Upload 3 files

App_Function_Libraries/Gradio_UI/Character_Interaction_tab.py

@@ -4,6 +4,7 @@
 # Imports
 import base64
 import io
+import uuid
 from datetime import datetime as datetime
 import logging
 import json
@@ -16,7 +17,7 @@ import gradio as gr
 from PIL import Image
 #
 # Local Imports
-from App_Function_Libraries.Chat import chat, load_characters
+from App_Function_Libraries.Chat import chat, load_characters, save_chat_history_to_db_wrapper
 from App_Function_Libraries.Gradio_UI.Chat_ui import chat_wrapper
 from App_Function_Libraries.Gradio_UI.Writing_tab import generate_writing_feedback
 #
@@ -165,7 +166,8 @@ def create_character_card_interaction_tab():
                 send_message_button = gr.Button("Send Message")
                 regenerate_button = gr.Button("Regenerate Last Message")
                 clear_chat_button = gr.Button("Clear Chat")
-                save_chat_button = gr.Button("Save This Chat")
+                chat_media_name = gr.Textbox(label="Custom Chat Name(optional)", visible=True)
+                save_chat_history_to_db = gr.Button("Save Chat History to DataBase")
                 save_status = gr.Textbox(label="Save Status", interactive=False)
 
         character_data = gr.State(None)
@@ -403,6 +405,10 @@ def create_character_card_interaction_tab():
         finally:
             logging.debug("Exiting update_character_info_with_error_handling")
 
+    # Define States for conversation_id and media_content, which are required for saving chat history
+    conversation_id = gr.State(str(uuid.uuid4()))
+    media_content = gr.State({})
+
     import_card_button.click(
         fn=import_character,
         inputs=[character_card_upload],
@@ -445,10 +451,11 @@ def create_character_card_interaction_tab():
         outputs=[user_name]
     )
 
-    save_chat_button.click(
-        fn=save_current_chat,
-        inputs=[chat_history, character_data],
-        outputs=[save_status]
+    # FIXME - Implement saving chat history to database; look at Chat_UI.py for reference
+    save_chat_history_to_db.click(
+        save_chat_history_to_db_wrapper,
+        inputs=[chat_history, conversation_id, media_content, chat_media_name],
+        outputs=[conversation_id, gr.Textbox(label="Save Status")]
     )
 
     return character_data, chat_history, user_input, user_name, character_image
@@ -598,6 +605,8 @@ def create_multiple_character_chat_tab():
             add_narration_btn = gr.Button("Add Narration")
             error_box = gr.Textbox(label="Error Messages", visible=False)
             reset_btn = gr.Button("Reset Conversation")
+            chat_media_name = gr.Textbox(label="Custom Chat Name(optional)", visible=True)
+            save_chat_history_to_db = gr.Button("Save Chat History to DataBase")
 
             def update_character_selectors(num):
                 return [gr.update(visible=True) if i < int(num) else gr.update(visible=False) for i in range(4)]
@@ -667,6 +676,10 @@ def create_multiple_character_chat_tab():
                     error_message = f"An error occurred: {str(e)}"
                     return conversation, current_index, gr.update(visible=True, value=error_message)
 
+            # Define States for conversation_id and media_content, which are required for saving chat history
+            media_content = gr.State({})
+            conversation_id = gr.State(str(uuid.uuid4()))
+
             next_turn_btn.click(
                 take_turn_with_error_handling,
                 inputs=[chat_display, current_index] + character_selectors + [api_endpoint, api_key, temperature,
@@ -685,6 +698,13 @@ def create_multiple_character_chat_tab():
                 outputs=[chat_display, current_index, scenario, narrator_input]
             )
 
+        # FIXME - Implement saving chat history to database; look at Chat_UI.py for reference
+        save_chat_history_to_db.click(
+            save_chat_history_to_db_wrapper,
+            inputs=[chat_display, conversation_id, media_content, chat_media_name],
+            outputs=[conversation_id, gr.Textbox(label="Save Status")]
+        )
+
         return character_interaction
 
 #
@@ -728,9 +748,15 @@ def create_narrator_controlled_conversation_tab():
         with gr.Row():
             generate_btn = gr.Button("Generate Next Interaction")
             reset_btn = gr.Button("Reset Conversation")
+            chat_media_name = gr.Textbox(label="Custom Chat Name(optional)", visible=True)
+            save_chat_history_to_db = gr.Button("Save Chat History to DataBase")
 
         error_box = gr.Textbox(label="Error Messages", visible=False)
 
