feat: nerd-Brain (呆脑子) - 初始提交

- anchor_writer.py: 记忆写入与情感打标
- anchor_search.py: 多维语义检索引擎
- anchor_decay.py: 遗忘曲线 + 归档 + 随机返场
- anchor_vault_sync.py: Vault 索引生成
- README.md: 项目说明文档

anchor_writer.py

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+#!/usr/bin/env python3
+"""
+Anchor Memory Writer
+Writes memory to Obsidian Vault with YAML frontmatter and emotion tags.
+Uses Qwen API (configured in Hermes) for summarization and tagging.
+"""
+import yaml
+import json
+import os
+import urllib.request
+import urllib.error
+from datetime import datetime
+import re
+
+VAULT_DIR = "/Users/fyah/Documents/如梦初醒/memory/test/Anchor-Memory"
+CONFIG_PATH = os.path.expanduser("~/.hermes/config.yaml")
+
+def get_api_config():
+    """Read API config from Hermes config.yaml"""
+    with open(CONFIG_PATH, 'r', encoding='utf-8') as f:
+        config = yaml.safe_load(f)
+    
+    providers = config.get('custom_providers', [])
+    if not providers:
+        raise ValueError("No custom providers found in config")
+    
+    # Find bailian provider
+    bailian = None
+    for p in providers:
+        if p.get('name') == 'bailian':
+            bailian = p
+            break
+            
+    if not bailian:
+        bailian = providers[0] # Fallback to first
+        
+    return bailian['api_key'], bailian['base_url'], bailian.get('model', 'qwen3.5-plus')
+
+def call_model(content):
+    """Call Qwen API to generate summary, tags, and emotion scores"""
+    api_key, base_url, model = get_api_config()
+    
+    # Simpler prompt, no response_format to avoid JSON parsing issues
+    prompt = f"Analyze this text. Output ONLY a valid JSON object. No markdown, no explanation. Keys: summary (max 50 words), tags (list of 3 keywords), valence (-1.0 to 1.0), arousal (0.0 to 1.0). Text: {content}"
+    
+    data = json.dumps({
+        "model": model,
+        "messages": [{"role": "user", "content": prompt}],
+        "temperature": 0.1
+    }).encode('utf-8')
+
+    req = urllib.request.Request(
+        f"{base_url}/chat/completions",
+        data=data,
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {api_key}"
+        }
+    )
+    
+    try:
+        with urllib.request.urlopen(req, timeout=30) as response:
+            result = json.loads(response.read().decode('utf-8'))
+            raw_content = result['choices'][0]['message']['content']
+            
+            # Clean up potential markdown code blocks
+            raw_content = re.sub(r'^```json\s*', '', raw_content)
+            raw_content = re.sub(r'\s*```$', '', raw_content)
+            raw_content = raw_content.strip()
+            
+            return json.loads(raw_content)
+    except Exception as e:
+        print(f"[!] API Error: {e}")
+        # Fallback if API fails
+        return {
+            "summary": content[:50],
+            "tags": ["error", "fallback"],
+            "valence": 0.0,
+            "arousal": 0.0
+        }
+
+def save_memory(content):
+    """Save memory to Obsidian Vault"""
+    meta = call_model(content)
+    now = datetime.now()
+    filename = f"{now.strftime('%Y-%m-%d_%H%M')}.md"
+    filepath = os.path.join(VAULT_DIR, filename)
+    
+    # Construct Markdown with YAML frontmatter
+    md_content = f"""---
+title: {meta.get('summary', 'Untitled')[:30]}
+date: {now.strftime('%Y-%m-%d %H:%M')}
+tags: {meta.get('tags', [])}
+emotion:
+  valence: {meta.get('valence', 0.0)}
+  arousal: {meta.get('arousal', 0.0)}
+status: active
+---
+
+# {meta.get('summary', 'Untitled')}
+
+{content}
+"""
+    with open(filepath, 'w', encoding='utf-8') as f:
+        f.write(md_content)
+    print(f"[+] Memory saved: {filepath}")
+
+if __name__ == "__main__":
+    import sys
+    if len(sys.argv) > 1:
+        content = " ".join(sys.argv[1:])
+        save_memory(content)
+    else:
+        print("Usage: python3 anchor_writer.py <content>")