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# Chat_Workflows.py
# Description: Gradio UI for Chat Workflows
#
# Imports
import json
import logging
from pathlib import Path
#
# External Imports
import gradio as gr
#
# Local Imports
from App_Function_Libraries.Gradio_UI.Chat_ui import chat_wrapper, search_conversations, \
load_conversation
from App_Function_Libraries.Chat.Chat_Functions import save_chat_history_to_db_wrapper
from App_Function_Libraries.Utils.Utils import default_api_endpoint, global_api_endpoints, format_api_name
#
############################################################################################################
#
# 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():
try:
default_value = None
if default_api_endpoint:
if default_api_endpoint in global_api_endpoints:
default_value = format_api_name(default_api_endpoint)
else:
logging.warning(f"Default API endpoint '{default_api_endpoint}' not found in global_api_endpoints")
except Exception as e:
logging.error(f"Error setting default API endpoint: {str(e)}")
default_value = None
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])
# Refactored API selection dropdown
api_selector = gr.Dropdown(
choices=["None"] + [format_api_name(api) for api in global_api_endpoints],
value=default_value,
label="API for Interaction (Optional)"
)
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")
save_status = gr.Textbox(label="Save Status", interactive=False)
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, 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
############################################################################################################
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