Update app.py

app.py

@@ -62,6 +62,13 @@ class get_datasets:
 
 
 
+    def show_about():
+        return "## About\n\nThis is an application for uploading datasets. You can upload files in .csv, .jsonl, or .txt format. The app will process the file and provide feedback."
+    
+    def show_upload():
+        return "## Upload\n\nUse the button below to upload your dataset."
+
+
 
 def train(model_name, 
           inject_prompt, 
@@ -97,124 +104,135 @@ def submit_weights(model, repository, model_out_name, token):
 
 ##################################### App UI #######################################
 
+
+
 def main():
     with gr.Blocks() as demo:
-    
-        ##### Title Block #####
-        gr.Markdown("# SLM Instruction Tuning with Unsloth")
-    
-        ##### Initial Model Inputs #####
-        gr.Markdown("### Model Inputs")
+
+        with gr.Row():
+            with gr.Column(scale=1, min_width=200):  # Sidebar navigation
+                gr.Markdown("### Navigation")
+                btn_about = gr.Button("About")
+                btn_upload = gr.Button("Upload Dataset")
+            with gr.Column(scale=4):  # Main content area
+                ##### Title Block #####
+                gr.Markdown("# SLM Instruction Tuning with Unsloth")
+            
+                ##### Initial Model Inputs #####
+                gr.Markdown("### Model Inputs")
+                
+                # Select Model
+                modelnames = conf['model']['choices']
+                model_name = gr.Dropdown(label="Supported Models", 
+                                         choices=modelnames, 
+                                         value=modelnames[0])
+                # Prompt template
+                inject_prompt = gr.Textbox(label="Prompt Template", 
+                                             value=prompt_template())
+                # Dataset choice
+                dataset_choice = gr.Radio(label="Choose Dataset", 
+                                          choices=["Hugging Face Hub Dataset", "Upload Your Own"], 
+                                          value="Hugging Face Hub Dataset")
         
-        # Select Model
-        modelnames = conf['model']['choices']
-        model_name = gr.Dropdown(label="Supported Models", 
-                                 choices=modelnames, 
-                                 value=modelnames[0])
-        # Prompt template
-        inject_prompt = gr.Textbox(label="Prompt Template", 
-                                     value=prompt_template())
-        # Dataset choice
-        dataset_choice = gr.Radio(label="Choose Dataset", 
-                                  choices=["Hugging Face Hub Dataset", "Upload Your Own"], 
-                                  value="Hugging Face Hub Dataset")
-
-        dataset_predefined = gr.Textbox(label="Hugging Face Hub Training Dataset", 
-                                        value='yahma/alpaca-cleaned', 
-                                        visible=True)
+                dataset_predefined = gr.Textbox(label="Hugging Face Hub Training Dataset", 
+                                                value='yahma/alpaca-cleaned', 
+                                                visible=True)
+                
+                dataset_predefined_load = gr.Button("Upload Dataset (.csv, .jsonl, or .txt)")
         
-        dataset_predefined_load = gr.Button("Upload Dataset (.csv, .jsonl, or .txt)")
-
-        dataset_uploaded_load = gr.UploadButton(label="Upload Dataset (.csv, .jsonl, or .txt)", 
-                                         file_types=[".csv",".jsonl", ".txt"], 
-                                         visible=False)
-        data_snippet = gr.Markdown()
+                dataset_uploaded_load = gr.UploadButton(label="Upload Dataset (.csv, .jsonl, or .txt)", 
+                                                 file_types=[".csv",".jsonl", ".txt"], 
+                                                 visible=False)
+                data_snippet = gr.Markdown()
+                
+                dataset_choice.change(update_visibility.textbox_vis, 
+                                      dataset_choice, 
+                                      dataset_predefined)
+                dataset_choice.change(update_visibility.upload_vis, 
+                                      dataset_choice,
+                                      dataset_uploaded_load)
+                dataset_choice.change(update_visibility.textbox_button_vis,
+                                      dataset_choice,
+                                      dataset_predefined_load)
+                
+                # Dataset button
+                dataset_predefined_load.click(fn=get_datasets.predefined_dataset,
+                                          inputs=dataset_predefined,
+                                          outputs=data_snippet)
         
-        dataset_choice.change(update_visibility.textbox_vis, 
-                              dataset_choice, 
-                              dataset_predefined)
-        dataset_choice.change(update_visibility.upload_vis, 
-                              dataset_choice,
-                              dataset_uploaded_load)
-        dataset_choice.change(update_visibility.textbox_button_vis,
-                              dataset_choice,
-                              dataset_predefined_load)
+                dataset_uploaded_load.click(fn=get_datasets.uploaded_dataset,
+                                         inputs=dataset_uploaded_load,
+                                         outputs=data_snippet)
         
-        # Dataset button
-        dataset_predefined_load.click(fn=get_datasets.predefined_dataset,
-                                  inputs=dataset_predefined,
-                                  outputs=data_snippet)
-
-        dataset_uploaded_load.click(fn=get_datasets.uploaded_dataset,
-                                 inputs=dataset_uploaded_load,
-                                 outputs=data_snippet)
-
-
-
         
