# Chat_Workflows.py # Description: UI for Chat Workflows # # Imports import json import logging from pathlib import Path # # External Imports import gradio as gr # 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 # ############################################################################################################ # # Functions: # Load workflows from a JSON file json_path = Path('./Helper_Scripts/Workflows/Workflows.json') with json_path.open('r') as f: workflows = json.load(f) def chat_workflows_tab(): with gr.TabItem("Chat Workflows", visible=True): 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(): 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=["Local-LLM", "OpenAI", "Anthropic", "Cohere", "Groq", "DeepSeek", "Mistral", "OpenRouter", "Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM", "ollama", "HuggingFace", "Custom-OpenAI-API"], value="HuggingFace" ) 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): 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}, "", [] 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, 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")] ) 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 # # End of script ############################################################################################################