Code quality improvements: Remove unused imports and fix whitespace issues

app.py

@@ -3,7 +3,7 @@
 import time
 from contextlib import contextmanager
 from functools import lru_cache
-from typing import Any, Dict, Optional
+from typing import Any
 
 # Third-party imports
 import streamlit as st
@@ -292,25 +292,25 @@ def run(self) -> None:
         """Run the application with improved error boundaries and state management"""
         try:
             self.setup_sidebar()
-            
+
             # Enhanced header with visual appeal
             st.markdown(
                 """
-                <div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); 
-                            padding: 2rem; 
-                            border-radius: 16px; 
+                <div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+                            padding: 2rem;
+                            border-radius: 16px;
                             margin-bottom: 2rem;
                             box-shadow: 0 8px 32px rgba(102, 126, 234, 0.3);">
-                    <h1 style="color: white; 
-                               margin: 0; 
+                    <h1 style="color: white;
+                               margin: 0;
                                text-align: center;
                                font-size: 2.5rem;
                                text-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
                                -webkit-text-fill-color: white;">
                         🚀 ML Model Fine-tuning Platform
                     </h1>
-                    <p style="color: rgba(255, 255, 255, 0.9); 
-                              text-align: center; 
+                    <p style="color: rgba(255, 255, 255, 0.9);
+                              text-align: center;
                               margin-top: 0.5rem;
                               font-size: 1.1rem;">
                         Advanced training and optimization for machine learning models

components/__init__.py

@@ -17,4 +17,4 @@
     "plugin_manager",
     "tokenizer_builder",
     "training_monitor",
-]
+]

components/dataset_selector.py

@@ -1,10 +1,8 @@
 import logging
 import re
 from functools import lru_cache
-from typing import Dict, Optional
 
 import streamlit as st
-from datasets import load_dataset
 
 from utils.argilla_dataset import ArgillaDatasetManager
 

components/documentation_viewer.py

@@ -1,5 +1,4 @@
 import os
-from typing import Dict, List
 
 import streamlit as st
 

components/loading_animation.py

@@ -1,6 +1,3 @@
-import time
-from typing import Optional
-
 import streamlit as st
 
 
@@ -128,24 +125,24 @@ def show_training_animation(progress: float | None = None) -> None:
     # Display emoji and progress
     progress_display = progress * 100 if progress is not None else 0
     progress_deg = progress_display * 3.6 if progress is not None else 0
-    
+
     st.markdown(
         f"""
         <div class="training-container">
             <div class="training-emoji">🤖</div>
             <div class="training-emoji">⚡</div>
             <div class="training-emoji">🚀</div>
-            
+
             <div class="progress-circle" style="--progress: {progress_deg}deg;">
                 <div class="progress-inner">
                     {progress_display:.1f}%
                 </div>
             </div>
-            
+
             <div class="training-message">
                 Training in Progress...
             </div>
-            
+
             <div class="training-stats">
                 <div class="stat-item">
                     <div>Progress</div>

components/model_export.py

@@ -1,7 +1,4 @@
-import os
-
 import streamlit as st
-import torch
 from huggingface_hub import HfApi, create_repo
 from transformers import AutoModelForCausalLM, AutoTokenizer
 

components/parameter_config.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Dict, Optional
+from typing import Any
 
 import streamlit as st
 

components/plugin_manager.py

@@ -1,5 +1,4 @@
 import logging
-from typing import Any, Dict
 
 import streamlit as st
 

components/training_monitor.py

@@ -1,6 +1,6 @@
 import logging
 from concurrent.futures import ThreadPoolExecutor
-from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
+from typing import TYPE_CHECKING, Any
 
 import numpy as np
 import plotly.graph_objects as go

plugins/__init__.py

@@ -3,4 +3,4 @@
 # Plugins are dynamically loaded by the registry
 # This file marks the directory as a Python package
 
-__all__ = []
+__all__ = []

plugins/anthropic_code_suggester.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import Any, Dict
+from typing import Any
 
 from anthropic import Anthropic
 

plugins/code_analyzer.py

@@ -1,5 +1,5 @@
 import ast
-from typing import Any, Dict, List
+from typing import Any
 
 from utils.plugins.base import AgentTool, ToolMetadata
 

plugins/openai_code_analyzer.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import Any, Dict
+from typing import Any
 
 from openai import OpenAI
 

utils/__init__.py

@@ -9,4 +9,4 @@
     "TrainingConfig",
     "TrainingMetric",
     "db",
-]
+]

utils/argilla_dataset.py

@@ -1,6 +1,6 @@
 import logging
 import os
-from typing import Any, Dict, List, Optional
+from typing import Any
 
 import argilla as rg
 from datasets import Dataset

utils/config_validator.py

@@ -1,6 +1,6 @@
 import logging
 import re
-from typing import Any, Dict, List, Union
+from typing import Any
 
 # Configure logging
 logging.basicConfig(

utils/distributed_trainer.py

@@ -2,7 +2,7 @@
 import logging
 import os
 from contextlib import contextmanager
-from typing import Any, Dict, Optional
+from typing import Any
 
 import torch
 import torch.distributed as dist

utils/documentation.py

@@ -1,9 +1,8 @@
 import ast
-import inspect
 import logging
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any, Dict, List, Optional
+from typing import Any
 
 logger = logging.getLogger(__name__)
 

utils/model_inference.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Dict, List, Optional, Set, Tuple, Union
+from typing import Any
 
 import torch
 from accelerate import init_empty_weights

utils/model_versioning.py

@@ -2,7 +2,7 @@
 import json
 import os
 from datetime import datetime
-from typing import Any, Dict, Optional
+from typing import Any
 
 
 class ModelVersion:

utils/peft_trainer.py

@@ -1,6 +1,6 @@
 import logging
 from contextlib import contextmanager
-from typing import Any, Dict, Optional, Union
+from typing import Any
 
 import torch
 from peft import (

utils/plugins/base.py

@@ -1,6 +1,6 @@
 import logging
 from abc import ABC, abstractmethod
-from typing import Any, Dict, List, Optional
+from typing import Any
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)

utils/plugins/registry.py

@@ -1,10 +1,8 @@
 import importlib.util
 import inspect
 import logging
-import os
 import sys
 from pathlib import Path
-from typing import Dict, List, Optional, Type
 
 from .base import AgentTool
 

utils/reddit_dataset.py

@@ -1,12 +1,10 @@
 import logging
 import os
 import random
-from datetime import datetime
 from functools import lru_cache
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any
 
 import numpy as np
-import torch
 from datasets import load_dataset
 from tqdm import tqdm