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Update app.py
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app.py
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@@ -1,437 +1,434 @@
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# app.py
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import os
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from flask import Flask, render_template, request, jsonify, redirect, url_for, flash, session
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import requests
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from werkzeug.utils import secure_filename
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import google.generativeai as genai
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import
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import
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import
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import
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genai.
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def
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def
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""
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{
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"title": "
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"link": "https://
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"snippet": "Bactericide for
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}
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if
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flash('No
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return redirect(url_for('index'))
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results
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if __name__ == '__main__':
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cleanup_thread
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# Get the port from environment variable for Hugging Face Spaces compatibility
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port = int(os.environ.get("PORT", 7860))
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app.run(host='0.0.0.0', port=port)
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# app.py
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import os
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from flask import Flask, render_template, request, jsonify, redirect, url_for, flash, session
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import requests
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from werkzeug.utils import secure_filename
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import google.generativeai as genai
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import base64
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import json
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from datetime import datetime, timedelta
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import threading
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import time
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from gtts import gTTS # <-- New import for audio generation
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# Configure the Gemini API
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GEMINI_API_KEY = "AIzaSyBtXV2xJbrWVV57B5RWy_meKXOA59HFMeY"
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if not GEMINI_API_KEY:
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raise ValueError("Google API Key not found. Set it as GEMINI_API_KEY in the Space settings.")
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genai.configure(api_key=GEMINI_API_KEY)
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# Setup the Gemini model
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model = genai.GenerativeModel('gemini-1.5-flash')
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app = Flask(__name__)
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app.secret_key = os.getenv("SECRET_KEY", "your-default-secret-key-for-flash-messages")
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# Configure upload folder
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UPLOAD_FOLDER = 'static/uploads'
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ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif'}
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if not os.path.exists(UPLOAD_FOLDER):
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os.makedirs(UPLOAD_FOLDER)
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# Configure audio folder (new)
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AUDIO_FOLDER = 'static/audio'
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if not os.path.exists(AUDIO_FOLDER):
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os.makedirs(AUDIO_FOLDER)
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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def allowed_file(filename):
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return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
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def encode_image(image_path):
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with open(image_path, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode('utf-8')
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def get_web_pesticide_info(disease, plant_type="Unknown"):
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"""Fetch pesticide information from web sources for a specific disease and plant type"""
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query = f"site:agrowon.esakal.com {disease} in {plant_type}"
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url = "https://www.googleapis.com/customsearch/v1"
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params = {
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"key": os.getenv("GOOGLE_API_KEY"),
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"cx": os.getenv("GOOGLE_CX"),
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"q": query,
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"num": 3
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}
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try:
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response = requests.get(url, params=params)
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response.raise_for_status()
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data = response.json()
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if "items" in data and len(data["items"]) > 0:
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item = data["items"][0]
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return {
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"title": item.get("title", "No title available"),
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"link": item.get("link", "#"),
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"snippet": item.get("snippet", "No snippet available"),
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"summary": item.get("snippet", "No snippet available")
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}
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except Exception as e:
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print(f"Error retrieving web pesticide info: {str(e)}")
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return None
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def get_more_web_info(query):
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"""Get more general web information based on a search query"""
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url = "https://www.googleapis.com/customsearch/v1"
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params = {
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"key": os.getenv("GOOGLE_API_KEY"),
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"cx": os.getenv("GOOGLE_CX"),
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"q": query,
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"num": 3
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}
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try:
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response = requests.get(url, params=params)
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response.raise_for_status()
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data = response.json()
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results = []
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if "items" in data:
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for item in data["items"]:
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results.append({
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"title": item.get("title", "No title available"),
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"link": item.get("link", "#"),
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"snippet": item.get("snippet", "No snippet available")
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})
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return results
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except Exception as e:
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print(f"Error retrieving additional articles: {str(e)}")
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return []
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def get_commercial_product_info(recommendation, disease_name):
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"""Fetch commercial product information related to a pesticide recommendation.
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If no relevant products are found from web sources, return default products based on issue type:
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bacterial, fungicide (disease), or insecticide.
