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| import streamlit as st | |
| from source_code import text_completion, chat, GEC, paraphrase, contextual_answer, summarize, improvements | |
| st.title("AI21 Studio Jurassic") | |
| st.image( | |
| image="jurassic.jpg", | |
| caption="Jurassic", | |
| ) | |
| st.sidebar.title("Select your preferred tasks") | |
| jurassic_models = [ | |
| "j2-light", | |
| "j2-ultra", | |
| "j2-mid", | |
| ] | |
| tasks = [ | |
| "Generic", | |
| "Specific" | |
| ] | |
| # task = st.sidebar.selectbox( | |
| # label="Select your Model", | |
| # options = tasks | |
| # ) | |
| disabled = False | |
| # if task == "Generic": | |
| # disabled = False | |
| # task_disable = False | |
| # if task == "Specific": | |
| # task_disable = True | |
| # generic_tasks = [ | |
| # "Text Completion", | |
| # # "Chat" | |
| # ] | |
| specific_tasks = [ | |
| # "Contextual Answers", | |
| "Paraphrase", | |
| "Summarize", | |
| "Grammetical Error Corrections", | |
| "Text Improvements" | |
| ] | |
| # choose_task = generic_tasks | |
| # if task == "Specific": | |
| # choose_task = specific_tasks | |
| choose_task = specific_tasks | |
| choose = st.sidebar.selectbox( | |
| label="Select your tasks", | |
| options = choose_task, | |
| ) | |
| # model = st.sidebar.selectbox( | |
| # label="Select your Model", | |
| # options = jurassic_models, | |
| # disabled=disabled | |
| # ) | |
| # numResults = st.sidebar.number_input( | |
| # label="Select Number of results", | |
| # min_value=1, | |
| # max_value=5, | |
| # value=1, | |
| # disabled=disabled | |
| # ) | |
| # maxTokens = st.sidebar.number_input( | |
| # label="Max Number of Tokens to generate", | |
| # min_value=32, | |
| # max_value=2048, | |
| # value=200, | |
| # step=2, | |
| # disabled=disabled | |
| # ) | |
| # temperature = st.sidebar.slider( | |
| # label="Temperature", | |
| # min_value=0.1, | |
| # max_value=1.0, | |
| # value=0.5, | |
| # step=0.1, | |
| # disabled=disabled | |
| # ) | |
| # topP = st.sidebar.slider( | |
| # label="Top P", | |
| # min_value=0.1, | |
| # max_value=1.0, | |
| # value=0.6, | |
| # step=0.1, | |
| # disabled=disabled | |
| # ) | |
| # topKReturn = st.sidebar.slider( | |
| # label="Top K", | |
| # min_value=1, | |
| # max_value=10, | |
| # value=5, | |
| # step=1, | |
| # disabled=disabled | |
| # ) | |
| # context = st.sidebar.text_input( | |
| # label="Context", | |
| # ) | |
| # if choose == "Chat": | |
| # question = st.chat_input(key="Question") | |
| # if context is None: | |
| # context = "Everything" | |
| # # template = f"<|system|>\nYou are a intelligent chatbot and expertise in {context}.</s>\n<|user|>\n{question}.\n<|assistant|>" | |
| # template = f"{context}\n{question}" | |
| # if "messages" not in st.session_state: | |
| # st.session_state.messages = [] | |
| # for message in st.session_state.messages: | |
| # with st.chat_message(message.get('role')): | |
| # st.write(message.get("content")) | |
| # st.session_state.messages.append( | |
| # { | |
| # "role":"user", | |
| # "content": f"Question: {question}" | |
| # } | |
| # ) | |
| # if question: | |
| # result = chat(model, template, numResults, maxTokens, temperature, topKReturn, topP) | |
| # with st.chat_message("user"): | |
| # st.write(f"Context: {context}\n\nQuestion: {question}") | |
| # if question.lower() == "clear": | |
| # del st.session_state.messages | |
| # st.session_state.messages.append( | |
| # { | |
| # "role": "assistant", | |
| # "content": result | |
| # } | |
| # ) | |
| # with st.chat_message('User'): | |
| # st.write(f"Context: {context}\n\nQuestion: {question}") | |
| # with st.chat_message('assistant'): | |
| # st.markdown(result) | |
| if 0 > 1: | |
| pass | |
| else: | |
| question = st.text_area(label="Question") | |
| # if context is None: | |
| # context = "Everything" | |
| # template = f"<|system|>\nYou are a intelligent chatbot and expertise in {context}.</s>\n<|user|>\n{question}.\n<|assistant|>" | |
| # if choose == "Text Completion": | |
| # if question: | |
| # result = text_completion(model, template, numResults, maxTokens, temperature, topKReturn, topP) | |
| # st.markdown(result) | |
| # if choose == "Contextual Answers": | |
| # if question: | |
| # result = contextual_answer(context, question) | |
| # st.markdown(result) | |
| if choose == "Paraphrase": | |
| if question: | |
| result = paraphrase(question) | |
| st.markdown(result) | |
| elif choose == "Summarize": | |
| if question: | |
| result = summarize(question) | |
| st.markdown(result) | |
| elif choose == "Grammetical Error Corrections": | |
| if question: | |
| result = GEC(question) | |
| st.markdown(result) | |
| elif choose == "Text Improvements": | |
| if question: | |
| result = improvements(question) | |
| st.markdown(result) | |