| ############################################################################## |
| # Main script that builds the UI & connects the logic for an LLM-driven |
| # query frontend to an ASDRP demo app. |
| # |
| # @philmui |
| # Tue Jun 20 23:35:59 PDT 2023 |
| ############################################################################## |
|
|
| import streamlit as st |
| from pprint import pprint |
|
|
| ############################################################################## |
|
|
| st.set_page_config(page_title="Transformers", |
| page_icon=":robot:", |
| layout="wide") |
| st.header("🤖 Transformers 👾") |
|
|
| col1, col2 = st.columns([1,1]) |
|
|
| with col1: |
| option_llm = st.selectbox( |
| "LLM", |
| ('text-davinci-003', |
| 'gpt-3.5-turbo', |
| 'gpt-4', |
| ) |
| ) |
| with col2: |
| option_embedding = st.selectbox( |
| "Embedding", |
| ("text-ada-002", |
| ) |
| ) |
| def get_question(): |
| input_text = st.text_area(label="Your question ...", |
| placeholder="Ask me anything ...", |
| key="question_text", label_visibility="collapsed") |
| return input_text |
|
|
| question_text = get_question() |
|
|
| if question_text and len(question_text) > 1: |
| output="(Response in the work)" |
| height = min(2*len(output), 240) |
| st.text_area(label="Response" , |
| value=output, height=height) |
|
|
|
|