EMP <emirhanempi5285@gmail.com>
Date: Wed, 22 Jul 2026 06:11:28 +0300
Subject: [PATCH] =?UTF-8?q?fix/feat:=20=E6=AF=8F=E6=97=A5=E6=97=A9?=
 =?UTF-8?q?=E6=8A=A5?=
MIME-Version: 1.0
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---
 ...17\346\227\245\346\227\251\346\212\245.py" | 95 +++++++++++++++++++
 1 file changed, 95 insertions(+)
 create mode 100644 "contributions/\346\257\217\346\227\245\346\227\251\346\212\245.py"

diff --git "a/contributions/\346\257\217\346\227\245\346\227\251\346\212\245.py" "b/contributions/\346\257\217\346\227\245\346\227\251\346\212\245.py"
new file mode 100644
index 0000000..6c9ab7b
--- /dev/null
+++ "b/contributions/\346\257\217\346\227\245\346\227\251\346\212\245.py"
@@ -0,0 +1,95 @@
+import re
+from datetime import date
+from typing import Dict, Any, List
+
+class DailyReportProcessor:
+    """
+    Analyzes and standardizes raw daily morning report text inputs 
+    into a consistent, predictable data structure (JSON/Dict).
+    """
+    
+    def __init__(self):
+        # Define standard schema keys for normalization
+        self.SCHEMA_KEYS = ["report_date", "source_type", "headline", "summary", "detail"]
+
+    def _cleanse_text(self, text: str) -> str:
+        """Strips common boilerplate/noise characters and excessive whitespace."""
+        # Remove promotional or non-content phrases aggressively
+        text = re.sub(r'欢迎大家来到.*|请联系微信\S+', '', text).strip()
+        # Normalize multiple spaces/newlines
+        return re.sub(r'\s+', ' ', text).strip()
+
+    def parse_product_launch(self, raw_content: str) -> Dict[str, Any]:
+        """Handles product launch formatted reports (Source 1)."""
+        report = {"source_type": "Product Launch", "detail": [], "summary": None}
+        
+        # Regex pattern to capture the main announcement structure
+        product_pattern = re.compile(r'([^\.]+\.)\s*(.*?)\.', re.DOTALL)
+        matches = product_pattern.findall(raw_content)
+
+        if matches:
+            report['summary'] = "Multiple new product announcements detected."
+            for match in matches:
+                # Assuming the structure is [Brand/Theme] + Product Details
+                theme = match[0].strip()
+                details = match[1].strip()
+                product_info = {
+                    "brand": theme,
+                    "headline": details.split("上新")[0].replace('-', '').strip(),
+                    "product": details.split("上新")[-1].strip().rstrip('.'),
+                    "description": details
+                }
+                report['detail'].append(product_info)
+        else:
+             report['summary'] = "Product pattern not found."
+
+        return report
+
+
+    def parse_global_news(self, raw_content: str) -> Dict[str, Any]:
+        """Handles structured global news reports (Source 2)."""
+        # Attempt to extract date/time metadata first
+        date_match = re.search(r'(\d{4}-\d{1,2}-\d{1,2})', raw_content)
+        report = {"source_type": "Global News Feed", "detail": [], "summary": ""}
+
+        if date_match:
+            report['report_date'] = date_match.group(1)
+        else:
+            report['report_date'] = str(date.today()) # Fallback
+
+        # Regex targeting structured news blocks (assuming format like 'Topic: Content...')
+        news_blocks = re.findall(r'([\w\s]+):\s*(.*?)(?=\n[\w\s]+\s*:|\Z)', raw_content, re.DOTALL)
+        
+        for topic, content in news_blocks:
+            summary = self._cleanse_text(content).replace('\n', ' ')
+            report['detail'].append({
+                "topic": topic.strip(),
+                "headline": summary[:70].strip() + "...",
+                "summary": summary
+            })
+        
+        return report
+
+
+    def generate_daily_report(self, raw_input: str, source_tag: str = None) -> Dict[str, Any]:
+        """Main dispatch function to route and process the input based on expected schema."""
+        raw_cleaned = self._cleanse_text(raw_input)
+        final_report = {
+            "source_type": "Unknown", 
+            "timestamp_processed": str(date.today()),
+            "content": {}
+        }
+
+        if source_tag == "PRODUCT":
+            final_report['content'] = self.parse_product_launch(raw_cleaned)
+        elif source_tag == "NEWS":
+            final_report['content'] = self.parse_global_news(raw_cleaned)
+        else: # Default/Generic fallthrough (e.g., Source 3 type content)
+             # Fallback for simple text blocks where only general summary is needed
+            final_report['content'] = {
+                "source_type": "General Update",
+                "summary": raw_cleaned[:200] + "..." if len(raw_cleaned) > 200 else raw_cleaned,
+                "detail": []
+            }
+        
+        return final_report