Fix/retrieve user isolation

app/main.py

@@ -202,8 +202,16 @@ async def retrieve(request: Request, payload: dict[str, Any]):
         raise HTTPException(status_code=400, detail="'query' must be a non-empty string")
     try:
         service = request.app.state.service
-        result = await service.retrieve([query.strip()])
-        return JSONResponse(content={"status": "success", "result": result})
+        user_id = payload.get("user_id")
+        where = {"user_id": user_id} if user_id else None
+        skip_routing = payload.get("skip_routing", True)
+        service.retrieve_config.route_intention = not skip_routing
+        result = await service.retrieve([query.strip()], where=where)
+        # Sanitize datetime objects for JSON serialization
+        import json as _json
+
+        sanitized = _json.loads(_json.dumps(result, default=str))
+        return JSONResponse(content={"status": "success", "result": sanitized})
     except Exception as exc:
         logger.exception("Retrieve request failed")
         raise HTTPException(status_code=500, detail="Internal server error") from exc

app/services/memu.py

@@ -8,29 +8,31 @@
 from config.settings import Settings
 
 
+def _deep_merge(base: dict, override: dict) -> dict:
+    """Merge override into base dict recursively. Override wins on conflicts."""
+    merged = {**base}
+    for key, val in override.items():
+        if key in merged and isinstance(merged[key], dict) and isinstance(val, dict):
+            merged[key] = _deep_merge(merged[key], val)
+        else:
+            merged[key] = val
+    return merged
+
+
 def create_memory_service(
     settings: Settings | None = None,
     memorize_config: dict[str, Any] | None = None,
     retrieve_config: dict[str, Any] | None = None,
 ) -> MemoryService:
-    """Create a configured MemoryService instance.
-
-    Args:
-        settings: Application settings. Uses default if not provided.
-        memorize_config: Optional memorize workflow config override.
-        retrieve_config: Optional retrieve workflow config override.
-
-    Returns:
-        Configured MemoryService instance.
-    """
     if settings is None:
         settings = Settings()
 
     memu_config = build_memu_config(settings)
 
     kwargs = {**memu_config}
     if memorize_config:
-        kwargs["memorize_config"] = memorize_config
+        base = kwargs.get("memorize_config", {})
+        kwargs["memorize_config"] = _deep_merge(base, memorize_config)
     if retrieve_config:
         kwargs["retrieve_config"] = retrieve_config
 

config/memu.py

@@ -1,21 +1,23 @@
 """MemU configuration for memory service."""
 
+import logging
+from pathlib import Path
 from typing import Any
 
+import yaml
 from pydantic import BaseModel
 
 from config.settings import Settings
 
+logger = logging.getLogger(__name__)
 
-class MemUUser(BaseModel):
-    """User model for memu-py."""
 
+class MemUUser(BaseModel):
     user_id: str
     agent_id: str | None = None
 
 
 def build_memu_llm_profiles(settings: Settings) -> dict[str, Any]:
-    """Build LLM profiles for memu-py."""
     return {
         "default": {
             "api_key": settings.OPENAI_API_KEY,
@@ -30,22 +32,61 @@ def build_memu_llm_profiles(settings: Settings) -> dict[str, Any]:
     }
 
 
-def build_memu_config(settings: Settings) -> dict[str, Any]:
-    """Build memu-py core configuration.
+def load_prompt_overrides(path: str) -> dict[str, Any] | None:
+    """Load custom prompt overrides from a YAML file.
 
-    This configures memu-py to:
-    1. Connect to PostgreSQL with pgvector
-    2. Auto-create tables (ddl_mode: create)
-    3. Use configured LLM profiles
+    The YAML structure should match memu-py's MemorizeConfig.memory_type_prompts:
+        profile:
+          rules:
+            ordinal: 30
+            prompt: |
+              # Rules
+              ...
+          examples:
+            ordinal: 60
+            prompt: |
+              # Examples
+              ...
+        event:
+          rules:
+            ordinal: 30
+            prompt: |
+              ...
     """
-    return {
+    if not path:
+        return None
+    p = Path(path)
+    if not p.exists():
+        logger.warning("PROMPT_CONFIG_PATH=%s does not exist, using defaults", path)
+        return None
+    try:
+        with p.open("r", encoding="utf-8") as f:
+            data = yaml.safe_load(f)
+        if data and isinstance(data, dict):
+            logger.info("Loaded prompt overrides from %s (types: %s)", path, list(data.keys()))
+            return data
+        logger.warning("PROMPT_CONFIG_PATH=%s is empty or invalid, using defaults", path)
+        return None
+    except Exception:
+        logger.exception("Failed to load prompt overrides from %s", path)
+        return None
+
+
+def build_memu_config(settings: Settings) -> dict[str, Any]:
+    config: dict[str, Any] = {
         "llm_profiles": build_memu_llm_profiles(settings),
         "database_config": {
             "metadata_store": {
                 "provider": "postgres",
-                "ddl_mode": "create",  # Auto-create tables
+                "ddl_mode": "create",
                 "dsn": settings.DATABASE_URL,
             }
         },
         "user_config": {"model": MemUUser},
     }
+
+    prompt_overrides = load_prompt_overrides(settings.PROMPT_CONFIG_PATH)
+    if prompt_overrides:
+        config["memorize_config"] = {"memory_type_prompts": prompt_overrides}
+
+    return config

