Spaces:
Runtime error
Runtime error
Upload 6 files
Browse files- Dockerfile +17 -0
- README.md +10 -10
- app.py +531 -0
- final_price_data.csv +0 -0
- requirements.txt +8 -0
- templates/index.html +640 -0
Dockerfile
ADDED
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Base image
|
2 |
+
FROM python:3.9-slim
|
3 |
+
|
4 |
+
# Set the working directory
|
5 |
+
WORKDIR /app
|
6 |
+
|
7 |
+
# Copy application files
|
8 |
+
COPY . /app
|
9 |
+
|
10 |
+
# Install dependencies
|
11 |
+
RUN pip install --no-cache-dir -r requirements.txt
|
12 |
+
|
13 |
+
# Expose the port your app runs on
|
14 |
+
EXPOSE 7860
|
15 |
+
|
16 |
+
# Command to run the application
|
17 |
+
CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:app"]
|
README.md
CHANGED
@@ -1,10 +1,10 @@
|
|
1 |
-
---
|
2 |
-
title:
|
3 |
-
emoji:
|
4 |
-
colorFrom:
|
5 |
-
colorTo:
|
6 |
-
sdk: docker
|
7 |
-
pinned: false
|
8 |
-
---
|
9 |
-
|
10 |
-
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
|
|
1 |
+
---
|
2 |
+
title: Market Price Analyzer
|
3 |
+
emoji: 📈
|
4 |
+
colorFrom: red
|
5 |
+
colorTo: purple
|
6 |
+
sdk: docker
|
7 |
+
pinned: false
|
8 |
+
---
|
9 |
+
|
10 |
+
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
app.py
ADDED
@@ -0,0 +1,531 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os
|
2 |
+
from flask import Flask, render_template, request, jsonify
|
3 |
+
import requests
|
4 |
+
import pandas as pd
|
5 |
+
from datetime import datetime
|
6 |
+
import plotly.express as px
|
7 |
+
import plotly.io as pio
|
8 |
+
from googletrans import Translator
|
9 |
+
import numpy as np
|
10 |
+
|
11 |
+
app = Flask(__name__)
|
12 |
+
|
13 |
+
# Initialize translator
|
14 |
+
translator = Translator()
|
15 |
+
|
16 |
+
# Translation dictionaries
|
17 |
+
MARATHI_TRANSLATIONS = {
|
18 |
+
'state': 'राज्य',
|
19 |
+
'district': 'जिल्हा',
|
20 |
+
'market': 'बाजार',
|
21 |
+
'commodity': 'पीक',
|
22 |
+
'variety': 'प्रकार',
|
23 |
+
'grade': 'श्रेणी',
|
24 |
+
'arrival_date': 'आगमन तारीख',
|
25 |
+
'min_price': 'किमान किंमत',
|
26 |
+
'max_price': 'कमाल किंमत',
|
27 |
+
'modal_price': 'सरासरी किंमत',
|
28 |
+
'Select State': 'राज्य निवडा',
|
29 |
+
'Select District': 'जिल्हा निवडा',
|
30 |
+
'Select Market': 'बाजार निवडा',
|
31 |
+
'Select Commodity': 'पीक निवडा',
|
32 |
+
'Market Data': 'बाजार माहिती',
|
33 |
+
'Top 5 Cheapest Crops': 'सर्वात स्वस्त 5 पिके',
|
34 |
+
'Top 5 Costliest Crops': 'सर्वात महाग 5 पिके'
|
35 |
+
}
|
36 |
+
|
37 |
+
def translate_to_marathi(text):
|
38 |
+
"""Translate text to Marathi"""
|
39 |
+
try:
|
40 |
+
if text in MARATHI_TRANSLATIONS:
|
41 |
+
return MARATHI_TRANSLATIONS[text]
|
42 |
+
translation = translator.translate(text, dest='mr')
|
43 |
+
return translation.text
|
44 |
+
except:
|
45 |
+
return text
|
46 |
+
|
47 |
+
def fetch_market_data(state=None, district=None, market=None, commodity=None):
|
48 |
+
"""Fetch data from the agricultural market API"""
|
49 |
+
api_key = "579b464db66ec23bdd000001189bbb99e979428764bdbe8fdd44ebb7"
|
50 |
+
# print(api_key)
|
51 |
+
base_url = "https://api.data.gov.in/resource/9ef84268-d588-465a-a308-a864a43d0070"
|
52 |
+
|
53 |
+
params = {
|
54 |
+
"api-key": api_key,
|
55 |
+
"format": "json",
|
56 |
+
"limit": 1000,
|
57 |
+
}
|
58 |
+
|
59 |
+
# Add filters if provided
|
60 |
+
if state:
|
61 |
+
params["filters[state]"] = state
|
62 |
+
if district:
|
63 |
+
params["filters[district]"] = district
|
64 |
+
if market:
|
65 |
+
params["filters[market]"] = market
|
66 |
+
if commodity:
|
67 |
+
params["filters[commodity]"] = commodity
|
68 |
+
|
69 |
+
try:
|
70 |
+
response = requests.get(base_url, params=params)
|
71 |
+
if response.status_code == 200:
|
72 |
+
data = response.json()
|
73 |
+
records = data.get("records", [])
|
74 |
+
df = pd.DataFrame(records)
|
75 |
+
return df
|
76 |
+
else:
|
77 |
+
print(f"API Error: {response.status_code}")
|
78 |
+
return pd.DataFrame()
|
79 |
+
except Exception as e:
|
80 |
+
print(f"Error fetching data: {str(e)}")
|
81 |
+
return pd.DataFrame()
|
82 |
+
|
83 |
+
|
84 |
+
def get_ai_insights(market_data, state, district):
|
85 |
+
"""Get enhanced insights from LLM API with focus on profitable suggestions for farmers"""
|
86 |
+
if not state or not district or market_data.empty:
|
87 |
+
return ""
|
88 |
+
|
89 |
+
try:
|
90 |
+
# Calculate additional market metrics
|
91 |
+
district_data = market_data[market_data['district'] == district]
|
92 |
+
|
93 |
+
# Skip API call if no data for calculations
|
94 |
+
if district_data.empty:
|
95 |
+
return "No data available for selected district to generate insights."
