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.env
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OPENAI_BASE_URL=https://example.org/v1/
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OPENAI_API_KEY=example api key
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config.py
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# AI Configuration
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ALGORITHM = 'g4f'
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# Model Configuration
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DEFAULT_MODEL = 'gpt-4o-mini'
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MODELS = {
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'GPT-4o': 'gpt-4o',
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'GPT-4o Mini': 'gpt-4o-mini'
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}
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# Rate Limiting (Session based) - Note: Implementing robust user-based rate limiting in Streamlit alone is complex and usually requires a backend. This is a basic session-based limit.
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RPM = 10
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RPH = 300
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RPD = 500
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# Queue System - Note: Implementing a full queue system in Streamlit alone is complex and usually requires a backend.
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QUEUE_ENABLED = 'enabled'
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QUEUE_LIMIT = 5
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MAX_QUEUE = 40
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QUEUE_WARNING = 10
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# App Information
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APP_NAME = 'GPT-4o'
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APP_DESCRIPTION = 'Simple AI chatbot for users'
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main.py
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import streamlit as st
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import uuid
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import os
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from dotenv import load_dotenv
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import config
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from g4f.client import Client
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import time
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load_dotenv()
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st.set_page_config(
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page_title=config.APP_NAME,
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page_icon=":robot_face:",
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layout="wide"
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)
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st.markdown("""
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<style>
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.stChatMessage {
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background-color: #262730;
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border-radius: 10px;
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padding: 15px;
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margin-bottom: 10px;
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color: white;
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box-shadow: 2px 2px 5px rgba(0, 0, 0, 0.2);
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}
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.stSidebar {
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background-color: #1E1E1E;
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color: white;
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padding: 20px;
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}
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.stSidebar h2, .stSidebar h3 {
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color: #007BFF;
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}
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.stSidebar .stButton>button {
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width: 100%;
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border-radius: 5px;
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margin-bottom: 10px;
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}
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.main .block-container {
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padding-top: 2rem;
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padding-bottom: 2rem;
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}
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.stChatInputContainer {
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margin-top: 20px;
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}
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body {
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color: white;
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}
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</style>
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""", unsafe_allow_html=True)
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if "chat_sessions" not in st.session_state:
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st.session_state.chat_sessions = {}
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if "current_chat_id" not in st.session_state:
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st.session_state.current_chat_id = None
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if "system_message" not in st.session_state:
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st.session_state.system_message = "Hello! I am ready to help you."
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if "selected_model" not in st.session_state:
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st.session_state.selected_model = config.DEFAULT_MODEL
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if "model_selected" not in st.session_state:
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st.session_state.model_selected = False
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if "request_timestamps" not in st.session_state:
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st.session_state.request_timestamps = []
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def start_new_chat():
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new_chat_id = str(uuid.uuid4())
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st.session_state.chat_sessions[new_chat_id] = [{"role": "assistant", "content": st.session_state.system_message}]
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st.session_state.current_chat_id = new_chat_id
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st.session_state.model_selected = False
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st.session_state.request_timestamps = []
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with st.sidebar:
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st.header("Chat History")
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if st.button("New Chat"):
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start_new_chat()
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st.rerun()
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if st.session_state.current_chat_id is None:
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start_new_chat()
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st.rerun()
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st.subheader("Existing Chats")
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if st.session_state.chat_sessions:
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for chat_id in reversed(list(st.session_state.chat_sessions.keys())):
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history = st.session_state.chat_sessions[chat_id]
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if len(history) > 1 and history[1]['role'] == 'user':
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chat_title_content = str(history[1]['content'])
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chat_title = chat_title_content[:30] + "..." if len(chat_title_content) > 30 else chat_title_content
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else:
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chat_title_content = str(history[0]['content'])
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chat_title = chat_title_content[:30] + "..." if len(chat_title_content) > 30 else chat_title_content
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button_style = "background-color: #007BFF;" if chat_id == st.session_state.current_chat_id else ""
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if st.button(chat_title, key=f"select_chat_{chat_id}"):
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st.session_state.current_chat_id = chat_id
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st.session_state.model_selected = True
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st.rerun()
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else:
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st.info("No chats yet.")
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st.title(config.APP_NAME)
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st.markdown(f"*{config.APP_DESCRIPTION}*")
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if not st.session_state.model_selected:
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available_models_display = list(config.MODELS.keys())
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available_models_api = list(config.MODELS.values())
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default_model_index = available_models_api.index(config.DEFAULT_MODEL) if config.DEFAULT_MODEL in available_models_api else 0
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st.session_state.selected_model = st.selectbox("Select AI Model", available_models_display, index=default_model_index)
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current_chat_history = st.session_state.chat_sessions.get(st.session_state.current_chat_id, [])
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chat_container = st.container(border=True)
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with chat_container:
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for message in current_chat_history:
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role = message["role"]
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content = message["content"]
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avatar_icon = "👤" if role == "user" else "🤖"
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with st.chat_message(role, avatar=avatar_icon):
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st.markdown(content)
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user_input = st.chat_input("Type your message here...")
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if user_input:
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current_time = time.time()
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st.session_state.request_timestamps.append(current_time)
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one_minute_ago = current_time - 60
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one_hour_ago = current_time - 3600
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one_day_ago = current_time - 86400
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recent_requests_minute = [ts for ts in st.session_state.request_timestamps if ts > one_minute_ago]
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recent_requests_hour = [ts for ts in st.session_state.request_timestamps if ts > one_hour_ago]
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recent_requests_day = [ts for ts in st.session_state.request_timestamps if ts > one_day_ago]
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st.session_state.request_timestamps = recent_requests_day
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if len(recent_requests_minute) > config.RPM or \
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len(recent_requests_hour) > config.RPH or \
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len(recent_requests_day) > config.RPD:
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st.warning("Rate limit exceeded. Please wait before sending another message.")
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else:
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st.session_state.chat_sessions[st.session_state.current_chat_id].append({"role": "user", "content": user_input})
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st.session_state.model_selected = True
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with chat_container:
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with st.chat_message("user", avatar="👤"):
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st.markdown(user_input)
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with chat_container:
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with st.chat_message("assistant", avatar="🤖"):
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message_placeholder = st.empty()
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full_response = ""
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with st.spinner(f"Generating response with {st.session_state.selected_model}..."):
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try:
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client_params = {}
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if config.ALGORITHM == 'openai':
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openai_base_url = os.getenv("OPENAI_BASE_URL")
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openai_api_key = os.getenv("OPENAI_API_KEY")
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if openai_base_url:
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client_params['base_url'] = openai_base_url
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if openai_api_key:
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client_params['api_key'] = openai_api_key
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client = Client(**client_params)
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messages_for_api = [{"role": msg["role"], "content": msg["content"]} for msg in st.session_state.chat_sessions[st.session_state.current_chat_id]]
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api_model_name = config.MODELS.get(st.session_state.selected_model, config.DEFAULT_MODEL)
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if api_model_name not in config.MODELS.values():
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api_model_name = config.DEFAULT_MODEL
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stream = client.chat.completions.create(
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model=api_model_name,
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messages=messages_for_api,
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stream=True,
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web_search=False
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)
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for chunk in stream:
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if chunk.choices[0].delta.content is not None:
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full_response += chunk.choices[0].delta.content
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message_placeholder.markdown(full_response + "▌")
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message_placeholder.markdown(full_response)
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except Exception as e:
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full_response = f"Error generating response: {e}"
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message_placeholder.markdown(full_response)
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st.session_state.chat_sessions[st.session_state.current_chat_id].append({"role": "assistant", "content": full_response})
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st.rerun()
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