config/prompts.yaml

@@ -0,0 +1,153 @@
+# memU 自定义提取 prompt 覆盖
+# 结构：memory_type → block_name → {ordinal, prompt}
+# ordinal 控制拼接顺序（20=workflow, 30=rules, 60=examples）
+
+profile:
+  workflow:
+    ordinal: 20
+    prompt: |
+      # Workflow
+      For each potential memory item, follow this strict 4-step process:
+
+      Step 1 — SOURCE CHECK: Identify WHO said it.
+        - Did the USER state this as a fact about themselves? → Proceed to Step 2.
+        - Did the ASSISTANT say it? → DISCARD immediately.
+        - Is it a QUESTION from either side? → DISCARD immediately.
+        - Is it a command (e.g., /new, /help)? → DISCARD immediately.
+        - Is it a greeting (你好, hi, hello, 你好啊)? → DISCARD immediately.
+
+      Step 2 — FACT VERIFICATION: Is this a declarative fact about the user?
+        - "我叫小明" → YES, fact → Proceed to Step 3.
+        - "我叫什么名字？" → NO, this is a question → DISCARD.
+        - "我不知道" (said by user) → borderline, only if user explicitly states ignorance as a trait.
+        - "我不确定" (said by assistant) → NO, this is assistant's state → DISCARD.
+
+      Step 3 — PERSISTENCE CHECK: Is this stable, lasting information?
+        - Preferences, name, age, job, hobbies → YES.
+        - Temporary mood, current action, situational comment → NO, DISCARD.
+
+      Step 4 — OUTPUT: Only items that passed ALL three steps are extracted.
+        If no items pass all checks, output NOTHING. Empty output is valid and preferred over noise.
+
+  rules:
+    ordinal: 30
+    prompt: |
+      # Rules
+      ## Absolute prohibitions (ANY violation = invalid extraction)
+      1. NEVER extract anything said by the ASSISTANT as a user fact.
+      2. NEVER extract questions as facts. A question contains no factual information.
+      3. NEVER extract greetings, farewells, or pleasantries.
+      4. NEVER extract slash commands or meta-conversation actions.
+      5. NEVER extract "the user asked/wanted to know/inquired about" — asking is not a fact.
+      6. NEVER extract "the user does not know X" unless the user EXPLICITLY stated "我不知道X".
+         If the ASSISTANT said "I don't know", that is NOT the user's trait.
+
+      ## What to extract
+      - Only declarative facts the user stated about themselves: name, age, job, preferences, habits, relationships.
+      - Each item must be < 30 words, self-contained, and written as a declarative sentence.
+      - Use "The user" as the subject consistently.
+      - Merge similar items into one.
+
+  examples:
+    ordinal: 60
+    prompt: |
+      # Examples
+      Example 1 — GOOD extraction
+      Input:
+        user: 我叫小明，今年28岁，在一家互联网公司做产品经理。我喜欢编程和打篮球。
+        assistant: 很高兴认识你，小明！
+      Output:
+        <item>
+            <memory><content>The user's name is 小明</content><categories><category>Basic Information</category></categories></memory>
+            <memory><content>The user is 28 years old</content><categories><category>Basic Information</category></categories></memory>
+            <memory><content>The user works as a product manager at an internet company</content><categories><category>Work</category></categories></memory>
+            <memory><content>The user likes programming and basketball</content><categories><category>Preferences</category></categories></memory>
+        </item>
+
+      Example 2 — NOISE (output must be EMPTY)
+      Input:
+        user: 我叫什么名字？
+        assistant: 很抱歉，我不确定您的名字。您能告诉我吗？
+        user: /new
+        assistant: 好的，我们开始新的对话吧！
+        user: 你好啊
+        assistant: 你好！有什么可以帮您的？
+      Output:
+        (empty)
+      Reason: "我叫什么名字？"=question. "我不确定"=assistant speech. "/new"=command. "你好啊"=greeting. ZERO facts about the user.