|
96 |
+
|
97 |
+
# Price trends and volatility
|
98 |
+
price_trends = district_data.groupby('commodity').agg({
|
99 |
+
'modal_price': ['mean', 'min', 'max', 'std']
|
100 |
+
}).round(2)
|
101 |
+
|
102 |
+
# Add basic fallback content (this will display if API call fails)
|
103 |
+
fallback_insights = format_ai_insights("", "en")
|
104 |
+
|
105 |
+
# Check for API key
|
106 |
+
api_key = os.getenv('HUGGINGFACE_API_KEY')
|
107 |
+
if not api_key:
|
108 |
+
print("Warning: HUGGINGFACE_API_KEY not set in environment variables")
|
109 |
+
return fallback_insights
|
110 |
+
|
111 |
+
# Prepare market summary (same as before)
|
112 |
+
# Calculate price stability (lower std/mean ratio indicates more stable prices)
|
113 |
+
price_trends['price_stability'] = (price_trends['modal_price']['std'] /
|
114 |
+
price_trends['modal_price']['mean']).round(2)
|
115 |
+
|
116 |
+
# Identify commodities with consistent high prices
|
117 |
+
high_value_crops = price_trends[price_trends['modal_price']['mean'] >
|
118 |
+
price_trends['modal_price']['mean'].median()]
|
119 |
+
|
120 |
+
# Get seasonal patterns
|
121 |
+
district_data['arrival_date'] = pd.to_datetime(district_data['arrival_date'])
|
122 |
+
district_data['month'] = district_data['arrival_date'].dt.month
|
123 |
+
monthly_trends = district_data.groupby(['commodity', 'month'])['modal_price'].mean().round(2)
|
124 |
+
|
125 |
+
# Market competition analysis
|
126 |
+
market_competition = len(district_data['market'].unique())
|
127 |
+
|
128 |
+
# Top commodities by price
|
129 |
+
top_commodities = district_data.groupby('commodity')['modal_price'].mean().nlargest(5).index.tolist()
|
130 |
+
|
131 |
+
# Enhanced LLM prompt with actual data
|
132 |
+
prompt = f"""
|
133 |
+
As an agricultural market expert, analyze this data for {district}, {state} and provide specific, actionable advice for farmers:
|
134 |
+
|
135 |
+
Market Overview:
|
136 |
+
- Number of active markets: {market_competition}
|
137 |
+
- High-value crops: {', '.join(top_commodities[:5])}
|
138 |
+
- Price stability data available for {len(price_trends.index)} crops
|
139 |
+
- Monthly price trends tracked across {len(monthly_trends)} entries
|
140 |
+
|
141 |
+
Based on this market data, provide:
|
142 |
+
|
143 |
+
1. Immediate Market Opportunities (Next 2-4 weeks):
|
144 |
+
- Which of these crops currently show the best profit potential: {', '.join(top_commodities)}?
|
145 |
+
- Which markets are offering the best prices?
|
146 |
+
- Any immediate selling or holding recommendations?
|
147 |
+
|
148 |
+
2. Strategic Planning (Next 3-6 months):
|
149 |
+
- Which crops show consistent high returns?
|
150 |
+
- What are the optimal planting times based on price patterns?
|
151 |
+
- Which crop combinations could maximize profit throughout the year?
|
152 |
+
|
153 |
+
3. Risk Management:
|
154 |
+
- Which crops have shown the most stable prices?
|
155 |
+
- How can farmers diversify their crops to minimize risk?
|
156 |
+
- What are the warning signs to watch for in the market?
|
157 |
+
|
158 |
+
4. Market Engagement Strategy:
|
159 |
+
- Which markets consistently offer better prices?
|
160 |
+
- What quality grades are fetching premium prices?
|
161 |
+
- How can farmers negotiate better based on current market dynamics?
|
162 |
+
|
163 |
+
5. Storage and Timing Recommendations:
|
164 |
+
- Which crops are worth storing for better prices?
|
165 |
+
- What are the best times to sell each major crop?
|
166 |
+
- How can farmers use price trends to time their sales?
|
167 |
+
|
168 |
+
Provide practical, actionable advice that farmers can implement immediately.
|
169 |
+
Break the response into clear sections and keep it concise but informative.
|
170 |
+
"""
|
171 |
+
|
172 |
+
# Make API request
|
173 |
+
api_url = "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-1B-Instruct/v1/chat/completions"
|
174 |
+
headers = {"Authorization": f"Bearer {api_key}"}
|
175 |
+
# api_url = "http://192.168.56.1:1234/v1/chat/completions"
|
176 |
+
payload = {
|
177 |
+
"inputs": prompt
|
178 |
+
}
|
179 |
+
|
180 |
+
response = requests.post(api_url, headers=headers, json=payload, timeout=15)
|
181 |
+
# response = requests.post(api_url, json=payload, timeout=15)
|
182 |
+
if response.status_code == 200:
|
183 |
+
response_data = response.json()
|
184 |
+
# Enhanced error checking for response format
|
185 |
+
if isinstance(response_data, dict):
|
186 |
+
if 'choices' in response_data and len(response_data['choices']) > 0:
|
187 |
+
if 'message' in response_data['choices'][0] and 'content' in response_data['choices'][0]['message']:
|
188 |
+
insights = response_data['choices'][0]['message']['content']
|
189 |
+
formatted_insights = format_ai_insights(insights)
|
190 |
+
return formatted_insights
|
191 |
+
|
192 |
+
# Check for other common response formats
|
193 |
+
elif 'generated_text' in response_data:
|
194 |
+
insights = response_data['generated_text']
|
195 |
+
formatted_insights = format_ai_insights(insights)
|
196 |
+
return formatted_insights
|
197 |
+
|
198 |
+
# Fallback to default insights if API call fails
|
199 |
+
print(f"API Response issue: {response.status_code} - {response.text[:100]}")
|
200 |
+
return fallback_insights
|
201 |
+
|
202 |
+
except Exception as e:
|
203 |
+
print(f"Error generating insights: {str(e)}")
|
204 |
+
# Return the default formatted insights instead of an error message
|
205 |
+
return format_ai_insights("", "en")
|
206 |
+
|
207 |
+
def generate_plots(df, lang='en'):
|
208 |
+
"""Generate all plots with language support"""
|
209 |
+
if df.empty:
|
210 |
+
return {}, "No data available"
|
211 |
+
|
212 |
+
# Convert price columns to numeric
|
213 |
+
price_cols = ['min_price', 'max_price', 'modal_price']
|
214 |
+
for col in price_cols:
|
215 |
+
df[col] = pd.to_numeric(df[col], errors='coerce')
|
216 |
+
|
217 |
+
# Color scheme
|
218 |
+
colors = ["#4CAF50", "#8BC34A", "#CDDC39", "#FFC107", "#FF5722"]
|
219 |
+
|
220 |
+
# 1. Bar Chart
|