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"""
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indiamart_query = f"site:indiamart.com pesticide '{disease_name}' '{recommendation}'"
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krishi_query = f"site:krishisevakendra.in/products pesticide '{disease_name}' '{recommendation}'"
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indiamart_results = get_more_web_info(indiamart_query)
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krishi_results = get_more_web_info(krishi_query)
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results = indiamart_results + krishi_results
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if not results:
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lower_disease = disease_name.lower()
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lower_recommendation = recommendation.lower()
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if ("bacteria" in lower_disease or "bacterial" in lower_disease or
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"bacteria" in lower_recommendation or "bacterial" in lower_recommendation):
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results = [
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{
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"title": "UPL SAAF Carbendazin Mancozeb Bactericide",
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"link": "https://www.amazon.in/UPL-SAAF-Carbendazinm12-Mancozeb63-Action/dp/B0DJLQRL44",
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"snippet": "Bactericide for controlling bacterial infections."
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},
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{
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"title": "Tropical Tagmycin Bactericide",
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"link": "https://krushidukan.bharatagri.com/en/products/tropical-tagmycin-bactericide",
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"snippet": "Bactericide for effective bacterial infection management."
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}
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]
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elif ("fungus" in lower_disease or "fungicide" in lower_recommendation or
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"antibiotic" in lower_recommendation or "disease" in lower_disease):
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results = [
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{
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"title": "Plantomycin Bio Organic Antibiotic Effective Disease",
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"link": "https://www.amazon.in/Plantomycin-Bio-Organic-Antibiotic-Effective-Disease/dp/B0DRVVJKQ4",
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"snippet": "Bio organic antibiotic for effective control of plant diseases."
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},
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{
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"title": "WET-TREE Larvicide Thuringiensis Insecticide",
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"link": "https://www.amazon.in/WET-TREE-Larvicide-Thuringiensis-Insecticide/dp/B0D6R72KHV",
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"snippet": "Larvicide with thuringiensis for disease prevention."
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}
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]
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elif ("insecticide" in lower_disease or "insect" in lower_disease or "pest" in lower_disease or
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"insecticide" in lower_recommendation or "insect" in lower_recommendation or "pest" in lower_recommendation):
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results = [
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{
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"title": "Syngenta Actara Insecticide",
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"link": "https://www.amazon.in/syngenta-Actara-Insect-Repellent-Insecticide/dp/B08W55XTHS",
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"snippet": "Effective systemic insecticide for pest control."
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},
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{
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+
"title": "Cyhalothrin Insecticide",
|
162 |
+
"link": "https://www.amazon.in/Cyhalothrin-Control-Eradication-Mosquitoes-Crawling/dp/B01N53VH1T",
|
163 |
+
"snippet": "Broad-spectrum insecticide for pest management."
|
164 |
+
}
|
165 |
+
]
|
166 |
+
else:
|
167 |
+
results = [
|
168 |
+
{
|
169 |
+
"title": "Syngenta Actara Insecticide",
|
170 |
+
"link": "https://www.amazon.in/syngenta-Actara-Insect-Repellent-Insecticide/dp/B08W55XTHS",
|
171 |
+
"snippet": "Effective systemic insecticide for pest control."
|
172 |
+
},
|
173 |
+
{
|
174 |
+
"title": "Cyhalothrin Insecticide",
|
175 |
+
"link": "https://www.amazon.in/Cyhalothrin-Control-Eradication-Mosquitoes-Crawling/dp/B01N53VH1T",
|
176 |
+
"snippet": "Broad-spectrum insecticide for pest management."
|
177 |
+
}
|
178 |
+
]
|
179 |
+
|
180 |
+
return results
|
181 |
+
|
182 |
+
|
183 |
+
def get_relevant_feedback(plant_name):
|
184 |
+
"""Retrieve feedback entries relevant to the given plant name from feedback.json."""
|
185 |
+
feedback_file = "feedback.json"
|
186 |
+
if os.path.exists(feedback_file):
|
187 |
+
try:
|
188 |
+
with open(feedback_file, "r") as f:
|
189 |
+
all_feedback = json.load(f)
|
190 |
+
relevant = [entry.get("feedback") for entry in all_feedback if
|
191 |
+
entry.get("plant_name", "").lower() == plant_name.lower()]
|
192 |
+
if relevant:
|
193 |
+
return " ".join(relevant[:3])
|
194 |
+
except Exception as e:
|
195 |
+
print(f"Error reading feedback for reinforcement: {e}")
|
196 |
+
return ""
|
197 |
+
|
198 |
+
|
199 |
+
def generate_audio(text, language, filename):
|
200 |
+
"""Generate an MP3 file from text using gTTS."""