+        # Define States for conversation_id and media_content, which are required for saving chat history
+        conversation_id = gr.State(str(uuid.uuid4()))
+        media_content = gr.State({})
+
         def generate_interaction(conversation, narrator_text, user_text, api_endpoint, api_key, temperature,
                                  *character_data):
             try:
@@ -790,6 +816,14 @@ def create_narrator_controlled_conversation_tab():
             outputs=[conversation_display, narrator_input, user_input, error_box]
         )
 
+        # FIXME - Implement saving chat history to database; look at Chat_UI.py for reference
+        save_chat_history_to_db.click(
+            save_chat_history_to_db_wrapper,
+            inputs=[conversation_display, conversation_id, media_content, chat_media_name],
+            outputs=[conversation_id, gr.Textbox(label="Save Status")]
+        )
+
+
     return api_endpoint, api_key, temperature, narrator_input, conversation_display, user_input, generate_btn, reset_btn, error_box
 
 #

App_Function_Libraries/Gradio_UI/Chat_Workflows.py

@@ -9,7 +9,9 @@ from pathlib import Path
 # External Imports
 import gradio as gr
 #
-from App_Function_Libraries.Gradio_UI.Chat_ui import process_with_llm
+from App_Function_Libraries.Gradio_UI.Chat_ui import chat_wrapper, search_conversations, \
+    load_conversation
+from App_Function_Libraries.Chat import save_chat_history_to_db_wrapper
 #
 ############################################################################################################
 #
@@ -25,164 +27,293 @@ with json_path.open('r') as f:
 def chat_workflows_tab():
     with gr.TabItem("Chat Workflows"):
         gr.Markdown("# Workflows using LLMs")
+        chat_history = gr.State([])
+        media_content = gr.State({})
+        selected_parts = gr.State([])
+        conversation_id = gr.State(None)
+        workflow_state = gr.State({"current_step": 0, "max_steps": 0, "conversation_id": None})
 
         with gr.Row():
-            workflow_selector = gr.Dropdown(label="Select Workflow", choices=[wf['name'] for wf in workflows])
-            api_selector = gr.Dropdown(
-                label="Select API Endpoint",
-                choices=["OpenAI", "Anthropic", "Cohere", "Groq", "DeepSeek", "Mistral", "OpenRouter",
-                         "Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM", "ollama", "HuggingFace"],
-                value="OpenAI"
-            )
-            api_key_input = gr.Textbox(label="API Key (optional)", type="password")
-
-        context_input = gr.Textbox(label="Initial Context (optional)", lines=5)
-
-        # Create a container for dynamic components
-        with gr.Column() as dynamic_components:
-            prompt_displays = []
-            user_inputs = []
-            output_boxes = []
-            process_buttons = []
-            regenerate_buttons = []
-
-            # Create the maximum number of components needed
-            max_steps = max(len(wf['prompts']) for wf in workflows)
-            for i in range(max_steps):
-                prompt_displays.append(gr.Markdown(visible=False))
-                user_inputs.append(gr.Textbox(label=f"Your Input", lines=2, visible=False))
-                output_boxes.append(gr.Textbox(label=f"AI Output", lines=5, visible=False))
-                with gr.Row():
-                    process_buttons.append(gr.Button(f"Process Step {i + 1}", visible=False))
-                    regenerate_buttons.append(gr.Button(f"🔄 Regenerate", visible=False))
+            with gr.Column():
+                workflow_selector = gr.Dropdown(label="Select Workflow", choices=[wf['name'] for wf in workflows])
+                api_selector = gr.Dropdown(
+                    label="Select API Endpoint",
+                    choices=["OpenAI", "Anthropic", "Cohere", "Groq", "DeepSeek", "Mistral", "OpenRouter",
+                             "Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM", "ollama", "HuggingFace"],
+                    value="OpenAI"
+                )
+                api_key_input = gr.Textbox(label="API Key (optional)", type="password")
+                temperature = gr.Slider(label="Temperature", minimum=0.00, maximum=1.0, step=0.05, value=0.7)
+                save_conversation = gr.Checkbox(label="Save Conversation", value=False)
+            with gr.Column():
+                gr.Markdown("Placeholder")
+        with gr.Row():
+            with gr.Column():
+                conversation_search = gr.Textbox(label="Search Conversations")
+                search_conversations_btn = gr.Button("Search Conversations")
+            with gr.Column():
+                previous_conversations = gr.Dropdown(label="Select Conversation", choices=[], interactive=True)
+                load_conversations_btn = gr.Button("Load Selected Conversation")
+        with gr.Row():
+            with gr.Column():
+                context_input = gr.Textbox(label="Initial Context", lines=5)
+                chatbot = gr.Chatbot(label="Workflow Chat")
+                msg = gr.Textbox(label="Your Input")
+                submit_btn = gr.Button("Submit")
+                clear_btn = gr.Button("Clear Chat")
+                chat_media_name = gr.Textbox(label="Custom Chat Name(optional)")
+                save_btn = gr.Button("Save Chat to Database")
 