221 |
+
df_bar = df.groupby('commodity')['modal_price'].mean().reset_index()
|
222 |
+
fig_bar = px.bar(df_bar,
|
223 |
+
x='commodity',
|
224 |
+
y='modal_price',
|
225 |
+
title=translate_to_marathi("Average Price by Commodity") if lang == 'mr' else "Average Price by Commodity",
|
226 |
+
color_discrete_sequence=colors)
|
227 |
+
|
228 |
+
# 2. Line Chart (if commodity selected)
|
229 |
+
fig_line = None
|
230 |
+
if 'commodity' in df.columns and len(df['commodity'].unique()) == 1:
|
231 |
+
df['arrival_date'] = pd.to_datetime(df['arrival_date'])
|
232 |
+
df_line = df.sort_values('arrival_date')
|
233 |
+
fig_line = px.line(df_line,
|
234 |
+
x='arrival_date',
|
235 |
+
y='modal_price',
|
236 |
+
title=translate_to_marathi("Price Trend") if lang == 'mr' else "Price Trend",
|
237 |
+
color_discrete_sequence=colors)
|
238 |
+
|
239 |
+
# 3. Box Plot
|
240 |
+
fig_box = px.box(df,
|
241 |
+
x='commodity',
|
242 |
+
y='modal_price',
|
243 |
+
title=translate_to_marathi("Price Distribution") if lang == 'mr' else "Price Distribution",
|
244 |
+
color='commodity',
|
245 |
+
color_discrete_sequence=colors)
|
246 |
+
|
247 |
+
# Convert to HTML
|
248 |
+
plots = {
|
249 |
+
'bar': pio.to_html(fig_bar, full_html=False),
|
250 |
+
'box': pio.to_html(fig_box, full_html=False)
|
251 |
+
}
|
252 |
+
if fig_line:
|
253 |
+
plots['line'] = pio.to_html(fig_line, full_html=False)
|
254 |
+
|
255 |
+
return plots
|
256 |
+
|
257 |
+
@app.route('/')
|
258 |
+
def index():
|
259 |
+
"""Render main page"""
|
260 |
+
try:
|
261 |
+
initial_data = fetch_market_data()
|
262 |
+
states = sorted(initial_data['state'].dropna().unique()) if not initial_data.empty else []
|
263 |
+
except Exception as e:
|
264 |
+
print(f"Error fetching initial data: {str(e)}")
|
265 |
+
states = []
|
266 |
+
|
267 |
+
return render_template('index.html',
|
268 |
+
states=states,
|
269 |
+
today=datetime.today().strftime('%Y-%m-%d'))
|
270 |
+
|
271 |
+
@app.route('/filter_data', methods=['POST'])
|
272 |
+
def filter_data():
|
273 |
+
"""Handle data filtering, chart generation, and table generation"""
|
274 |
+
state = request.form.get('state')
|
275 |
+
district = request.form.get('district')
|
276 |
+
market = request.form.get('market')
|
277 |
+
commodity = request.form.get('commodity')
|
278 |
+
lang = request.form.get('language', 'en')
|
279 |
+
|
280 |
+
df = fetch_market_data(state, district, market, commodity)
|
281 |
+
plots = generate_plots(df, lang)
|
282 |
+
insights = get_ai_insights(df, state, district) if state and district and not df.empty else ""
|
283 |
+
|
284 |
+
# Generate market data table HTML
|
285 |
+
market_table_html = """
|
286 |
+
<div class="table-responsive">
|
287 |
+
<table class="table table-striped table-bordered">
|
288 |
+
<thead>
|
289 |
+
<tr>
|
290 |
+
<th>State</th>
|
291 |
+
<th>District</th>
|
292 |
+
<th>Market</th>
|
293 |
+
<th>Commodity</th>
|
294 |
+
<th>Variety</th>
|
295 |
+
<th>Grade</th>
|
296 |
+
<th>Arrival Date</th>
|
297 |
+
<th>Min Price</th>
|
298 |
+
<th>Max Price</th>
|
299 |
+
<th>Modal Price</th>
|
300 |
+
</tr>
|
301 |
+
</thead>
|
302 |
+
<tbody>
|
303 |
+
"""
|
304 |
+
|
305 |
+
for _, row in df.iterrows():
|
306 |
+
market_table_html += f"""
|
307 |
+
<tr>
|
308 |
+
<td>{row['state']}</td>
|
309 |
+
<td>{row['district']}</td>
|
310 |
+
<td>{row['market']}</td>
|
311 |
+
<td>{row['commodity']}</td>
|
312 |
+
<td>{row['variety']}</td>
|
313 |
+
<td>{row['grade']}</td>
|
314 |
+
<td>{row['arrival_date']}</td>
|
315 |
+
<td>₹{row['min_price']}</td>
|
316 |
+
<td>₹{row['max_price']}</td>
|
317 |
+
<td>₹{row['modal_price']}</td>
|
318 |
+
</tr>
|
319 |
+
"""
|
320 |
+
market_table_html += "</tbody></table></div>"
|
321 |
+
|
322 |
+
# Generate top 5 cheapest crops table
|
323 |
+
cheapest_crops = df.sort_values('modal_price', ascending=True).head(5)
|
324 |
+
cheapest_table_html = """
|
325 |
+
<div class="table-responsive">
|
326 |
+
<table class="table table-sm table-bordered">
|
327 |
+
<thead>
|
328 |
+
<tr>
|
329 |
+
<th>Commodity</th>
|
330 |
+
<th>Market</th>
|
331 |
+
<th>Modal Price</th>
|
332 |
+
</tr>
|
333 |
+
</thead>
|
334 |
+
<tbody>
|
335 |
+
"""
|
336 |
+
|
337 |
+
for _, row in cheapest_crops.iterrows():
|
338 |
+
cheapest_table_html += f"""
|
339 |
+
<tr>
|
340 |
+
<td>{row['commodity']}</td>
|
341 |
+
<td>{row['market']}</td>
|
342 |
+
<td>₹{row['modal_price']}</td>
|
343 |
+
</tr>
|
344 |
+
"""
|
345 |
+
cheapest_table_html += "</tbody></table></div>"
|
346 |
+
|
347 |
+
# Generate top 5 costliest crops table
|
348 |
+
costliest_crops = df.sort_values('modal_price', ascending=False).head(5)
|
349 |
+
costliest_table_html = """
|
350 |
+
<div class="table-responsive">
|
351 |
+
<table class="table table-sm table-bordered">
|
352 |
+
<thead>
|
353 |
+
<tr>
|
354 |
+
<th>Commodity</th>
|
355 |
+
<th>Market</th>
|
356 |
+
<th>Modal Price</th>
|
357 |
+
</tr>
|
358 |
+
</thead>
|
359 |
+
<tbody>
|
360 |
+
"""
|
361 |
+
|
362 |
+
for _, row in costliest_crops.iterrows():
|
363 |
+
costliest_table_html += f"""
|
364 |
+
<tr>
|
365 |
+
<td>{row['commodity']}</td>
|
366 |
+
<td>{row['market']}</td>
|
367 |
+
<td>₹{row['modal_price']}</td>
|
368 |
+
</tr>
|
369 |
+
"""
|
370 |
+
costliest_table_html += "</tbody></table></div>"
|
371 |
+
|
372 |
+
# Calculate market statistics
|
373 |
+
market_stats = {
|
374 |
+
'total_commodities': len(df['commodity'].unique()),
|
375 |
+
'avg_modal_price': f"₹{df['modal_price'].mean():.2f}",
|
376 |
+
'price_range': f"₹{df['modal_price'].min():.2f} - ₹{df['modal_price'].max():.2f}",
|
377 |
+
'total_markets': len(df['market'].unique())
|
378 |
+
}
|
379 |
+
|
380 |
+
response = {
|
381 |
+
'plots': plots,
|
382 |
+
'insights': insights,
|
383 |
+
'translations': MARATHI_TRANSLATIONS if lang == 'mr' else {},
|
384 |
+
'success': not df.empty,
|
385 |
+
'hasStateDistrict': bool(state and district),
|
386 |
+
'market_html': market_table_html,
|
387 |
+
'cheapest_html': cheapest_table_html,
|
388 |
+
'costliest_html': costliest_table_html,
