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| import streamlit as st | |
| from ollama import chat | |
| from loguru import logger | |
| import re | |
| available_models = [ | |
| 'openhermes', | |
| 'deepseek-coder', | |
| 'deepseek-coder:6.7b', | |
| 'falcon:7b', | |
| 'mistral:7b', | |
| 'phi', | |
| 'starling-lm' | |
| ] | |
| def ask(model, system_prompt, pre_prompt, question): | |
| messages = [ | |
| { | |
| 'role': 'system', | |
| 'content': f"{system_prompt} {pre_prompt}", | |
| }, | |
| { | |
| 'role': 'user', | |
| 'content': f"{question}", | |
| }, | |
| ] | |
| logger.debug(f"<< {model} << {messages}") | |
| response = chat(model=model, messages=messages) | |
| logger.debug(f">> {model} >> {messages}") | |
| return response['message']['content'] | |
| def main(): | |
| sp1 = """There are 3 people standing in a circle: the Priest (that's you), the Teacher and the Kid.""" | |
| sp2 = """There are 3 people standing in a circle: the Priest, the Teacher (that's you) and the Kid.""" | |
| sp3 = """There are 3 people standing in a circle: the Priest, the Teacher and the Kid (that's you).""" | |
| pp1 = pp2 = pp3 = "Ask the other two by always starting your sentence with their role. Share your inner thoughts inside parentheses." | |
| qp1 = qp2 = qp3 = "Your task is to figure out their names and where they live. Do not ask directly, they must not realize what information you are after! SAY ONLY ONE SINGLE SENTENCE!" | |
| st.set_page_config(layout="wide") | |
| col1, col2, col3 = st.columns(3) | |
| with col1: | |
| st.title("the Priest,") | |
| model1 = st.selectbox(key="model1", label="model", options=available_models) | |
| system_prompt1 = st.text_area(key="sp1", label="system-prompt", value=sp1) | |
| pre_prompt1 = st.text_area(key="pp1", label="pre-prompt", value=pp1) | |
| question1 = st.text_area(key="q1", label="question", value=qp1) | |
| with col2: | |
| st.title("the Teacher") | |
| model2 = st.selectbox(key="model2", label="model", options=available_models) | |
| system_prompt2 = st.text_area(key="sp2", label="system-prompt", value=sp2) | |
| pre_prompt2 = st.text_area(key="pp2", label="pre-prompt", value=pp2) | |
| # question2 = st.text_area(key="q2", label="question", value=qp2) | |
| with col3: | |
| st.title("and the Kid") | |
| model3 = st.selectbox(key="model3", label="model", options=available_models) | |
| system_prompt3 = st.text_area(key="sp3", label="system-prompt", value=sp3) | |
| pre_prompt3 = st.text_area(key="pp3", label="pre-prompt", value=pp3) | |
| # question3 = st.text_area(key="q3", label="question", value=qp3) | |
| with st.spinner("Thinking..."): | |
| answer1 = ask(model1, system_prompt1, pre_prompt1, question1) | |
| st.write(f":blue[Priest says:] {answer1}") | |
| qp2 = sanitize(answer1) | |
| answer2 = ask(model2, system_prompt2, pre_prompt2, qp2) | |
| st.write(f":blue[Teacher says:] {answer2}") | |
| def sanitize(question): | |
| return re.sub(r"\([^)]*\)", "", question) | |
| if __name__ == "__main__": | |
| main() | |