PhalAI / app.py
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import streamlit as st
from typing import List, Dict, Any, Optional
import asyncio
from back import (ChatConfig, ChatLogger, ChatMemory, QuestionGenerator,
GeminiRAG, ProductDatabase, UserManager, UserInfo)
import os
# UI Text in English
UI_TEXT = {
"welcome_message": """
Welcome to the Career Guidance Chatbot! πŸŽ“
Hi! We are here to help you navigate your career journey.
Ask any questions you have about internships, placements, skills development, career paths, or anything else related to your future career.
Choose a question below or ask your own.
""",
"input_placeholder": "Enter your question here...",
"input_label": "Ask Anything:",
"clear_chat": "Clear Chat",
"sidebar_title": "Tell Us About Yourself for Personalized Guidance",
"form_name": "Your Name",
"form_college": "College Name",
"form_degree": "Degree",
"form_year": "Year of Study",
"form_goals": "Your Career Goals",
"form_internship": "Have you done an internship?",
"form_placement": "Have you secured a placement?",
"form_submit": "Get Personalized Advice",
"form_success": "βœ… Personalized advice activated!",
"form_error": "❌ Error saving information. Please try again.",
"form_required": "Please fill in all required fields.",
"initial_questions": [
"What are some good career options in my field?",
"How do I get an internship in my desired field?",
"What skills are most important for success in this career path?",
"What are some tips for preparing for job interviews?"
]
}
def init_session_state():
"""Initialize all session state variables"""
defaults = {
'initialized': False,
'chat_memory': ChatMemory(),
'messages': [],
'message_counter': 0,
'processed_questions': set(),
'trigger_rerun': False,
'user_info': None,
'show_suggestions': False
}
for key, value in defaults.items():
if key not in st.session_state:
st.session_state[key] = value
# Configure the page
st.set_page_config(
page_title="Career Guidance Chatbot",
page_icon="πŸŽ“",
layout="wide"
)
# Custom CSS
st.markdown("""
<style>
.user-message {
background-color: #98BF64;
color: black;
padding: 15px;
border-radius: 15px;
margin: 10px 0;
}
.assistant-message {
background-color: #F9CB9C;
color: #F6B26B;
padding: 15px;
border-radius: 15px;
margin: 10px 0;
}
.stButton > button {
background-color: #212B2A;
color: white;
border: none;
padding: 10px 15px;
border-radius: 5px;
transition: background-color 0.3s;
}
.stButton > button:hover {
background-color: #45A049;
}
</style>
""", unsafe_allow_html=True)
def initialize_components():
"""Initialize and cache application components"""
try:
config = ChatConfig()
logger = ChatLogger(config.log_file)
question_gen = QuestionGenerator(config.gemini_api_key)
rag = GeminiRAG(config.gemini_api_key)
user_manager = UserManager(config.user_data_file)
return config, logger, question_gen, rag, user_manager
except Exception as e:
st.error(f"Error initializing components: {str(e)}")
raise e
def load_initial_database():
"""Load the default database"""
if not st.session_state.initialized:
try:
config, logger, question_gen, rag, user_manager = initialize_components()
db = ProductDatabase(config)
# Here, you would process your markdown files to create the database
# Replace 'path/to/your/markdown/files' with the actual path
for filename in os.listdir("blogs"):
if filename.endswith(".md"):
with open(os.path.join("blogs", filename), "r", encoding="utf-8") as f:
markdown_content = f.read()
db.process_markdown(markdown_content)
st.session_state.db = db
st.session_state.config = config
st.session_state.logger = logger
st.session_state.question_gen = question_gen
st.session_state.rag = rag
st.session_state.user_manager = user_manager
st.session_state.initialized = True
except Exception as e:
st.error(f"Error loading initial database: {str(e)}")
return None
async def process_question(question: str):
"""Process a question and update the chat state"""
try:
relevant_docs = st.session_state.db.search(question)