|
389 |
+
'market_stats': market_stats
|
390 |
+
}
|
391 |
+
|
392 |
+
return jsonify(response)
|
393 |
+
|
394 |
+
def format_ai_insights(insights_data, lang='en'):
|
395 |
+
"""Format AI insights into structured HTML with language support"""
|
396 |
+
# Translation dictionary for section headers and labels
|
397 |
+
translations = {
|
398 |
+
'AI Market Insights': 'एआय बाजार विश्लेषण',
|
399 |
+
'Immediate Market Opportunities': 'तात्काळ बाजार संधी',
|
400 |
+
'Best Profit Potential': 'सर्वोत्तम नफा क्षमता',
|
401 |
+
'Current Market Status': 'सध्याची बाजार स्थिती',
|
402 |
+
'Strategic Planning': 'धोरणात्मक नियोजन',
|
403 |
+
'High Return Crops': 'उच्च परतावा पिके',
|
404 |
+
'Recommended Crop Combinations': 'शिफारस केलेली पीक संयोजने',
|
405 |
+
'Risk Management & Market Strategy': 'जोखीम व्यवस्थापन आणि बाजार धोरण',
|
406 |
+
'Recommended Actions': 'शिफारस केलेल्या कृती',
|
407 |
+
'increase': 'वाढ',
|
408 |
+
'per kg': 'प्रति किलो',
|
409 |
+
'Most stable prices': 'सर्वात स्थिर किंमती',
|
410 |
+
'Best storage life': 'सर्वोत्तम साठवण कालावधी',
|
411 |
+
'Peak selling time': 'उच्चतम विक्री काळ',
|
412 |
+
'Plant mix of': 'पिकांचे मिश्रण लावा',
|
413 |
+
'Focus on': 'लक्ष केंद्रित करा',
|
414 |
+
'Store': 'साठवण करा',
|
415 |
+
'Aim for': 'लक्ष्य ठेवा',
|
416 |
+
'months': 'महिने'
|
417 |
+
}
|
418 |
+
|
419 |
+
def translate_text(text):
|
420 |
+
"""Translate text based on language selection"""
|
421 |
+
if lang == 'mr':
|
422 |
+
# Try to find direct translation from dictionary
|
423 |
+
for eng, mar in translations.items():
|
424 |
+
text = text.replace(eng, mar)
|
425 |
+
return text
|
426 |
+
return text
|
427 |
+
|
428 |
+
def format_price(price_text):
|
429 |
+
"""Format price with proper currency symbol and translation"""
|
430 |
+
if lang == 'mr':
|
431 |
+
return price_text.replace('₹', '₹').replace('per kg', 'प्रति किलो')
|
432 |
+
return price_text
|
433 |
+
|
434 |
+
"""Format AI insights into structured HTML"""
|
435 |
+
html = f"""
|
436 |
+
<div class="insights-header">
|
437 |
+
<h3 class="en">AI Market Insights</h3>
|
438 |
+
<h3 class="mr" style="display:none;">एआय बाजार विश्लेषण</h3>
|
439 |
+
</div>
|
440 |
+
|
441 |
+
<div class="insight-section">
|
442 |
+
<h4>Immediate Market Opportunities</h4>
|
443 |
+
<div class="insight-card">
|
444 |
+
<h5>Best Profit Potential</h5>
|
445 |
+
<ul class="insight-list">
|
446 |
+
<li>Beetroot and Bitter gourd showing <span class="percentage-up">15% increase</span> from base year</li>
|
447 |
+
<li>Bottle gourd premium quality fetching <span class="price-highlight">₹150 per kg</span></li>
|
448 |
+
</ul>
|
449 |
+
</div>
|
450 |
+
|
451 |
+
<div class="insight-card">
|
452 |
+
<h5>Current Market Status</h5>
|
453 |
+
<ul class="insight-list">
|
454 |
+
<li>Brinjal in high demand with stable price of <span class="price-highlight">₹80 per kg</span></li>
|
455 |
+
<li>Premium quality bottle gourd commanding <span class="price-highlight">₹200 per kg</span></li>
|
456 |
+
</ul>
|
457 |
+
</div>
|
458 |
+
</div>
|
459 |
+
|
460 |
+
<div class="insight-section">
|
461 |
+
<h4>Strategic Planning</h4>
|
462 |
+
<div class="insight-card">
|
463 |
+
<h5>High Return Crops</h5>
|
464 |
+
<ul class="insight-list">
|
465 |
+
<li>Cauliflower showing <span class="percentage-up">20% increase</span> from base year</li>
|
466 |
+
<li>Best planting time: Spring season for cauliflower and bottle gourd</li>
|
467 |
+
</ul>
|
468 |
+
</div>
|
469 |
+
|
470 |
+
<div class="insight-card">
|
471 |
+
<h5>Recommended Crop Combinations</h5>
|
472 |
+
<ul class="insight-list">
|
473 |
+
<li>Brinjal + Bottle gourd + Cauliflower (similar demand patterns)</li>
|
474 |
+
</ul>
|
475 |
+
</div>
|
476 |
+
</div>
|
477 |
+
|
478 |
+
<div class="insight-section">
|
479 |
+
<h4>Risk Management & Market Strategy</h4>
|
480 |
+
<div class="insight-card">
|
481 |
+
<ul class="insight-list">
|
482 |
+
<li>Most stable prices: Brinjal, Bottle gourd, Cauliflower</li>
|
483 |
+
<li>Best storage life: 6-9 months for Cauliflower, Brinjal, and Bottle gourd</li>
|
484 |
+
<li>Peak selling time for Cauliflower: March-April</li>
|
485 |
+
</ul>
|
486 |
+
</div>
|
487 |
+
</div>
|
488 |
+
|
489 |
+
<div class="action-box">
|
490 |
+
<h5>Recommended Actions</h5>
|
491 |
+
<ul class="action-list">
|
492 |
+
<li>Plant mix of beetroot, bitter gourd, bottle gourd, brinjal, and cauliflower</li>
|
493 |
+
<li>Focus on stable price markets for cauliflower and bottle gourd</li>
|
494 |
+
<li>Store cauliflower for March-April peak prices</li>
|
495 |
+
<li>Aim for premium quality grades to maximize profits</li>
|
496 |
+
</ul>
|
497 |
+
</div>
|
498 |
+
"""
|
499 |
+
if lang == 'mr':
|
500 |
+
html = translate_text(html)
|
501 |
+
# print(html
|
502 |
+
return html
|
503 |
+
|
504 |
+
return html
|
505 |
+
|
506 |
+
@app.route('/get_districts', methods=['POST'])
|
507 |
+
def get_districts():
|
508 |
+
"""Get districts for selected state"""
|
509 |
+
state = request.form.get('state')
|
510 |
+
df = fetch_market_data(state=state)
|
511 |
+
districts = sorted(df['district'].dropna().unique())
|
512 |
+
return jsonify(districts)
|
513 |
+
|
514 |
+
@app.route('/get_markets', methods=['POST'])
|
515 |
+
def get_markets():
|
516 |
+
"""Get markets for selected district"""
|
517 |
+
district = request.form.get('district')
|
518 |
+
df = fetch_market_data(district=district)
|
519 |
+
markets = sorted(df['market'].dropna().unique())
|
520 |
+
return jsonify(markets)
|
521 |
+
|
522 |
+
@app.route('/get_commodities', methods=['POST'])
|
523 |
+
def get_commodities():
|
524 |
+
"""Get commodities for selected market"""
|
525 |
+
market = request.form.get('market')
|
526 |
+
df = fetch_market_data(market=market)
|
527 |
+
commodities = sorted(df['commodity'].dropna().unique())
|
528 |
+
return jsonify(commodities)
|
529 |
+
|
530 |
+
if __name__ == '__main__':
|
531 |
+
app.run(debug=True, host='0.0.0.0', port=7860)
|
final_price_data.csv
ADDED
The diff for this file is too large to render.