         def update_workflow_ui(workflow_name):
-            selected_workflow = next(wf for wf in workflows if wf['name'] == workflow_name)
-            num_prompts = len(selected_workflow['prompts'])
-
-            prompt_updates = []
-            input_updates = []
-            output_updates = []
-            button_updates = []
-            regenerate_updates = []
-
-            for i in range(max_steps):
-                if i < num_prompts:
-                    prompt_updates.append(
-                        gr.update(value=f"**Step {i + 1}:** {selected_workflow['prompts'][i]}", visible=True))
-                    input_updates.append(gr.update(value="", visible=True, interactive=(i == 0)))
-                    output_updates.append(gr.update(value="", visible=True))
-                    button_updates.append(gr.update(visible=(i == 0)))
-                    regenerate_updates.append(gr.update(visible=False))
-                else:
-                    prompt_updates.append(gr.update(visible=False))
-                    input_updates.append(gr.update(visible=False))
-                    output_updates.append(gr.update(visible=False))
-                    button_updates.append(gr.update(visible=False))
-                    regenerate_updates.append(gr.update(visible=False))
+            if not workflow_name:
+                return {"current_step": 0, "max_steps": 0, "conversation_id": None}, "", []
+            selected_workflow = next((wf for wf in workflows if wf['name'] == workflow_name), None)
+            if selected_workflow:
+                num_prompts = len(selected_workflow['prompts'])
+                context = selected_workflow.get('context', '')
+                first_prompt = selected_workflow['prompts'][0]
+                initial_chat = [(None, f"{first_prompt}")]
+                logging.info(f"Initializing workflow: {workflow_name} with {num_prompts} steps")
+                return {"current_step": 0, "max_steps": num_prompts, "conversation_id": None}, context, initial_chat
+            else:
+                logging.error(f"Selected workflow not found: {workflow_name}")
+                return {"current_step": 0, "max_steps": 0, "conversation_id": None}, "", []
 
-            return prompt_updates + input_updates + output_updates + button_updates + regenerate_updates
-
-        def process(context, workflow_name, api_endpoint, api_key, step, *user_inputs):
+        def process_workflow_step(message, history, context, workflow_name, api_endpoint, api_key, workflow_state,
+                                  save_conv, temp):
+            logging.info(f"Process workflow step called with message: {message}")
+            logging.info(f"Current workflow state: {workflow_state}")
             try:
-                selected_workflow = next(wf for wf in workflows if wf['name'] == workflow_name)
-            except StopIteration:
-                # Handle the case where no matching workflow is found
-                error_message = f"No workflow found with name: {workflow_name}"
-                logging.error(error_message)
-                return [gr.update(value=error_message)] * (
-                            len(prompt_displays) + len(user_inputs) + len(output_boxes) + len(process_buttons) + len(
-                        regenerate_buttons))
-
-            # Ensure we don't go out of bounds
-            if step >= len(selected_workflow['prompts']):
-                error_message = f"Step {step} is out of range for workflow: {workflow_name}"
-                logging.error(error_message)
-                return [gr.update(value=error_message)] * (
-                            len(prompt_displays) + len(user_inputs) + len(output_boxes) + len(process_buttons) + len(
-                        regenerate_buttons))
-
-            # Build up the context from previous steps
-            full_context = context + "\n\n"
-            for i in range(step + 1):
-                full_context += f"Question: {selected_workflow['prompts'][i]}\n"
-                full_context += f"Answer: {user_inputs[i]}\n"
-                if i < step:
-                    full_context += f"AI Output: {output_boxes[i].value}\n\n"
+                selected_workflow = next((wf for wf in workflows if wf['name'] == workflow_name), None)
+                if not selected_workflow:
+                    logging.error(f"Selected workflow not found: {workflow_name}")
+                    return history, workflow_state, gr.update(interactive=True)
 
