fix bug in make pre_commit

Author: yuan.wang

evaluation/scripts/PrefEval/pref_memos.py

@@ -12,6 +12,7 @@
 from openai import OpenAI
 from tqdm import tqdm
 
+
 ROOT_DIR = os.path.dirname(
     os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 )
@@ -20,13 +21,6 @@
 sys.path.insert(0, ROOT_DIR)
 sys.path.insert(0, EVAL_SCRIPTS_DIR)
 
-from utils.pref_mem_utils import (
-    add_pref_instruction,
-    create_mem_string,
-    remove_pref_mem_from_mem_string,
-)
-from utils.prompts import PREFEVAL_ANSWER_PROMPT
-
 
 load_dotenv()
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
@@ -78,6 +72,8 @@ def search_memory_for_line(line_data: tuple, mem_client, top_k_value: int) -> di
     """
     Processes a single line of data, searching memory based on the question.
     """
+    from utils.pref_mem_utils import create_mem_string
+
     i, line = line_data
     try:
         original_data = json.loads(line)
@@ -123,6 +119,9 @@ def generate_response_for_line(line_data: tuple, openai_client: OpenAI, lib: str
     """
     Generates a response for a single line of data using pre-fetched memories.
     """
+    from utils.pref_mem_utils import add_pref_instruction, remove_pref_mem_from_mem_string
+    from utils.prompts import PREFEVAL_ANSWER_PROMPT
+
     i, line = line_data
     try:
         original_data = json.loads(line)

evaluation/scripts/locomo/locomo_responses.py

@@ -3,6 +3,7 @@
 import json
 import os
 import sys
+
 from time import time
 
 import pandas as pd
@@ -12,6 +13,7 @@
 from prompts import ANSWER_PROMPT_MEM0, ANSWER_PROMPT_MEMOS, ANSWER_PROMPT_ZEP
 from tqdm import tqdm
 
+
 ROOT_DIR = os.path.dirname(
     os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 )
@@ -34,6 +36,7 @@ async def locomo_response(frame, llm_client, context: str, question: str) -> str
         )
     else:
         from utils.pref_mem_utils import add_pref_instruction
+
         template = add_pref_instruction(ANSWER_PROMPT_MEMOS, frame=frame)
         prompt = template.format(
             context=context,
@@ -53,6 +56,7 @@ async def locomo_response(frame, llm_client, context: str, question: str) -> str
 
 async def process_qa(frame, qa, search_result, oai_client):
     from utils.pref_mem_utils import remove_pref_mem_from_mem_string
+
     start = time()
     query = qa.get("question")
     gold_answer = qa.get("answer")

evaluation/scripts/locomo/locomo_search.py

@@ -12,6 +12,7 @@
 from dotenv import load_dotenv
 from tqdm import tqdm
 
+
 ROOT_DIR = os.path.dirname(
     os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 )
@@ -21,7 +22,6 @@
 sys.path.insert(0, EVAL_SCRIPTS_DIR)
 
 
-
 def mem0_search(client, query, speaker_a_user_id, speaker_b_user_id, top_k, speaker_a, speaker_b):
     from prompts import TEMPLATE_MEM0
 

evaluation/scripts/personamem/pm_ingestion.py

@@ -37,7 +37,7 @@ def ingest_session(session, user_id, session_id, frame, client):
             client.add(messages=session, user_id=user_id, conv_id=session_id)
             print(f"[{frame}] ✅ Session [{session_id}]: Ingested {len(session)} messages")
     elif frame == "memobase":
-        for idx, msg in enumerate(session):
+        for _idx, msg in enumerate(session):
             if msg["role"] != "system":
                 messages.append(
                     {

evaluation/scripts/personamem/pm_metric.py

@@ -80,7 +80,7 @@ def calculate_scores(data, grade_path, output_path):
     print(f"📋 Processing response data for {len(data)} users...")
 
     # First pass: determine number of runs and initialize run accuracy arrays
-    for user_id, user_data in data.items():
+    for _user_id, user_data in data.items():
         # Skip incomplete data (users with only topic field)
         if len(user_data) <= 2 and "topic" in user_data:
             continue

evaluation/scripts/utils/pref_mem_utils.py

@@ -1,16 +1,19 @@
 import os
 import sys
+
+
 sys.path.append(os.path.dirname(os.path.abspath(__file__)))
 from prompts import PREF_INSTRUCTIONS
 