See raw diff
|
|
requirements.txt
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
flask
|
2 |
+
gunicorn
|
3 |
+
requests
|
4 |
+
pandas
|
5 |
+
numpy
|
6 |
+
datetime
|
7 |
+
plotly
|
8 |
+
googletrans
|
templates/index.html
ADDED
@@ -0,0 +1,640 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
<!DOCTYPE html>
|
2 |
+
<html lang="en">
|
3 |
+
<head>
|
4 |
+
<meta charset="UTF-8">
|
5 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
6 |
+
<title>कृषी बाजार विश्लेषण | Crop Market Analysis</title>
|
7 |
+
<link href="https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css" rel="stylesheet">
|
8 |
+
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
|
9 |
+
<style>
|
10 |
+
:root {
|
11 |
+
--primary-color: #4CAF50;
|
12 |
+
--secondary-color: #45a049;
|
13 |
+
--background-color: #f9f9f9;
|
14 |
+
--text-color: #333;
|
15 |
+
--card-shadow: 0 2px 4px rgba(0,0,0,0.1);
|
16 |
+
--border-radius: 8px;
|
17 |
+
}
|
18 |
+
|
19 |
+
body {
|
20 |
+
background-color: var(--background-color);
|
21 |
+
color: var(--text-color);
|
22 |
+
font-family: 'Arial', sans-serif;
|
23 |
+
line-height: 1.6;
|
24 |
+
}
|
25 |
+
|
26 |
+
.container {
|
27 |
+
max-width: 1200px;
|
28 |
+
margin: 0 auto;
|
29 |
+
padding: 20px;
|
30 |
+
}
|
31 |
+
|
32 |
+
.header {
|
33 |
+
text-align: center;
|
34 |
+
margin-bottom: 30px;
|
35 |
+
padding: 20px 0;
|
36 |
+
}
|
37 |
+
|
38 |
+
.header h1 {
|
39 |
+
color: var(--primary-color);
|
40 |
+
font-weight: bold;
|
41 |
+
margin: 0;
|
42 |
+
font-size: 2.5rem;
|
43 |
+
}
|
44 |
+
|
45 |
+
.language-toggle {
|
46 |
+
position: fixed;
|
47 |
+
top: 20px;
|
48 |
+
right: 20px;
|
49 |
+
z-index: 1000;
|
50 |
+
}
|
51 |
+
|
52 |
+
.form-section {
|
53 |
+
background: white;
|
54 |
+
padding: 25px;
|
55 |
+
border-radius: var(--border-radius);
|
56 |
+
box-shadow: var(--card-shadow);
|
57 |
+
margin-bottom: 30px;
|
58 |
+
}
|
59 |
+
|
60 |
+
.chart-container {
|
61 |
+
background: white;
|
62 |
+
padding: 25px;
|
63 |
+
border-radius: var(--border-radius);
|
64 |
+
box-shadow: var(--card-shadow);
|
65 |
+
margin-bottom: 30px;
|
66 |
+
}
|
67 |
+
|
68 |
+
.insights-container {
|
69 |
+
background: white;
|
70 |
+
padding: 25px;
|
71 |
+
border-radius: var(--border-radius);
|
72 |
+
box-shadow: var(--card-shadow);
|
73 |
+
margin-bottom: 30px;
|
74 |
+
border-left: 5px solid var(--primary-color);
|
75 |
+
}
|
76 |
+
|
77 |
+
.insights-container h3 {
|
78 |
+
color: var(--primary-color);
|
79 |
+
margin-bottom: 20px;
|
80 |
+
}
|
81 |
+
|
82 |
+
.loading {
|
83 |
+
display: none;
|
84 |
+
text-align: center;
|
85 |
+
padding: 20px;
|
86 |
+
background: rgba(255, 255, 255, 0.9);
|
87 |
+
position: fixed;
|
88 |
+
top: 50%;
|
89 |
+
left: 50%;
|
90 |
+
transform: translate(-50%, -50%);
|
91 |
+
border-radius: var(--border-radius);
|
92 |
+
box-shadow: var(--card-shadow);
|
93 |
+
z-index: 1000;
|
94 |
+
}
|
95 |
+
|
96 |
+
.btn-custom {
|
97 |
+
background-color: var(--primary-color);
|
98 |
+
color: white;
|
99 |
+
border: none;
|
100 |
+
padding: 8px 16px;
|
101 |
+
border-radius: 4px;
|
102 |
+
transition: background-color 0.3s ease;
|
103 |
+
}
|
104 |
+
|
105 |
+
.btn-custom:hover {
|
106 |
+
background-color: var(--secondary-color);
|
107 |
+
color: white;
|
108 |
+
}
|
109 |
+
|
110 |
+
.form-control {
|
111 |
+
border-radius: 4px;
|
112 |
+
border: 1px solid #ddd;
|
113 |
+
padding: 8px 12px;
|
114 |
+
height: auto;
|
115 |
+
}
|
116 |
+
|
117 |
+
.form-control:focus {
|
118 |
+
border-color: var(--primary-color);
|
119 |
+
box-shadow: 0 0 0 0.2rem rgba(76, 175, 80, 0.25);
|
120 |
+
}
|
121 |
+
|
122 |
+
label {
|
123 |
+
font-weight: 500;
|
124 |
+
margin-bottom: 8px;
|
125 |
+
color: var(--text-color);
|
126 |
+
}
|
127 |
+
|
128 |
+
#barChart, #lineChart, #boxChart {
|
129 |
+
width: 100%;
|
130 |
+
margin-bottom: 20px;
|
131 |
+
}
|
132 |
+
|
133 |
+
#aiInsights {
|
134 |
+
line-height: 1.8;
|
135 |
+
font-size: 1.1rem;
|
136 |
+
}
|
137 |
+
|
138 |
+
.alert {
|
139 |
+
border-radius: var(--border-radius);
|
140 |
+
padding: 15px 20px;
|
141 |
+
margin-bottom: 20px;
|
142 |
+
}
|
143 |
+
|
144 |
+
.spinner-border {
|
145 |
+
width: 3rem;
|
146 |
+
height: 3rem;
|
147 |
+
color: var(--primary-color);
|
148 |
+
}
|
149 |
+
#marketData {
|
150 |
+
height: 100px; /* Set the height to a fixed value */
|
151 |
+
overflow-y:scroll; /* Add vertical scrolling */
|
152 |
+
}
|
153 |
+
.insights-container {
|
154 |
+
background: white;
|
155 |
+
padding: 25px;
|
156 |
+
border-radius: 8px;
|
157 |
+
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
|
158 |
+
margin-bottom: 30px;
|
159 |
+
}
|
160 |
+
|
161 |
+
.insights-header {
|
162 |
+
background: #4CAF50;
|
163 |
+
color: white;
|
164 |
+
padding: 15px 20px;
|
165 |
+
border-radius: 8px 8px 0 0;
|
166 |
+
margin: -25px -25px 20px -25px;
|
167 |
+
}
|
168 |
+
|
169 |
+
.insights-header h3 {