-            try:
-                result = process_with_llm(workflow_name, full_context, selected_workflow['prompts'][step], api_endpoint,
-                                          api_key)
-            except Exception as e:
-                error_message = f"Error processing with LLM: {str(e)}"
-                logging.error(error_message)
-                result = error_message
-
-            updates = []
-            for i in range(max_steps):
-                if i == step:
-                    updates.extend([
-                        gr.update(),  # Markdown (prompt_displays)
-                        gr.update(interactive=False),  # Textbox (user_inputs)
-                        gr.update(value=result),  # Textbox (output_boxes)
-                        gr.update(visible=False),  # Button (process_buttons)
-                        gr.update(visible=True)  # Button (regenerate_buttons)
-                    ])
-                elif i == step + 1:
-                    updates.extend([
-                        gr.update(),  # Markdown (prompt_displays)
-                        gr.update(interactive=True),  # Textbox (user_inputs)
-                        gr.update(),  # Textbox (output_boxes)
-                        gr.update(visible=True),  # Button (process_buttons)
-                        gr.update(visible=False)  # Button (regenerate_buttons)
-                    ])
-                elif i > step + 1:
-                    updates.extend([
-                        gr.update(),  # Markdown (prompt_displays)
-                        gr.update(interactive=False),  # Textbox (user_inputs)
-                        gr.update(),  # Textbox (output_boxes)
-                        gr.update(visible=False),  # Button (process_buttons)
-                        gr.update(visible=False)  # Button (regenerate_buttons)
-                    ])
-                else:
-                    updates.extend([
-                        gr.update(),  # Markdown (prompt_displays)
-                        gr.update(interactive=False),  # Textbox (user_inputs)
-                        gr.update(),  # Textbox (output_boxes)
-                        gr.update(visible=False),  # Button (process_buttons)
-                        gr.update(visible=True)  # Button (regenerate_buttons)
-                    ])
+                current_step = workflow_state["current_step"]
+                max_steps = workflow_state["max_steps"]
+
+                logging.info(f"Current step: {current_step}, Max steps: {max_steps}")
+
+                if current_step >= max_steps:
+                    logging.info("Workflow completed, disabling input")
+                    return history, workflow_state, gr.update(interactive=False)
+
+                prompt = selected_workflow['prompts'][current_step]
+                full_message = f"{context}\n\nStep {current_step + 1}: {prompt}\nUser: {message}"
+
+                logging.info(f"Calling chat_wrapper with full_message: {full_message[:100]}...")
+                bot_message, new_history, new_conversation_id = chat_wrapper(
+                    full_message, history, media_content.value, selected_parts.value,
+                    api_endpoint, api_key, "", workflow_state["conversation_id"],
+                    save_conv, temp, "You are a helpful assistant guiding through a workflow."
+                )
+
+                logging.info(f"Received bot_message: {bot_message[:100]}...")
 
-            return updates
+                next_step = current_step + 1
+                new_workflow_state = {
+                    "current_step": next_step,
+                    "max_steps": max_steps,
+                    "conversation_id": new_conversation_id
+                }
+
+                if next_step >= max_steps:
+                    logging.info("Workflow completed after this step")
+                    return new_history, new_workflow_state, gr.update(interactive=False)
+                else:
+                    next_prompt = selected_workflow['prompts'][next_step]
+                    new_history.append((None, f"Step {next_step + 1}: {next_prompt}"))
+                    logging.info(f"Moving to next step: {next_step}")
+                    return new_history, new_workflow_state, gr.update(interactive=True)
+            except Exception as e:
+                logging.error(f"Error in process_workflow_step: {str(e)}")
+                return history, workflow_state, gr.update(interactive=True)
 
