Fix: Use OpenLLM modules from uploaded files (model.py and data_loader.py)

app.py

@@ -1,16 +1,15 @@
 #!/usr/bin/env python3
 """
-OpenLLM Training Space Application - OpenLLM Compatible
+OpenLLM Training Space Application - Fixed with Uploaded Modules
 
-This version uses OpenLLM's actual custom model architecture and loading approach:
-- Uses custom GPTModel class (not Hugging Face Transformers)
-- Loads models using torch.load() and load_state_dict()
-- Uses sentencepiece.SentencePieceProcessor() for tokenization
-- Compatible with OpenLLM's actual implementation
+This version imports OpenLLM modules from the uploaded files in the HF Space:
+- Imports model.py and data_loader.py that were uploaded to the Space
+- Uses OpenLLM's actual custom model architecture
+- Compatible with OpenLLM's implementation
 
 Author: Louis Chua Bean Chong
 License: GPL-3.0
-Version: 2.0.9
+Version: 2.1.0
 Last Updated: 2024
 """
 
@@ -26,15 +25,13 @@ import threading
 from dataclasses import dataclass
 from pathlib import Path
 
-# Import OpenLLM's custom model architecture
+# Import OpenLLM's custom model architecture from uploaded files
 try:
-    # Try to import from local OpenLLM code
-    import sys
-    sys.path.append('core/src')
+    # Import from the uploaded files in the HF Space
     from model import GPTModel, GPTConfig, create_model
     from data_loader import TextDataLoader
     OPENLLM_AVAILABLE = True
-    print("✅ OpenLLM custom model architecture imported successfully")
+    print("✅ OpenLLM custom model architecture imported successfully from uploaded files")
 except ImportError as e:
     print(f"❌ OpenLLM imports failed: {e}")
     OPENLLM_AVAILABLE = False
@@ -455,20 +452,20 @@ def main():
     
     # Create the main Gradio application interface
     with gr.Blocks(
-        title="OpenLLM Training Space - OpenLLM Compatible",
+        title="OpenLLM Training Space - Fixed with Uploaded Modules",
         theme=gr.themes.Soft()
     ) as demo:
         
         # Application Header
-        gr.Markdown("# 🚀 OpenLLM Training Space - OpenLLM Compatible")
-        gr.Markdown("### *Uses OpenLLM's Custom Model Architecture*")
+        gr.Markdown("# 🚀 OpenLLM Training Space - Fixed with Uploaded Modules")
+        gr.Markdown("### *Uses OpenLLM's Custom Model Architecture from Uploaded Files*")
         gr.Markdown("---")
         
         # Status Information
         gr.Markdown(f"**OpenLLM Available**: {'✅ Yes' if OPENLLM_AVAILABLE else '❌ No'}")
         gr.Markdown(f"**SentencePiece Available**: {'✅ Yes' if SENTENCEPIECE_AVAILABLE else '❌ No'}")
         gr.Markdown(f"**Dependencies Available**: {'✅ Yes' if DEPENDENCIES_AVAILABLE else '❌ No'}")
-        gr.Markdown("**Architecture**: ✅ OpenLLM Custom GPTModel (Not Hugging Face)")
+        gr.Markdown("**Architecture**: ✅ OpenLLM Custom GPTModel (From Uploaded Files)")
         
         # Main Content Area
         with gr.Row():
@@ -535,9 +532,9 @@ def main():
                     stop_btn = gr.Button("⏹️ Stop Training", variant="stop")
         
         # Instructions Section
-        gr.Markdown("## 📋 OpenLLM Compatible Training Instructions")
+        gr.Markdown("## 📋 OpenLLM Training Instructions")
         gr.Markdown("""
-        This interface uses **OpenLLM's actual custom model architecture**:
+        This interface uses **OpenLLM's actual custom model architecture** from uploaded files:
         
         ### **Step 1: Configure Parameters**
         - **Model Size**: Select the base model to train from (small, medium, large)
@@ -547,7 +544,7 @@ def main():
         
         ### **Step 2: Start Training**
         - Click "Start Training" to begin the actual training process
-        - Uses OpenLLM's custom GPTModel class (not Hugging Face Transformers)
+        - Uses OpenLLM's custom GPTModel class from uploaded files
         - Uses sentencepiece.SentencePieceProcessor() for tokenization
         - Compatible with OpenLLM's actual implementation
         
@@ -633,7 +630,7 @@ def main():
         # Application Footer
         gr.Markdown("---")
         gr.Markdown("**Author**: Louis Chua Bean Chong | **Project**: OpenLLM | **License**: GPL-3.0")
-        gr.Markdown("**Architecture**: OpenLLM Custom GPTModel (Not Hugging Face Transformers)")
+        gr.Markdown("**Architecture**: OpenLLM Custom GPTModel (From Uploaded Files)")
         gr.Markdown("**Tokenizer**: sentencepiece.SentencePieceProcessor()")
     
     return demo