|
201 |
+
try:
|
202 |
+
tts = gTTS(text=text, lang=language, slow=False)
|
203 |
+
tts.save(filename)
|
204 |
+
except Exception as e:
|
205 |
+
print(f"Error generating audio: {e}")
|
206 |
+
|
207 |
+
|
208 |
+
def analyze_plant_image(image_path, plant_name, language):
|
209 |
+
try:
|
210 |
+
# Load the image
|
211 |
+
image_parts = [
|
212 |
+
{
|
213 |
+
"mime_type": "image/jpeg",
|
214 |
+
"data": encode_image(image_path)
|
215 |
+
}
|
216 |
+
]
|
217 |
+
|
218 |
+
# Load relevant feedback (reinforcement data) for this plant
|
219 |
+
feedback_context = get_relevant_feedback(plant_name)
|
220 |
+
feedback_instruction = f" Please consider the following user feedback from similar cases: {feedback_context}" if feedback_context else ""
|
221 |
+
|
222 |
+
# Create prompt for Gemini API with language instruction and feedback reinforcement if available
|
223 |
+
prompt = f"""
|
224 |
+
Analyze this image of a {plant_name} plant and prioritize determining if it's healthy or has a disease or pest infestation.
|
225 |
+
|
226 |
+
If a disease or pest is detected, provide the following information in JSON format:
|
227 |
+
{{"results": [{{"type": "disease/pest", "name": "Name of disease or pest", "probability": "Probability as a percentage", "symptoms": "Describe the visible symptoms", "causes": "Main causes of the disease or pest", "severity": "Low/Medium/High", "spreading": "How it spreads", "treatment": "Treatment options", "prevention": "Preventive measures"}},{{}},{{}}], "is_healthy": boolean indicating if the plant appears healthy, "confidence": "Overall confidence in the analysis as a percentage"}}
|
228 |
+
|
229 |
+
Only return the JSON data and nothing else. Ensure the JSON is valid and properly formatted.
|
230 |
+
If the plant appears completely healthy, set is_healthy to true and include an empty results array.
|
231 |
+
Additionally, provide the response in {language} language.
|
232 |
+
and at end show which all data from feedback was taken into consideration and if no data was taken so no data.
|
233 |
+
"""
|
234 |
+
|
235 |
+
# Send request to Gemini API
|
236 |
+
response = model.generate_content([prompt] + image_parts)
|
237 |
+
|
238 |
+
# Extract the JSON response
|
239 |
+
response_text = response.text
|
240 |
+
|
241 |
+
# Find JSON within response text if needed
|
242 |
+
json_start = response_text.find('{')
|
243 |
+
json_end = response_text.rfind('}') + 1
|
244 |
+
|
245 |
+
if json_start >= 0 and json_end > 0:
|
246 |
+
json_str = response_text[json_start:json_end]
|
247 |
+
analysis_result = json.loads(json_str)
|
248 |
+
else:
|
249 |
+
return {
|
250 |
+
"error": "Failed to parse the API response",
|
251 |
+
"raw_response": response_text
|
252 |
+
}
|
253 |
+
|
254 |
+
# ---- Added audio generation feature ----
|
255 |
+
# Create a summary text based on the analysis including Spreading, Treatment, and Prevention
|
256 |
+
if analysis_result.get('is_healthy', False):
|
257 |
+
summary_text = f"Your {plant_name} plant appears to be healthy. Continue with your current care practices."
|
258 |
+
elif 'results' in analysis_result and analysis_result['results']:
|
259 |
+
summary_text = "Detected issues: "
|
260 |
+
for result in analysis_result['results']:
|
261 |
+
summary_text += (f"{result.get('name', 'Unknown')}. Symptoms: {result.get('symptoms', '')}. "
|
262 |
+
f"Causes: {result.get('causes', '')}. Spreading: {result.get('spreading', '')}. "
|
263 |
+
f"Treatment: {result.get('treatment', '')}. Prevention: {result.get('prevention', '')}. ")
|
264 |
+
else:
|
265 |
+
summary_text = "Analysis inconclusive."