-        # Set up event handlers
         workflow_selector.change(
             update_workflow_ui,
             inputs=[workflow_selector],
-            outputs=prompt_displays + user_inputs + output_boxes + process_buttons + regenerate_buttons
+            outputs=[workflow_state, context_input, chatbot]
+        )
+
+        submit_btn.click(
+            process_workflow_step,
+            inputs=[msg, chatbot, context_input, workflow_selector, api_selector, api_key_input, workflow_state,
+                    save_conversation, temperature],
+            outputs=[chatbot, workflow_state, msg]
+        ).then(
+            lambda: gr.update(value=""),
+            outputs=[msg]
+        )
+
+        clear_btn.click(
+            lambda: ([], {"current_step": 0, "max_steps": 0, "conversation_id": None}, ""),
+            outputs=[chatbot, workflow_state, context_input]
+        )
+
+        save_btn.click(
+            save_chat_history_to_db_wrapper,
+            inputs=[chatbot, conversation_id, media_content, chat_media_name],
+            outputs=[conversation_id, gr.Textbox(label="Save Status")]
         )
 
-        # Set up process button click events
-        for i, button in enumerate(process_buttons):
-            button.click(
-                fn=lambda context, wf_name, api_endpoint, api_key, *inputs, step=i: process(context, wf_name,
-                                                                                            api_endpoint, api_key, step,
-                                                                                            *inputs),
-                inputs=[context_input, workflow_selector, api_selector, api_key_input] + user_inputs,
-                outputs=prompt_displays + user_inputs + output_boxes + process_buttons + regenerate_buttons
-            ).then(lambda: gr.update(value=""), outputs=[user_inputs[i]])
-
-        # Set up regenerate button click events
-        for i, button in enumerate(regenerate_buttons):
-            button.click(
-                fn=lambda context, wf_name, api_endpoint, api_key, *inputs, step=i: process(context, wf_name,
-                                                                                            api_endpoint, api_key, step,
-                                                                                            *inputs),
-                inputs=[context_input, workflow_selector, api_selector, api_key_input] + user_inputs,
-                outputs=prompt_displays + user_inputs + output_boxes + process_buttons + regenerate_buttons
-            )
-
-    return workflow_selector, api_selector, api_key_input, context_input, dynamic_components
+        search_conversations_btn.click(
+            search_conversations,
+            inputs=[conversation_search],
+            outputs=[previous_conversations]
+        )
+
+        load_conversations_btn.click(
+            lambda: ([], {"current_step": 0, "max_steps": 0, "conversation_id": None}, ""),
+            outputs=[chatbot, workflow_state, context_input]
+        ).then(
+            load_conversation,
+            inputs=[previous_conversations],
+            outputs=[chatbot, conversation_id]
+        )
+
+    return workflow_selector, api_selector, api_key_input, context_input, chatbot, msg, submit_btn, clear_btn, save_btn
+# def chat_workflows_tab():
+#     with gr.TabItem("Chat Workflows"):
+#         gr.Markdown("# Workflows using LLMs")
+#         chat_history = gr.State([])
+#         media_content = gr.State({})
+#         selected_parts = gr.State([])
+#         conversation_id = gr.State(None)
+#         workflow_state = gr.State({"current_step": 0, "max_steps": 0, "conversation_id": None})
+#
+#         with gr.Row():
+#             workflow_selector = gr.Dropdown(label="Select Workflow", choices=[wf['name'] for wf in workflows])
+#             api_selector = gr.Dropdown(
+#                 label="Select API Endpoint",
+#                 choices=["OpenAI", "Anthropic", "Cohere", "Groq", "DeepSeek", "Mistral", "OpenRouter",
+#                          "Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM", "ollama", "HuggingFace"],
+#                 value="OpenAI"
+#             )
+#             api_key_input = gr.Textbox(label="API Key (optional)", type="password")
+#
+#         context_input = gr.Textbox(label="Initial Context (optional)", lines=5)
+#
+#         with gr.Row():
+#             temperature = gr.Slider(label="Temperature", minimum=0.00, maximum=1.0, step=0.05, value=0.7)
+#             save_conversation = gr.Checkbox(label="Save Conversation", value=False)
+#
+#         chatbot = gr.Chatbot(label="Workflow Chat")
+#         msg = gr.Textbox(label="Your Input")
+#         submit_btn = gr.Button("Submit")
+#         clear_btn = gr.Button("Clear Chat")
+#         save_btn = gr.Button("Save Chat to Database")
+#
+#         with gr.Row():
+#             conversation_search = gr.Textbox(label="Search Conversations")
+#             search_conversations_btn = gr.Button("Search Conversations")
+#         previous_conversations = gr.Dropdown(label="Select Conversation", choices=[], interactive=True)
+#         load_conversations_btn = gr.Button("Load Selected Conversation")
+#
+#         def update_workflow_ui(workflow_name):
