Samuele E. Locatelli
67 lines
2.0 KiB
Python
67 lines
2.0 KiB
Python
####
|
|
#### Streamlit Streaming using LM Studio as OpenAI Standin
|
|
#### run with `streamlit run app.py`
|
|
|
|
# !pip install pypdf langchain langchain_openai
|
|
|
|
import streamlit as st
|
|
from langchain_core.messages import AIMessage, HumanMessage
|
|
from langchain_openai import ChatOpenAI
|
|
from langchain_core.output_parsers import StrOutputParser
|
|
from langchain_core.prompts import ChatPromptTemplate
|
|
|
|
# app config
|
|
st.set_page_config(page_title="Egalware Chatbot", page_icon="🤖")
|
|
st.title("Egalware's Streaming Chatbot")
|
|
|
|
def get_response(user_query, chat_history):
|
|
|
|
template = """
|
|
You are a helpful assistant. Answer the following questions considering the history of the conversation:
|
|
|
|
Chat history: {chat_history}
|
|
|
|
User question: {user_question}
|
|
"""
|
|
|
|
prompt = ChatPromptTemplate.from_template(template)
|
|
|
|
# Using LM Studio Local Inference Server
|
|
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({
|
|
"chat_history": chat_history,
|
|
"user_question": user_query,
|
|
})
|
|
|
|
# session state
|
|
if "chat_history" not in st.session_state:
|
|
st.session_state.chat_history = [
|
|
AIMessage(content="Hello, I am a bot. How can I help you?"),
|
|
]
|
|
|
|
|
|
# conversation
|
|
for message in st.session_state.chat_history:
|
|
if isinstance(message, AIMessage):
|
|
with st.chat_message("AI"):
|
|
st.write(message.content)
|
|
elif isinstance(message, HumanMessage):
|
|
with st.chat_message("Human"):
|
|
st.write(message.content)
|
|
|
|
# user input
|
|
user_query = st.chat_input("Type your message here...")
|
|
if user_query is not None 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 = st.write_stream(get_response(user_query, st.session_state.chat_history))
|
|
|
|
st.session_state.chat_history.append(AIMessage(content=response))
|