|
266 |
+
|
267 |
+
# Map language name to gTTS language code
|
268 |
+
lang_mapping = {"English": "en", "Hindi": "hi", "Bengali": "bn", "Telugu": "te", "Marathi": "mr", "Tamil": "ta",
|
269 |
+
"Gujarati": "gu", "Urdu": "ur", "Kannada": "kn", "Odia": "or", "Malayalam": "ml"}
|
270 |
+
gtts_lang = lang_mapping.get(language, 'en')
|
271 |
+
|
272 |
+
# Generate unique audio filename
|
273 |
+
timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
|
274 |
+
audio_filename = f"audio_result.mp3"
|
275 |
+
audio_path = os.path.join(AUDIO_FOLDER, audio_filename)
|
276 |
+
generate_audio(summary_text, gtts_lang, audio_path)
|
277 |
+
|
278 |
+
# Wait until the audio file is created and has nonzero size (up to 5 seconds)
|
279 |
+
wait_time = 0
|
280 |
+
while (not os.path.exists(audio_path) or os.path.getsize(audio_path) == 0) and wait_time < 5:
|
281 |
+
time.sleep(0.5)
|
282 |
+
wait_time += 0.5
|
283 |
+
|
284 |
+
# Add relative audio file path for template rendering
|
285 |
+
analysis_result['audio_file'] = os.path.join('audio', audio_filename)
|
286 |
+
# -----------------------------------------
|
287 |
+
|
288 |
+
return analysis_result
|
289 |
+
|
290 |
+
except Exception as e:
|
291 |
+
return {
|
292 |
+
"error": str(e),
|
293 |
+
"is_healthy": None,
|
294 |
+
"results": []
|
295 |
+
}
|
296 |
+
|
297 |
+
|
298 |
+
def cleanup_old_files(directory, max_age_hours=1): # Reduced to 1 hour for Hugging Face
|
299 |
+
"""Remove files older than the specified age from the directory"""
|
300 |
+
while True:
|
301 |
+
now = datetime.now()
|
302 |
+
for filename in os.listdir(directory):
|
303 |
+
if filename == '.gitkeep': # Skip the .gitkeep file
|
304 |
+
continue
|
305 |
+
file_path = os.path.join(directory, filename)
|
306 |
+
file_age = now - datetime.fromtimestamp(os.path.getctime(file_path))
|
307 |
+
if file_age > timedelta(hours=max_age_hours):
|
308 |
+
try:
|
309 |
+
os.remove(file_path)
|
310 |
+
print(f"Removed old file: {file_path}")
|
311 |
+
except Exception as e:
|
312 |
+
print(f"Error removing {file_path}: {e}")
|
313 |
+
time.sleep(300) # 5 minutes
|
314 |
+
|
315 |
+
|
316 |
+
@app.route('/', methods=['GET'])
|
317 |
+
def index():
|
318 |
+
# GET request - show the upload form
|
319 |
+
return render_template('index.html', show_results=False)
|
320 |
+
|
321 |
+
|
322 |
+
@app.route('/feedback', methods=['POST'])
|
323 |
+
def feedback():
|
324 |
+
# Get feedback from form submission
|
325 |
+
feedback_text = request.form.get("feedback")
|
326 |
+
plant_name = request.form.get("plant_name", "Unknown")
|
327 |
+
if not feedback_text:
|
328 |
+
flash("Please provide your feedback before submitting.")
|
329 |
+
return redirect(url_for('index'))
|
330 |
+
feedback_data = {
|
331 |
+
"plant_name": plant_name,
|
332 |
+
"feedback": feedback_text,
|
333 |
+
"timestamp": datetime.now().isoformat()
|
334 |
+
}
|
335 |
+
feedback_file = "feedback.json"
|
336 |
+
if os.path.exists(feedback_file):
|
337 |
+
try:
|
338 |
+
with open(feedback_file, "r") as f:
|
339 |
+
existing_feedback = json.load(f)
|
340 |
+
except Exception as e:
|
341 |
+
print(f"Error reading feedback file: {e}")
|
342 |
+
existing_feedback = []
|
343 |
+
else:
|
344 |
+
existing_feedback = []
|
345 |
+
existing_feedback.append(feedback_data)
|
346 |
+
try:
|
347 |
+
with open(feedback_file, "w") as f:
|
348 |
+
json.dump(existing_feedback, f, indent=4)
|
349 |
+
except Exception as e:
|
350 |
+
flash(f"Error saving your feedback: {str(e)}")
|
351 |
+
return redirect(url_for('index'))
|
352 |
+
flash("Thank you for your feedback!")
