Spaces:
Sleeping
Sleeping
File size: 2,297 Bytes
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import streamlit as st
import os
import google.generativeai as genai
# Set your Google API Key directly or use Hugging Face Spaces' Secrets
genai.configure(api_key=os.getenv("GOOGLE_KEY")) # Make sure to set this in the Spaces secrets
model = genai.GenerativeModel("gemini-pro")
chat = model.start_chat(history=[])
def get_gemini_response(prompt):
try:
response = chat.send_message(prompt, stream=True)
return response
except Exception as e:
return f"An error occurred: {str(e)}"
# Streamlit app configuration
st.set_page_config(page_title="Med ChatBot")
st.header("Medical ChatBot")
# Initialize session state for chat history
if "chat_history" not in st.session_state:
st.session_state["chat_history"] = []
# Input and submission button
input_text = st.text_input("Input: ", key="input")
submit = st.button("Ask the question")
if submit and input_text:
# Context for the LLM with history included
chat_history_text = " ".join([f"{role}: {text}" for role, text in st.session_state["chat_history"]])
context = (
"You are a medical chatbot designed to assist users in understanding their symptoms. "
"Provide clear, concise, and informative responses based on NHS guidelines. "
"Avoid technical jargon and code snippets. If asked a question unrelated to medical topics, "
"respond with: 'I am a medical bot and I don't have that knowledge.' "
f"Previous conversation: {chat_history_text} "
)
prompt = f"{context} User's latest input: {input_text}" # Include the latest user input
response = get_gemini_response(prompt)
# Add user query to session state chat history
st.session_state['chat_history'].append(("You", input_text))
st.subheader("The Response is")
# If the response is a list of chunks, combine them into a single string
if isinstance(response, list):
full_response = " ".join([chunk.text for chunk in response])
st.write(full_response)
st.session_state['chat_history'].append(("Bot", full_response))
else:
st.write(response)
st.session_state['chat_history'].append(("Bot", response))
st.subheader("The Chat History is")
for role, text in st.session_state['chat_history']:
st.write(f"{role}: {text}")
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