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Add cache for streamlit

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This commit is contained in:
Samuele E. Locatelli
2025-08-21 17:07:29 +00:00
parent b9310364df
commit ba3280280d
2 changed files with 127 additions and 51 deletions
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backend/main.py
+1 -1
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@@ -6,7 +6,7 @@ import redis
import json
import httpx
r = redis.Redis(host='localhost', port=6379, db=0)
r = redis.Redis(host='localhost', port=6379, db=1)
def save_chat(user_id, message):
r.rpush(f"chat:{user_id}", json.dumps(message))
streamlit/app.py
+126 -50
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@@ -1,12 +1,9 @@
####
#### Streamlit Streaming using LM Studio + Redis for multi-user context
#### run with: streamlit run app.py
#### Requires: pip install pypdf langchain langchain_openai redis
import streamlit as st
import streamlit.components.v1 as components
import redis
import json
import uuid
import hashlib
from langchain_core.messages import AIMessage, HumanMessage
from langchain_openai import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
@@ -15,92 +12,171 @@ from langchain_core.prompts import ChatPromptTemplate
# ---------------------
# Redis connection
# ---------------------
# Adjust host/port as needed
r = redis.Redis(host="localhost", port=6379, db=1, decode_responses=True)
r = redis.Redis(host="localhost", port=6379, decode_responses=True)
# ---------------------
# Helpers for session & history
# Session ID helpers
# ---------------------
def get_session_id():
"""Ensure each user gets a unique, persistent session ID."""
if "session_id" not in st.session_state:
st.session_state.session_id = str(uuid.uuid4())
return st.session_state.session_id
def get_or_set_session_id():
"""Get or set session_id from browser localStorage and trigger rerun when first set."""
if "session_id" in st.session_state:
return st.session_state.session_id
components.html(f"""
<script>
const key = 'egalware_session_id';
let sid = window.localStorage.getItem(key);
if (!sid) {{
sid = '{uuid.uuid4()}';
window.localStorage.setItem(key, sid);
}}
const streamlitDoc = window.parent.document;
let hidden = streamlitDoc.querySelector('#session_id_input');
if (!hidden) {{
hidden = document.createElement('input');
hidden.type = 'hidden';
hidden.id = 'session_id_input';
streamlitDoc.body.appendChild(hidden);
}}
hidden.value = sid;
hidden.dispatchEvent(new Event('input', {{ bubbles: true }}));
</script>
""", height=0)
sid = st.text_input("session_id_input", label_visibility="collapsed")
if sid and sid != st.session_state.get("session_id"):
st.session_state.session_id = sid
st.rerun() # immediately rerun with the new ID
return st.session_state.get("session_id")
# ---------------------
# Chat history persistence
# ---------------------
def load_history(session_id):
"""Retrieve chat history for a given session from Redis."""
raw = r.get(f"chatbot:history:{session_id}")
if raw:
messages = json.loads(raw)
return [AIMessage(content=m["content"]) if m["type"] == "ai"
else HumanMessage(content=m["content"])
for m in messages]
return [AIMessage(content="Hello, I am EgalWare's current ChatBot. How can I help you? (puoi fare domande in italiano, ma in inglese funziona meglio...)")]
return [
AIMessage(content=m["content"]) if m["type"] == "ai"
else HumanMessage(content=m["content"])
for m in messages
]
return [AIMessage(content="Hello, I am EgalWare's ChatBot. How can I help you? (puoi fare domande in italiano, ma in inglese funziona meglio...)")]
def save_history(session_id, history):
"""Save chat history back to Redis."""