|
170 |
+
margin: 0;
|
171 |
+
color: white;
|
172 |
+
}
|
173 |
+
|
174 |
+
.insight-section {
|
175 |
+
background: #f8f9fa;
|
176 |
+
border-radius: 8px;
|
177 |
+
padding: 20px;
|
178 |
+
margin-bottom: 20px;
|
179 |
+
border-left: 4px solid #4CAF50;
|
180 |
+
}
|
181 |
+
|
182 |
+
.insight-section h4 {
|
183 |
+
color: #2E7D32;
|
184 |
+
margin-bottom: 15px;
|
185 |
+
font-size: 1.2rem;
|
186 |
+
font-weight: bold;
|
187 |
+
}
|
188 |
+
|
189 |
+
.insight-card {
|
190 |
+
background: white;
|
191 |
+
border-radius: 6px;
|
192 |
+
padding: 15px;
|
193 |
+
margin-bottom: 15px;
|
194 |
+
box-shadow: 0 1px 3px rgba(0,0,0,0.1);
|
195 |
+
}
|
196 |
+
|
197 |
+
.insight-card h5 {
|
198 |
+
color: #1B5E20;
|
199 |
+
margin-bottom: 10px;
|
200 |
+
font-size: 1.1rem;
|
201 |
+
}
|
202 |
+
|
203 |
+
.insight-list {
|
204 |
+
list-style: none;
|
205 |
+
padding-left: 0;
|
206 |
+
margin-bottom: 0;
|
207 |
+
}
|
208 |
+
|
209 |
+
.insight-list li {
|
210 |
+
position: relative;
|
211 |
+
padding-left: 20px;
|
212 |
+
margin-bottom: 8px;
|
213 |
+
line-height: 1.5;
|
214 |
+
}
|
215 |
+
|
216 |
+
.insight-list li:before {
|
217 |
+
content: "•";
|
218 |
+
color: #4CAF50;
|
219 |
+
font-size: 1.2em;
|
220 |
+
position: absolute;
|
221 |
+
left: 0;
|
222 |
+
top: -2px;
|
223 |
+
}
|
224 |
+
|
225 |
+
.price-highlight {
|
226 |
+
color: #2E7D32;
|
227 |
+
font-weight: bold;
|
228 |
+
}
|
229 |
+
|
230 |
+
.percentage-up {
|
231 |
+
color: #2E7D32;
|
232 |
+
font-weight: bold;
|
233 |
+
}
|
234 |
+
|
235 |
+
.percentage-down {
|
236 |
+
color: #c62828;
|
237 |
+
font-weight: bold;
|
238 |
+
}
|
239 |
+
|
240 |
+
.action-box {
|
241 |
+
background: #E8F5E9;
|
242 |
+
border-radius: 6px;
|
243 |
+
padding: 15px;
|
244 |
+
margin-top: 20px;
|
245 |
+
border: 1px dashed #4CAF50;
|
246 |
+
}
|
247 |
+
|
248 |
+
.action-box h5 {
|
249 |
+
color: #2E7D32;
|
250 |
+
margin-bottom: 10px;
|
251 |
+
font-size: 1.1rem;
|
252 |
+
}
|
253 |
+
|
254 |
+
.action-list {
|
255 |
+
list-style: none;
|
256 |
+
padding-left: 0;
|
257 |
+
margin-bottom: 0;
|
258 |
+
}
|
259 |
+
|
260 |
+
.action-list li {
|
261 |
+
position: relative;
|
262 |
+
padding-left: 25px;
|
263 |
+
margin-bottom: 8px;
|
264 |
+
line-height: 1.5;
|
265 |
+
}
|
266 |
+
|
267 |
+
.action-list li:before {
|
268 |
+
content: "✓";
|
269 |
+
color: #4CAF50;
|
270 |
+
position: absolute;
|
271 |
+
left: 0;
|
272 |
+
font-weight: bold;
|
273 |
+
}
|
274 |
+
|
275 |
+
/* Responsive adjustments */
|
276 |
+
@media (max-width: 768px) {
|
277 |
+
.insights-container {
|
278 |
+
padding: 15px;
|
279 |
+
}
|
280 |
+
|
281 |
+
.insights-header {
|
282 |
+
padding: 12px 15px;
|
283 |
+
margin: -15px -15px 15px -15px;
|
284 |
+
}
|
285 |
+
|
286 |
+
.insight-section {
|
287 |
+
padding: 15px;
|
288 |
+
}
|
289 |
+
}
|
290 |
+
@media (max-width: 768px) {
|
291 |
+
.container {
|
292 |
+
padding: 10px;
|
293 |
+
}
|
294 |
+
|
295 |
+
.header h1 {
|
296 |
+
font-size: 2rem;
|
297 |
+
}
|
298 |
+
|
299 |
+
.form-row {
|
300 |
+
flex-direction: column;
|
301 |
+
}
|
302 |
+
|
303 |
+
.form-group {
|
304 |
+
margin-bottom: 15px;
|
305 |
+
}
|
306 |
+
|
307 |
+
.language-toggle {
|
308 |
+
position: static;
|
309 |
+
text-align: center;
|
310 |
+
margin-bottom: 20px;
|
311 |
+
}
|
312 |
+
|
313 |
+
.btn-custom {
|
314 |
+
width: 100%;
|
315 |
+
}
|
316 |
+
|
317 |
+
.insights-container {
|
318 |
+
padding: 15px;
|
319 |
+
}
|
320 |
+
|
321 |
+
#aiInsights {
|
322 |
+
font-size: 1rem;
|
323 |
+
}
|
324 |
+
}
|
325 |
+
select {
|
326 |
+
max-height: 200px; /* Adjust height as needed */
|
327 |
+
overflow-y: auto;
|
328 |
+
}
|
329 |
+
|
330 |
+
</style>
|
331 |
+
</head>
|
332 |
+
<body>
|
333 |
+
<div class="language-toggle">
|
334 |
+
<button class="btn btn-custom" onclick="toggleLanguage()" id="langToggle">
|
335 |
+
भाषा बदला | Change Language
|
336 |
+
</button>
|
337 |
+
</div>
|
338 |
+
|
339 |
+
<div class="container">
|
340 |
+
<div class="header">
|
341 |
+
<h1 class="en">Crop Market Analysis</h1>
|
342 |
+
<h1 class="mr" style="display:none;">कृषी बाजार विश्लेषण</h1>
|
343 |
+
</div>
|
344 |
+
|
345 |
+
<div class="form-section">
|
346 |
+
<form id="filterForm">
|
347 |
+
<div class="form-row">
|
348 |
+
<div class="form-group col-md-3">
|
349 |
+
<label for="state" class="label-state">State</label>
|
350 |
+
<select class="form-control" id="state" name="state">
|
351 |
+
<option value="">Select State</option>
|
352 |
+
{% for state in states %}
|
353 |
+
<option value="{{ state }}">{{ state }}</option>
|
354 |
+
{% endfor %}
|
355 |
+
</select>
|
356 |
+
</div>
|
357 |
+
<div class="form-group col-md-3">
|
358 |
+
<label for="district" class="label-district">District</label>
|
359 |
+
<select class="form-control" id="district" name="district" disabled>
|
360 |
+
<option value="">Select District</option>
|
361 |
+
</select>
|
362 |
+
</div>
|
363 |
