Fix all lint errors (#2627)

evaluation/src/langmem.py

@@ -1,28 +1,24 @@
+import json
+import multiprocessing as mp
+import os
+import time
+from collections import defaultdict
+
+from dotenv import load_dotenv
+from jinja2 import Template
 from langgraph.checkpoint.memory import MemorySaver
 from langgraph.prebuilt import create_react_agent
 from langgraph.store.memory import InMemoryStore
 from langgraph.utils.config import get_store
-from langmem import (
-    create_manage_memory_tool,
-    create_search_memory_tool
-)
-import time
-import multiprocessing as mp
-import json
-from functools import partial
-import os
-from tqdm import tqdm
+from langmem import create_manage_memory_tool, create_search_memory_tool
 from openai import OpenAI
-from collections import defaultdict
-from dotenv import load_dotenv
 from prompts import ANSWER_PROMPT
+from tqdm import tqdm
 
 load_dotenv()
 
 client = OpenAI()
 
-from jinja2 import Template
-
 ANSWER_PROMPT_TEMPLATE = Template(ANSWER_PROMPT)
 
 

evaluation/src/memzero/add.py

@@ -1,11 +1,13 @@
-from mem0 import MemoryClient
 import json
-import time
 import os
 import threading
-from tqdm import tqdm
+import time
 from concurrent.futures import ThreadPoolExecutor
+
 from dotenv import load_dotenv
+from tqdm import tqdm
+
+from mem0 import MemoryClient
 
 load_dotenv()
 

evaluation/src/memzero/search.py

@@ -1,14 +1,16 @@
+import json
+import os
+import time
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor
-from tqdm import tqdm
-from mem0 import MemoryClient
-import json
-import time
+
+from dotenv import load_dotenv
 from jinja2 import Template
 from openai import OpenAI
-from prompts import ANSWER_PROMPT_GRAPH, ANSWER_PROMPT
-import os
-from dotenv import load_dotenv
+from prompts import ANSWER_PROMPT, ANSWER_PROMPT_GRAPH
+from tqdm import tqdm
+
+from mem0 import MemoryClient
 
 load_dotenv()
 

evaluation/src/openai/predict.py

@@ -1,12 +1,13 @@
-from openai import OpenAI
-import os
+import argparse
 import json
-from jinja2 import Template
-from tqdm import tqdm
+import os
 import time
 from collections import defaultdict
+
 from dotenv import load_dotenv
-import argparse
+from jinja2 import Template
+from openai import OpenAI
+from tqdm import tqdm
 
 load_dotenv()
 

evaluation/src/rag.py

@@ -1,13 +1,14 @@
-from openai import OpenAI
 import json
-import numpy as np
-from tqdm import tqdm
-from jinja2 import Template
-import tiktoken
+import os
 import time
 from collections import defaultdict
-import os
+
+import numpy as np
+import tiktoken
 from dotenv import load_dotenv
+from jinja2 import Template
+from openai import OpenAI
+from tqdm import tqdm
 
 load_dotenv()
 

evaluation/src/zep/add.py

@@ -1,6 +1,7 @@
 import argparse
 import json
 import os
+
 from dotenv import load_dotenv
 from tqdm import tqdm
 from zep_cloud import Message

evaluation/src/zep/search.py

@@ -1,16 +1,16 @@
 import argparse
+import json
+import os
+import time
 from collections import defaultdict
+
 from dotenv import load_dotenv
 from jinja2 import Template
 from openai import OpenAI
+from prompts import ANSWER_PROMPT_ZEP
 from tqdm import tqdm
 from zep_cloud import EntityEdge, EntityNode
 from zep_cloud.client import Zep
-import json
-import os
-import pandas as pd
-import time
-from prompts import ANSWER_PROMPT_ZEP
 
 load_dotenv()
 
@@ -52,7 +52,6 @@ class ZepSearch:
         while retries < max_retries:
             try:
                 user_id = f"run_id_{run_id}_experiment_user_{idx}"
-                session_id = f"run_id_{run_id}_experiment_session_{idx}"
                 edges_results = (self.zep_client.graph.search(user_id=user_id, reranker='cross_encoder', query=query, scope='edges', limit=20)).edges
                 node_results = (self.zep_client.graph.search(user_id=user_id, reranker='rrf', query=query, scope='nodes', limit=20)).nodes
                 context = self.compose_search_context(edges_results, node_results)