|
353 |
+
return redirect(url_for('index'))
|
354 |
+
|
355 |
+
|
356 |
+
@app.route('/analyze', methods=['POST'])
|
357 |
+
def analyze():
|
358 |
+
if 'plant_image' not in request.files:
|
359 |
+
flash('No file part')
|
360 |
+
return redirect(url_for('index'))
|
361 |
+
|
362 |
+
file = request.files['plant_image']
|
363 |
+
plant_name = request.form.get('plant_name', 'unknown')
|
364 |
+
language = request.form.get('language', 'English')
|
365 |
+
|
366 |
+
if file.filename == '':
|
367 |
+
flash('No selected file')
|
368 |
+
return redirect(url_for('index'))
|
369 |
+
|
370 |
+
if file and allowed_file(file.filename):
|
371 |
+
timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
|
372 |
+
original_filename = secure_filename(file.filename)
|
373 |
+
filename = f"{timestamp}_{original_filename}"
|
374 |
+
file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
|
375 |
+
file.save(file_path)
|
376 |
+
|
377 |
+
try:
|
378 |
+
analysis_result = analyze_plant_image(file_path, plant_name, language)
|
379 |
+
if 'error' in analysis_result:
|
380 |
+
flash(f"Error analyzing image: {analysis_result['error']}")
|
381 |
+
if os.path.exists(file_path):
|
382 |
+
os.remove(file_path)
|
383 |
+
return redirect(url_for('index'))
|
384 |
+
web_info = {}
|
385 |
+
product_info = {}
|
386 |
+
if not analysis_result.get('is_healthy', False) and 'results' in analysis_result:
|
387 |
+
for result in analysis_result['results']:
|
388 |
+
disease_name = result.get('name', '')
|
389 |
+
if disease_name:
|
390 |
+
web_info[disease_name] = get_web_pesticide_info(disease_name, plant_name)
|
391 |
+
treatment = result.get('treatment', '')
|
392 |
+
if treatment:
|
393 |
+
product_info[disease_name] = get_commercial_product_info(treatment, disease_name)
|
394 |
+
response = render_template(
|
395 |
+
'results.html',
|
396 |
+
results=analysis_result,
|
397 |
+
plant_name=plant_name,
|
398 |
+
image_path=file_path.replace('static/', '', 1),
|
399 |
+
web_info=web_info,
|
400 |
+
product_info=product_info
|
401 |
+
)
|
402 |
+
|
403 |
+
def delete_file_after_delay(path, delay=30):
|
404 |
+
time.sleep(delay)
|
405 |
+
if os.path.exists(path):
|
406 |
+
try:
|
407 |
+
os.remove(path)
|
408 |
+
print(f"Deleted analyzed file: {path}")
|
409 |
+
except Exception as e:
|
410 |
+
print(f"Error deleting {path}: {e}")
|
411 |
+
|
412 |
+
threading.Thread(
|
413 |
+
target=delete_file_after_delay,
|
414 |
+
args=(file_path,),
|
415 |
+
daemon=True
|
416 |
+
).start()
|
417 |
+
|
418 |
+
return response
|
419 |
+
|
420 |
+
except Exception as e:
|
421 |
+
flash(f"An error occurred: {str(e)}")
|
422 |
+
if os.path.exists(file_path):
|
423 |
+
os.remove(file_path)
|
424 |
+
return redirect(url_for('index'))
|
425 |
+
|
426 |
+
flash('Invalid file type. Please upload an image (png, jpg, jpeg, gif).')
|
427 |
+
return redirect(url_for('index'))
|
428 |
+
|
429 |
+
|
430 |
+
if __name__ == '__main__':
|
431 |
+
cleanup_thread = threading.Thread(target=cleanup_old_files, args=(app.config['UPLOAD_FOLDER'],), daemon=True)
|
432 |
+
cleanup_thread.start()
|
433 |
+
port = int(os.environ.get("PORT", 7860))
|
|
|
|
|
|
|
434 |
app.run(host='0.0.0.0', port=port)
|