Update app.py

app.py

@@ -21,7 +21,7 @@ def llm_intro(selected_model):
 model_cache = {}  # Global cache
 
 
-def load_model_with_cache(model_name):
+def load_model(model_name):
     """
     This function checks the cache before loading a model.
     If the model is cached, it returns the cached version.
@@ -63,39 +63,68 @@ def generate_text(input_text, selected_model):
 #              analytics_enabled=True, 
 #              title="GPT4All Text Generation Experiment").launch()
 
-with gr.Blocks() as demo:
-    gr.Markdown("## GPT4All Text Generation Experiment")
+# with gr.Blocks() as demo:
+#     gr.Markdown("## GPT4All Text Generation Experiment")
 
-    with gr.Row():
+#     with gr.Row():
         
     
-        model_selection = gr.Dropdown(choices=model_choices(), 
-                                     multiselect=False, 
-                                     label="LLMs to choose from", 
-                                     type="value", 
-                                     value="orca-mini-3b-gguf2-q4_0.gguf")
+#         model_selection = gr.Dropdown(choices=model_choices(), 
+#                                      multiselect=False, 
+#                                      label="LLMs to choose from", 
+#                                      type="value", 
+#                                      value="orca-mini-3b-gguf2-q4_0.gguf")
     
-        explanation = gr.Textbox(label="Model Description", lines=3, interactive=False, value=llm_intro("orca-mini-3b-gguf2-q4_0.gguf"))
+#         explanation = gr.Textbox(label="Model Description", lines=3, interactive=False, value=llm_intro("orca-mini-3b-gguf2-q4_0.gguf"))
     
-        # Link the dropdown with the textbox to update the description based on the selected model
-        model_selection.change(fn=llm_intro, inputs=model_selection, outputs=explanation)
-
-    chatbot = gr.Chatbot()
-    input_text = gr.Textbox(lines=3, label="Press shift+Enter to submit")
-    # output_text = gr.Textbox(lines=10, label="Generated Text")
-    clear = gr.ClearButton([input_text, chatbot])
-
-    def respond(message, chat_history, selected_model):
-        bot_message = generate_text(message, selected_model)
-        chat_history.append((message, bot_message))
-        time.sleep(2)  # Simulating processing delay if necessary
+#         # Link the dropdown with the textbox to update the description based on the selected model
+#         model_selection.change(fn=llm_intro, inputs=model_selection, outputs=explanation)
+
+#     chatbot = gr.Chatbot()
+#     input_text = gr.Textbox(lines=3, label="Press shift+Enter to submit")
+#     # output_text = gr.Textbox(lines=10, label="Generated Text")
+#     clear = gr.ClearButton([input_text, chatbot])
+
+#     def respond(message, chat_history, selected_model):
+#         bot_message = generate_text(message, selected_model)
+#         chat_history.append((message, bot_message))
+#         time.sleep(2)  # Simulating processing delay if necessary
     
-        return bot_message, chat_history
+#         return bot_message, chat_history
 
-    input_text.submit(respond, [input_text, chatbot, model_selection], [chatbot])
+#     input_text.submit(respond, [input_text, chatbot, model_selection], [chatbot])
         
-    # # Button to generate text
-    # generate_btn = gr.Button("Generate")
-    # generate_btn.click(fn=generate_text, inputs=[input_text, model_selection], outputs=output_text)
+#     # # Button to generate text
+#     # generate_btn = gr.Button("Generate")
+#     # generate_btn.click(fn=generate_text, inputs=[input_text, model_selection], outputs=output_text)
+
+# demo.launch()
 
-demo.launch()
+# Define the chatbot function
+def chatbot(model_name, message, chat_history):
+    model = load_model(model_name)
+    response = model.generate(message, chat_history)
+    chat_history.append((message, response))
+    return chat_history, response
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# GPT4All Chatbot")
+    with gr.Row():
+        with gr.Column(scale=1):
+            model_dropdown = gr.Dropdown(
+                choices=model_choices(),  
+                multiselect=False,
+                type="value",
+                value="orca-mini-3b-gguf2-q4_0.gguf",
+                label="LLMs to choose from"
+            )
+        with gr.Column(scale=4):
+            chatbot = gr.Chatbot(label="Conversation")
+    message = gr.Textbox(label="Message")
+    state = gr.State()
+
+    message.submit(chatbot, inputs=[model_dropdown, message, state], outputs=[chatbot, state])
+
+# Launch the Gradio app
+demo.launch()