Dhruv0730/Dual_Agent_Simulation

1# -*- coding: utf-8 -*-2"""app.ipynb3 4Automatically generated by Colab.5 6Original file is located at7    https://colab.research.google.com/drive/1eWv35WwsifbbT9K-FV8p8S_FAEekBnLz8"""9 10import streamlit as st11import os12import pandas as pd13from together import Together14from utils.helper import *15 16 17st.set_page_config(layout="wide")18st.title("Duel Agent Simulation 🦙🦙")19 20 21with st.sidebar:22    with st.expander("Instruction Manual"):23        st.markdown("""24            # 🦙🦙 Duel Agent Simulation Streamlit App25 26            ## Overview27 28            Welcome to the **Duel Agent Simulation** app! This Streamlit application allows you to chat with Meta's Llama3 model in a unique interview simulation. The app features two agents in an interview scenario, with a judge providing feedback. The best part? You simply provide a topic, and the simulation runs itself!29 30            ## Features31 32            ### 📝 Instruction Manual33 34            **Meta Llama3 🦙 Chatbot**35 36            This application lets you interact with Meta's Llama3 model through a fun interview-style chat.37 38            **How to Use:**39            1. **Input:** Type a topic into the input box labeled "Enter a topic".40            2. **Submit:** Press the "Submit" button to start the simulation.41            3. **Chat History:** View the previous conversations as the simulation unfolds.42 43            **Credits:**44            - **Developer:** Yiqiao Yin45               - [Site](https://www.y-yin.io/)46               - [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/)47               - [YouTube](https://youtube.com/YiqiaoYin/)48        """)49 50    # Text input51    user_topic = st.text_input("Enter a topic", "Data Science")52 53    # Add a button to submit54    submit_button = st.button("Run Simulation!")55 56    # Add a button to clear the session state57    if st.button("Clear Session"):58        st.session_state.messages = []59        st.experimental_rerun()60 61 62# Initialize chat history63if "messages" not in st.session_state:64    st.session_state.messages = []65 66 67# Display chat messages from history on app rerun68for message in st.session_state.messages:69    with st.chat_message(message["role"]):70        st.markdown(message["content"])71 72 73# Create agents74interviewer = call_llama75interviewee = call_llama76judge = call_llama77 78 79# React to user input80iter = 081list_of_iters = []82list_of_questions = []83list_of_answers = []84list_of_judge_comments = []85list_of_passes = []86if submit_button:87 88    # Initiatization89    prompt = f"Ask a question about this topic: {user_topic}"90 91    # Display user message in chat message container92    # Default: user=interviewee, assistant=interviewer93    st.chat_message("user").markdown(prompt)94    st.session_state.messages.append({"role": "user", "content": prompt})95 96    while True:97 98        # Interview asks a question99        question = interviewer(prompt)100 101        # Display assistant response in chat message container102        st.chat_message("assistant").markdown(question)103        st.session_state.messages.append({"role": "assistant", "content": question})104 105        # Interviewee attempts an answer106        if iter < 5:107            answer = interviewee(108                f"""109                    Answer the question: {question} in a mediocre way110                    Because you are an inexperienced interviewee.111                """112            )113            st.chat_message("user").markdown(answer)114            st.session_state.messages.append({"role": "user", "content": answer})115        else:116            answer = interviewee(117                f"""118                    Answer the question: {question} in a mediocre way119                    Because you are an inexperienced interviewee but you really want to learn,120                    so you learn from the judge comments: {judge_comments}121                """122            )123            st.chat_message("user").markdown(answer)124            st.session_state.messages.append({"role": "user", "content": answer})125 126        # Judge thinks and advises but the thoughts are hidden127        judge_comments = judge(128            f"""129                The question is: {question}130                The answer is: {answer}131                Provide feedback and rate the answer from 1 to 10 while 10 being the best and 1 is the worst.132            """133        )134 135 136        # Collect all responses137        passed_or_not = 1 if '8' in judge_comments else 0138        list_of_iters.append(iter)139        list_of_questions.append(question)140        list_of_answers.append(answer)141        list_of_judge_comments.append(judge_comments)142        list_of_passes.append(passed_or_not)143        results_tab = pd.DataFrame({144            "Iter.": list_of_iters,145            "Questions": list_of_questions,146            "Answers": list_of_answers,147            "Judge Comments": list_of_judge_comments,148            "Passed": list_of_passes149        })150 151        with st.expander("See explanation"):152            st.table(results_tab)153 154        # Stopping rule155        if '8' in judge_comments:156            break157 158        # Checkpoint159        iter += 1