-
-        ##### Model Parameter Inputs #####
-        gr.Markdown("### Model Parameter Selection")
-        # Parameters
-        data_field = gr.Textbox(label="Dataset Training Field Name",
-                                value=conf['model']['general']["dataset_text_field"])
-        max_seq_length = gr.Textbox(label="Maximum sequence length", 
-                                     value=conf['model']['general']["max_seq_length"])
-        random_seed = gr.Textbox(label="Seed",
-                                value=conf['model']['general']["seed"])
-        num_epochs = gr.Textbox(label="Training Epochs",
-                                value=conf['model']['general']["num_train_epochs"])
-        max_steps = gr.Textbox(label="Maximum steps",
-                                value=conf['model']['general']["max_steps"])   
-        repository = gr.Textbox(label="Repository Name",
-                                value=conf['model']['general']["repository"])   
-        model_out_name = gr.Textbox(label="Model Output Name",
-                                value=conf['model']['general']["model_name"])   
-
-        # Hyperparameters (allow selection, but hide in accordion.)
-        with gr.Accordion("Advanced Tuning", open=False):
-
-            sftparams = conf['model']['general']
-            # accordion container content
-            dict_string = json.dumps(dict(conf['model']['peft']), indent=4)
-            peft = gr.Textbox(label="PEFT Parameters (json)", value=dict_string)
-            
-            dict_string = json.dumps(dict(conf['model']['sft']), indent=4)
-            sft = gr.Textbox(label="SFT Parameters (json)", value=dict_string)            
         
-        ##### Execution #####
-    
-        # Setup buttons
-        tune_btn = gr.Button("Start Fine Tuning")
-        gr.Markdown("### Model Progress")
-        # Text output (for now)
-        output = gr.Textbox(label="Output") 
+                
         
+                ##### Model Parameter Inputs #####
+                gr.Markdown("### Model Parameter Selection")
+                # Parameters
+                data_field = gr.Textbox(label="Dataset Training Field Name",
+                                        value=conf['model']['general']["dataset_text_field"])
+                max_seq_length = gr.Textbox(label="Maximum sequence length", 
+                                             value=conf['model']['general']["max_seq_length"])
+                random_seed = gr.Textbox(label="Seed",
+                                        value=conf['model']['general']["seed"])
+                num_epochs = gr.Textbox(label="Training Epochs",
+                                        value=conf['model']['general']["num_train_epochs"])
+                max_steps = gr.Textbox(label="Maximum steps",
+                                        value=conf['model']['general']["max_steps"])   
+                repository = gr.Textbox(label="Repository Name",
+                                        value=conf['model']['general']["repository"])   
+                model_out_name = gr.Textbox(label="Model Output Name",
+                                        value=conf['model']['general']["model_name"])   
         
-        # Data retrieval
+                # Hyperparameters (allow selection, but hide in accordion.)
+                with gr.Accordion("Advanced Tuning", open=False):
         
+                    sftparams = conf['model']['general']
+                    # accordion container content
+                    dict_string = json.dumps(dict(conf['model']['peft']), indent=4)
+                    peft = gr.Textbox(label="PEFT Parameters (json)", value=dict_string)
+                    
+                    dict_string = json.dumps(dict(conf['model']['sft']), indent=4)
+                    sft = gr.Textbox(label="SFT Parameters (json)", value=dict_string)            
+                
+                ##### Execution #####
+            
+                # Setup buttons
+                tune_btn = gr.Button("Start Fine Tuning")
+                gr.Markdown("### Model Progress")
+                # Text output (for now)
+                output = gr.Textbox(label="Output") 
+                
+                
+                # Data retrieval
+                
+                
+                # Execute buttons
+                tune_btn.click(fn=train, 
+                               inputs=[model_name, 
+                                       inject_prompt, 
+                                       dataset_predefined,
+                                       peft,
+                                       sft,
+                                       max_seq_length,
+                                       random_seed,
+                                       num_epochs,
+                                       max_steps,
+                                       data_field,
+                                       repository,
+                                       model_out_name
+                                      ],
+                               outputs=output)
+                # stop button
         
-        # Execute buttons
-        tune_btn.click(fn=train, 
-                       inputs=[model_name, 
-                               inject_prompt, 
-                               dataset_predefined,
-                               peft,
-                               sft,
-                               max_seq_length,
-                               random_seed,
-                               num_epochs,
-                               max_steps,
-                               data_field,
-                               repository,
-                               model_out_name
-                              ],
-                       outputs=output)
-        # stop button
-
-        # submit button
-
+                # submit button
         
+            # Link buttons to functions
+        btn_about.click(fn=show_about, outputs=main_content)
+        btn_upload.click(fn=lambda: ("", gr.update(visible=True)), outputs=[main_content, dataset_uploaded_load])
+
         # Launch baby
         demo.launch()