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| # 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 | |
| ############################################################################################################ | |