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import streamlit as st
import os
import pickle
import time
import g4f
st.set_page_config(page_title="MEDICAL ASSISTANT")
st.markdown(
"""
<style>
.title {
text-align: center;
font-size: 2em;
font-weight: bold;
}
</style>
<div class="title">🧠 MEDICAL ASSISTANT</div>
""",
unsafe_allow_html=True
)
# Load and Save Conversations
conversations_file = "conversations.pkl"
@st.cache_data
def load_conversations():
try:
with open(conversations_file, "rb") as f:
return pickle.load(f)
except (FileNotFoundError, EOFError):
return []
def save_conversations(conversations):
temp_conversations_file = conversations_file
with open(temp_conversations_file, "wb") as f:
pickle.dump(conversations, f)
os.replace(temp_conversations_file, conversations_file)
if 'conversations' not in st.session_state:
st.session_state.conversations = load_conversations()
if 'current_conversation' not in st.session_state:
st.session_state.current_conversation = [{"role": "assistant", "content": "How may I assist you today?"}]
def truncate_string(s, length=30):
return s[:length].rstrip() + "..." if len(s) > length else s
def display_chats_sidebar():
with st.sidebar.container():
st.header('Settings')
col1, col2 = st.columns([1, 1])
with col1:
if col1.button('Start New Chat', key="new_chat"):
st.session_state.current_conversation = []
st.session_state.conversations.append(st.session_state.current_conversation)
with col2:
if col2.button('Clear All Chats', key="clear_all"):
st.session_state.conversations = []
st.session_state.current_conversation = []
with st.sidebar.container():
st.header('Conversations')
for idx, conversation in enumerate(st.session_state.conversations):
if conversation:
chat_title_raw = next((msg["content"] for msg in conversation if msg["role"] == "user"), "New Chat")
chat_title = truncate_string(chat_title_raw)
if st.sidebar.button(f"{chat_title}", key=f"chat_button_{idx}"):
st.session_state.current_conversation = st.session_state.conversations[idx]
def main_app():
for message in st.session_state.current_conversation:
with st.chat_message(message["role"]):
st.write(message["content"])
def generate_response(prompt_input):
string_dialogue = "You are a helpful Medical Assistant. You will Only respond to Medical related Queries. Say Sorry to any other Type of Queries."
for dict_message in st.session_state.current_conversation:
string_dialogue += dict_message["role"].capitalize() + ": " + dict_message["content"] + "\\n\\n"
prompt = f"{string_dialogue}\n {prompt_input} Assistant: "
response_generator = g4f.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": prompt}],
stream=True,
)
return response_generator
if prompt := st.chat_input('Send a Message'):
st.session_state.current_conversation.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.write(prompt)
with st.chat_message("assistant"):
with st.spinner("Thinking..."):
response = generate_response(prompt)
placeholder = st.empty()
full_response = ''
for item in response:
full_response += item
time.sleep(0.003)
placeholder.markdown(full_response)
placeholder.markdown(full_response)
st.session_state.current_conversation.append({"role": "assistant", "content": full_response})
save_conversations(st.session_state.conversations)
display_chats_sidebar()
main_app()
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