+#             if not workflow_name:
+#                 return {"current_step": 0, "max_steps": 0, "conversation_id": None}
+#             selected_workflow = next((wf for wf in workflows if wf['name'] == workflow_name), None)
+#             if selected_workflow:
+#                 num_prompts = len(selected_workflow['prompts'])
+#                 logging.info(f"Initializing workflow: {workflow_name} with {num_prompts} steps")
+#                 return {"current_step": 0, "max_steps": num_prompts, "conversation_id": None}
+#             else:
+#                 logging.error(f"Selected workflow not found: {workflow_name}")
+#                 return {"current_step": 0, "max_steps": 0, "conversation_id": None}
+#
+#         def process_workflow_step(message, history, context, workflow_name, api_endpoint, api_key, workflow_state,
+#                                   save_conv, temp):
+#             logging.info(f"Process workflow step called with message: {message}")
+#             logging.info(f"Current workflow state: {workflow_state}")
+#             try:
+#                 selected_workflow = next((wf for wf in workflows if wf['name'] == workflow_name), None)
+#                 if not selected_workflow:
+#                     logging.error(f"Selected workflow not found: {workflow_name}")
+#                     return history, workflow_state, gr.update(interactive=True)
+#
+#                 current_step = workflow_state["current_step"]
+#                 max_steps = workflow_state["max_steps"]
+#
+#                 logging.info(f"Current step: {current_step}, Max steps: {max_steps}")
+#
+#                 if current_step >= max_steps:
+#                     logging.info("Workflow completed, disabling input")
+#                     return history, workflow_state, gr.update(interactive=False)
+#
+#                 prompt = selected_workflow['prompts'][current_step]
+#                 full_message = f"{context}\n\nStep {current_step + 1}: {prompt}\nUser: {message}"
+#
+#                 logging.info(f"Calling chat_wrapper with full_message: {full_message[:100]}...")
+#                 bot_message, new_history, new_conversation_id = chat_wrapper(
+#                     full_message, history, media_content.value, selected_parts.value,
+#                     api_endpoint, api_key, "", workflow_state["conversation_id"],
+#                     save_conv, temp, "You are a helpful assistant guiding through a workflow."
+#                 )
+#
+#                 logging.info(f"Received bot_message: {bot_message[:100]}...")
+#
+#                 next_step = current_step + 1
+#                 new_workflow_state = {
+#                     "current_step": next_step,
+#                     "max_steps": max_steps,
+#                     "conversation_id": new_conversation_id
+#                 }
+#
+#                 if next_step >= max_steps:
+#                     logging.info("Workflow completed after this step")
+#                     return new_history, new_workflow_state, gr.update(interactive=False)
+#                 else:
+#                     next_prompt = selected_workflow['prompts'][next_step]
+#                     new_history.append((None, f"Step {next_step + 1}: {next_prompt}"))
+#                     logging.info(f"Moving to next step: {next_step}")
+#                     return new_history, new_workflow_state, gr.update(interactive=True)
+#             except Exception as e:
+#                 logging.error(f"Error in process_workflow_step: {str(e)}")
+#                 return history, workflow_state, gr.update(interactive=True)
+#
+#         workflow_selector.change(
+#             update_workflow_ui,
+#             inputs=[workflow_selector],
+#             outputs=[workflow_state]
+#         )
+#
+#         submit_btn.click(
+#             process_workflow_step,
+#             inputs=[msg, chatbot, context_input, workflow_selector, api_selector, api_key_input, workflow_state,
+#                     save_conversation, temperature],
+#             outputs=[chatbot, workflow_state, msg]
+#         ).then(
+#             lambda: gr.update(value=""),
+#             outputs=[msg]
+#         )
+#
+#         clear_btn.click(
+#             lambda: ([], {"current_step": 0, "max_steps": 0, "conversation_id": None}),
+#             outputs=[chatbot, workflow_state]
+#         )
+#
+#         save_btn.click(
+#             save_chat_history_to_db_wrapper,
+#             inputs=[chatbot, conversation_id, media_content],
+#             outputs=[conversation_id, gr.Textbox(label="Save Status")]
+#         )
+#
+#         search_conversations_btn.click(
+#             search_conversations,
+#             inputs=[conversation_search],
+#             outputs=[previous_conversations]
+#         )
+#
+#         load_conversations_btn.click(
+#             lambda: ([], {"current_step": 0, "max_steps": 0, "conversation_id": None}),
+#             outputs=[chatbot, workflow_state]
+#         ).then(
+#             load_conversation,
+#             inputs=[previous_conversations],
+#             outputs=[chatbot, conversation_id]
+#         )
+#
+#     return workflow_selector, api_selector, api_key_input, context_input, chatbot, msg, submit_btn, clear_btn, save_btn
 