context = st.session_state.rag.create_context(relevant_docs)
answer = await st.session_state.rag.get_answer(
question=question,
context=context,
user_info=st.session_state.user_info
)
follow_up_questions = await st.session_state.question_gen.generate_questions(
question,
answer,
st.session_state.user_info
)
st.session_state.chat_memory.add_interaction(question, answer)
st.session_state.logger.log_interaction(
question,
answer,
st.session_state.user_info
)
st.session_state.message_counter += 1
st.session_state.messages.append({
"role": "user",
"content": question,
"message_id": st.session_state.message_counter
})
st.session_state.messages.append({
"role": "assistant",
"content": answer,
"questions": follow_up_questions,
"message_id": st.session_state.message_counter
})
except Exception as e:
st.error(f"Error processing question: {str(e)}")
def render_user_form():
"""Render the user information form in the sidebar"""
st.sidebar.title(UI_TEXT["sidebar_title"])
with st.sidebar.form("user_info_form"):
name = st.text_input(UI_TEXT["form_name"])
college = st.text_input(UI_TEXT["form_college"])
degree = st.text_input(UI_TEXT["form_degree"])
year = st.number_input(UI_TEXT["form_year"], min_value=1, max_value=5, step=1)
career_goals = st.text_area(UI_TEXT["form_goals"])
has_internship = st.checkbox(UI_TEXT["form_internship"])
has_placement = st.checkbox(UI_TEXT["form_placement"])
submitted = st.form_submit_button(UI_TEXT["form_submit"])
if submitted:
if name and college and degree and year and career_goals:
user_info = UserInfo(
name=name,
college=college,
degree=degree,
year=year,
career_goals=career_goals,
has_internship=has_internship,
has_placement=has_placement
)
if st.session_state.user_manager.save_user_info(user_info):
st.session_state.user_info = user_info
st.sidebar.success(UI_TEXT["form_success"])
else:
st.sidebar.error(UI_TEXT["form_error"])
else:
st.sidebar.warning(UI_TEXT["form_required"])
def main():
# Initialize session state
init_session_state()
# Load initial database and components if not already initialized
if not st.session_state.initialized:
load_initial_database()
# Render user form in sidebar
render_user_form()
# Display title
st.title("Career Guidance Chatbot")
# Welcome message
if not st.session_state.messages:
st.markdown(UI_TEXT["welcome_message"])
# Display initial questions as buttons
cols = st.columns(2)
for i, question in enumerate(UI_TEXT["initial_questions"]):
if cols[i % 2].button(question, key=f"initial_{i}", use_container_width=True):
asyncio.run(process_question(question))
# Display chat history
for message in st.session_state.messages:
if message["role"] == "user":
st.markdown(
f'<div class="user-message">πŸ‘€ {message["content"]}</div>',
unsafe_allow_html=True
)
else:
st.markdown(
f'<div class="assistant-message">πŸŽ“ {message["content"]}</div>',
unsafe_allow_html=True
)
if message.get("questions"):
cols = st.columns(2)
for i, question in enumerate(message["questions"]):
if cols[i % 2].button(
question,
key=f"followup_{message['message_id']}_{i}",
use_container_width=True
):
asyncio.run(process_question(question))
# Input area
with st.container():
# Create a form for input
with st.form(key='input_form'):
question = st.text_input(
UI_TEXT["input_label"],
key="user_input",
placeholder=UI_TEXT["input_placeholder"]
)
submit = st.form_submit_button("Send")
# Process input when submitted
if submit and question:
with st.spinner("πŸ”„ Processing your message..."):
asyncio.run(process_question(question))
if 'processed_questions' not in st.session_state:
st.session_state.processed_questions = set()
st.session_state.processed_questions.add(question)
st.rerun()
# Clear chat controls
cols = st.columns([4, 1])
if cols[1].button(UI_TEXT["clear_chat"], use_container_width=True):
st.session_state.messages = []
st.session_state.chat_memory.clear_history()
st.session_state.message_counter = 0
if 'processed_questions' in st.session_state:
st.session_state.processed_questions = set()
st.rerun()
if __name__ == "__main__":
main()