+
 def create_mem_string(relevant_memories) -> str:
     text_memories = []
     explicit = []
     implicit = []
     for item in relevant_memories["text_mem"]:
         for mem in item["memories"]:
             text_memories.append(mem["memory"])
-    text_memories_text = "\n".join(f"{i+1}. {mem}" for i, mem in enumerate(text_memories)).strip()
+    text_memories_text = "\n".join(f"{i + 1}. {mem}" for i, mem in enumerate(text_memories)).strip()
     text_context = f"Plaintext Memory:\n{text_memories_text}\n" if text_memories_text else ""
 
     for item in relevant_memories.get("prefs", []):
@@ -19,9 +22,9 @@ def create_mem_string(relevant_memories) -> str:
                 explicit.append(mem["metadata"]["explicit_preference"])
             elif mem["metadata"]["preference_type"] == "implicit_preference":
                 implicit.append(mem["metadata"]["implicit_preference"])
-    explicit_text = "\n".join(f"{i+1}. {pref}" for i, pref in enumerate(explicit)).strip()
+    explicit_text = "\n".join(f"{i + 1}. {pref}" for i, pref in enumerate(explicit)).strip()
     explicit_context = f"Explicit Preference:\n{explicit_text}\n" if explicit_text else ""
-    implicit_text = "\n".join(f"{i+1}. {pref}" for i, pref in enumerate(implicit)).strip()
+    implicit_text = "\n".join(f"{i + 1}. {pref}" for i, pref in enumerate(implicit)).strip()
     implicit_context = f"Implicit Preference:\n{implicit_text}\n" if implicit_text else ""
     return text_context + explicit_context + implicit_context
 

src/memos/api/routers/server_router.py

@@ -266,7 +266,13 @@ def _format_memory_item(memory_data: Any) -> dict[str, Any]:
 
     return memory
 
-def _post_process_pref_mem(memories_result: list[dict[str, Any]], pref_formatted_mem: list[dict[str, Any]], mem_cube_id: str, handle_pref_mem: bool):
+
+def _post_process_pref_mem(
+    memories_result: list[dict[str, Any]],
+    pref_formatted_mem: list[dict[str, Any]],
+    mem_cube_id: str,
+    handle_pref_mem: bool,
+):
     if os.getenv("RETURN_ORIGINAL_PREF_MEM", "false").lower() == "true" and pref_formatted_mem:
         memories_result["prefs"] = []
         memories_result["prefs"].append(
@@ -279,9 +285,8 @@ def _post_process_pref_mem(memories_result: list[dict[str, Any]], pref_formatted
     if handle_pref_mem:
         pref_instruction: str = instruct_completion(pref_formatted_mem)
         memories_result["pref_mem"] = pref_instruction
-    
-    return memories_result
 
+    return memories_result
 
 
 @router.post("/search", summary="Search memories", response_model=SearchResponse)
@@ -325,7 +330,7 @@ def _search_text():
         return [_format_memory_item(data) for data in results]
 
     def _search_pref():
-        if not os.getenv("ENABLE_PREFERENCE_MEMORY", "false").lower() == "true":
+        if os.getenv("ENABLE_PREFERENCE_MEMORY", "false").lower() != "true":
             return []
         results = naive_mem_cube.pref_mem.search(
             query=search_req.query,
@@ -351,7 +356,9 @@ def _search_pref():
         }
     )
 
-    memories_result = _post_process_pref_mem(memories_result, pref_formatted_memories, search_req.mem_cube_id, search_req.handle_pref_mem)
+    memories_result = _post_process_pref_mem(
+        memories_result, pref_formatted_memories, search_req.mem_cube_id, search_req.handle_pref_mem
+    )
 
     return SearchResponse(
         message="Search completed successfully",
@@ -402,7 +409,7 @@ def _process_text_mem() -> list[dict[str, str]]:
         ]
 
     def _process_pref_mem() -> list[dict[str, str]]:
-        if not os.getenv("ENABLE_PREFERENCE_MEMORY", "false").lower() == "true":
+        if os.getenv("ENABLE_PREFERENCE_MEMORY", "false").lower() != "true":
             return []
         pref_memories_local = naive_mem_cube.pref_mem.get_memory(
             [add_req.messages],

src/memos/templates/instruction_completion.py

@@ -21,10 +21,16 @@ def instruct_completion(
                 implicit_pref.append(pref)
 
     explicit_pref_str = (
-        "Explicit Preference:\n" + "\n".join(f"{i+1}. {pref}" for i, pref in enumerate(explicit_pref)) if explicit_pref else ""
+        "Explicit Preference:\n"
+        + "\n".join(f"{i + 1}. {pref}" for i, pref in enumerate(explicit_pref))
+        if explicit_pref
+        else ""
     )
     implicit_pref_str = (
-        "Implicit Preference:\n" + "\n".join(f"{i+1}. {pref}" for i, pref in enumerate(implicit_pref)) if implicit_pref else ""
+        "Implicit Preference:\n"
+        + "\n".join(f"{i + 1}. {pref}" for i, pref in enumerate(implicit_pref))
+        if implicit_pref
+        else ""
     )
 
     if not explicit_pref_str and not implicit_pref_str: