Streamlit: Build and Deploy ML Apps in Pure Python in 10 Minutes

import streamlit as st
import pandas as pd

st.title("Sales Dashboard")

uploaded = st.file_uploader("Upload CSV", type="csv")
if uploaded:
    df = pd.read_csv(uploaded)

    region = st.selectbox("Filter by region", df["region"].unique())
    filtered = df[df["region"] == region]

    st.dataframe(filtered)
    st.bar_chart(filtered.groupby("product")["revenue"].sum())

import streamlit as st
import pandas as pd
from sentence_transformers import SentenceTransformer

@st.cache_data  # cache data loading  -  reruns only when inputs change
def load_data(path: str) -> pd.DataFrame:
    return pd.read_parquet(path)

@st.cache_resource  # cache heavy objects  -  loaded once, shared across sessions
def load_model() -> SentenceTransformer:
    return SentenceTransformer("all-MiniLM-L6-v2")

df = load_data("embeddings.parquet")  # cached after first run
model = load_model()  # loaded once, reused

import streamlit as st
from openai import OpenAI

client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])

if "messages" not in st.session_state:
    st.session_state.messages = []

for msg in st.session_state.messages:
    with st.chat_message(msg["role"]):
        st.write(msg["content"])

if prompt := st.chat_input("Ask anything..."):
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.write(prompt)

    with st.chat_message("assistant"):
        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=st.session_state.messages,
            stream=True,
        )
        content = st.write_stream(response)

    st.session_state.messages.append({"role": "assistant", "content": content})

import streamlit as st

if "counter" not in st.session_state:
    st.session_state.counter = 0

if st.button("Increment"):
    st.session_state.counter += 1

st.write(f"Count: {st.session_state.counter}")

# .streamlit/secrets.toml (never commit this)
OPENAI_API_KEY = "sk-..."
DATABASE_URL = "mongodb+srv://..."

import streamlit as st
key = st.secrets["OPENAI_API_KEY"]