 #
 # End of script

App_Function_Libraries/Gradio_UI/Chat_ui.py

@@ -95,20 +95,21 @@ def chat_wrapper(message, history, media_content, selected_parts, api_endpoint,
         # Generate bot response
         bot_message = chat(full_message, history, media_content, selected_parts, api_endpoint, api_key, custom_prompt,
                            temperature, system_prompt)
+
         logging.debug(f"Bot message being returned: {bot_message}")
+
         if save_conversation:
             # Add assistant message to the database
             add_chat_message(conversation_id, "assistant", bot_message)
 
         # Update history
-        history.append((message, bot_message))
+        new_history = history + [(message, bot_message)]
 
-        return bot_message, history, conversation_id
+        return bot_message, new_history, conversation_id
     except Exception as e:
         logging.error(f"Error in chat wrapper: {str(e)}")
         return "An error occurred.", history, conversation_id
 
-
 def search_conversations(query):
     try:
         conversations = search_chat_conversations(query)
@@ -226,6 +227,7 @@ def create_chat_interface():
                 delete_message_id = gr.Number(label="Message ID to Delete", visible=False)
                 delete_message_button = gr.Button("Delete Message", visible=False)
 
+                chat_media_name = gr.Textbox(label="Custom Chat Name(optional)")
                 save_chat_history_to_db = gr.Button("Save Chat History to DataBase")
                 save_chat_history_as_file = gr.Button("Save Chat History as File")
                 download_file = gr.File(label="Download Chat History")
@@ -348,7 +350,7 @@ def create_chat_interface():
 
         save_chat_history_to_db.click(
             save_chat_history_to_db_wrapper,
-            inputs=[chatbot, conversation_id, media_content],
+            inputs=[chatbot, conversation_id, media_content, chat_media_name],
             outputs=[conversation_id, gr.Textbox(label="Save Status")]
         )
 
@@ -416,13 +418,7 @@ def create_chat_interface_stacked():
             with gr.Column():
                 submit = gr.Button("Submit")
                 clear_chat_button = gr.Button("Clear Chat")
-
-                edit_message_id = gr.Number(label="Message ID to Edit", visible=False)
-                edit_message_text = gr.Textbox(label="Edit Message", visible=False)
-                update_message_button = gr.Button("Update Message", visible=False)
-
-                delete_message_id = gr.Number(label="Message ID to Delete", visible=False)
-                delete_message_button = gr.Button("Delete Message", visible=False)
+                chat_media_name = gr.Textbox(label="Custom Chat Name(optional)", visible=True)
                 save_chat_history_to_db = gr.Button("Save Chat History to DataBase")
                 save_chat_history_as_file = gr.Button("Save Chat History as File")
             with gr.Column():
@@ -500,18 +496,6 @@ def create_chat_interface_stacked():
             outputs=[chat_history]
         )
 
-        update_message_button.click(
-            update_message_in_chat,
-            inputs=[edit_message_id, edit_message_text, chat_history],
-            outputs=[chatbot]
-        )
-
-        delete_message_button.click(
-            delete_message_from_chat,
-            inputs=[delete_message_id, chat_history],
-            outputs=[chatbot]
-        )
-
         save_chat_history_as_file.click(
             save_chat_history,
             inputs=[chatbot, conversation_id],
@@ -520,13 +504,10 @@ def create_chat_interface_stacked():
 
         save_chat_history_to_db.click(
             save_chat_history_to_db_wrapper,
-            inputs=[chatbot, conversation_id, media_content],
+            inputs=[chatbot, conversation_id, media_content, chat_media_name],
             outputs=[conversation_id, gr.Textbox(label="Save Status")]
         )
 
-        chatbot.select(show_edit_message, None, [edit_message_text, edit_message_id, update_message_button])
-        chatbot.select(show_delete_message, None, [delete_message_id, delete_message_button])
-
 
 # FIXME - System prompts
 def create_chat_interface_multi_api():