app.py

import streamlit as st
import pandas as pd
import threading
import time
import random
from streamlit_autorefresh import st_autorefresh

# Lane definitions (same as before)
lanes = [
    {"src": "Dallas, TX", "dst": "Atlanta, GA", "type": "Dry Van", "rate": "$2.15/mi",
     "src_coords": (32.7767, -96.7970), "dst_coords": (33.7490, -84.3880)},
    {"src": "Houston, TX", "dst": "Chicago, IL", "type": "Flatbed", "rate": "$2.40/mi",
     "src_coords": (29.7604, -95.3698), "dst_coords": (41.8781, -87.6298)},
    {"src": "Savannah, GA", "dst": "Charlotte, NC", "type": "Reefer", "rate": "$2.75/mi",
     "src_coords": (32.0809, -81.0912), "dst_coords": (35.2271, -80.8431)},
    {"src": "Memphis, TN", "dst": "Birmingham, AL", "type": "Auto Parts", "rate": "$2.10/mi",
     "src_coords": (35.1495, -90.0490), "dst_coords": (33.5186, -86.8104)},
    {"src": "Mobile, AL", "dst": "New Orleans, LA", "type": "Tanker", "rate": "$3.15/mi",
     "src_coords": (30.6954, -88.0399), "dst_coords": (29.9511, -90.0715)},
]

# Initialize session state
if "messages" not in st.session_state:
    st.session_state.messages = []
if "lane_counts" not in st.session_state:
    st.session_state.lane_counts = {f"{l['src']} → {l['dst']}": 0 for l in lanes}
if "markers" not in st.session_state:
    st.session_state.markers = []
if "running" not in st.session_state:
    st.session_state.running = False

# Safe background loader
def generate_loads():
    while st.session_state.running:
        lane = random.choice(lanes)
        key = f"{lane['src']} → {lane['dst']}"
        # build and append message
        msg = f"FreightMinded AI: Booked load {key} ({lane['type']}, {lane['rate']})"
        st.session_state.messages.append(msg)
        st.session_state.lane_counts[key] += 1
        st.session_state.markers.extend([
            {"lat": lane['src_coords'][0], "lon": lane['src_coords'][1]},
            {"lat": lane['dst_coords'][0], "lon": lane['dst_coords'][1]},
        ])
        time.sleep(5)

# Auto-refresh mechanism
stad = st_autorefresh(interval=2000, limit=None, key="auto")

# Page layout
st.set_page_config(page_title="Freight Minded Dispatch Automation", layout="wide")
st.title("🚚 Freight Minded Dispatch Automation")
st.caption("Let your truck pay like it weigh")

# Controls
col1, col2 = st.columns(2)
with col1:
    if st.session_state.running:
        if st.button("Stop Simulation"):
            st.session_state.running = False
    else:
        if st.button("Start Simulation"):
            st.session_state.running = True
            threading.Thread(target=generate_loads, daemon=True).start()
with col2:
    if st.button("Reset"):
        st.session_state.running = False
        st.session_state.messages.clear()
        st.session_state.lane_counts = {f"{l['src']} → {l['dst']}": 0 for l in lanes}
        st.session_state.markers.clear()

# Main layout
left, right = st.columns([2, 1])
with left:
    st.subheader("Live Feed")
    feed = st.empty()
    recent = st.session_state.messages[-20:][::-1]
    feed.markdown("\n".join(f"- {m}" for m in recent))

with right:
    st.subheader("📊 Key Metrics")
    total = len(st.session_state.messages)
    avg_rate = None
    # compute average rate if any
    if total > 0:
        # naive parse: sum numeric from string
        rates = [float(m.split("$")[1].split("/")[0]) for m in st.session_state.messages]
        avg_rate = sum(rates) / len(rates)
    st.metric("Total Loads", total)
    if avg_rate:
        st.metric("Avg Rate ($/mi)", f"{avg_rate:.2f}")

    st.subheader("Loads by Lane")
    df = pd.DataFrame({
        "Lane": list(st.session_state.lane_counts.keys()),
        "Count": list(st.session_state.lane_counts.values())
    }).set_index("Lane")
    st.bar_chart(df)

    st.subheader("Route Map")
    if st.session_state.markers:
        map_df = pd.DataFrame(st.session_state.markers)
        st.map(map_df)
    else:
        st.info("No routes booked yet.")

    st.download_button("Download Report",
                       data="\n".join(st.session_state.messages),
                       file_name="daily_report.txt",
                       mime="text/plain")