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#!/usr/bin/env python3
"""
Minimalna aplikacja LLM w 50 linijkach!
Streamlit + Ollama = zero konfiguracji
"""
import streamlit as st
import ollama
import os
from typing import Generator
# Konfiguracja
OLLAMA_URL = os.getenv("OLLAMA_URL", "http://localhost:11434")
MODEL_NAME = "mistral:7b-instruct"
# Setup Ollama client
client = ollama.Client(host=OLLAMA_URL)
def stream_response(prompt: str) -> Generator[str, None, None]:
"""Generator dla streaming response"""
try:
stream = client.chat(
model=MODEL_NAME,
messages=[{"role": "user", "content": prompt}],
stream=True
)
for chunk in stream:
if chunk['message']['content']:
yield chunk['message']['content']
except Exception as e:
yield f"Error: {str(e)}"
def main():
# UI Setup
st.set_page_config(
page_title="🤖 Minimal LLM Chat",
page_icon="🤖",
layout="wide"
)
st.title("🤖 Minimal LLM Chat")
st.markdown("*Powered by Ollama + Mistral 7B*")
# Sidebar z ustawieniami
with st.sidebar:
st.header("⚙️ Settings")
# Model info
try:
models = client.list()
available_models = [m['name'] for m in models['models']]
st.success(f"✅ Connected to Ollama")
st.info(f"Available models: {len(available_models)}")
except:
st.error("❌ Cannot connect to Ollama")
st.stop()
# Parameters
temperature = st.slider("Temperature", 0.0, 2.0, 0.7, 0.1)
max_tokens = st.slider("Max tokens", 50, 1000, 500, 50)
# System prompt
system_prompt = st.text_area(
"System prompt:",
"You are a helpful AI assistant. Answer concisely and accurately.",
height=100
)
# Chat interface
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat history
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input
if prompt := st.chat_input("Type your message here..."):
# Add user message
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Generate response
with st.chat_message("assistant"):
response_placeholder = st.empty()
full_response = ""
# Streaming response
for chunk in stream_response(prompt):
full_response += chunk
response_placeholder.markdown(full_response + "▌")
response_placeholder.markdown(full_response)
# Add assistant message
st.session_state.messages.append({"role": "assistant", "content": full_response})
# Quick actions
col1, col2, col3 = st.columns(3)
with col1:
if st.button("🗑️ Clear Chat"):
st.session_state.messages = []
st.rerun()
with col2:
if st.button("💡 Example Question"):
example = "Explain quantum computing in simple terms"
st.session_state.messages.append({"role": "user", "content": example})
st.rerun()
with col3:
if st.button("📊 Model Info"):
try:
info = client.show(MODEL_NAME)
st.json(info)
except:
st.error("Cannot get model info")
if __name__ == "__main__":
main() |