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import markdown |
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import streamlit as st |
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from streamlit_chat import message |
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from streamlit_extras.colored_header import colored_header |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig |
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model_id = "Narrativaai/BioGPT-Large-finetuned-chatdoctor" |
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tokenizer = AutoTokenizer.from_pretrained("microsoft/BioGPT-Large") |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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def answer_question( |
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prompt, temperature=0.1, top_p=0.75, top_k=40, num_beams=2, **kwargs |
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): |
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inputs = tokenizer(prompt, return_tensors="pt") |
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input_ids = inputs["input_ids"].to("cpu") |
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attention_mask = inputs["attention_mask"].to("cpu") |
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generation_config = GenerationConfig( |
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temperature=temperature, top_p=top_p, top_k=top_k, num_beams=num_beams, **kwargs |
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) |
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with torch.no_grad(): |
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generation_output = model.generate( |
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input_ids=input_ids, |
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attention_mask=attention_mask, |
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generation_config=generation_config, |
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return_dict_in_generate=True, |
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output_scores=True, |
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max_new_tokens=512, |
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eos_token_id=tokenizer.eos_token_id, |
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) |
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s = generation_output.sequences[0] |
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output = tokenizer.decode(s, skip_special_tokens=True) |
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return output.split(" Response:")[1] |
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st.set_page_config(page_title="Talk To Me", page_icon=":ambulance:", layout="wide") |
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colored_header( |
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label="Talk To Me", |
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description="Talk your way to better health", |
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color_name="violet-70", |
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) |
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with open("./sidebar.md", "r") as sidebar_file: |
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sidebar_content = sidebar_file.read() |
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with open("./styles.md", "r") as styles_file: |
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styles_content = styles_file.read() |
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def add_sbg_from_url(): |
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st.markdown( |
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f""" |
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<style> |
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.css-6qob1r {{ |
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background-image: url("https://images.unsplash.com/photo-1524169358666-79f22534bc6e?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=3540&q=80"); |
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background-attachment: fixed; |
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background-size: cover |
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}} |
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</style> |
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""", |
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unsafe_allow_html=True, |
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) |
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add_sbg_from_url() |
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def add_mbg_from_url(): |
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st.markdown( |
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f""" |
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<style> |
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.stApp {{ |
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background-image: url("https://images.unsplash.com/photo-1536353602887-521e965eb03f?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=987&q=80"); |
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background-attachment: fixed; |
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background-size: cover |
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}} |
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</style> |
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""", |
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unsafe_allow_html=True, |
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) |
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add_mbg_from_url() |
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st.sidebar.markdown(sidebar_content) |
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st.write(styles_content, unsafe_allow_html=True) |
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if "chat_history" not in st.session_state: |
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st.session_state.chat_history = [] |
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if not st.session_state.chat_history: |
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message("Hi, I'm a medical chat bot. Ask me a question!") |
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for chat in st.session_state.chat_history: |
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if chat["is_user"]: |
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message(chat["message"], is_user=True) |
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else: |
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message(chat["message"]) |
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with st.form("user_input_form"): |
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st.write("Please enter your question below:") |
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user_input = st.text_input("You: ") |
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if st.form_submit_button("Submit") and user_input: |
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with st.spinner('Loading model and generating response...'): |
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bot_response = answer_question(f"Input: {user_input}\nResponse:") |
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st.session_state.chat_history.append({"message": user_input, "is_user": True}) |
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st.session_state.chat_history.append( |
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{"message": bot_response, "is_user": False} |
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) |
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if st.session_state.chat_history: |
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latest_chat = st.session_state.chat_history[-1] |
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if latest_chat["is_user"]: |
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message(latest_chat["message"], is_user=True) |
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else: |
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message(latest_chat["message"]) |
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