Spaces:
Running
Running
File size: 8,489 Bytes
43cd37c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 |
# 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
############################################################################################################
|