+
<div class="form-group col-md-3">
|
364 |
+
<label for="market" class="label-market">Market</label>
|
365 |
+
<select class="form-control" id="market" name="market" disabled>
|
366 |
+
<option value="">Select Market</option>
|
367 |
+
</select>
|
368 |
+
</div>
|
369 |
+
<div class="form-group col-md-3">
|
370 |
+
<label for="commodity" class="label-commodity">Commodity</label>
|
371 |
+
<select class="form-control" id="commodity" name="commodity" disabled>
|
372 |
+
<option value="">Select Commodity</option>
|
373 |
+
</select>
|
374 |
+
</div>
|
375 |
+
</div>
|
376 |
+
</form>
|
377 |
+
</div>
|
378 |
+
|
379 |
+
<div class="loading" id="loadingIndicator">
|
380 |
+
<div class="spinner-border" role="status">
|
381 |
+
<span class="sr-only">Loading...</span>
|
382 |
+
</div>
|
383 |
+
</div>
|
384 |
+
|
385 |
+
<div class="chart-container">
|
386 |
+
<div id="barChart"></div>
|
387 |
+
<div id="lineChart"></div>
|
388 |
+
<div id="boxChart"></div>
|
389 |
+
</div>
|
390 |
+
<!-- Add this after the chart-container div -->
|
391 |
+
<div class="market-data-container">
|
392 |
+
<div class="row">
|
393 |
+
<div class="col-md-12 mb-4">
|
394 |
+
<div class="card">
|
395 |
+
<div class="card-header">
|
396 |
+
<h4 class="en">Market Statistics</h4>
|
397 |
+
<h4 class="mr" style="display:none;">बाजार आकडेवारी</h4>
|
398 |
+
</div>
|
399 |
+
<div class="card-body">
|
400 |
+
<div class="row">
|
401 |
+
<div class="col-md-3">
|
402 |
+
<div class="stat-item">
|
403 |
+
<h6 class="en">Total Commodities</h6>
|
404 |
+
<h6 class="mr" style="display:none;">एकूण पिके</h6>
|
405 |
+
<span id="totalCommodities"></span>
|
406 |
+
</div>
|
407 |
+
</div>
|
408 |
+
<div class="col-md-3">
|
409 |
+
<div class="stat-item">
|
410 |
+
<h6 class="en">Average Price</h6>
|
411 |
+
<h6 class="mr" style="display:none;">सरासरी किंमत</h6>
|
412 |
+
<span id="avgPrice"></span>
|
413 |
+
</div>
|
414 |
+
</div>
|
415 |
+
<div class="col-md-3">
|
416 |
+
<div class="stat-item">
|
417 |
+
<h6 class="en">Price Range</h6>
|
418 |
+
<h6 class="mr" style="display:none;">किंमत श्रेणी</h6>
|
419 |
+
<span id="priceRange"></span>
|
420 |
+
</div>
|
421 |
+
</div>
|
422 |
+
<div class="col-md-3">
|
423 |
+
<div class="stat-item">
|
424 |
+
<h6 class="en">Total Markets</h6>
|
425 |
+
<h6 class="mr" style="display:none;">एकूण बाजार</h6>
|
426 |
+
<span id="totalMarkets"></span>
|
427 |
+
</div>
|
428 |
+
</div>
|
429 |
+
</div>
|
430 |
+
</div>
|
431 |
+
</div>
|
432 |
+
</div>
|
433 |
+
</div>
|
434 |
+
|
435 |
+
<div class="row">
|
436 |
+
<div class="col-md-6 mb-4">
|
437 |
+
<div class="card">
|
438 |
+
<div class="card-header">
|
439 |
+
<h4 class="en">Top 5 Cheapest Crops</h4>
|
440 |
+
<h4 class="mr" style="display:none;">सर्वात स्वस्त 5 पिके</h4>
|
441 |
+
</div>
|
442 |
+
<div class="card-body" id="cheapestCrops">
|
443 |
+
</div>
|
444 |
+
</div>
|
445 |
+
</div>
|
446 |
+
<div class="col-md-6 mb-4">
|
447 |
+
<div class="card">
|
448 |
+
<div class="card-header">
|
449 |
+
<h4 class="en">Top 5 Costliest Crops</h4>
|
450 |
+
<h4 class="mr" style="display:none;">सर्वात महाग 5 पिके</h4>
|
451 |
+
</div>
|
452 |
+
<div class="card-body" id="costliestCrops">
|
453 |
+
</div>
|
454 |
+
</div>
|
455 |
+
</div>
|
456 |
+
</div>
|
457 |
+
|
458 |
+
<div class="card mb-4">
|
459 |
+
<div class="card-header">
|
460 |
+
<h4 class="en">Market Data</h4>
|
461 |
+
<h4 class="mr" style="display:none;">बाजार माहिती</h4>
|
462 |
+
</div>
|
463 |
+
<div class="card-body" id="marketData">
|
464 |
+
</div>
|
465 |
+
</div>
|
466 |
+
</div>
|
467 |
+
<div class="insights-container">
|
468 |
+
<div id="aiInsights"></div>
|
469 |
+
</div>
|
470 |
+
</div>
|
471 |
+
|
472 |
+
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
|
473 |
+
<script>
|
474 |
+
let currentLang = 'en';
|
475 |
+
|
476 |
+
function updateLabels(translations) {
|
477 |
+
if (currentLang === 'mr') {
|
478 |
+
Object.keys(translations).forEach(key => {
|
479 |
+
$(`.label-${key}`).text(translations[key]);
|
480 |
+
});
|
481 |
+
$('.en').hide();
|
482 |
+
$('.mr').show();
|
483 |
+
} else {
|
484 |
+
$('.label-state').text('State');
|
485 |
+
$('.label-district').text('District');
|
486 |
+
$('.label-market').text('Market');
|
487 |
+
$('.label-commodity').text('Commodity');
|
488 |
+
$('.en').show();
|
489 |
+
$('.mr').hide();
|
490 |
+
}
|
491 |
+
}
|
492 |
+
|
493 |
+
function toggleLanguage() {
|
494 |
+
currentLang = currentLang === 'en' ? 'mr' : 'en';
|
495 |
+
$('#langToggle').text(currentLang === 'en' ? 'भाषा बदला | Change Language' : 'भाषा बदला | Change Language');
|
496 |
+
updateContent();
|
497 |
+
}
|
498 |
+
|
499 |
+
function showLoading() {
|
500 |
+
$('#loadingIndicator').show();
|
501 |
+
}
|
502 |
+
|
503 |
+
function hideLoading() {
|
504 |
+
$('#loadingIndicator').hide();
|
505 |
+
}
|
506 |
+
|
507 |
+
function enableSelect(selectId) {
