Create app.py

app.py

@@ -1,116 +1,33 @@
-import gradio as gr
-from src.utils.upload_file import UploadFile
-from src.utils.chatbot import ChatBot
-from src.utils.ui_settings import UISettings
-from src.utils.load_config import LoadConfig
+import subprocess
+import time
 
-APPCFG = LoadConfig()
-# # Prepare the LLm and Tokenizer
-# tokenizer = AutoTokenizer.from_pretrained(
-#     APPCFG.llm_engine, token=APPCFG.gemma_token, device=APPCFG.device)
-# model = model = AutoModelForCausalLM.from_pretrained(pretrained_model_name_or_path="google/gemma-7b-it",
-#                                                      token=APPCFG.gemma_token,
-#                                                      torch_dtype=torch.float16,
-#                                                      device_map=APPCFG.device
-#                                                      )
-# app_pipeline = pipeline(
-#     "text-generation",
-#     model=model,
-#     tokenizer=tokenizer
-# )
-with gr.Blocks() as demo:
-    with gr.Tabs():
-        with gr.TabItem("Med-App"):
-            ##############
-            # First ROW:
-            ##############
-            with gr.Row() as row_one:
-                with gr.Column(visible=False) as reference_bar:
-                    ref_output = gr.Markdown()
+def run_process(command):
+    """
+    Function to run a command in a separate terminal window.
+    This is platform-dependent; works for Windows (cmd) in this example.
+    """
+    return subprocess.Popen(['start', 'cmd', '/k', command], shell=True)
 
-                with gr.Column() as chatbot_output:
-                    chatbot = gr.Chatbot(
-                        [],
-                        elem_id="chatbot",
-                        bubble_full_width=False,
-                        height=500,
-                        avatar_images=(
-                            ("images/test.png"), "images/Gemma-logo.png"),
-                        # render=False
-                    )
-                    # **Adding like/dislike icons
-                    chatbot.like(UISettings.feedback, None, None)
-            ##############
-            # SECOND ROW:
-            ##############
-            with gr.Row():
-                input_txt = gr.Textbox(
-                    lines=4,
-                    scale=8,
-                    placeholder="Enter text and press enter, or upload PDF files",
-                    container=False,
-                )
-
-            ##############
-            # Third ROW:
-            ##############
-            with gr.Row() as row_two:
-                text_submit_btn = gr.Button(value="Submit text")
-                sidebar_state = gr.State(False)
-                btn_toggle_sidebar = gr.Button(
-                    value="References")
-                btn_toggle_sidebar.click(UISettings.toggle_sidebar, [sidebar_state], [
-                    reference_bar, sidebar_state])
-                upload_btn = gr.UploadButton(
-                    "📁 Upload PDF or doc files", file_types=[
-                        '.pdf',
-                        '.doc'
-                    ],
-                    file_count="multiple")
-                clear_button = gr.ClearButton([input_txt, chatbot])
-                rag_with_dropdown = gr.Dropdown(
-                    label="RAG with", choices=["Preprocessed doc", "Upload doc: Process for RAG"], value="Preprocessed doc")
-            ##############
-            # Fourth ROW:
-            ##############
-            with gr.Row() as row_four:
-                temperature_bar = gr.Slider(minimum=0.1, maximum=1, value=0.1, step=0.1,
-                                            label="Temperature", info="Increasing the temperature will make the model answer more creatively.")
-                top_k = gr.Slider(minimum=0.0,
-                                  maximum=100.0,
-                                  step=1,
-                                  label="top_k",
-                                  value=50,
-                                  info="A lower value (e.g. 10) will result in more conservative answers.")
-                top_p = gr.Slider(minimum=0.0,
-                                  maximum=1.0,
-                                  step=0.01,
-                                  label="top_p",
-                                  value=0.95,
-                                  info=" Works together with top-k. lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.0)")
+if __name__ == "__main__":
+    # Step 1: Run the data upload script
+    print("Running upload_data_manually.py...")
+    subprocess.call('python src\\upload_data_manually.py', shell=True)
 
-            ##############
-            # Process:
-            ##############
-            file_msg = upload_btn.upload(fn=UploadFile.process_uploaded_files, inputs=[
-                upload_btn, chatbot, rag_with_dropdown], outputs=[input_txt, chatbot], queue=False)
+    # Give some time for the upload script to complete
+    time.sleep(5)
 
-            txt_msg = input_txt.submit(fn=ChatBot.respond,
-                                       inputs=[chatbot, input_txt,
-                                               rag_with_dropdown, temperature_bar, top_k, top_p],
-                                       outputs=[input_txt,
-                                                chatbot, ref_output],
-                                       queue=False).then(lambda: gr.Textbox(interactive=True),
-                                                         None, [input_txt], queue=False)
+    # Step 2: Run the reference server
+    print("Starting reference_serve.py in a new terminal...")
+    run_process('python src\\reference_serve.py')
 
-            txt_msg = text_submit_btn.click(fn=ChatBot.respond,
-                                            inputs=[chatbot, input_txt,
-                                                    rag_with_dropdown, temperature_bar, top_k, top_p],
-                                            outputs=[input_txt,
-                                                     chatbot, ref_output],
-                                            queue=False).then(lambda: gr.Textbox(interactive=True),
-                                                              None, [input_txt], queue=False)
+    # Step 3: Run the LLM service
+    time.sleep(2)
+    print("Starting llm_service.py in a new terminal...")
+    run_process('python src\\llm_service.py')
 
+    # Step 4: Run the app
+    time.sleep(2)
+    print("Starting app.py in a new terminal...")
+    run_process('python src\\app.py')
 
-if __name__ == "__main__":
-    demo.launch()
+    print("All services are running. Check the separate terminal windows.")