FlorianSC/agritech-interface

1import streamlit as st2import requests3import pandas as pd4 5# Configuration des URL6API_URL_PREDICT = "http://localhost:8000/predict"7API_URL_RECO = "http://localhost:8000/recommend"8 9st.set_page_config(page_title="Agritech Predictor", layout="wide")10 11st.title("🌾 Système de Recommandation Agricole")12 13# Dictionnaire des infos mape à afficher dans l'encart14infos_mape = {15    "Maize": "18,45%",16    "Potatoes": "13,77%",17    "Rice": "13,07%",18    "Wheat": "16,79%",19    "Sorghum": "22,50%",20    "Soybean": "20,23%",21    "Cassava": "16,35%",22    "Yams": "28,40%",23    "Sweet potatoes": "17,24%",24    "Plantains and others": "17,46%"25}26# Dictionnaire des infos de perte économqiue à afficher dans l'encart27infos_economic = {28    "Maize": "137.09 $",29    "Potatoes": "547.61 $",30    "Rice": "123.23 $",31    "Wheat": "71.89 $",32    "Sorghum": "71.33 $",33    "Soybean": "88.31 $",34    "Cassava": "316.57 $",35    "Yams": "1244.71 $",36    "Sweet potatoes": "278.97 $",37    "Plantains and others": "325.10 $"38}39 40# Utilisation d'onglets41tab1, tab2 = st.tabs(["🔮 Prédiction de Rendement", "💡 Recommandation de Culture"])42 43# --- ONGLET 1 : PRÉDICTION ---44with tab1:45    st.header("Estimer le rendement d'une culture précise")46 47    # 2 colonnes : gauche formulaire / droite encart48    left_col, right_col = st.columns([3, 1])49 50    with left_col:51        with st.form("form_prediction"):52            col1, col2 = st.columns(2)53 54            with col1:55                item = st.selectbox(56                    "Culture",57                    ['Maize', 'Potatoes', 'Rice', 'Wheat', 'Sorghum', 'Soybean',58                     'Cassava', 'Yams', 'Sweet potatoes', 'Plantains and others'],59                    key="item_p"60                )61                region = st.selectbox(62                    "Région",63                    ['Southern Asia', 'Southern Europe', 'Northern Africa', 'Polynesia',64                     'Sub-Saharan Africa', 'Latin America and the Caribbean',65                     'Western Asia', 'Australia and New Zealand', 'Western Europe',66                     'Eastern Europe', 'Northern America', 'South-eastern Asia', 'Eastern Asia',67                     'Northern Europe', 'Melanesia', 'Micronesia', 'Central Asia'],68                    key="reg_p"69                )70 71            with col2:72                avg_temp = st.slider("Température Moyenne (°C)", -5.0, 45.0, 15.0, key="temp_p")73                rainfall = st.slider("Précipitations (mm)", min_value=0, value=3500, key="rain_p")74                pesticides = st.slider("Pesticides (tonnes)", min_value=0.0, value=1850000.0, key="pest_p")75 76            submit_p = st.form_submit_button("Lancer la prédiction")77 78    with right_col:79        st.markdown("### Taux d'erreur en %")80        st.info(infos_mape.get(st.session_state.get("item_p", "Maize"), "Aucune info disponible."))81        st.markdown("### Perte économique en dollars (par hectare)")82        st.info(infos_economic.get(st.session_state.get("item_p", "Maize"), "Aucune info disponible."))83 84    if submit_p:85        payload = {86            "region": region,87            "item": item,88            "avg_temp": avg_temp,89            "rainfall_mm": rainfall,90            "pesticides_tonnes": pesticides91        }92        try:93            with st.spinner("Calcul en cours..."):94                res = requests.post(API_URL_PREDICT, json=payload)95                res.raise_for_status()96                data = res.json()97                st.success(f"### Résultat : {data['prediction']:.2f} kg/ha")98        except Exception as e:99            st.error(f"Erreur : {e}")100 101# --- ONGLET 2 : RECOMMANDATION ---102with tab2:103    st.header("Quelle culture est la plus adaptée ?")104    st.info("Cette fonction testera toutes les cultures pour vos conditions climatiques.")105    with st.form("form_reco"):106        col1, col2 = st.columns(2)107        with col1:108            region_r = st.selectbox("Région", ['Southern Asia', 'Southern Europe', 'Northern Africa', 'Polynesia',109                                                 'Sub-Saharan Africa', 'Latin America and the Caribbean',110                                                 'Western Asia', 'Australia and New Zealand', 'Western Europe',111                                                 'Eastern Europe', 'Northern America', 'South-eastern Asia','Eastern Asia',112                                                 'Northern Europe', 'Melanesia', 'Micronesia','Central Asia'], key="reg_r")113        114        with col2:115            avg_temp_r = st.slider("Température Moyenne (°C)", -5.0, 45.0, 15.0, key="temp_r")116            rainfall_r = st.slider("Précipitations (mm)", min_value=0, value=3500, key="rain_r")117            pesticides_r = st.slider("Pesticides (tonnes)", min_value=0.0, value=1850000.0, key="pest_r")118        119        submit_r = st.form_submit_button("Trouver la meilleure culture")120 121    if submit_r:122        payload_r = {123            "region": region_r,124            "avg_temp": avg_temp_r, "rainfall_mm": rainfall_r, "pesticides_tonnes": pesticides_r125        }126        try:127            with st.spinner("Analyse des cultures..."):128                res = requests.post(API_URL_RECO, json=payload_r)129                res.raise_for_status()130                data = res.json()131 132                # Préparation des données pour le graphique133                df_reco = pd.DataFrame(data['ranking'])134                df_reco = df_reco.set_index('crop')135                df_reco = df_reco.sort_values(by='predicted_yield', ascending=False)136 137                st.success(f"🏆 La meilleure culture est : **{data['best_crop']}**")138                # Afficher le classement139                st.write("Classement complet :")140                st.table(data['ranking'])141 142                # Affichage du graphique 143                st.subheader("📊 Comparaison des rendements (kg/ha)")144                st.bar_chart(df_reco)145 146        except Exception as e:147            st.error(f"Erreur : {e}")148 149