| from utills import * | |
| import streamlit as st | |
| from streamlit_chat import message | |
| from streamlit_lottie import st_lottie | |
| import json | |
| from Functions import RFPProcessor | |
| from Prompts_and_Chains import LLMChains | |
| function = RFPProcessor() | |
| chains_obj = LLMChains() | |
| if "is_category_selected" not in st.session_state: | |
| st.session_state["is_category_selected"] = False | |
| if "user_input" not in st.session_state: | |
| st.session_state["user_input"] = "" | |
| def local_css(file_name): | |
| with open(file_name, "r") as f: | |
| st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True) | |
| def load_lottiefile(filepath: str): | |
| '''Load lottie animation file''' | |
| with open(filepath, "r") as f: | |
| return json.load(f) | |
| def main(): | |
| st.set_page_config(page_title="Justice League Chatbot", | |
| page_icon="⚖️", layout="wide") | |
| local_css("style.css") | |
| st_lottie(load_lottiefile("images/welcome.json"), speed=1, | |
| reverse=False, loop=True, quality="high", height=300) | |
| st.title("🦸♂️ Justice League Chatbot") | |
| st.subheader("Your AI-powered legal assistant") | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| st.session_state.user_inputs = {} | |
| st.session_state.current_question = "start" | |
| for i, msg in enumerate(st.session_state.messages): | |
| message(msg["content"], is_user=msg["role"] == "user", key=str(i)) | |
| if not st.session_state.messages: | |
| initial_message = "Welcome to the Justice League Chatbot! I'm here to help you find the right lawyer or provide general legal information. How can I assist you today?" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": initial_message}) | |
| show_options() | |
| def show_options(): | |
| options = get_options() | |
| if st.session_state.current_question == "additional_info": | |
| get_additional_info() | |
| else: | |
| col1, col2 = st.columns([3, 1]) | |
| with col1: | |
| st.text_input( | |
| "Type your response or choose an option:", | |
| st.session_state["user_input"], | |
| key="user_input", | |
| on_change=ask_llm | |
| ) | |
| with col2: | |
| if st.session_state["is_category_selected"] == False: | |
| st.write("Quick options:") | |
| for option in options: | |
| if st.button(option, key=f"button_{option}"): | |
| handle_user_input(option) | |
| def get_options(): | |
| options_dict = { | |
| "start": ["Find a lawyer", "Get general legal advice"], | |
| "category": ["Criminal", "Family", "Corporate", "Immigration"], | |
| "cost_range": ["Low", "Medium", "High", "Very High"], | |
| "experience": ["0-5 years", "6-10 years", "11-20 years", "20+ years"], | |
| "location": ["Jabalpur", "Bhopal", "Indore", "Gwalior"] | |
| } | |
| return options_dict.get(st.session_state.current_question, ["Find a lawyer", "Get general legal advice"]) | |
| def get_additional_info(): | |
| user_input = st.text_area( | |
| "Please provide any additional information about your case or specific needs:", key="additional_info") | |
| if st.button("Submit"): | |
| handle_user_input(user_input) | |
| def handle_user_input(user_input): | |
| st.session_state.messages.append({"role": "user", "content": user_input}) | |
| if user_input == "Find a lawyer": | |
| ask_category() | |
| elif user_input == "Get general legal advice": | |
| provide_legal_advice() | |
| elif st.session_state.current_question == "category": | |
| st.session_state.user_inputs['category'] = user_input | |
| ask_cost_range() | |
| elif st.session_state.current_question == "cost_range": | |
| st.session_state.user_inputs['cost_range'] = user_input | |
| ask_experience() | |
| elif st.session_state.current_question == "experience": | |
| st.session_state.user_inputs['experience'] = user_input | |
| ask_location() | |
| elif st.session_state.current_question == "location": | |
| st.session_state.user_inputs['location'] = user_input | |
| ask_additional_info() | |
| elif st.session_state.current_question == "additional_info": | |
| st.session_state.user_inputs['additional_info'] = user_input | |
| show_results(user_input) | |
| st.experimental_rerun() | |
| def ask_llm(): | |
| user_input = st.session_state["user_input"] | |
| st.session_state.messages.append({"role": "user", "content": user_input}) | |
| last_5_entries = st.session_state.messages[-5:] | |
| inputs = { | |
| "chat_history":last_5_entries, | |
| "input": user_input, | |
| } | |
| output = chains_obj.legal_adviser_bot_chain.run(inputs) | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": output}) | |
| st.session_state["user_input"] = "" | |
| def ask_category(): | |
| response = "What type of lawyer are you looking for?" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "category" | |
| def ask_cost_range(): | |
| response = "What's your budget range?" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "cost_range" | |
| def ask_experience(): | |
| response = "How many years of experience should the lawyer have?" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "experience" | |
| def ask_location(): | |
| response = "Where are you looking for a lawyer?" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "location" | |
| def ask_additional_info(): | |
| response = "Please provide any additional information about your case or specific needs that might help us find the best lawyer for you:" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "additional_info" | |
| def suggest_options(): | |
| response = "I'm not sure how to help with that. Would you like to:" | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| st.session_state.current_question = "start" | |
| def provide_legal_advice(): | |
| response = "Hello, I'm LegalAssist, an AI chatbot specializing in legal information. I can answer general questions about law and legal procedures, but I can't provide personalized legal advice. How can I assist you with legal information today?" | |
| st.session_state["is_category_selected"] = True | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": response}) | |
| def show_results(additional_info): | |
| category = st.session_state.user_inputs['category'] | |
| cost_range = st.session_state.user_inputs['cost_range'] | |
| experience = st.session_state.user_inputs['experience'] | |
| location = st.session_state.user_inputs['location'] | |
| user_inputs = {"category":category,"cost_range":cost_range, "experience":experience, "location":location} | |
| matching_lawyers = search_lawyers( | |
| category, cost_range, experience, location) | |
| output = chains_obj.lawyer_recommendations_chain( | |
| {"user_inputs":user_inputs, "matching_lawyers":matching_lawyers, "additional_info":additional_info}) | |
| st.session_state.messages.append( | |
| {"role": "assistant", "content": output['text']}) | |
| st.session_state.current_question = "start" | |
| if __name__ == "__main__": | |
| main() | |