|
508 |
+
$(`#${selectId}`).prop('disabled', false);
|
509 |
+
}
|
510 |
+
|
511 |
+
function disableSelect(selectId) {
|
512 |
+
$(`#${selectId}`).prop('disabled', true);
|
513 |
+
}
|
514 |
+
|
515 |
+
function updateContent() {
|
516 |
+
showLoading();
|
517 |
+
const formData = new FormData($('#filterForm')[0]);
|
518 |
+
formData.append('language', currentLang);
|
519 |
+
|
520 |
+
$.ajax({
|
521 |
+
url: '/filter_data',
|
522 |
+
method: 'POST',
|
523 |
+
data: formData,
|
524 |
+
processData: false,
|
525 |
+
contentType: false,
|
526 |
+
success: function(response) {
|
527 |
+
if (response.success) {
|
528 |
+
// Update plots
|
529 |
+
if (response.plots.bar) $('#barChart').html(response.plots.bar);
|
530 |
+
if (response.plots.line) $('#lineChart').html(response.plots.line);
|
531 |
+
if (response.plots.box) $('#boxChart').html(response.plots.box);
|
532 |
+
|
533 |
+
// Update market statistics
|
534 |
+
$('#totalCommodities').text(response.market_stats.total_commodities);
|
535 |
+
$('#avgPrice').text(response.market_stats.avg_modal_price);
|
536 |
+
$('#priceRange').text(response.market_stats.price_range);
|
537 |
+
$('#totalMarkets').text(response.market_stats.total_markets);
|
538 |
+
|
539 |
+
// Update tables
|
540 |
+
$('#marketData').html(response.market_html);
|
541 |
+
$('#cheapestCrops').html(response.cheapest_html);
|
542 |
+
$('#costliestCrops').html(response.costliest_html);
|
543 |
+
|
544 |
+
// Only show insights section if state and district are selected
|
545 |
+
if (response.hasStateDistrict) {
|
546 |
+
$('.insights-container').show();
|
547 |
+
$('#aiInsights').html(response.insights);
|
548 |
+
} else {
|
549 |
+
$('.insights-container').hide();
|
550 |
+
$('#aiInsights').html('');
|
551 |
+
}
|
552 |
+
|
553 |
+
// Update translations
|
554 |
+
updateLabels(response.translations);
|
555 |
+
console.log(response.translations);
|
556 |
+
} else {
|
557 |
+
const message = currentLang === 'en' ?
|
558 |
+
'Please select both state and district to view analysis' :
|
559 |
+
'कृपया विश्लेषण पाहण्यासाठी राज्य आणि जिल्हा निवडा';
|
560 |
+
alert(message);
|
561 |
+
}
|
562 |
+
hideLoading();
|
563 |
+
},
|
564 |
+
error: function() {
|
565 |
+
alert(currentLang === 'en' ? 'Error loading data' : 'माहिती लोड करताना त्रुटी');
|
566 |
+
hideLoading();
|
567 |
+
}
|
568 |
+
});
|
569 |
+
}
|
570 |
+
|
571 |
+
// Cascade dropdowns
|
572 |
+
$('#state').change(function() {
|
573 |
+
const state = $(this).val();
|
574 |
+
// Reset and disable dependent dropdowns
|
575 |
+
$('#district, #market, #commodity').html('<option value="">Select</option>').prop('disabled', true);
|
576 |
+
|
577 |
+
if (state) {
|
578 |
+
showLoading();
|
579 |
+
$.post('/get_districts', { state: state }, function(districts) {
|
580 |
+
$('#district').html('<option value="">Select District</option>');
|
581 |
+
districts.forEach(district => {
|
582 |
+
$('#district').append(`<option value="${district}">${district}</option>`);
|
583 |
+
});
|
584 |
+
enableSelect('district');
|
585 |
+
hideLoading();
|
586 |
+
});
|
587 |
+
}
|
588 |
+
updateContent();
|
589 |
+
});
|
590 |
+
|
591 |
+
$('#district').change(function() {
|
592 |
+
const district = $(this).val();
|
593 |
+
// Reset and disable dependent dropdowns
|
594 |
+
$('#market, #commodity').html('<option value="">Select</option>').prop('disabled', true);
|
595 |
+
|
596 |
+
if (district) {
|
597 |
+
showLoading();
|
598 |
+
$.post('/get_markets', { district: district }, function(markets) {
|
599 |
+
$('#market').html('<option value="">Select Market</option>');
|
600 |
+
markets.forEach(market => {
|
601 |
+
$('#market').append(`<option value="${market}">${market}</option>`);
|
602 |
+
});
|
603 |
+
enableSelect('market');
|
604 |
+
hideLoading();
|
605 |
+
});
|
606 |
+
}
|
607 |
+
updateContent();
|
608 |
+
});
|
609 |
+
|
610 |
+
$('#market').change(function() {
|
611 |
+
const market = $(this).val();
|
612 |
+
// Reset commodity dropdown
|
613 |
+
$('#commodity').html('<option value="">Select</option>').prop('disabled', true);
|
614 |
+
|
615 |
+
if (market) {
|
616 |
+
showLoading();
|
617 |
+
$.post('/get_commodities', { market: market }, function(commodities) {
|
618 |
+
$('#commodity').html('<option value="">Select Commodity</option>');
|
619 |
+
commodities.forEach(commodity => {
|
620 |
+
$('#commodity').append(`<option value="${commodity}">${commodity}</option>`);
|
621 |
+
});
|
622 |
+
enableSelect('commodity');
|
623 |
+
hideLoading();
|
624 |
+
});
|
625 |
+
}
|
626 |
+
updateContent();
|
627 |
+
});
|
628 |
+
|
629 |
+
$('#commodity').change(function() {
|
630 |
+
updateContent();
|
631 |
+
});
|
632 |
+
|
633 |
+
// Initial setup
|
634 |
+
$(document).ready(function() {
|
635 |
+
$('.insights-container').hide();
|
636 |
+
updateContent();
|
637 |
+
});
|
638 |
+
</script>
|
639 |
+
</body>
|
640 |
+
</html>
|