messages = []
for m in history:
messages.append({"type": "ai" if isinstance(m, AIMessage) else "human", "content": m.content})
messages = [
{"type": "ai" if isinstance(m, AIMessage) else "human", "content": m.content}
for m in history
]
r.set(f"chatbot:history:{session_id}", json.dumps(messages))
# Optional TTL so old sessions expire:
r.expire(f"chatbot:history:{session_id}", 60 * 60 * 24 * 7) # 7 days
r.expire(f"chatbot:history:{session_id}", 60*60*24*7)
def delete_history(session_id):
r.delete(f"chatbot:history:{session_id}")
for key in r.scan_iter(f"chatbot:cache:{session_id}:*"):
r.delete(key)
# ---------------------
# LLM interaction
# Caching
# ---------------------
def get_response(user_query, chat_history):
template = """
You are a helpful assistant. Answer the following questions considering the history of the conversation:
def get_cache_key(session_id, prompt):
digest = hashlib.sha256(prompt.encode()).hexdigest()
return f"chatbot:cache:{session_id}:{digest}"
Chat history: {chat_history}
def get_cached_response(session_id, prompt):
return r.get(get_cache_key(session_id, prompt))
User question: {user_question}
"""
prompt = ChatPromptTemplate.from_template(template)
def set_cached_response(session_id, prompt, response):
r.setex(get_cache_key(session_id, prompt), 300, response)
# ---------------------
# LLM
# ---------------------
def get_response(session_id, user_query, chat_history):
cached = get_cached_response(session_id, user_query)
if cached:
yield cached
return
prompt = ChatPromptTemplate.from_template(
"You are a helpful assistant. Answer the following considering the history:\n\n"
"Chat history: {chat_history}\n\nUser question: {user_question}"
)
llm = ChatOpenAI(
base_url="http://10.74.83.100:1234/v1",
api_key="lm-studio",
model="qwen/qwen3-4b-2507"
)
chain = prompt | llm | StrOutputParser()
return chain.stream({
full_resp = ""
for chunk in chain.stream({
"chat_history": chat_history,
"user_question": user_query,
})
"user_question": user_query
}):
full_resp += chunk
yield chunk
set_cached_response(session_id, user_query, full_resp)
# ---------------------
# Streamlit app setup
# UI
# ---------------------
st.set_page_config(page_title="Egalware Chatbot", page_icon="🤖")
st.title("Egalware's Chatbot")
session_id = get_or_set_session_id()
# Identify user & load history from Redis
session_id = get_session_id()
st.session_state.chat_history = load_history(session_id)
# Sticky header CSS
st.markdown("""
<style>
.sticky-header {
position: sticky;
top: 0;
background-color: white;
padding-top: 0.5rem;
padding-bottom: 0.5rem;
z-index: 999;
border-bottom: 1px solid #ddd;
}
</style>
""", unsafe_allow_html=True)
# Render conversation
# Header
st.markdown('<div class="sticky-header">', unsafe_allow_html=True)
col_title, col_btn = st.columns([0.9, 0.1])
with col_title:
st.title("Egalware's Chatbot")
with col_btn:
if st.button("🗑️", help="Clear conversation", type="secondary"):
delete_history(session_id)
st.session_state.chat_history = load_history(session_id)
st.rerun()
st.markdown('</div>', unsafe_allow_html=True)
# If still no ID, display placeholder history so UI doesn't look empty
if not session_id:
if "chat_history" not in st.session_state:
st.session_state.chat_history = [AIMessage(content="Initializing session… please wait")]
else:
if "chat_history" not in st.session_state:
st.session_state.chat_history = load_history(session_id)
# Conversation display
for message in st.session_state.chat_history:
role = "AI" if isinstance(message, AIMessage) else "Human"
with st.chat_message(role):
st.write(message.content)
# Handle new input
user_query = st.chat_input("Type your message here...")
if user_query:
# Input
user_query = st.chat_input("Type your message here…")
if session_id and user_query:
st.session_state.chat_history.append(HumanMessage(content=user_query))
with st.chat_message("Human"):
st.markdown(user_query)
with st.chat_message("AI"):
response_text = st.write_stream(get_response(user_query, st.session_state.chat_history))
response_text = st.write_stream(
get_response(session_id, user_query, st.session_state.chat_history)
)
st.session_state.chat_history.append(AIMessage(content=response_text))
# Save updated history to Redis
save_history(session_id, st.session_state.chat_history)