+
+      Example 3 — NOISE (output must be EMPTY)
+      Input:
+        user: 你知道明天天气怎么样吗？
+        assistant: 我无法获取实时天气信息。
+        user: 好的谢谢
+        assistant: 不客气！
+      Output:
+        (empty)
+      Reason: All utterances are questions, assistant limitations, and pleasantries. ZERO user facts.
+
+event:
+  workflow:
+    ordinal: 20
+    prompt: |
+      # Workflow
+      For each potential event, follow this strict 4-step process:
+
+      Step 1 — SOURCE CHECK: Identify WHO said it and WHAT was said.
+        - Did the USER describe a concrete event that happened? → Proceed to Step 2.
+        - Did the ASSISTANT say it? → DISCARD immediately.
+        - Is it a QUESTION about something? → DISCARD immediately.
+        - Is it a command (/new, /help) or greeting (你好, hi, hello, 你好啊, hey)? → DISCARD immediately.
+        - Is it a response to a greeting (不客气, glad to meet you)? → DISCARD immediately.
+        - Is it a social pleasantry (谢谢, 好的, sure)? → DISCARD immediately.
+
+      Step 2 — EVENT VERIFICATION: Is this a specific, significant happening?
+        - "I traveled to Japan last month" → YES, event → Proceed.
+        - "I asked about my schedule" → NO, asking is not an event → DISCARD.
+        - "I don't know my plans" (user said) → borderline, not an event → DISCARD.
+
+      Step 3 — SIGNIFICANCE CHECK: Does this event matter long-term?
+        - Life milestones, travel, major decisions → YES.
+        - Routine daily activities → NO, DISCARD.
+
+      Step 4 — OUTPUT: Only events that passed ALL three steps.
+        Empty output is valid and preferred over noise.
+
+  rules:
+    ordinal: 30
+    prompt: |
+      # Rules
+      ## Absolute prohibitions (ANY violation = invalid extraction)
+      1. NEVER extract anything said by the ASSISTANT as a user event.
+      2. NEVER extract questions as events.
+      3. NEVER extract greetings (你好, hi, hello), farewells, commands, or social pleasantries as events.
+      4. NEVER extract "the user asked about X" — asking is not an event.
+      5. NEVER extract "the user does not know X" — ignorance is not an event.
+      6. NEVER extract "the user greeted" or "the user said hello" — greetings are NOT events.
+
+      ## What to extract
+      - Only concrete events with time, place, or participants that the user described.
+      - Focus on significant happenings, not routine activities.
+      - Each item < 50 words, self-contained, declarative sentence.
+
+  examples:
+    ordinal: 60
+    prompt: |
+      # Examples
+      Example 1 — GOOD extraction
+      Input:
+        user: 上周我去了东京旅游，玩了5天，吃了好多寿司。
+        assistant: 听起来很棒！东京好玩吗？
+      Output:
+        <item>
+            <memory><content>The user traveled to Tokyo for 5 days last week and ate a lot of sushi</content><categories><category>Travel</category></categories></memory>
+        </item>
+
+      Example 2 — NOISE (output must be EMPTY)
+      Input:
+        user: 我明天有什么安排？
+        assistant: 很抱歉，我没有您明天的日程安排信息。
+        user: /new
+      Output:
+        (empty)
+      Reason: "我明天有什么安排？"=question. "我没有信息"=assistant speech. "/new"=command. ZERO events.

config/settings.py

@@ -42,6 +42,11 @@ class Settings(BaseSettings):
     # ── Storage ──
     STORAGE_PATH: str = "./data/storage"
 
+    # ── Prompt Configuration ──
+    # Path to a YAML file containing custom prompt overrides for memu-py.
+    # If empty or the file does not exist, memu-py defaults are used.
+    PROMPT_CONFIG_PATH: str = ""
+
     @field_validator("DATABASE_URL", mode="after")
     @classmethod
     def assemble_db_url(cls, v: str, info: ValidationInfo) -> str: