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import gradio as gr
import datetime
from typing import Dict, List, Any, Union, Optional
import random
import os
import json
import numpy as np
from pathlib import Path
# Import utilities
from utils.storage import load_data, save_data
from utils.state import generate_id, get_timestamp, record_activity
from utils.ai_models import (
generate_text, answer_question, analyze_image, transcribe_speech,
translate_text, analyze_sentiment, summarize_text, generate_code
)
from utils.config import AI_MODELS, DATA_DIR
from utils.logging import get_logger
from utils.error_handling import handle_ai_model_exceptions, AIModelError
# Initialize logger
logger = get_logger(__name__)
# Define AI assistant types and their descriptions
AI_ASSISTANT_TYPES = {
"General Chat": {
"description": "Have natural conversations on any topic",
"icon": "💬",
"model": "microsoft/DialoGPT-medium",
"task": "text_generation",
"placeholder": "Chat with me about anything...",
"examples": [
"Tell me about the benefits of meditation",
"What are some good productivity habits?",
"Can you recommend some books on personal growth?"
]
},
"Task Assistant": {
"description": "Get help with planning and organizing tasks",
"icon": "📋",
"model": "microsoft/DialoGPT-medium",
"task": "text_generation",
"placeholder": "Ask for help with your tasks and planning...",
"examples": [
"Help me break down this project into smaller tasks",
"How can I prioritize my workload better?",
"Create a schedule for my day"
]
},
"Writing Helper": {
"description": "Assistance with writing and content creation",
"icon": "✍️",
"model": "microsoft/DialoGPT-medium",
"task": "text_generation",
"placeholder": "What would you like help writing?",
"examples": [
"Help me draft an email to my team about the project delay",
"Give me ideas for a blog post about productivity",
"Improve this paragraph: [your text here]"
]
},
"Code Assistant": {
"description": "Get help with programming and coding",
"icon": "💻",
"model": "microsoft/CodeBERT-base",
"task": "code_generation",
"placeholder": "Describe what code you need help with...",
"examples": [
"Write a Python function to sort a list of dictionaries by a specific key",
"How do I create a responsive navbar with CSS?",
"Debug this code: [your code here]"
]
},
"Research Agent": {
"description": "Help with gathering and organizing information",
"icon": "🔎",
"model": "distilbert-base-uncased-distilled-squad",
"task": "question_answering",
"placeholder": "What topic would you like to research?",
"examples": [
"Summarize the key points about climate change",
"What are the main theories of motivation?",
"Compare different project management methodologies"
]
},
"Learning Tutor": {
"description": "Educational support and explanations",
"icon": "🎓",
"model": "microsoft/DialoGPT-medium",
"task": "text_generation",
"placeholder": "What would you like to learn about?",
"examples": [
"Explain quantum computing in simple terms",
"Help me understand the concept of compound interest",
"What are the key events of World War II?"
]
},
"Wellness Coach": {
"description": "Guidance on health, fitness, and wellbeing",
"icon": "🧘",
"model": "microsoft/DialoGPT-medium",
"task": "text_generation",
"placeholder": "Ask about health, fitness, or wellbeing...",
"examples": [
"What are some good exercises for stress relief?",
"Give me a simple meditation routine for beginners",
"How can I improve my sleep quality?"
]
}
}
@handle_ai_model_exceptions
def create_ai_assistant_page(state: Dict[str, Any]) -> None:
"""
Create the AI Assistant Hub page with various AI assistants
Args:
state: Application state
"""
logger.info("Creating AI Assistant Hub page")
# Create the AI Assistant Hub layout
with gr.Column(elem_id="ai-assistant-page"):
gr.Markdown("# 🤖 AI Assistant Hub")
# Assistant selector
with gr.Row():
assistant_selector = gr.Radio(
choices=list(AI_ASSISTANT_TYPES.keys()),
value=list(AI_ASSISTANT_TYPES.keys())[0],
label="Select Assistant",
elem_id="assistant-selector"
)
# Assistant description
assistant_description = gr.Markdown(
f"### {AI_ASSISTANT_TYPES[list(AI_ASSISTANT_TYPES.keys())[0]]['icon']} {list(AI_ASSISTANT_TYPES.keys())[0]}"
f"\n{AI_ASSISTANT_TYPES[list(AI_ASSISTANT_TYPES.keys())[0]]['description']}"
)
# Chat interface
with gr.Group(elem_id="chat-interface"):
# Chat history
chat_history = gr.Chatbot(
elem_id="chat-history",
height=400
)
# Input and send button
with gr.Row():
with gr.Column(scale=4):
chat_input = gr.Textbox(
placeholder=AI_ASSISTANT_TYPES[list(AI_ASSISTANT_TYPES.keys())[0]]['placeholder'],
label="",
elem_id="chat-input"
)
with gr.Column(scale=1):
send_btn = gr.Button("Send", elem_id="send-btn")
# Example queries
with gr.Group(elem_id="example-queries"):
gr.Markdown("### Example Queries")
example_btns = []
for example in AI_ASSISTANT_TYPES[list(AI_ASSISTANT_TYPES.keys())[0]]['examples']:
example_btns.append(gr.Button(example))
# Function to update assistant description
@handle_ai_model_exceptions
def update_assistant_description(assistant_name):
"""
Update the assistant description based on selection
Args:
assistant_name: Name of the selected assistant
Returns:
Updated description markdown
"""
logger.debug(f"Updating assistant description for: {assistant_name}")
assistant_info = AI_ASSISTANT_TYPES[assistant_name]
# Update chat input placeholder
chat_input.placeholder = assistant_info['placeholder']
# Update example queries
for i, example_btn in enumerate(example_btns):
if i < len(assistant_info['examples']):
example_btn.value = assistant_info['examples'][i]
return f"### {assistant_info['icon']} {assistant_name}\n{assistant_info['description']}"
# Connect assistant selector to description update
assistant_selector.change(
update_assistant_description,
inputs=[assistant_selector],
outputs=[assistant_description]
)
# Function to handle chat messages
@handle_ai_model_exceptions
def chat_with_assistant(message, history, assistant_name):
"""
Process chat messages and generate responses
Args:
message: User message
history: Chat history
assistant_name: Name of the selected assistant
Returns:
Updated chat history
"""
if not message.strip():
return history
logger.info(f"Processing message for {assistant_name}: {message[:30]}...")
# Get assistant info
assistant_info = AI_ASSISTANT_TYPES[assistant_name]
task = assistant_info['task']
try:
# Generate response based on assistant type
if task == "text_generation":
# Prepare context from history
context = "\n".join([f"User: {h[0]}\nAssistant: {h[1]}" for h in history[-3:]])
context += f"\nUser: {message}\nAssistant:"
response = generate_text(context)
elif task == "question_answering":
# For QA, we need a context, so we'll use the history as context
context = "\n".join([f"Q: {h[0]}\nA: {h[1]}" for h in history[-3:]])
response = answer_question(message, context)
elif task == "code_generation":
# For code generation, we'll use a specialized prompt
prompt = f"Generate code for: {message}"
response = generate_code(prompt)
else:
# Default to text generation
response = generate_text(message)
# Record activity
record_activity({
"type": "ai_assistant_used",
"assistant": assistant_name,
"message": message[:50] + ("..." if len(message) > 50 else ""),
"timestamp": datetime.datetime.now().isoformat()
})
# Update history
history.append((message, response))
return history
except AIModelError as e:
logger.error(f"AI model error: {str(e)}")
return history + [(message, f"I'm sorry, I encountered an error: {e.message}")]
except Exception as e:
logger.error(f"Unexpected error in chat: {str(e)}")
return history + [(message, "I'm sorry, I encountered an unexpected error. Please try again.")]
# Connect send button to chat function
send_btn.click(
chat_with_assistant,
inputs=[chat_input, chat_history, assistant_selector],
outputs=[chat_history],
clear_button=chat_input
)
# Connect chat input to chat function (for Enter key)
chat_input.submit(
chat_with_assistant,
inputs=[chat_input, chat_history, assistant_selector],
outputs=[chat_history],
clear_button=chat_input
)
# Connect example buttons to chat input
for example_btn in example_btns:
example_btn.click(
lambda example: example,
inputs=[example_btn],
outputs=[chat_input]
) |